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real_eval.py
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real_eval.py
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import os
import time
import tqdm
import numpy as np
import transformations as tf
from envs.real_camera import CameraL515
from envs.real_robot import Panda
from utilities.data_utils import transform_pc, transform_dir
from utilities.vis_utils import visualize
from utilities.network_utils import send, read
if __name__ == '__main__':
print("please manually set the robot to a specific pose, make sure remote services all running")
cam2EE_path = "/home/franka/junbo/data/robot/l515_franka.npy"
cam2EE = np.load(cam2EE_path)
camera_loaded = False
robot_loaded = False
vis = True
temp_observation_path = "./temp_data/observation.npz"
temp_service_path = "./temp_data/service.npz"
temp_flag_path = "./temp_data/flag.npy"
remote_repo_path = "TODO" # TODO: set your own remote repo path
remote_observation_path = f"{remote_repo_path}/temp_data/observation.npz"
remote_service_path = f"{remote_repo_path}/temp_data/service.npz"
remote_flag_path = f"{remote_repo_path}/temp_data/flag.npy"
remote_ip = "TODO" # TODO: set your own remote ip
port = TODO # TODO: set your own remote port
username = "TODO" # TODO: set your own remote username
key_filename = "TODO" # TODO: set your own local key file path
task = -1 # close as 1, open as -1
time_steps = 10
try:
print("===> initializing camera")
start_time = time.time()
camera = CameraL515()
camera_loaded = True
end_time = time.time()
print("===> camera initialized", end_time - start_time)
print("===> initializing robot")
start_time = time.time()
robot = Panda()
robot.gripper_open()
robot.homing()
robot_loaded = True
end_time = time.time()
print("===> robot initialized", end_time - start_time)
print("===> getting observation")
start_time = time.time()
color, depth = camera.get_data(hole_filling=False)
depth_sensor = camera.pipeline_profile.get_device().first_depth_sensor()
depth_scale = depth_sensor.get_depth_scale()
xyzrgb = camera.getXYZRGB(color, depth, np.identity(4), np.identity(4), camera.getIntrinsics(), inpaint=False, depth_scale=depth_scale)
# xyzrgb = xyzrgb[xyzrgb[:, 2] <= 1.5, :]
xyzrgb = xyzrgb[xyzrgb[:, 2] > 0.05, :]
cam_pc = xyzrgb[:, 0:3]
pc_color = xyzrgb[:, 3:6]
end_time = time.time()
print("===> observation got", end_time - start_time)
print("===> preprocessing observation")
start_time = time.time()
EE2robot = robot.readPose()
cam2robot = EE2robot @ cam2EE
robot2cam = np.linalg.inv(cam2robot)
base_pc = transform_pc(cam_pc, cam2robot)
space_mask_x = np.logical_and(base_pc[:, 0] > 0, base_pc[:, 0] < 1.1)
space_mask_y = np.logical_and(base_pc[:, 1] > -0.27, base_pc[:, 1] < 0.55)
# space_mask_z = base_pc[:, 2] > 0.02
# space_mask_z = base_pc[:, 2] > 0.55 # microwave: pad + safe (rotate)
# space_mask_z = base_pc[:, 2] > 0.52 # refrigerator: storagefurniture
# space_mask_z = base_pc[:, 2] > 0.4 # safe: pad + microwave
# space_mask_z = base_pc[:, 2] > 0.27 # storagefurniture: microwave
# space_mask_z = base_pc[:, 2] > 0.27 # drawer: microwave
space_mask_z = base_pc[:, 2] > 0.4 # washingmachine: pad + microwave
space_mask = np.logical_and(np.logical_and(space_mask_x, space_mask_y), space_mask_z)
base_pc_space = base_pc[space_mask, :]
pc_color_space = pc_color[space_mask, :]
cam_pc_space = transform_pc(base_pc_space, robot2cam)
end_time = time.time()
print("===> observation preprocessed", end_time - start_time)
np.savez("./observation.npz", point_cloud=cam_pc_space, rgb=pc_color_space)
if vis:
visualize(cam_pc_space, pc_color_space, whether_frame=True, whether_bbox=True, window_name="observation")
print("===> sending request")
start_time = time.time()
np.savez(temp_observation_path, point_cloud=cam_pc_space, rgb=pc_color_space)
time.sleep(0.5)
while not (os.path.isfile(temp_observation_path) and os.access(temp_observation_path, os.R_OK)):
time.sleep(0.1)
send(temp_observation_path, remote_observation_path,
remote_ip=remote_ip, port=port, username=username, key_filename=key_filename)
time.sleep(0.5)
os.remove(temp_observation_path)
end_time = time.time()
print("===> request sent", end_time - start_time)
print("===> reading response")
start_time = time.time()
while True:
read(temp_flag_path, remote_flag_path,
remote_ip=remote_ip, port=port, username=username, key_filename=key_filename)
time.sleep(0.5)
got_service = np.load(temp_flag_path).item()
if got_service:
os.remove(temp_flag_path)
break
else:
time.sleep(0.5)
read(temp_service_path, remote_service_path,
remote_ip=remote_ip, port=port, username=username, key_filename=key_filename)
time.sleep(0.5)
service = np.load(temp_service_path, allow_pickle=True)
num_grasps = service['num_grasps']
if num_grasps == 0:
print("no grasps detected")
else:
cam_joint_base = service['joint_base']
cam_joint_direction = service['joint_direction']
cam_affordable_position = service['affordable_position']
joint_type = service['joint_type']
joint_re = service['joint_re']
grasp_score = service['grasp_score']
grasp_width = service['grasp_width']
grasp_depth = service['grasp_depth']
grasp_affordance = service['grasp_affordance']
cam_grasp_translation = service['grasp_translation']
cam_grasp_rotation = service['grasp_rotation']
cam_grasp_pose = np.eye(4)
cam_grasp_pose[:3, 3] = cam_grasp_translation
cam_grasp_pose[:3, :3] = cam_grasp_rotation
base_joint_base = transform_pc(cam_joint_base[None, :], cam2robot)[0]
base_joint_direction = transform_dir(cam_joint_direction[None, :], cam2robot)[0]
base_affordable_position = transform_pc(cam_affordable_position[None, :], cam2robot)[0]
base_grasp_pose = cam2robot @ cam_grasp_pose
base_grasp_pose[:3, 3] += (grasp_depth - 0.05) * base_grasp_pose[:3, 0] # TODO: hardcode to avoid collision
if joint_type == 0:
# TODO: only for horizontal grasp to avoid singular robot state
flip = np.arccos(np.dot(base_grasp_pose[:3, 2], np.array([0., 0., 1.]))) / np.pi * 180.0 < 45
if flip:
print("flipped")
base_grasp_pose[:3, 1] = -base_grasp_pose[:3, 1]
base_grasp_pose[:3, 2] = -base_grasp_pose[:3, 2]
rotate = base_grasp_pose[:3, 0][2] > 0
if rotate:
print("rotated")
target_x_axis = base_grasp_pose[:3, 0].copy()
target_x_axis[2] = -target_x_axis[2]
rotation_angle = np.arccos(np.dot(base_grasp_pose[:3, 0], target_x_axis))
rotation_direction = np.array([base_grasp_pose[:3, 0][0], base_grasp_pose[:3, 0][1]])
rotation_direction /= np.linalg.norm(rotation_direction)
rotation_direction = np.array([-rotation_direction[1], rotation_direction[0], 0.])
rotation_matrix = tf.rotation_matrix(angle=rotation_angle, direction=rotation_direction, point=base_grasp_pose[:3, 3])
base_grasp_pose = rotation_matrix @ base_grasp_pose
elif joint_type == 1:
horizontal = np.arccos(np.dot(base_grasp_pose[:3, 0], np.array([1., 0., 0.]))) / np.pi * 180.0 < 45
if horizontal:
print("horizontal")
else:
print("vertical")
else:
raise ValueError
base_pre_grasp_pose = base_grasp_pose.copy()
base_pre_grasp_pose[:3, 3] -= 0.05 * base_pre_grasp_pose[:3, 0]
g2g = np.array([[0., 0., -1.], [0., -1., 0.], [-1., 0., 0.]])
base_gripper_pose = np.eye(4)
base_gripper_pose[:3, :3] = base_grasp_pose[:3, :3] @ g2g
base_gripper_pose[:3, 3] = base_grasp_pose[:3, 3]
base_pre_gripper_pose = np.eye(4)
base_pre_gripper_pose[:3, :3] = base_pre_grasp_pose[:3, :3] @ g2g
base_pre_gripper_pose[:3, 3] = base_pre_grasp_pose[:3, 3]
np.savez("./joint.npz", joint_base=base_joint_base, joint_direction=base_joint_direction, affordable_position=base_affordable_position)
np.savez("./grasp.npz", grasp_pose=base_grasp_pose, grasp_width=grasp_width)
time.sleep(0.5)
os.remove(temp_service_path)
end_time = time.time()
print("===> response read", end_time - start_time)
if vis:
if num_grasps != 0:
visualize(base_pc_space, pc_color_space,
joint_translations=base_joint_base[None, :], joint_rotations=base_joint_direction[None, :], affordable_positions=base_affordable_position[None, :],
grasp_poses=base_grasp_pose[None, ...], grasp_widths=np.array([grasp_width]), grasp_depths=np.array([0.]), grasp_affordances=np.array([grasp_affordance]),
whether_frame=True, whether_bbox=True, window_name="prediction")
print("===> resetting flag")
serviced = np.array(False)
np.save(temp_flag_path, serviced)
time.sleep(0.5)
while not (os.path.isfile(temp_flag_path) and os.access(temp_flag_path, os.R_OK)):
time.sleep(0.1)
send(temp_flag_path, remote_flag_path,
remote_ip=remote_ip, port=port, username=username, key_filename=key_filename)
time.sleep(0.5)
os.remove(temp_flag_path)
end_time = time.time()
print("===> flag reset", end_time - start_time)
print("===> starting manipulation")
import pdb; pdb.set_trace()
start_time = time.time()
if num_grasps == 0:
exit(1)
else:
robot.move_gripper(grasp_width)
robot.movePose(base_pre_gripper_pose)
robot.movePose(base_gripper_pose)
# grasp
is_graspped = robot.gripper_close()
is_graspped = is_graspped and robot.is_grasping()
print(is_graspped)
# move
real_trajectory = []
target_trajectory = []
wrench_trajectory = []
robot.start_impedance_control()
for time_step in tqdm.trange(time_steps):
current_EE2robot = robot.readPose()
current_wrench= robot.readWrench()
if joint_type == 0:
rotation_angle = -5.0 * task * joint_re / 180.0 * np.pi
delta_pose = tf.rotation_matrix(angle=rotation_angle, direction=base_joint_direction, point=base_joint_base)
elif joint_type == 1:
translation_distance = -5.0 * task / 100.0
delta_pose = tf.translation_matrix(base_joint_direction * translation_distance)
else:
raise ValueError
target_EE2robot = delta_pose @ current_EE2robot
robot.movePose(target_EE2robot)
time.sleep(0.3)
real_trajectory.append(current_EE2robot)
target_trajectory.append(target_EE2robot)
wrench_trajectory.append(current_wrench)
robot.end_impedance_control()
real_trajectory = np.array(real_trajectory)
target_trajectory = np.array(target_trajectory)
wrench_trajectory = np.array(wrench_trajectory)
np.savez("./trajectory.npz", real_trajectory=real_trajectory, target_trajectory=target_trajectory, wrench_trajectory=wrench_trajectory)
end_time = time.time()
print("===> manipulation done", end_time - start_time)
robot.gripper_open()
# robot.homing()
except Exception as e:
print(e)
if camera_loaded:
del camera
if robot_loaded:
del robot