From dbcd0124503898794e108ed04989577fd73d971b Mon Sep 17 00:00:00 2001 From: hayabolotski <115126057+hayabolotski@users.noreply.github.com> Date: Tue, 15 Oct 2024 14:39:22 -0700 Subject: [PATCH 1/3] Add hollow fork handle design to urdf (#47) * [WIP] Added hollow fork and cover STLs to mesh folder * Positioned fork handle components and added cog, mass, and inertia for each --- .../forque/2024_06_24_forkHandleCover.stl | Bin 0 -> 122384 bytes .../forque/2024_06_24_forkHandleHollow.stl | Bin 0 -> 2918234 bytes ada_description/urdf/forque/forque.xacro | 11 ++++++++--- 3 files changed, 8 insertions(+), 3 deletions(-) create mode 100644 ada_description/meshes/forque/2024_06_24_forkHandleCover.stl create mode 100644 ada_description/meshes/forque/2024_06_24_forkHandleHollow.stl diff --git a/ada_description/meshes/forque/2024_06_24_forkHandleCover.stl b/ada_description/meshes/forque/2024_06_24_forkHandleCover.stl new file mode 100644 index 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a/ada_description/urdf/forque/forque.xacro b/ada_description/urdf/forque/forque.xacro index e647603..bcf87e7 100644 --- a/ada_description/urdf/forque/forque.xacro +++ b/ada_description/urdf/forque/forque.xacro @@ -78,10 +78,15 @@ - - + + - + + + + + + From 93230997c702bce1411872b50d74e6447e5b628b Mon Sep 17 00:00:00 2001 From: Amal Nanavati Date: Wed, 30 Oct 2024 17:07:23 -0700 Subject: [PATCH 2/3] Add an auto-camera calibration script (#48) * [WIP] Adding auto camera calib procedure * [WIP] Adding camera calibration script * [WIP] added cartesian motion, need to add charucoboard code * [WIP] almost done, need to test in-person * Mostly working but for error computation * Fixed bug in calculating transformation error * Change default calib to autocalib * [WIP] moved to separate package, yet to test * Finalized TODOs * Changes from final testing * Reject calibrations that are too far from the manual reference * Make teh hardcoded path consistent with lovelace * Fix off-center issue (#49) Co-authored-by: Ethan K. Gordon * Update forque centering given updated URDF * Small updates to camera calibration scripts --------- Co-authored-by: Amal Nanavati Co-authored-by: Ethan K. Gordon --- ada_calibrate_camera/LICENSE | 25 + ada_calibrate_camera/README.md | 20 + .../ada_calibrate_camera/__init__.py | 0 .../calibrate_camera_node.py | 1469 +++++++++++++++++ .../camera_calibration.py | 514 ++++++ .../ada_calibrate_camera/charuco_detector.py | 176 ++ .../ada_calibrate_camera/helpers.py | 172 ++ .../publish_camera_extrinsics_node.py | 100 ++ .../calibrate_camera_start.py | 285 ++++ .../config/calibrate_camera.yaml | 32 + ada_calibrate_camera/config/calibs/auto.yaml | 14 + .../config/calibs/manual.yaml | 14 + .../data/2024_10_16_17_16_32/0_rgb_img.png | Bin 0 -> 476164 bytes .../data/2024_10_16_17_16_32/0_sample.npz | Bin 0 -> 970 bytes .../data/2024_10_16_17_16_32/10_rgb_img.png | Bin 0 -> 601646 bytes .../data/2024_10_16_17_16_32/10_sample.npz | Bin 0 -> 971 bytes .../data/2024_10_16_17_16_32/11_rgb_img.png | Bin 0 -> 529271 bytes .../data/2024_10_16_17_16_32/11_sample.npz | Bin 0 -> 969 bytes .../data/2024_10_16_17_16_32/12_rgb_img.png | Bin 0 -> 546975 bytes 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.../autocalib/calib_camera_pose.launch.py | 48 - ada_moveit/calib/calib_target.png | Bin 17056 -> 0 bytes ada_moveit/calib/default/README.md | 40 - .../calib1/camera_calib_pose.launch.py | 54 - .../calib/default/calib1/joint_states_0.yaml | 15 - .../calib/default/calib1/joint_states_1.yaml | 15 - .../calib/default/calib1/joint_states_10.yaml | 127 -- .../calib/default/calib1/joint_states_11.yaml | 134 -- .../calib/default/calib1/joint_states_12.yaml | 141 -- .../calib/default/calib1/joint_states_13.yaml | 148 -- .../calib/default/calib1/joint_states_14.yaml | 155 -- .../calib/default/calib1/joint_states_2.yaml | 29 - .../calib/default/calib1/joint_states_3.yaml | 36 - .../calib/default/calib1/joint_states_4.yaml | 43 - .../calib/default/calib1/joint_states_5.yaml | 50 - .../calib/default/calib1/joint_states_6.yaml | 92 -- .../calib/default/calib1/joint_states_7.yaml | 113 -- .../calib/default/calib1/joint_states_8.yaml | 113 -- .../calib/default/calib1/joint_states_9.yaml | 120 -- ada_moveit/calib/default/calib1/samples.yaml | 510 ------ .../calib2/camera_calib_pose.launch.py | 54 - ada_moveit/calib/default/calib2/samples.yaml | 340 ---- .../calib/default/calib_camera_pose.launch.py | 46 - ada_moveit/calib/default/transform.py | 65 - .../calib/manual/calib_camera_pose.launch.py | 52 - .../calib/none/calib_camera_pose.launch.py | 6 - ada_moveit/calib/ros2/README.md | 1 - .../calib/ros2/calib_camera_pose.launch.py | 54 - .../calib/ros2/calib_joint_samples.yaml | 204 --- ada_moveit/calib/ros2/calib_joint_states.yaml | 50 - ada_moveit/config/ada.srdf | 13 +- ada_moveit/launch/demo.launch.py | 37 +- ada_moveit/launch/move_group.launch.py | 10 +- 100 files changed, 2949 insertions(+), 2878 deletions(-) create mode 100644 ada_calibrate_camera/LICENSE create mode 100644 ada_calibrate_camera/README.md create mode 100644 ada_calibrate_camera/ada_calibrate_camera/__init__.py create mode 100755 ada_calibrate_camera/ada_calibrate_camera/calibrate_camera_node.py create mode 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file mode 100644 index 0000000..574ef07 --- /dev/null +++ b/ada_calibrate_camera/LICENSE @@ -0,0 +1,25 @@ +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + * Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + * Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +POSSIBILITY OF SUCH DAMAGE. diff --git a/ada_calibrate_camera/README.md b/ada_calibrate_camera/README.md new file mode 100644 index 0000000..dd567a5 --- /dev/null +++ b/ada_calibrate_camera/README.md @@ -0,0 +1,20 @@ +# ada_camera_calibration + +This file contains a nodes to do the following: +1. Calibrate ADA's eye-in-hand system's extrinsics (run every time the eye-in-hand system changes); +2. Publish the transform between ADA's end-effector and the camera (run every time the robot is used with perception). + +## Calibrating the Camera's Extrinsics +1. Be in the `src` directory of your workspace. +2. `python3 src/ada_ros2/ada_calibrate_camera/calibrate_camera_start.py` +3. `screen -r calibrate` + 1. (See here for relevant [`screen`` commands](https://gist.github.com/jctosta/af918e1618682638aa82)) +4. Follow the instructions on-screen. (Motions are expected to take ~6 mins and collect up to 30 samples) +5. Once it is done, verify it: + 1. Re-build your workspace. + 2. Run `ros2 launch ada_moveit demo.launch.py sim:=mock` + 3. In RVIZ, add an axis for `camera_color_optical_frame` + 4. Verify it looks like the frame is correct. + +## Publishing the Transform +1. `ros2 launch ada_calibrate_camera publish_camera_extrinsics_launch.xml` (this is done by default in the `ada_moveit` launchfile). diff --git a/ada_calibrate_camera/ada_calibrate_camera/__init__.py b/ada_calibrate_camera/ada_calibrate_camera/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/ada_calibrate_camera/ada_calibrate_camera/calibrate_camera_node.py b/ada_calibrate_camera/ada_calibrate_camera/calibrate_camera_node.py new file mode 100755 index 0000000..5c1addf --- /dev/null +++ b/ada_calibrate_camera/ada_calibrate_camera/calibrate_camera_node.py @@ -0,0 +1,1469 @@ +#!/usr/bin/env python3 +""" +This module defines a node that calibrates the camera using a charucoboard. +""" + +# Standard imports +import copy +import os +import readline # pylint: disable=unused-import +import sys +import threading +from typing import List, Optional, Tuple, Union + +# Third-party imports +from action_msgs.msg import GoalStatus +from controller_manager_msgs.srv import SwitchController +import cv2 +from cv_bridge import CvBridge +from geometry_msgs.msg import TwistStamped, Vector3 +from moveit_msgs.msg import MoveItErrorCodes +import numpy as np +from pymoveit2 import MoveIt2, MoveIt2State +from pymoveit2.robots import kinova +import rclpy +from rclpy.callback_groups import MutuallyExclusiveCallbackGroup, ReentrantCallbackGroup +from rclpy.duration import Duration +from rclpy.executors import MultiThreadedExecutor +from rclpy.node import Node +from rclpy.qos import QoSProfile, ReliabilityPolicy +from rclpy.time import Time +from rclpy.timer import Rate +from rcl_interfaces.msg import ParameterDescriptor, ParameterType +import ros2_numpy +from scipy.spatial.transform import Rotation as R +from sensor_msgs.msg import CameraInfo, CompressedImage +from std_srvs.srv import SetBool +from tf2_geometry_msgs import PoseStamped, Vector3Stamped +import tf2_py as tf2 +import tf2_ros +import yaml + +# Local imports +from ada_calibrate_camera.charuco_detector import CharucoDetector +from ada_calibrate_camera.camera_calibration import CameraCalibration +from ada_calibrate_camera.helpers import ( + pose_to_matrix, + pose_to_twist, + matrix_to_pose, +) + + +# pylint: disable=invalid-name +# Although names like R_gripper2base are not snake case, they align with OpenCV +# conventions. + +# pylint: disable=too-many-lines +# It is only slightly over. + + +class CalibrateCameraNode(Node): + """ + This node uses a command-line interface to enable users to calibrate ADA's + eye-on-hand camera using a charucoboard of known size. The robot base should + be mounted on the tripod, for ease of changing height, and in a location with + at least 1m empty space on all sides of the robot's base. After detecting the + initial charucoboard, this node automatically moves the robot around it, and + saves the images and joint states. It then computes the camera calibration, + given those images. Users are then encouraged to change the height of the robot + relative to the charucoboard and repeat the process to improve the calibration. + """ + + # pylint: disable=too-many-instance-attributes + + def __init__(self): + """ + Do the initialization steps that don't require rclpy to be spinning. + """ + super().__init__("calibrate_camera") + + # Read the parameters + self.active_controller = None + self.read_params() + + # Create the TF2 listener + self.tf_buffer = tf2_ros.Buffer() + self.tf_listener = tf2_ros.TransformListener(self.tf_buffer, self) + + # Create the twist publisher + self.twist_pub = self.create_publisher( + TwistStamped, + "/jaco_arm_cartesian_controller/twist_cmd", + qos_profile=QoSProfile(depth=1, reliability=ReliabilityPolicy.RELIABLE), + ) + + # Create the MoveIt2 object + callback_group = ReentrantCallbackGroup() + self.moveit2 = MoveIt2( + node=self, + joint_names=kinova.joint_names(), + base_link_name=kinova.base_link_name(), + end_effector_name=self.robot_end_effector_frame, + group_name="jaco_arm", + callback_group=callback_group, + ) + + # Create the charuco detector + self.charuco_detector = CharucoDetector( + n_rows=self.charuco_n_rows, + n_cols=self.charuco_n_cols, + sq_length_m=self.charuco_sq_length_m, + marker_length_m=self.charuco_marker_length_m, + predefined_dictionary=self.charuco_predefined_dictionary, + ) + + # Subscribe to the camera info + self.camera_info_sub = self.create_subscription( + CameraInfo, + "/local/camera/aligned_depth_to_color/camera_info", + self.camera_info_callback, + qos_profile=QoSProfile(depth=1, reliability=ReliabilityPolicy.BEST_EFFORT), + callback_group=MutuallyExclusiveCallbackGroup(), + ) + + # Subscribe to the RGB camera feed + self.bridge = CvBridge() + self.latest_img_lock = threading.Lock() + self.latest_annotated_img = None + self.latest_raw_img = None + self.latest_charuco_rvec = None + self.latest_charuco_tvec = None + self.rgb_img_sub = self.create_subscription( + CompressedImage, + "/local/camera/color/image_raw/compressed", + self.rgb_img_callback, + qos_profile=QoSProfile(depth=1, reliability=ReliabilityPolicy.BEST_EFFORT), + callback_group=MutuallyExclusiveCallbackGroup(), + ) + + # Create the service to (de)activate the controller + self.switch_controller_client = self.create_client( + SwitchController, + "/controller_manager/switch_controller", + qos_profile=QoSProfile(depth=1, reliability=ReliabilityPolicy.RELIABLE), + ) + + # Create the service to re-tare the F/T sensor + self.re_tare_ft_sensor_client = self.create_client( + SetBool, + "/wireless_ft/set_bias", + qos_profile=QoSProfile(depth=1, reliability=ReliabilityPolicy.RELIABLE), + ) + + def read_params(self): + """ + Read the parameters from the parameter server. + """ + # General parameters + self.run_node_online = self.declare_parameter( + "run_online", + True, + ParameterDescriptor( + name="run_online", + type=ParameterType.PARAMETER_BOOL, + description="Whether to run the calibration online.", + read_only=True, + ), + ).value + data_dir = self.declare_parameter( + "data_dir", + "data", + ParameterDescriptor( + name="data_dir", + type=ParameterType.PARAMETER_STRING, + description="The directory to save the data, relative to the package's source directory", + read_only=True, + ), + ).value + self.data_dir = os.path.expanduser(data_dir) + self.offline_data_dir = self.declare_parameter( + "offline_data_dir", + "2024_10_09_21_12_30", + ParameterDescriptor( + name="offline_data_dir", + type=ParameterType.PARAMETER_STRING, + description="The directory to load the offline data, relative to the data_dir.", + read_only=True, + ), + ).value + self.offline_data_dir = os.path.join(self.data_dir, self.offline_data_dir) + output_calib_file = self.declare_parameter( + "output_calib_name", + "config/calibs/auto.yaml", + ParameterDescriptor( + name="output_calib_name", + type=ParameterType.PARAMETER_STRING, + description="The name of the output calibration file, relative to the package's source directory", + read_only=True, + ), + ).value + self.output_calib_file = os.path.expanduser(output_calib_file) + ref_calib_file = self.declare_parameter( + "reference_calib_name", + "config/calibs/manual.yaml", + ParameterDescriptor( + name="reference_calib_name", + type=ParameterType.PARAMETER_STRING, + description="The name of the reference calibration file, relative to the package's source directory", + read_only=True, + ), + ).value + self.ref_calib_file = os.path.expanduser(ref_calib_file) + self.ref_translation_error_threshold = self.declare_parameter( + "reference_translation_error_threshold", + 0.03, + ParameterDescriptor( + name="reference_translation_error_threshold", + type=ParameterType.PARAMETER_DOUBLE, + description=( + "If the computed camera calibration's translation differs from the reference by more than " + "this threshold, the calibration is considered invalid." + ), + read_only=True, + ), + ).value + self.ref_rotation_error_threshold = self.declare_parameter( + "reference_rotation_error_threshold", + 0.03, + ParameterDescriptor( + name="reference_rotation_error_threshold", + type=ParameterType.PARAMETER_DOUBLE, + description=( + "If the computed camera calibration's rotation differs from the reference by more than " + "this threshold, the calibration is considered invalid." + ), + read_only=True, + ), + ).value + self.child_frame_id = self.declare_parameter( + "child_frame_id", + "camera_color_optical_frame", + ParameterDescriptor( + name="child_frame_id", + type=ParameterType.PARAMETER_STRING, + description="The child frame ID (camera optical frame ID).", + read_only=True, + ), + ).value + + # Frame names + self.robot_end_effector_frame = self.declare_parameter( + "robot_end_effector_frame", + "forkTip", + ParameterDescriptor( + name="robot_end_effector_frame", + type=ParameterType.PARAMETER_STRING, + description="The robot end effector frame. Used for cartesian motions.", + read_only=True, + ), + ).value + self.extrinsics_base_frame = self.declare_parameter( + "extrinsics_base_frame", + "j2n6s200_end_effector", + ParameterDescriptor( + name="extrinsics_base_frame", + type=ParameterType.PARAMETER_STRING, + description=( + "The extrinsics base frame. The camera should have a static transform " + "from this frame. This frame should be on the robot arm." + ), + read_only=True, + ), + ).value + + # Controller parameters + self.all_controllers = self.declare_parameter( + "all_controllers", + [ + "jaco_arm_servo_controller", + "jaco_arm_cartesian_controller", + "jaco_arm_controller", + ], + ParameterDescriptor( + name="all_controllers", + type=ParameterType.PARAMETER_STRING_ARRAY, + description="The names of all the controllers.", + read_only=True, + ), + ).value + self.default_moveit2_controller = self.declare_parameter( + "default_moveit2_controller", + "jaco_arm_controller", + ParameterDescriptor( + name="default_moveit2_controller", + type=ParameterType.PARAMETER_STRING, + description="The default controller for MoveIt2.", + read_only=True, + ), + ).value + if self.default_moveit2_controller not in self.all_controllers: + self.get_logger().error( + "The default controller for MoveIt2 is not in the list of all controllers." + ) + sys.exit(1) + + # Arm parameters + self.starting_arm_configuration = self.declare_parameter( + "starting_arm_configuration", + [ + -2.3149168248766614, # j2n6s200_joint_1 + 3.1444595465032634, # j2n6s200_joint_2 + 1.7332586075115999, # j2n6s200_joint_3 + -2.3609596843308234, # j2n6s200_joint_4 + 4.43936623280362, # j2n6s200_joint_5 + 3.06866544924739, # j2n6s200_joint_6 + ], + ParameterDescriptor( + name="starting_arm_configuration", + type=ParameterType.PARAMETER_DOUBLE_ARRAY, + description="The starting configuration of the arm.", + read_only=True, + ), + ).value + + self.wait_before_capture_secs = self.declare_parameter( + "wait_before_capture_secs", + 2.0, + ParameterDescriptor( + name="wait_before_capture_secs", + type=ParameterType.PARAMETER_DOUBLE, + description="The time to wait between the end of motion and capturing the image.", + read_only=True, + ), + ).value + + # Charuco board parameters + self.charuco_n_rows = self.declare_parameter( + "charuco_n_rows", + 5, + ParameterDescriptor( + name="charuco_n_rows", + type=ParameterType.PARAMETER_INTEGER, + description="The number of rows in the charucoboard.", + read_only=True, + ), + ).value + self.charuco_n_cols = self.declare_parameter( + "charuco_n_cols", + 5, + ParameterDescriptor( + name="charuco_n_cols", + type=ParameterType.PARAMETER_INTEGER, + description="The number of columns in the charucoboard.", + read_only=True, + ), + ).value + self.charuco_sq_length_m = self.declare_parameter( + "charuco_sq_length_m", + 0.0351, + ParameterDescriptor( + name="charuco_sq_length_m", + type=ParameterType.PARAMETER_DOUBLE, + description="The length of a square in the charucoboard.", + read_only=True, + ), + ).value + self.charuco_marker_length_m = self.declare_parameter( + "charuco_marker_length_m", + 0.0257, + ParameterDescriptor( + name="charuco_marker_length_m", + type=ParameterType.PARAMETER_DOUBLE, + description="The length of a marker in the charucoboard.", + read_only=True, + ), + ).value + self.charuco_predefined_dictionary = self.declare_parameter( + "charuco_predefined_dictionary", + cv2.aruco.DICT_5X5_50, + ParameterDescriptor( + name="charuco_predefined_dictionary", + type=ParameterType.PARAMETER_INTEGER, + description=( + "The predefined dictionary to use. See cv::aruco::PredefinedDictionaryType for the enum: " + "https://docs.opencv.org/4.x/de/d67/group__objdetect__aruco.html#ga4e13135a118f497c6172311d601ce00d" + ), + read_only=True, + ), + ).value + + # Hand-eye calibration method + hand_eye_calibration_method = self.declare_parameter( + "hand_eye_calibration_method", + "andreff", + ParameterDescriptor( + name="hand_eye_calibration_method", + type=ParameterType.PARAMETER_STRING, + description=( + "The hand-eye calibration method to use. Valid values include: " + "'all', 'tsai', 'park', 'horaud', 'andreff', 'daniilidis'. " + "See cv::HandEyeCalibrationMethod for more " + "https://docs.opencv.org/4.5.4/d9/d0c/group__calib3d.html#gad10a5ef12ee3499a0774c7904a801b99" + ), + read_only=True, + ), + ).value + self.hand_eye_calibration_methods = [] + if hand_eye_calibration_method.lower().strip() in ["all", "tsai"]: + self.hand_eye_calibration_methods.append(cv2.CALIB_HAND_EYE_TSAI) + if hand_eye_calibration_method.lower().strip() in ["all", "park"]: + self.hand_eye_calibration_methods.append(cv2.CALIB_HAND_EYE_PARK) + if hand_eye_calibration_method.lower().strip() in ["all", "horaud"]: + self.hand_eye_calibration_methods.append(cv2.CALIB_HAND_EYE_HORAUD) + if hand_eye_calibration_method.lower().strip() in ["all", "andreff"]: + self.hand_eye_calibration_methods.append(cv2.CALIB_HAND_EYE_ANDREFF) + if hand_eye_calibration_method.lower().strip() in ["all", "daniilidis"]: + self.hand_eye_calibration_methods.append(cv2.CALIB_HAND_EYE_DANIILIDIS) + if len(self.hand_eye_calibration_methods) == 0: + self.get_logger().error( + f"Invalid hand-eye calibration method {hand_eye_calibration_method}. " + "Valid values include: 'all', 'tsai', 'park', 'horaud', 'andreff', 'daniilidis'." + ) + sys.exit(1) + + def initialize( + self, + timeout_secs: float = 10.0, + rate: Union[Rate, float] = 10.0, + ) -> bool: + """ + Do the initialization steps that require rclpy to be spinning. + """ + # Configuration for the timeout + start_time = self.get_clock().now() + timeout = Duration(seconds=timeout_secs) + created_rate = False + if isinstance(rate, float): + rate = self.create_rate(rate) + created_rate = True + + def cleanup(retval: bool) -> bool: + if created_rate: + self.destroy_rate(rate) + return retval + + if self.run_node_online: + # Wait for the joint states + while self.moveit2.joint_state is None: + if not rclpy.ok(): + self.get_logger().error( + "Interrupted while waiting for the joint states." + ) + return cleanup(False) + if self.get_clock().now() - start_time > timeout: + self.get_logger().error("Timed out while getting the joint states.") + return cleanup(False) + rate.sleep() + + # Wait for the RGB image + latest_raw_img = None + while latest_raw_img is None: + with self.latest_img_lock: + latest_raw_img = self.latest_raw_img + if not rclpy.ok(): + self.get_logger().error( + "Interrupted while waiting for the RGB image." + ) + return cleanup(False) + if self.get_clock().now() - start_time > timeout: + self.get_logger().error("Timed out while getting the RGB image.") + return cleanup(False) + rate.sleep() + + return cleanup(True) + + def get_remaining_time(self, start_time: Time, timeout_secs: float) -> float: + """ + Get the remaining time before the timeout. + + Parameters + ---------- + start_time : Time + The start time. + timeout_secs : float + The timeout in seconds. + + Returns + ------- + float + The remaining time in seconds. + """ + return timeout_secs - (self.get_clock().now() - start_time).nanoseconds / 1e9 + + def activate_controller( + self, + controller_name: str = "jaco_arm_cartesian_controller", + timeout_secs: float = 10.0, + rate: Union[Rate, float] = 10.0, + ) -> bool: + """ + Activate the specified controller and deactivate all others. + """ + if self.active_controller == controller_name: + return True + + # Configuration for the timeout + start_time = self.get_clock().now() + timeout = Duration(seconds=timeout_secs) + created_rate = False + if isinstance(rate, float): + rate = self.create_rate(rate) + created_rate = True + + def cleanup(retval: bool) -> bool: + if created_rate: + self.destroy_rate(rate) + return retval + + # Activate the controller + request = SwitchController.Request( + activate_controllers=[controller_name], + deactivate_controllers=[ + controller + for controller in self.all_controllers + if controller != controller_name + ], + activate_asap=True, + strictness=SwitchController.Request.BEST_EFFORT, + ) + if not self.switch_controller_client.wait_for_service( + timeout_sec=self.get_remaining_time(start_time, timeout_secs), + ): + self.get_logger().error( + "Failed to connect to the switch_controller service." + ) + return cleanup(False) + future = self.switch_controller_client.call_async(request) + while not future.done(): + if not rclpy.ok(): + self.get_logger().error("Interrupted while activating the controller.") + return cleanup(False) + if self.get_clock().now() - start_time > timeout: + self.get_logger().error("Timeout while activating the controller.") + return cleanup(False) + rate.sleep() + response = future.result() + if not response.ok: + self.get_logger().error("Failed to activate the controller.") + return cleanup(False) + + self.active_controller = controller_name + return cleanup(True) + + def re_tare_ft_sensor( + self, + timeout_secs: float = 10.0, + rate: Union[Rate, float] = 10.0, + ) -> bool: + """ + Re-tare the F/T sensor. + """ + # Configuration for the timeout + start_time = self.get_clock().now() + timeout = Duration(seconds=timeout_secs) + created_rate = False + if isinstance(rate, float): + rate = self.create_rate(rate) + created_rate = True + + def cleanup(retval: bool) -> bool: + if created_rate: + self.destroy_rate(rate) + return retval + + # Re-tare the F/T sensor + request = SetBool.Request(data=True) + if not self.re_tare_ft_sensor_client.wait_for_service( + timeout_sec=self.get_remaining_time(start_time, timeout_secs), + ): + self.get_logger().error("Failed to connect to the re-tare service.") + return cleanup(False) + future = self.re_tare_ft_sensor_client.call_async(request) + while not future.done(): + if not rclpy.ok(): + self.get_logger().error("Interrupted while re-taring the F/T sensor.") + return cleanup(False) + if self.get_clock().now() - start_time > timeout: + self.get_logger().error("Timeout while re-taring the F/T sensor.") + return cleanup(False) + rate.sleep() + response = future.result() + if not response.success: + self.get_logger().error("Failed to re-tare the F/T sensor.") + return cleanup(False) + return cleanup(True) + + def move_to_configuration( + self, + configuration: List[float], + timeout_secs: float = 10.0, + rate: Union[Rate, float] = 10.0, + ) -> bool: + """ + Move the robot to the specified configuration. + """ + # pylint: disable=too-many-return-statements, too-many-branches + # Okay due to extensive error checking + + # Configuration for the timeout + start_time = self.get_clock().now() + timeout = Duration(seconds=timeout_secs) + created_rate = False + if isinstance(rate, float): + rate = self.create_rate(rate) + created_rate = True + + def cleanup(retval: bool) -> bool: + if created_rate: + self.destroy_rate(rate) + return retval + + # Re-tare the F/T sensor + if not self.re_tare_ft_sensor(timeout_secs=timeout_secs, rate=rate): + return cleanup(False) + + # Plan the motion to the configuration + future = self.moveit2.plan_async( + joint_positions=configuration, + ) + while not future.done(): + if not rclpy.ok(): + self.get_logger().error( + "Interrupted while moving to the configuration." + ) + return cleanup(False) + if self.get_clock().now() - start_time > timeout: + self.get_logger().error("Timeout while moving to the configuration.") + return cleanup(False) + rate.sleep() + traj = self.moveit2.get_trajectory(future) + if traj is None: + self.get_logger().error("Failed to plan to the configuration.") + return cleanup(False) + + # Execute the motion + self.moveit2.execute(traj) + while self.moveit2.query_state() != MoveIt2State.EXECUTING: + if not rclpy.ok(): + self.get_logger().error("Interrupted while executing the trajectory.") + return cleanup(False) + if self.get_clock().now() - start_time > timeout: + self.get_logger().error("Timeout while executing the trajectory.") + return cleanup(False) + rate.sleep() + self.active_controller = ( + self.default_moveit2_controller + ) # MoveIt2 automatically activates this controller + future = self.moveit2.get_execution_future() + while not future.done(): + if not rclpy.ok(): + self.get_logger().error("Interrupted while executing the trajectory.") + return cleanup(False) + if self.get_clock().now() - start_time > timeout: + self.get_logger().error("Timeout while executing the trajectory.") + return cleanup(False) + rate.sleep() + result = future.result() + if ( + result.status != GoalStatus.STATUS_SUCCEEDED + or result.result.error_code.val != MoveItErrorCodes.SUCCESS + ): + self.get_logger().error("Failed to execute the trajectory.") + return cleanup(False) + return cleanup(True) + + def transform_stamped_msg( + self, + stamped_msg: Union[PoseStamped, TwistStamped], + target_frame: str, + timeout_secs: float = 10.0, + ) -> Optional[Union[PoseStamped, TwistStamped]]: + """ + Transform the pose stamped to the target frame. + + Parameters + ---------- + stamped_msg : Union[PoseStamped, TwistStamped] + The stamped message to transform. + target_frame : str + The target frame. + timeout_secs : float + The timeout in seconds. + + Returns + ------- + Optional[Union[PoseStamped, TwistStamped]] + The transformed stamped message, or None if the transformation failed. + """ + stamped_msgs = [] + if isinstance(stamped_msg, PoseStamped): + stamped_msgs.append(stamped_msg) + else: + stamped_msgs.append( + Vector3Stamped( + header=stamped_msg.header, vector=stamped_msg.twist.linear + ) + ) + stamped_msgs.append( + Vector3Stamped( + header=stamped_msg.header, vector=stamped_msg.twist.angular + ) + ) + transformed_msgs = [] + for msg in stamped_msgs: + try: + transformed_msg = self.tf_buffer.transform( + msg, + target_frame, + timeout=Duration(seconds=timeout_secs), + ) + transformed_msgs.append(transformed_msg) + except ( + tf2.ConnectivityException, + tf2.ExtrapolationException, + tf2.InvalidArgumentException, + tf2.LookupException, + tf2.TimeoutException, + tf2.TransformException, + tf2_ros.TypeException, + ) as e: + self.get_logger().error(f"Failed to transform the pose: {e}") + return None + if isinstance(stamped_msg, PoseStamped): + return transformed_msgs[0] + transformed_twist = TwistStamped() + transformed_twist.header = transformed_msgs[0].header + transformed_twist.twist.linear = transformed_msgs[0].vector + transformed_twist.twist.angular = transformed_msgs[1].vector + return transformed_twist + + def move_end_effector_to_pose_cartesian( + self, + pose_stamped: PoseStamped, + timeout_secs: float = 10.0, + rate: Union[Rate, float] = 10.0, + linear_threshold: float = 0.01, # meters + angular_threshold: float = 0.01, # radians + only_linear: bool = False, + only_angular: bool = False, + do_not_oscillate: bool = True, + verbose: bool = False, + ): + """ + Move the end-effector to the specified pose via Cartesian motion. + + Parameters + ---------- + pose_stamped : PoseStamped + The target pose. + timeout_secs : float + The timeout in seconds. + rate : Union[Rate, float] + The rate at which to run the loop. + linear_threshold : float + The linear threshold to consider the pose reached. + angular_threshold : float + The angular threshold to consider the pose reached. + only_linear : bool + If true, only move in the linear dimensions. + only_angular : bool + If true, only move in the angular dimensions. + do_not_oscillate : bool + If true, as soon as the sign of any of the velocities changes, zero out + that dimension of the velocity. + verbose : bool + If true, print verbose output. + """ + # pylint: disable=too-many-arguments, too-many-locals, too-many-branches + # pylint: disable=too-many-return-statements, too-many-statements + # This is intended to be a flexible function. + + # Configuration for the timeout + start_time = self.get_clock().now() + timeout = Duration(seconds=timeout_secs) + created_rate = False + if isinstance(rate, float): + rate = self.create_rate(rate) + created_rate = True + + def cleanup(retval: bool) -> bool: + zero_twist = TwistStamped() + zero_twist.header.frame_id = self.moveit2.base_link_name + self.twist_pub.publish(zero_twist) # Stop the motion + if created_rate: + self.destroy_rate(rate) + return retval + + # Re-tare the F/T sensor + if not self.re_tare_ft_sensor(timeout_secs, rate): + return cleanup(False) + + # Activate the controller + if not self.activate_controller( + "jaco_arm_cartesian_controller", timeout_secs, rate + ): + return cleanup(False) + + # Convert pose to base link frame if it isn't already + if pose_stamped.header.frame_id != self.moveit2.base_link_name: + pose_stamped_base = self.transform_stamped_msg( + pose_stamped, + self.moveit2.base_link_name, + self.get_remaining_time(start_time, timeout_secs), + ) + if pose_stamped_base is None: + return cleanup(False) + else: + pose_stamped_base = pose_stamped + + # Move towards the pose until it is reached or timeout + signs = None + while self.get_clock().now() - start_time < timeout: + if not rclpy.ok(): + return cleanup(False) + + # Convert the target pose to the end-effector frame + pose_stamped_base.header.stamp = self.get_clock().now().to_msg() + pose_stamped_ee = self.transform_stamped_msg( + pose_stamped_base, + self.moveit2.end_effector_name, + self.get_remaining_time(start_time, timeout_secs), + ) + if verbose: + print(f"Pose in end-effector frame: {pose_stamped_ee}", flush=True) + if pose_stamped_ee is None: + return cleanup(False) + + # Check if the pose is reached + if only_angular: + position_diff = 0.0 + else: + position_diff = np.linalg.norm( + ros2_numpy.numpify(pose_stamped_ee.pose.position) + ) + if only_linear: + angular_diff = 0.0 + else: + angular_diff = np.linalg.norm( + R.from_quat( + ros2_numpy.numpify(pose_stamped_ee.pose.orientation) + ).as_rotvec() + ) + if position_diff < linear_threshold and angular_diff < angular_threshold: + return cleanup(True) + + # Compute the twist required to move the end effector to the target pose + twist_stamped = pose_to_twist( + pose_stamped_ee, + rate_hz=1.0e9 + / rate._timer.timer_period_ns, # pylint: disable=protected-access + ) + if only_angular: + twist_stamped.twist.linear = Vector3() + if only_linear: + twist_stamped.twist.angular = Vector3() + if do_not_oscillate and signs is not None: + # pylint: disable=unsubscriptable-object + # Okay since signs is a numpy array + if np.sign(twist_stamped.twist.linear.x) != signs[0]: + twist_stamped.twist.linear.x = 0.0 + if np.sign(twist_stamped.twist.linear.y) != signs[1]: + twist_stamped.twist.linear.y = 0.0 + if np.sign(twist_stamped.twist.linear.z) != signs[2]: + twist_stamped.twist.linear.z = 0.0 + if np.sign(twist_stamped.twist.angular.x) != signs[3]: + twist_stamped.twist.angular.x = 0.0 + if np.sign(twist_stamped.twist.angular.y) != signs[4]: + twist_stamped.twist.angular.y = 0.0 + if np.sign(twist_stamped.twist.angular.z) != signs[5]: + twist_stamped.twist.angular.z = 0.0 + if signs is None: + signs = np.sign( + np.concatenate( + [ + ros2_numpy.numpify(twist_stamped.twist.linear), + ros2_numpy.numpify(twist_stamped.twist.angular), + ] + ) + ) + if verbose: + print(f"Twist in EE frame{twist_stamped}", flush=True) + + # Transform to the base frame + twist_stamped_base = self.transform_stamped_msg( + twist_stamped, + self.moveit2.base_link_name, + self.get_remaining_time(start_time, timeout_secs), + ) + if verbose: + print(f"Twist in base frame{twist_stamped_base}", flush=True) + if twist_stamped_base is None: + return cleanup(False) + + # Publish the twist + self.twist_pub.publish(twist_stamped_base) + + # If the commanded twist is 0, succeed + if ( + np.linalg.norm(ros2_numpy.numpify(twist_stamped_base.twist.linear)) + < 1.0e-6 + and np.linalg.norm(ros2_numpy.numpify(twist_stamped_base.twist.angular)) + < 1.0e-6 + ): + return cleanup(True) + + # Sleep + rate.sleep() + + self.get_logger().error("Timeout while moving the end-effector to the pose.") + return cleanup(False) + + def camera_info_callback(self, msg: CameraInfo): + """ + Callback for the camera info. + + Parameters + ---------- + msg : CameraInfo + The camera info message. + """ + if not self.charuco_detector.got_camera_intrinsics(): + self.charuco_detector.set_camera_intrinsics( + np.array(msg.k).reshape((3, 3)), + np.array(msg.d), + ) + self.destroy_subscription(self.camera_info_sub) + + def rgb_img_callback(self, msg: CompressedImage): + """ + Callback for the RGB image. + + Parameters + ---------- + msg : CompressedImage + The compressed image message. + """ + img = self.bridge.compressed_imgmsg_to_cv2(msg, desired_encoding="passthrough") + succ, rvec, tvec, annotated_img = self.charuco_detector.detect(img, viz=True) + if succ: + with self.latest_img_lock: + self.latest_annotated_img = annotated_img + self.latest_raw_img = img + self.latest_charuco_rvec = rvec + self.latest_charuco_tvec = tvec + else: + with self.latest_img_lock: + self.latest_annotated_img = img + self.latest_raw_img = img + self.latest_charuco_rvec = None + self.latest_charuco_tvec = None + + def get_input(self, prompt: str) -> str: + """ + Get input from the user. + + Parameters + ---------- + prompt : str + The prompt to display. + + Returns + ------- + str + The input from the user. + """ + print(prompt, flush=True) + return input() + + def run_online( + self, + rate: Union[Rate, float] = 10.0, + ): + """ + Run the node. + + Parameters + ---------- + rate : Union[Rate, float] + The rate at which to run the loop. + """ + # pylint: disable=too-many-locals, too-many-branches, too-many-statements + # pylint: disable=too-many-nested-blocks + # Fine since this does the main work. + + try: + created_rate = False + if isinstance(rate, float): + rate = self.create_rate(rate) + created_rate = True + # Wait for the user to place the robot on its tripod mount + _ = self.get_input( + "Place the robot on a mount (e.g., wheelchair mount). Ensure " + "there is at least 30cm of empty space below and around the robot's " + "gripper in the home position. Press Enter when done." + ) + print("Moving the robot...", flush=True) + + # Move the robot to the starting configuration + self.move_to_configuration( + configuration=self.starting_arm_configuration, + rate=rate, + ) + + # Wait for the user to place the charucoboard in front of the robot + _ = self.get_input( + "Place the charucoboard on the hospital table. Roll the hospital table " + "under the robot's end-effector. Adjust the height of the tripod and hospital " + "table so the end-effector is around 10cm above the charuboard while " + "the charucoboard is still fully visible in the camera. Press Enter when done." + ) + + # Load the reference calibration + ref_R_cam2gripper, ref_t_cam2gripper = self.load_yaml(self.ref_calib_file) + + # Get the current end-effector pose in base frame + zero_pose_ee_frame = PoseStamped() + zero_pose_ee_frame.header.frame_id = self.moveit2.end_effector_name + zero_pose_ee_frame.pose.orientation.w = 1.0 + zero_pose_extrinsics_frame = copy.deepcopy(zero_pose_ee_frame) + zero_pose_extrinsics_frame.header.frame_id = self.extrinsics_base_frame + init_ee_pose = self.transform_stamped_msg( + copy.deepcopy(zero_pose_ee_frame), + self.moveit2.base_link_name, + ) + if init_ee_pose is None: + return + init_ee_M = pose_to_matrix(init_ee_pose.pose) + print(f"Initial end-effector transform: {init_ee_pose}", flush=True) + + # Capture the poses and images. + camera_calibration = CameraCalibration( + data_dir=self.data_dir, + methods=self.hand_eye_calibration_methods, + ) + lateral_radius = 0.10 # meters + lateral_intervals = 5 + wait_before_capture = Duration(seconds=self.wait_before_capture_secs) + # In practice, modifying pitch resulted in too much variation in z, which hindered reliability. + # This is kept here for legacy purposes. + pitches = [0.0] + prev_target_pose = None + for d_z in [0.0, 0.05, -0.05]: + for lateral_i in range(-1, lateral_intervals): + # Get the target pose + if lateral_i == -1: + d_x = 0.0 + d_y = 0.0 + yaws = [0.0, np.pi] + else: + theta = 2 * np.pi * lateral_i / lateral_intervals + d_x = lateral_radius * np.cos(theta) + d_y = lateral_radius * np.sin(theta) + if (np.pi / 4 <= theta <= 3 * np.pi / 4) or ( + 5 * np.pi / 4 <= theta <= 7 * np.pi / 4 + ): + yaws = [0.0, np.pi] + else: + yaws = [np.pi / 2, 3 * np.pi / 2] + pitches.reverse() + for d_yaw in yaws: + for d_pitch in pitches: + # Rotation is in EE frame, translation is in base frame + target_M = np.eye(4) + target_M[:3, :3] = ( + init_ee_M[:3, :3] + @ R.from_euler("ZYX", [d_yaw, 0.0, d_pitch]).as_matrix() + ) + target_M[:3, 3] = init_ee_M[:3, 3] + [d_x, d_y, d_z] + + target_pose = copy.deepcopy(init_ee_pose) + target_pose.pose = matrix_to_pose(target_M) + target_pose.header.stamp = self.get_clock().now().to_msg() + + # Move to the target pose. First move linearly, then rotate. + print( + f"Moving to the target pose: {target_pose}", flush=True + ) + if ( + prev_target_pose is None + or prev_target_pose.pose.position.x + != target_pose.pose.position.x + or prev_target_pose.pose.position.y + != target_pose.pose.position.y + or prev_target_pose.pose.position.z + != target_pose.pose.position.z + ): + self.move_end_effector_to_pose_cartesian( + target_pose, + rate=rate, + only_linear=True, + ) + if ( + prev_target_pose is None + or prev_target_pose.pose.orientation.x + != target_pose.pose.orientation.x + or prev_target_pose.pose.orientation.y + != target_pose.pose.orientation.y + or prev_target_pose.pose.orientation.z + != target_pose.pose.orientation.z + or prev_target_pose.pose.orientation.w + != target_pose.pose.orientation.w + ): + self.move_end_effector_to_pose_cartesian( + target_pose, + rate=rate, + only_angular=True, + ) + prev_target_pose = target_pose + + # Wait for the joint states to update + print( + f"Waiting {self.wait_before_capture_secs} secs...", + flush=True, + ) + wait_start_time = self.get_clock().now() + while ( + self.get_clock().now() - wait_start_time + < wait_before_capture + ): + if not rclpy.ok(): + return + rate.sleep() + + # Capture the transform from the end effector to the base link + ee_pose_in_base_frame = self.transform_stamped_msg( + copy.deepcopy(zero_pose_extrinsics_frame), + self.moveit2.base_link_name, + ) + if ee_pose_in_base_frame is None: + self.get_logger().error( + "Failed to capture the EE pose in base frame. Skipping this sample." + ) + continue + + # Capture the transform from the camera to the charucoboard + with self.latest_img_lock: + latest_raw_img = self.latest_raw_img + charuco_rvec = self.latest_charuco_rvec + charuco_tvec = self.latest_charuco_tvec + if charuco_rvec is None or charuco_tvec is None: + self.get_logger().error( + "Failed to detect the CharucoBoard. Skipping this sample." + ) + continue + + # Save the transforms + camera_calibration.add_sample( + latest_raw_img, + ee_pose_in_base_frame, + (charuco_rvec, charuco_tvec), + ) + + # Compute the camera extrinsics calibration + ( + R_cam2gripper, + T_cam2gripper, + rotation_error, + translation_error, + method, + ) = camera_calibration.compute_calibration( + save_data=False, + ref_R_cam2gripper=ref_R_cam2gripper, + ref_t_cam2gripper=ref_t_cam2gripper, + ref_translation_error_threshold=self.ref_translation_error_threshold, + ref_rotation_error_threshold=self.ref_rotation_error_threshold, + ) + if R_cam2gripper is not None: + print(f"Rotation error: {rotation_error}", flush=True) + print( + f"Translation error: {translation_error}", + flush=True, + ) + print( + f"R_cam2gripper: {R.from_matrix(R_cam2gripper).as_quat()}", + flush=True, + ) + print( + f"R_cam2gripper: {R.from_matrix(R_cam2gripper).as_euler('ZYX')}", + flush=True, + ) + print(f"T_cam2gripper: {T_cam2gripper}", flush=True) + + # Save the latest camera calibration to the yaml file + if R_cam2gripper is not None: + self.save_yaml( + R_cam2gripper, + T_cam2gripper, + rotation_error, + translation_error, + method, + ) + + if created_rate: + self.destroy_rate(rate) + except KeyboardInterrupt: + zero_twist = TwistStamped() + zero_twist.header.frame_id = self.moveit2.base_link_name + self.twist_pub.publish(zero_twist) + return + + def run_offline( + self, + _: Union[Rate, float] = 10.0, + ): + """ + Run the node offline. + """ + # Load the reference calibration + ref_R_cam2gripper, ref_t_cam2gripper = self.load_yaml(self.ref_calib_file) + + # Load the camera calibration data + camera_calibration = CameraCalibration( + methods=self.hand_eye_calibration_methods, + ) + camera_calibration.add_samples_from_folder(self.offline_data_dir) + + # Compute the camera extrinsics calibration + ( + R_cam2gripper, + T_cam2gripper, + rotation_error, + translation_error, + method, + ) = camera_calibration.compute_calibration( + save_data=False, + ref_R_cam2gripper=ref_R_cam2gripper, + ref_t_cam2gripper=ref_t_cam2gripper, + ref_translation_error_threshold=self.ref_translation_error_threshold, + ref_rotation_error_threshold=self.ref_rotation_error_threshold, + verbose=len(self.hand_eye_calibration_methods) > 1, + ) + + # Print the results + if R_cam2gripper is not None: + print(f"Used method: {method}", flush=True) + print(f"Rotation error: {rotation_error}", flush=True) + print(f"Translation error: {translation_error}", flush=True) + print( + f"R_cam2gripper: {R.from_matrix(R_cam2gripper).as_quat()}", flush=True + ) + print( + f"R_cam2gripper: {R.from_matrix(R_cam2gripper).as_euler('ZYX')}", + flush=True, + ) + print(f"T_cam2gripper: {T_cam2gripper}", flush=True) + + # Save the camera calibration to the yaml file + self.save_yaml( + R_cam2gripper, + T_cam2gripper, + rotation_error, + translation_error, + method, + ) + + def run( + self, + rate: Union[Rate, float] = 10.0, + ): + """ + Run the node. + """ + if self.run_node_online: + self.run_online(rate) + else: + self.run_offline(rate) + + def save_yaml( + self, + R_cam2gripper: np.ndarray, + t_cam2gripper: np.ndarray, + rotation_error: float, + translation_error: float, + method: int, + ) -> None: + """ + Save the camera calibration to a yaml file. + + Parameters + ---------- + R_cam2gripper : np.ndarray + The rotation matrix from the camera to the gripper. + t_cam2gripper : np.ndarray + The translation vector from the camera to the gripper. + rotation_error : float + The rotation error. + translation_error : float + The translation error. + method : int + The method used for the calibration. + """ + # pylint: disable=too-many-arguments, too-many-locals + # Okay since this is a utility function. + + # Generate the yaml data + x, y, z = t_cam2gripper.flatten() + yaw, pitch, roll = R.from_matrix(R_cam2gripper).as_euler("ZYX") + yaml_data = { + "publish_camera_extrinsics": { + "ros__parameters": { + "x": float(x), + "y": float(y), + "z": float(z), + "roll": float(roll), + "pitch": float(pitch), + "yaw": float(yaw), + "child_frame_id": self.child_frame_id, + "frame_id": self.extrinsics_base_frame, + } + } + } + + # Create the comment on top of the yaml file + method_str = "" + if method == cv2.CALIB_HAND_EYE_TSAI: + method_str = "tsai" + elif method == cv2.CALIB_HAND_EYE_PARK: + method_str = "park" + elif method == cv2.CALIB_HAND_EYE_HORAUD: + method_str = "horaud" + elif method == cv2.CALIB_HAND_EYE_ANDREFF: + method_str = "andreff" + elif method == cv2.CALIB_HAND_EYE_DANIILIDIS: + method_str = "daniilidis" + comment = ( + "# This file was auto-generated by the ada_calibrate_camera node.\n" + f"# It used the following hand-eye calibration method: '{method_str}'.\n" + f"# The rotation error is {rotation_error} and the translation error is {translation_error}.\n" + "# See the README for more details.\n" + ) + + # Save the camera calibration to the yaml file + with open(self.output_calib_file, "w", encoding="utf-8") as f: + f.write(comment) + yaml.dump(yaml_data, f) + print(f"Saved the camera calibration to {self.output_calib_file}", flush=True) + + def load_yaml(self, yaml_file: str) -> Tuple[np.ndarray, np.ndarray]: + """ + Load the camera calibration from a yaml file. + + Parameters + ---------- + yaml_file : str + The yaml file to load. + + Returns + ------- + Tuple[np.ndarray, np.ndarray] + The rotation matrix and translation vector. + """ + # Load the yaml file + with open(yaml_file, "r", encoding="utf-8") as f: + yaml_data = yaml.safe_load(f) + x = yaml_data["publish_camera_extrinsics"]["ros__parameters"]["x"] + y = yaml_data["publish_camera_extrinsics"]["ros__parameters"]["y"] + z = yaml_data["publish_camera_extrinsics"]["ros__parameters"]["z"] + roll = yaml_data["publish_camera_extrinsics"]["ros__parameters"]["roll"] + pitch = yaml_data["publish_camera_extrinsics"]["ros__parameters"]["pitch"] + yaw = yaml_data["publish_camera_extrinsics"]["ros__parameters"]["yaw"] + + # Create the rotation matrix and translation vector + R_cam2gripper = R.from_euler("ZYX", [yaw, pitch, roll]).as_matrix() + t_cam2gripper = np.array([x, y, z]).reshape((3, 1)) + return R_cam2gripper, t_cam2gripper + + def show_img(self, rate_hz: float = 10.0): + """ + Show the latest RGB image. + """ + if not self.run_node_online: + return + # Configuration for the timeout + rate = self.create_rate(rate_hz) + try: + cv2.namedWindow("RGB Image", cv2.WINDOW_NORMAL) + while rclpy.ok(): + with self.latest_img_lock: + img = self.latest_annotated_img + if img is not None: + cv2.imshow("RGB Image", img) + cv2.waitKey(int(1000 // rate_hz)) + rate.sleep() + self.destroy_rate(rate) + except (KeyboardInterrupt, rclpy.exceptions.ROSInterruptException): + pass + + +def spin(node: Node, executor: rclpy.executors.Executor): + """ + Spin the node in the background. + + Parameters + ---------- + node : Node + The node to spin. + executor : rclpy.executors.Executor + The executor to spin. + """ + try: + rclpy.spin(node, executor) + except rclpy.executors.ExternalShutdownException: + pass + + +def main(): + """ + Initialize and execute the node. + """ + # Initialize the node + rclpy.init() + node = CalibrateCameraNode() + print("Node created.", flush=True) + + # Spin in the background, as the node initializes + executor = MultiThreadedExecutor(num_threads=4) + spin_thread = threading.Thread( + target=spin, + args=(node,), + kwargs={"executor": executor}, + daemon=True, + ) + spin_thread.start() + + # Run the node + print("Initializing node", flush=True) + initialized = node.initialize() + show_img_thread = None + if initialized: + print("Node initialized", flush=True) + # Show the image stream in the background + show_img_thread = threading.Thread( + target=node.show_img, + daemon=True, + ) + show_img_thread.start() + + # Run the node in the main thread + try: + node.run() + except KeyboardInterrupt: + zero_twist = TwistStamped() + zero_twist.header.frame_id = node.moveit2.base_link_name + node.twist_pub.publish(zero_twist) + + # Cleanly terminate the node + print("Terminating node", flush=True) + node.destroy_node() + try: + rclpy.shutdown() + except rclpy._rclpy_pybind11.RCLError: # pylint: disable=protected-access + pass + if show_img_thread: + show_img_thread.join() + spin_thread.join() + print("Terminated", flush=True) + + +if __name__ == "__main__": + main() diff --git a/ada_calibrate_camera/ada_calibrate_camera/camera_calibration.py b/ada_calibrate_camera/ada_calibrate_camera/camera_calibration.py new file mode 100644 index 0000000..640413b --- /dev/null +++ b/ada_calibrate_camera/ada_calibrate_camera/camera_calibration.py @@ -0,0 +1,514 @@ +""" +This module defines the CameraCalibration class, which allows users to add samples +consisting of an RGB image, a gripper2base transform, and a target2cam transform. +It saves the data in the specified data directory, and computes the cam2gripper +transform. It also computes the transformation error. +""" + +# Standard imports +from datetime import datetime +import os +from typing import List, Optional, Tuple, Union + +# Third-party imports +import cv2 +from geometry_msgs.msg import PoseStamped +import numpy as np +from scipy.spatial.transform import Rotation as R + +# Local imports +from ada_calibrate_camera.helpers import pose_to_rot_trans + +# pylint: disable=invalid-name +# Although names like R_gripper2base are not snake case, they align with OpenCV +# conventions. + + +class CameraCalibration: + """ + This class performs camera calibration. It allows users to add samples, which + consist of an RGB image, a gripper2base transform, and a target2cam transform. + It saves the data in the specified data directory, and computes the cam2gripper + transform. It also computes the transformation error. + """ + + # pylint: disable=too-many-instance-attributes + # One over is okay. + + # pylint: disable=dangerous-default-value + def __init__( + self, + data_dir: Optional[str] = None, + methods: List[int] = [cv2.CALIB_HAND_EYE_ANDREFF], + ): + """ + Initialize the CameraCalibration. + + Parameters + ---------- + data_dir : Optional[str] + The directory to save the data. + methods : List[int] + The hand-eye calibration methods. + """ + # Saving data in a folder corresponding to the datetime: YYYY_MM_DD_HH_MM_SS + self.data_dir = None + if data_dir is not None: + folder_name = datetime.now().strftime("%Y_%m_%d_%H_%M_%S") + self.data_dir = os.path.join(data_dir, folder_name) + print(f"Saving data to: {self.data_dir}", flush=True) + os.makedirs(self.data_dir, exist_ok=True) + self.sample_i = 0 + + # Hand-eye calibration method + self.methods = methods + + # Tracking samples + self.rgb_images = [] + self.Rs_gripper2base = [] + self.ts_gripper2base = [] + self.Rs_target2cam = [] + self.ts_target2cam = [] + + def add_sample( + self, + rgb_img: np.ndarray, + gripper2base: Union[PoseStamped, Tuple[np.ndarray, np.ndarray]], + target2cam: Union[PoseStamped, Tuple[np.ndarray, np.ndarray]], + save_data: bool = True, + ): + """ + Add a sample to the camera calibration. + + Parameters + ---------- + rgb_img : np.ndarray + The RGB image. + gripper2base : Union[PoseStamped, Tuple[np.ndarray, np.ndarray]] + The gripper2base transform. + target2cam : Union[PoseStamped, Tuple[np.ndarray, np.ndarray]] + The target2cam transform. + save_data : bool + Whether to save the data. + """ + if isinstance(gripper2base, PoseStamped): + R_gripper2base, t_gripper2base = pose_to_rot_trans( + gripper2base, rot_vec=False + ) + else: + R_gripper2base, t_gripper2base = gripper2base + if np.prod(R_gripper2base.shape) == 3: + R_gripper2base = R_gripper2base.reshape((3,)) + if np.prod(t_gripper2base.shape) == 3: + t_gripper2base = t_gripper2base.reshape((3,)) + if isinstance(target2cam, PoseStamped): + R_target2cam, t_target2cam = pose_to_rot_trans(target2cam, rot_vec=False) + else: + R_target2cam, t_target2cam = target2cam + if np.prod(R_target2cam.shape) == 3: + R_target2cam = R_target2cam.reshape((3,)) + if np.prod(t_target2cam.shape) == 3: + t_target2cam = t_target2cam.reshape((3,)) + self.rgb_images.append(rgb_img) + self.Rs_gripper2base.append(R_gripper2base) + self.ts_gripper2base.append(t_gripper2base) + self.Rs_target2cam.append(R_target2cam) + self.ts_target2cam.append(t_target2cam) + + # Save the data + if save_data and self.data_dir is not None: + self.save_sample( + self.data_dir, + self.sample_i, + rgb_img, + R_gripper2base, + t_gripper2base, + R_target2cam, + t_target2cam, + ) + self.sample_i += 1 + + def add_samples_from_folder( + self, + data_dir: str, + exclude_samples: Optional[List[int]] = None, + ): + """ + Add samples from a folder. + + Parameters + ---------- + data_dir : str + The directory to load the data from. + exclude_samples : Optional[List[int]] + The samples to exclude. + """ + if not os.path.exists(data_dir): + print(f"Data directory {data_dir} does not exist.", flush=True) + return + if exclude_samples is None: + exclude_samples = [] + + # Load the samples + sample_i = -1 + while True: + sample_i += 1 + if sample_i in exclude_samples: + continue + if not os.path.exists(os.path.join(data_dir, f"{sample_i}_rgb_img.png")): + break + ( + rgb_img, + R_gripper2base, + t_gripper2base, + R_target2cam, + t_target2cam, + ) = self.load_sample(data_dir, sample_i) + self.rgb_images.append(rgb_img) + self.Rs_gripper2base.append(R_gripper2base) + self.ts_gripper2base.append(t_gripper2base) + self.Rs_target2cam.append(R_target2cam) + self.ts_target2cam.append(t_target2cam) + + @staticmethod + def save_sample( + data_dir: str, + sample_i: int, + rgb_img: np.ndarray, + R_gripper2base: np.ndarray, + t_gripper2base: np.ndarray, + R_target2cam: np.ndarray, + t_target2cam: np.ndarray, + ) -> None: + """ + Save the sample to the data directory. + + Parameters + ---------- + data_dir : str + The directory to save the data. + sample_i : int + The sample index. + rgb_img : np.ndarray + The RGB image. + R_gripper2base : np.ndarray + The gripper2base rotation vector. + t_gripper2base : np.ndarray + The gripper2base translation vector. + R_target2cam : np.ndarray + The target2cam rotation vector. + t_target2cam : np.ndarray + The target2cam translation vector. + """ + # pylint: disable=too-many-arguments + # Necessay to get all the data for this sample. + cv2.imwrite(os.path.join(data_dir, f"{sample_i}_rgb_img.png"), rgb_img) + np.savez_compressed( + os.path.join(data_dir, f"{sample_i}_sample.npz"), + R_gripper2base=R_gripper2base, + t_gripper2base=t_gripper2base, + R_target2cam=R_target2cam, + t_target2cam=t_target2cam, + ) + + @staticmethod + def load_sample( + data_dir: str, + sample_i: int, + ) -> Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]: + """ + Load the sample from the data directory. + + Parameters + ---------- + data_dir : str + The directory to save the data. + sample_i : int + The sample index. + + Returns + ------- + np.ndarray + The RGB image. + np.ndarray + The gripper2base rotation vector. + np.ndarray + The gripper2base translation vector. + np.ndarray + The target2cam rotation vector. + np.ndarray + The target2cam translation vector. + """ + rgb_img = cv2.imread(os.path.join(data_dir, f"{sample_i}_rgb_img.png")) + data = np.load(os.path.join(data_dir, f"{sample_i}_sample.npz")) + return ( + rgb_img, + data["R_gripper2base"], + data["t_gripper2base"], + data["R_target2cam"], + data["t_target2cam"], + ) + + @staticmethod + def translation_error( + t1: np.ndarray, + t2: np.ndarray, + ) -> float: + """ + Compute the translation error between two translation vectors. + + Parameters + ---------- + t1 : np.ndarray + The first translation vector. + t2 : np.ndarray + The second translation vector. + + Returns + ------- + float + The translation error. + """ + return np.linalg.norm(t1 - t2) + + @staticmethod + def rotation_error( + R1: np.ndarray, + R2: np.ndarray, + ) -> float: + """ + Compute the rotation error between two rotation matrices. + + Parameters + ---------- + R1 : np.ndarray + The first rotation matrix. + R2 : np.ndarray + The second rotation matrix. + + Returns + ------- + float + The rotation error. + """ + return (R.from_matrix(R1).inv() * R.from_matrix(R2)).magnitude() + + def compute_calibration( + self, + save_data: bool = False, + ref_R_cam2gripper: Optional[np.ndarray] = None, + ref_t_cam2gripper: Optional[np.ndarray] = None, + ref_translation_error_threshold: Optional[float] = None, + ref_rotation_error_threshold: Optional[float] = None, + verbose: bool = False, + ) -> Tuple[ + Optional[np.ndarray], + Optional[np.ndarray], + Optional[float], + Optional[float], + Optional[int], + ]: + """ + Compute the camera calibration and return the rotation and translation + errors. For the rotation and translation errors, we compute the pose of the + target in the base frame across all samples. In theory, this should be the + same across all samples. We then take the pairwise translation and rotation + distance between the samples, and average them. + + References: + - Eq 27A and 28A here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9581431/pdf/pone.0273261.pdf + - The derivation of AX=XB for eye-in-hand calibration from: + https://docs.opencv.org/4.5.4/d9/d0c/group__calib3d.html#gaebfc1c9f7434196a374c382abf43439b + + Parameters + ---------- + save_data : bool + Whether to save the data. + ref_R_cam2gripper : Optional[np.ndarray] + The reference rotation matrix from the camera to the gripper. + ref_t_cam2gripper : Optional[np.ndarray] + The reference translation vector from the camera to the gripper. + ref_translation_error_threshold : Optional[float] + The reference translation error threshold. If the translation error is + greater than this threshold, the calibration is considered invalid. + ref_rotation_error_threshold : Optional[float] + The reference rotation error threshold. If the rotation error is greater + than this threshold, the calibration is considered invalid. + verbose : bool + Whether to print the calibration results. + + Returns + ------- + np.ndarray + The rotation matrix from the camera to the gripper. + np.ndarray + The translation vector from the camera to the gripper. + float + The rotation error. + float + The translation error. + int + The calibration method that got the least error. + """ + # pylint: disable=too-many-locals, too-many-branches, too-many-statements, too-many-arguments + # The comaprison to the reference data requires many arguments. + + if len(self.Rs_gripper2base) < 3: + print("Need at least 3 samples to calibrate the camera.", flush=True) + return None, None, None, None, None + + # Check if we have reference data + check_reference = False + if ( + ref_R_cam2gripper is not None + and ref_t_cam2gripper is not None + and ( + ref_translation_error_threshold is not None + or ref_rotation_error_threshold is not None + ) + ): + check_reference = True + + # Compute the camera extrinsics calibration + best_R_cam2gripper = None + best_t_cam2gripper = None + best_translation_error = np.inf + best_rotation_error = np.inf + best_method = None + for method in self.methods: + R_cam2gripper, t_cam2gripper = cv2.calibrateHandEye( + self.Rs_gripper2base, + self.ts_gripper2base, + self.Rs_target2cam, + self.ts_target2cam, + method=method, + ) + + # Check if the calibration is valid relative to the reference + if check_reference: + translation_error = CameraCalibration.translation_error( + ref_t_cam2gripper, t_cam2gripper + ) + rotation_error = CameraCalibration.rotation_error( + ref_R_cam2gripper, R_cam2gripper + ) + if ( + ref_translation_error_threshold is not None + and translation_error > ref_translation_error_threshold + ): + print( + ( + f"WARNING: Translation error from reference is {translation_error}, greater than " + f"the threshold {ref_translation_error_threshold}. Rejecting." + ), + flush=True, + ) + continue + if ( + ref_rotation_error_threshold is not None + and rotation_error > ref_rotation_error_threshold + ): + print( + ( + f"WARNING: Rotation error from reference is {rotation_error}, greater than " + f"the threshold {ref_rotation_error_threshold}. Rejecting." + ), + flush=True, + ) + continue + + # Convert to a homogenous transform + T_cam2gripper = np.eye(4) + T_cam2gripper[:3, :3] = R_cam2gripper + T_cam2gripper[:3, 3] = t_cam2gripper.reshape((3,)) + + # For each sample, get the target's pose is base frame + Rs_target2base = [] + ts_target2base = [] + # pylint: disable=consider-using-enumerate + for i in range(len(self.Rs_target2cam)): + # Get the homogenous transform from the gripper to the base + T_gripper2base = np.eye(4) + if self.Rs_gripper2base[i].shape == (3,): + T_gripper2base[:3, :3] = R.from_rotvec( + self.Rs_gripper2base[i] + ).as_matrix() + else: + T_gripper2base[:3, :3] = self.Rs_gripper2base[i] + T_gripper2base[:3, 3] = self.ts_gripper2base[i] + + # Get the homogenous transform from the target to the camera + T_target2cam = np.eye(4) + if self.Rs_target2cam[i].shape == (3,): + T_target2cam[:3, :3] = R.from_rotvec( + self.Rs_target2cam[i] + ).as_matrix() + else: + T_target2cam[:3, :3] = self.Rs_target2cam[i] + T_target2cam[:3, 3] = self.ts_target2cam[i] + + # Compute the homogenous transform from the target to the base + T_target2base = T_gripper2base @ T_cam2gripper @ T_target2cam + + # Extract the rotation and translation + Rs_target2base.append(R.from_matrix(T_target2base[:3, :3])) + ts_target2base.append(T_target2base[:3, 3]) + + # Compute the translation and rotation errors + translation_errors = [] + rotation_errors = [] + for i in range( + len(Rs_target2base) + ): # pylint: disable=consider-using-enumerate + for j in range(i + 1, len(Rs_target2base)): + translation_errors.append( + CameraCalibration.translation_error( + ts_target2base[i], ts_target2base[j] + ) + ) + rotation_errors.append( + CameraCalibration.rotation_error( + Rs_target2base[i].as_matrix(), Rs_target2base[j].as_matrix() + ) + ) + + # Average the errors + translation_error = np.percentile(translation_errors, 50) + rotation_error = np.percentile(rotation_errors, 50) + + # Print the calibration results + if verbose: + print(f"Method: {method}", flush=True) + print(f"Translation error: {translation_error}", flush=True) + print(f"Rotation error: {rotation_error}", flush=True) + print( + f"R_cam2gripper: {R.from_matrix(R_cam2gripper).as_euler('ZYX')}", + flush=True, + ) + print(f"t_cam2gripper: {t_cam2gripper}", flush=True) + + # Save the best calibration + if translation_error < best_translation_error: + best_translation_error = translation_error + best_rotation_error = rotation_error + best_R_cam2gripper = R_cam2gripper + best_t_cam2gripper = t_cam2gripper + best_method = method + + # Save the calibration + if save_data and self.data_dir is not None and best_R_cam2gripper is not None: + np.savez_compressed( + os.path.join(self.data_dir, f"{self.sample_i}_calib.npz"), + R_cam2gripper=best_R_cam2gripper, + t_cam2gripper=best_t_cam2gripper, + translation_error=best_translation_error, + rotation_error=best_rotation_error, + ) + + return ( + best_R_cam2gripper, + best_t_cam2gripper, + best_rotation_error, + best_translation_error, + best_method, + ) diff --git a/ada_calibrate_camera/ada_calibrate_camera/charuco_detector.py b/ada_calibrate_camera/ada_calibrate_camera/charuco_detector.py new file mode 100644 index 0000000..5f05cbe --- /dev/null +++ b/ada_calibrate_camera/ada_calibrate_camera/charuco_detector.py @@ -0,0 +1,176 @@ +""" +This module defines the CharucoDetector class, which is used to detect a charucoboard in an image. +""" + +# Standard imports +import copy +from typing import Optional, Tuple + +# Third-party imports +import cv2 +import numpy as np + +# Local imports + + +class CharucoDetector: + """ + This class returns the pose of a charucoboard in an image. + """ + + def __init__( + self, + n_rows: int, + n_cols: int, + sq_length_m: float, + marker_length_m: float, + predefined_dictionary: int, + ): + """ + Initialize the CharucoDetector. + + Parameters + ---------- + n_rows : int + The number of rows in the charucoboard. + n_cols : int + The number of columns in the charucoboard. + sq_length_m : float + The length of a square in the charucoboard. + marker_length_m : float + The length of a marker in the charucoboard. + predefined_dictionary : int + The predefined dictionary to use, e.g., cv2.aruco.DICT_4X4_50. + """ + # pylint: disable=too-many-arguments + # This is meant to be a flexible class, hence the many arguments. + self.camera_matrix = None + self.dist_coeffs = None + self.board = cv2.aruco.CharucoBoard_create( + squaresX=n_cols, + squaresY=n_rows, + squareLength=sq_length_m, + markerLength=marker_length_m, + dictionary=cv2.aruco.getPredefinedDictionary(predefined_dictionary), + ) + self.detector_params = cv2.aruco.DetectorParameters_create() + + def set_camera_intrinsics(self, camera_matrix: np.ndarray, dist_coeffs: np.ndarray): + """ + Set the camera intrinsics. + + Parameters + ---------- + camera_matrix : np.ndarray + The camera matrix. + dist_coeffs : np.ndarray + The distortion coefficients. + """ + self.camera_matrix = camera_matrix + self.dist_coeffs = dist_coeffs + + def got_camera_intrinsics(self) -> bool: + """ + Check if the camera intrinsics have been set. + + Returns + ------- + bool + Whether the camera intrinsics have been set. + """ + return self.camera_matrix is not None + + def detect( + self, img: np.ndarray, viz: bool = False, verbose: bool = False + ) -> Tuple[bool, Optional[np.ndarray], Optional[np.ndarray], Optional[np.ndarray]]: + """ + Detect the charucoboard in the image. + + Parameters + ---------- + img : np.ndarray + The image. + viz : bool + Whether to visualize the detection. + verbose : bool + Whether to print verbose output. + + Returns + ------- + bool + Whether the charucoboard was detected. + np.ndarray + The rotation vector for the charucoboard in the camera's frame. + np.ndarray + The translation vector for the charucoboard in the camera's frame. + np.ndarray + if viz is True, the image with the charucoboard drawn on it. + + """ + # pylint: disable=too-many-return-statements + # This is meant to be a flexible function, hence the many return statements. + if self.camera_matrix is None: + print("Camera intrinsics not set.", flush=True) + return False, None, None, None + + marker_corners, marker_ids, _ = cv2.aruco.detectMarkers( + img, + self.board.dictionary, + parameters=self.detector_params, + cameraMatrix=self.camera_matrix, + distCoeff=self.dist_coeffs, + ) + if marker_ids is None or len(marker_ids) == 0: + if verbose: + print("Failed to detect the markers.", flush=True) + return False, None, None, None + _, charuco_corners, charuco_ids = cv2.aruco.interpolateCornersCharuco( + marker_corners, + marker_ids, + img, + self.board, + cameraMatrix=self.camera_matrix, + distCoeffs=self.dist_coeffs, + ) + if charuco_corners is None or len(charuco_corners) == 0: + if verbose: + print("Failed to interpolate the charucoboard corners.", flush=True) + return False, None, None, None + if viz: + retval_img = copy.deepcopy(img) + retval_img = cv2.aruco.drawDetectedMarkers( + retval_img, marker_corners, marker_ids, (0, 255, 0) + ) + retval_img = cv2.aruco.drawDetectedCornersCharuco( + retval_img, charuco_corners, charuco_ids, (255, 0, 0) + ) + if len(charuco_ids) >= 4: + rvec = np.zeros((3, 1)) + tvec = np.zeros((3, 1)) + succ, rvec, tvec = cv2.aruco.estimatePoseCharucoBoard( + charuco_corners, + charuco_ids, + self.board, + self.camera_matrix, + self.dist_coeffs, + rvec, + tvec, + ) + if not succ: + if verbose: + print("Failed to get charucoboard pose.", flush=True) + return False, None, None, retval_img + if viz: + cv2.drawFrameAxes( + retval_img, + self.camera_matrix, + self.dist_coeffs, + rvec, + tvec, + 0.1, + ) + return True, rvec, tvec, retval_img + return True, rvec, tvec, None + if verbose: + print("Failed to detect the charucoboard.", flush=True) + return False, None, None, None diff --git a/ada_calibrate_camera/ada_calibrate_camera/helpers.py b/ada_calibrate_camera/ada_calibrate_camera/helpers.py new file mode 100644 index 0000000..1730854 --- /dev/null +++ b/ada_calibrate_camera/ada_calibrate_camera/helpers.py @@ -0,0 +1,172 @@ +""" +This module contains helper functions for calibrating the camera. +""" + +# Standard imports +from typing import Tuple, Optional + +# Third-party imports +import numpy as np +from geometry_msgs.msg import ( + Point, + Pose, + PoseStamped, + Quaternion, + Transform, + TwistStamped, + Vector3, +) +from scipy.spatial.transform import Rotation as R +import ros2_numpy + + +def pose_to_rot_trans( + pose: PoseStamped, rot_vec: bool = True +) -> Tuple[np.ndarray, np.ndarray]: + """ + Disaggregates a into its rotation and translation components. + + Parameters + ---------- + pose : PoseStamped + The pose. + rot_vec : bool + Whether to return the rotation as a rotation vector or a matrix + + Returns + ------- + np.ndarray + The rotation vector. + np.ndarray + The translation vector. + """ + if rot_vec: + rot = R.from_quat(ros2_numpy.numpify(pose.pose.orientation)).as_rotvec() + else: + rot = R.from_quat(ros2_numpy.numpify(pose.pose.orientation)).as_matrix() + trans = ros2_numpy.numpify(pose.pose.position) + return rot, trans + + +def pose_to_matrix(pose: Pose) -> np.ndarray: + """ + Convert a Pose message to a homogenous transformation matrix. + + Parameters + ---------- + pose : Pose + The pose. + + Returns + ------- + np.ndarray + The homogenous transformation matrix. + """ + M = np.eye(4) + M[:3, :3] = R.from_quat(ros2_numpy.numpify(pose.orientation)).as_matrix() + M[:3, 3] = ros2_numpy.numpify(pose.position) + return M + + +def transform_to_matrix(transform: Transform) -> np.ndarray: + """ + Convert a Transform message to a homogenous transformation matrix. + + Parameters + ---------- + transform : Transform + The transform. + + Returns + ------- + np.ndarray + The homogenous transformation matrix. + """ + M = np.eye(4) + M[:3, :3] = R.from_quat(ros2_numpy.numpify(transform.rotation)).as_matrix() + M[:3, 3] = ros2_numpy.numpify(transform.translation) + return M + + +def matrix_to_pose(M: np.ndarray) -> Pose: + """ + Convert a homogenous transformation matrix to a Pose message. + + Parameters + ---------- + M : np.ndarray + The homogenous transformation matrix. + + Returns + ------- + Pose + The pose. + """ + pose = Pose() + pose.position = ros2_numpy.msgify( + Point, + M[:3, 3], + ) + pose.orientation = ros2_numpy.msgify( + Quaternion, + R.from_matrix(M[:3, :3]).as_quat(), + ) + return pose + + +def pose_to_twist( + pose_stamped: PoseStamped, + max_linear_speed: float = 0.1, # m/s + max_angular_speed: float = 0.5, # rad/s + round_decimals: Optional[int] = 6, + rate_hz: float = 10.0, +) -> TwistStamped: + """ + Convert a PoseStamped message to a TwistStamped message. Essentially, it + returns the lienar and angular velocities to execute for 1/rate_hz sec to + move the pose's frame_id to the pose. Based on + ada_feeding/ada_feeding/behaviors/ros/msgs.py's PoseStampedToTwistStamped behavior. + """ + # pylint: disable=too-many-locals, too-many-arguments + # Okay to provide considerable flexibility. + + # For the linear velocity, normalize the pose's position and multiply + # it by the linear_speed + linear_displacement = ros2_numpy.numpify(pose_stamped.pose.position) + linear_distance = np.linalg.norm(linear_displacement) + linear_speed = min(linear_distance * rate_hz, max_linear_speed) + linear_velocity = linear_displacement / linear_distance * linear_speed + + # Round it + if round_decimals is not None: + linear_velocity = np.round(linear_velocity, round_decimals) + + # Convert to a msg + linear_msg = ros2_numpy.msgify(Vector3, linear_velocity) + + # For the angular velocity, convert the pose's orientation to a + # rotation vector, normalize it, and multiply it by the angular_speed + angular_displacement = R.from_quat( + ros2_numpy.numpify(pose_stamped.pose.orientation) + ).as_rotvec() + angular_distance = np.linalg.norm(angular_displacement) + angular_speed = min(angular_distance * rate_hz, max_angular_speed) + if angular_distance == 0.0: + angular_velocity = np.zeros(3) + else: + angular_velocity = angular_displacement / angular_distance * angular_speed + + # Round it + if round_decimals is not None: + angular_velocity = np.round(angular_velocity, round_decimals) + + # Convert to a msg + angular_msg = ros2_numpy.msgify(Vector3, angular_velocity) + + # Create the twist stamped message + twist_stamped = TwistStamped() + twist_stamped.header = pose_stamped.header + twist_stamped.twist.linear = linear_msg + twist_stamped.twist.angular = angular_msg + + return twist_stamped diff --git a/ada_calibrate_camera/ada_calibrate_camera/publish_camera_extrinsics_node.py b/ada_calibrate_camera/ada_calibrate_camera/publish_camera_extrinsics_node.py new file mode 100755 index 0000000..7287255 --- /dev/null +++ b/ada_calibrate_camera/ada_calibrate_camera/publish_camera_extrinsics_node.py @@ -0,0 +1,100 @@ +# !/usr/bin/env python3 +""" +This module contains a rclpy ROS2 node that takes in parameters for the translation +and rotation (quaternion) as well as the frame_id's and publishes the requested transform. +""" + +# Standard imports + +# Third-party imports +from geometry_msgs.msg import TransformStamped +import rclpy +from rclpy.node import Node +from scipy.spatial.transform import Rotation as R +from tf2_ros.static_transform_broadcaster import StaticTransformBroadcaster + +# Local imports + + +class PublishCameraExtrinsics(Node): + """ + This class defines a ROS2 node that takes in parameters for the translation + and rotation (quaternion) as well as the frame_id's and publishes the requested transform. + """ + + def __init__(self): + """ + Initializes the node and sets up the timer to publish the transform + """ + super().__init__("publish_camera_extrinsics") + self.declare_parameters( + namespace="", + parameters=[ + ("frame_id", "j2n6s200_end_effector"), + ("child_frame_id", "camera_color_optical_frame"), + ("x", 0.0), + ("y", 0.0), + ("z", 0.0), + ("roll", 0.0), + ("pitch", 0.0), + ("yaw", 0.0), + ("rate_hz", 10.0), + ], + ) + + self.tf_broadcaster = StaticTransformBroadcaster(self) + + timer_interval = ( + 1.0 / self.get_parameter("rate_hz").get_parameter_value().double_value + ) + self.timer = self.create_timer(timer_interval, self.publish_transform) + + def publish_transform(self): + """ + Publishes the transform from the frame_id to the child_frame_id + """ + transform = TransformStamped() + transform.header.stamp = self.get_clock().now().to_msg() + transform.header.frame_id = ( + self.get_parameter("frame_id").get_parameter_value().string_value + ) + transform.child_frame_id = ( + self.get_parameter("child_frame_id").get_parameter_value().string_value + ) + transform.transform.translation.x = ( + self.get_parameter("x").get_parameter_value().double_value + ) + transform.transform.translation.y = ( + self.get_parameter("y").get_parameter_value().double_value + ) + transform.transform.translation.z = ( + self.get_parameter("z").get_parameter_value().double_value + ) + quat = R.from_euler( + "ZYX", + [ + self.get_parameter("yaw").get_parameter_value().double_value, + self.get_parameter("pitch").get_parameter_value().double_value, + self.get_parameter("roll").get_parameter_value().double_value, + ], + ).as_quat() + transform.transform.rotation.x = quat[0] + transform.transform.rotation.y = quat[1] + transform.transform.rotation.z = quat[2] + transform.transform.rotation.w = quat[3] + + self.tf_broadcaster.sendTransform(transform) + + +def main(): + """ + The main function to create and spin the node + """ + rclpy.init() + node = PublishCameraExtrinsics() + rclpy.spin(node) + rclpy.shutdown() + + +if __name__ == "__main__": + main() diff --git a/ada_calibrate_camera/calibrate_camera_start.py b/ada_calibrate_camera/calibrate_camera_start.py new file mode 100644 index 0000000..831dd7f --- /dev/null +++ b/ada_calibrate_camera/calibrate_camera_start.py @@ -0,0 +1,285 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +This module starts all the screen sessions to run the ada_feeding demo. +""" + +import asyncio +import argparse +import getpass +import os +import sys + +# pylint: disable=duplicate-code +# This is intentionally similar to start_nano.py + +parser = argparse.ArgumentParser() +parser.add_argument( + "--sim", + default="real", + help=( + "`real` or `mock` (default `real`). `real` executes all commands for running " + "the calibrate camera code on the real robot. `mock` uses a simulated robot." + ), +) +parser.add_argument( + "-t", + "--termination_wait_secs", + default=5, + help="How long (secs) to wait for the code within screens to terminate (default, 5)", +) +parser.add_argument( + "-l", + "--launch_wait_secs", + default=0.1, + help=( + "How long (secs) to wait between running code in screens. Not that " + "too low of a value can result in commands getting rearranged. (default, 0.1)" + ), +) +parser.add_argument( + "-c", + "--close", + action="store_true", + help="If set, only terminate the code in the screens.", +) +parser.add_argument( + "--dev", + action="store_true", + help=( + "If set, show RVIZ in `moveit`." + ), +) +parser.add_argument( + "--real_domain_id", + default=42, + type=int, + help=( + "If sim is set to real, export this ROS_DOMAIN_ID before running code in " + "every screen session. (default: 42)" + ), +) + + +async def get_existing_screens(): + """ + Get a list of active screen sessions. + + Adapted from + https://serverfault.com/questions/886405/create-screen-session-in-background-only-if-it-doesnt-already-exist + """ + proc = await asyncio.create_subprocess_shell( + "screen -ls", stdout=asyncio.subprocess.PIPE + ) + stdout, _ = await proc.communicate() + existing_screens = [ + line.split(".")[1].split("\t")[0].rstrip() + for line in stdout.decode("utf-8").splitlines() + if line.startswith("\t") + ] + return existing_screens + + +async def execute_command(screen_name: str, command: str, indent: int = 8) -> None: + """ + Execute a command in a screen. + """ + global sudo_password # pylint: disable=global-statement + indentation = " " * indent + printable_command = command.replace("\003", "SIGINT") + print(f"# {indentation}`{printable_command}`") + if command != "\003": + command += "\n" + await asyncio.create_subprocess_shell( + f"screen -S {screen_name} -X stuff '{command}'" + ) + await asyncio.sleep(args.launch_wait_secs) + if command.startswith("sudo"): + if sudo_password is None: + sudo_password = getpass.getpass( + prompt=f"# {indentation}Enter sudo password: " + ) + await asyncio.create_subprocess_shell( + f"screen -S {screen_name} -X stuff '{sudo_password}\n'" + ) + await asyncio.sleep(args.launch_wait_secs) + elif command.startswith("ssh"): + ssh_password = getpass.getpass(prompt=f"# {indentation}Enter ssh password: ") + await asyncio.create_subprocess_shell( + f"screen -S {screen_name} -X stuff '{ssh_password}\n'" + ) + await asyncio.sleep(args.launch_wait_secs) + + +async def main(args: argparse.Namespace, pwd: str) -> None: + """ + Start the ada_feeding demo. + + Args: + args: The command-line arguments. + pwd: The absolute path to the current directory. + """ + + # pylint: disable=too-many-branches, too-many-statements + # This is meant to be a flexible function, hence the many branches and statements. + # pylint: disable=redefined-outer-name + # That is okay in this case. + + print( + "################################################################################" + ) + if not args.close: + print("# Starting the calibrate_camera code") + print("# Prerequisites / Notes:") + print("# 1. Be in the top-level of your colcon workspace") + print( + "# 2. Your workspace should be built (e.g., `colcon build --symlink-install`)" + ) + else: + print("# Terminating the calibrate_camera code") + print( + "################################################################################" + ) + + # Determine which screen sessions to start and what commands to run + screen_sessions = { + "ft": [ + "ros2 run forque_sensor_hardware forque_sensor_hardware --ros-args -p host:=ft-sensor-2", + ], + "camera": [ + "ssh nano -t './start_nano.sh'", + ], + "receiver": [ + "ros2 launch nano_bridge receiver.launch.xml", + ], + "moveit": [ + "Xvfb :5 -screen 0 800x600x24 &" if not args.dev else "", + "export DISPLAY=:5" if not args.dev else "", + ( + f"ros2 launch ada_moveit demo.launch.py use_rviz:={'true' if args.dev else 'false'} " + f"sim:={args.sim} use_octomap:=false" + ), + ], + "calibrate": [ + "export DISPLAY=:5" if not args.dev else "", + ( + "ros2 run ada_calibrate_camera calibrate_camera --ros-args " + f"--params-file {os.path.join(pwd, 'src/ada_ros2/ada_calibrate_camera/config/calibrate_camera.yaml')}" + ) + ], + } + close_commands = {} + initial_close_commands = ["\003"] + initial_start_commands = [ + f"cd {pwd}", + "source install/setup.bash", + f"export ROS_DOMAIN_ID={args.real_domain_id}", + ] + for screen_name, commands in screen_sessions.items(): + screen_sessions[screen_name] = initial_start_commands + commands + if screen_name not in close_commands: + close_commands[screen_name] = [] + close_commands[screen_name] = ( + initial_close_commands + close_commands[screen_name] + ) + + # Determine which screens are already running + print("# Checking for existing screen sessions") + terminated_screen = False + existing_screens = await get_existing_screens() + for screen_name in screen_sessions: + if screen_name in existing_screens: + print(f"# Found session `{screen_name}`: ") + for command in close_commands[screen_name]: + await execute_command(screen_name, command) + terminated_screen = True + elif not args.close: + print(f"# Creating session `{screen_name}`") + await asyncio.create_subprocess_shell(f"screen -dmS {screen_name}") + await asyncio.sleep(args.launch_wait_secs) + + print( + "################################################################################" + ) + + if not args.close: + # Sleep for a bit to allow the screens to terminate + if terminated_screen: + print(f"# Waiting {args.termination_wait_secs} secs for code to terminate") + await asyncio.sleep(args.termination_wait_secs) + print( + "################################################################################" + ) + + # Start the screen sessions + print("# Starting robot feeding code") + for screen_name, commands in screen_sessions.items(): + print(f"# `{screen_name}`") + for command in commands: + await execute_command(screen_name, command) + print( + "################################################################################" + ) + + print("# Done! Next steps:") + print( + "# 1. Check individual screens to verify code is working as expected." + ) + print("# 2. `screen -r calibrate` to actually run calibration.") + + +def check_pwd_is_colcon_workspace() -> str: + """ + Check that the script is being run from the top-level colcon workspace. + Return the absolute path to the current directory. + """ + # The below are a smattering of directories and files that should exist in the + # top-level colcon workspace. + dirs_to_check = ["src", "build", "install", "log"] + files_to_check = [ + "src/feeding_web_interface/feedingwebapp/server.js", + "src/feeding_web_interface/feedingwebapp/.env", + "src/feeding_web_interface/feedingwebapp/start_robot_browser.js", + "src/ada_feeding/ada_feeding_perception/config/republisher.yaml", + ] + for dir_to_check in dirs_to_check: + if not os.path.isdir(dir_to_check): + print( + f"ERROR: This script must be run from the top-level colcon workspace. Could not find `{dir_to_check}`", + file=sys.stderr, + ) + sys.exit(1) + for file_to_check in files_to_check: + if not os.path.isfile(file_to_check): + print( + f"ERROR: This script must be run from the top-level colcon workspace. Could not find `{file_to_check}`", + file=sys.stderr, + ) + sys.exit(1) + + # Return the absolute path to the current directory + return os.path.abspath(".") + + +if __name__ == "__main__": + # Get the arguments + args = parser.parse_args() + + # Ensure the script is not being run as sudo. Sudo has a different screen + # server and may have different versions of libraries installed. + if os.geteuid() == 0: + print( + "ERROR: This script should not be run as sudo. Run as a regular user.", + file=sys.stderr, + ) + sys.exit(1) + + # Check that the script is being run from the top-level colcon workspace + pwd = check_pwd_is_colcon_workspace() + + # Run the main function + sudo_password = None # pylint: disable=invalid-name + asyncio.run(main(args, pwd)) + + # Return success + sys.exit(0) diff --git a/ada_calibrate_camera/config/calibrate_camera.yaml b/ada_calibrate_camera/config/calibrate_camera.yaml new file mode 100644 index 0000000..1739f31 --- /dev/null +++ b/ada_calibrate_camera/config/calibrate_camera.yaml @@ -0,0 +1,32 @@ +calibrate_camera: + ros__parameters: + # Frame names + robot_end_effector_frame: "forkTip" + extrinsics_base_frame: "j2n6s200_end_effector" + + # Whether to run camera calibration online or not + run_online: true + # Where to save/load calibration data. + # NOTE: Although it is not good practice to hardcode paths, the only way to avoid this is to + # save the files to the built package's share directory, which hinders pushing it to Github. + data_dir: ~/Workspace/ada_ws/src/ada_ros2/ada_calibrate_camera/data + # Where to save the calibration results + output_calib_name: ~/Workspace/ada_ws/src/ada_ros2/ada_calibrate_camera/config/calibs/auto.yaml + # A calibration file to serve as reference. If the translation or rotation error from the reference + # calibration is higher than thresholds, reject the calibration. + reference_calib_name: ~/Workspace/ada_ws/src/ada_ros2/ada_calibrate_camera/config/calibs/manual.yaml + reference_translation_error_threshold: 0.03 # meters + reference_rotation_error_threshold: 0.15 # radians + # If run_online is false, this parameter specifies the folder to load data from + offline_data_dir: "2024_10_16_17_16_32" + + # Charuco board parameters + charuco_n_rows: 9 + charuco_n_cols: 14 + charuco_sq_length_m: 0.0188 # 0.0351 + charuco_marker_length_m: 0.0138 # 0.0257 + charuco_predefined_dictionary: 5 # https://docs.opencv.org/4.x/de/d67/group__objdetect__aruco.html#ga4e13135a118f497c6172311d601ce00d + + # Hand-eye calibration method. Options: "all", "tsai", "park", "horaud", "andreff", "daniilidis" + # More details: https://docs.opencv.org/4.5.4/d9/d0c/group__calib3d.html#gad10a5ef12ee3499a0774c7904a801b99 + hand_eye_calibration_method: "park" diff --git a/ada_calibrate_camera/config/calibs/auto.yaml b/ada_calibrate_camera/config/calibs/auto.yaml new file mode 100644 index 0000000..23407ac --- /dev/null +++ b/ada_calibrate_camera/config/calibs/auto.yaml @@ -0,0 +1,14 @@ +# This file was auto-generated by the ada_calibrate_camera node. +# It used the following hand-eye calibration method: 'park'. +# The rotation error is 0.016407379903910026 and the translation error is 0.009963572232739004. +# See the README for more details. +publish_camera_extrinsics: + ros__parameters: + child_frame_id: camera_color_optical_frame + frame_id: j2n6s200_end_effector + pitch: -0.005679467602140109 + roll: -0.24264555089529039 + x: 0.04298988343257808 + y: 0.13152553261843783 + yaw: 3.057148318374235 + z: -0.14201903964568033 diff --git a/ada_calibrate_camera/config/calibs/manual.yaml b/ada_calibrate_camera/config/calibs/manual.yaml new file mode 100644 index 0000000..1b4dc97 --- /dev/null +++ b/ada_calibrate_camera/config/calibs/manual.yaml @@ -0,0 +1,14 @@ + + + + +publish_camera_extrinsics: + ros__parameters: + child_frame_id: camera_color_optical_frame + frame_id: j2n6s200_end_effector + pitch: 0.00 + roll: -0.2385 + x: 0.032 + y: 0.127 + yaw: -3.08 + z: -0.159 diff --git a/ada_calibrate_camera/data/2024_10_16_17_16_32/0_rgb_img.png b/ada_calibrate_camera/data/2024_10_16_17_16_32/0_rgb_img.png new file mode 100644 index 0000000000000000000000000000000000000000..46883c2ea011e29ae10769f707ce3887b63188d1 GIT binary patch literal 476164 zcmXtfdpwi>`~ST;)GBXU2TC#ABMM1PB2?0D(!twwa4b@?O_K9zl@4;6TS$m%9ZU|1 zEtW$i^3Ex8+FFz{(#ZL2zn9PN@%^JmkA!=By{_l=JY3hJj~zKAw_@W82!iAgvZWma zVHpsF=~<2iUnzTK^9q6p5MsH{J_zIV-MQ)M+ey$>=uT7NPKLPOvB>g^;_tG6- zTc&8Au!gd%BT3mJD1}e^6yufdg4`i)7}@vc%bP8X1phwo{HZ@&arazkq@;3IUy>^s 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