Verti-Wheelers: Verti-4-Wheeler (V4W) and Verti-6-Wheeler (V6W) Installation Guidance
ROS Noetic.
PyTorch.
Torchvision
Arduino Arduino Mega 2560.
Python 3.8.10.
RGBD Camera Driver Azure Kinect Camera.
Direct LiDAR-Inertial Odometry (https://github.com/vectr-ucla/direct_lidar_inertial_odometry.git).
Elevation Mapping cupy (https://github.com/leggedrobotics/elevation_mapping_cupy.git)
mkdir -p catkin_ws/src; cd catkin_ws/src; catkin_init_workspace
git clone https://github.com/microsoft/Azure_Kinect_ROS_Driver
git clone https://github.com/microsoft/Azure-Kinect-Sensor-SDK
git clone https://github.com/RobotiXX/Verti-Wheelers.git
Install dependencies with rosdep
:
cd catkin_ws; rosdep install --from-paths . --ignore-src --rosdistro=noetic
Install Azure Kinect Sensor SDK on Ubuntu 20.04+ (Current Sensor SDK only supports for Ubuntu 18.04) :
- Downlaod the k4a-tools 1.4.1amd64.deb file.
- Download the libk4a1.4, libk4a1.4-dev files.
- Install SDK.
- Create a new file: sudo gedit /etc/udev/rules.d/99-k4a.rules, add the contents as below:
# Bus 002 Device 116: ID 045e:097a Microsoft Corp. - Generic Superspeed USB Hub
# Bus 001 Device 015: ID 045e:097b Microsoft Corp. - Generic USB Hub
# Bus 002 Device 118: ID 045e:097c Microsoft Corp. - Azure Kinect Depth Camera
# Bus 002 Device 117: ID 045e:097d Microsoft Corp. - Azure Kinect 4K Camera
# Bus 001 Device 016: ID 045e:097e Microsoft Corp. - Azure Kinect Microphone Array
BUS!="usb", ACTION!="add", SUBSYSTEM!=="usb_device", GOTO="k4a_logic_rules_end"
ATTRS{idVendor}=="045e", ATTRS{idProduct}=="097a", MODE="0666", GROUP="plugdev"
ATTRS{idVendor}=="045e", ATTRS{idProduct}=="097b", MODE="0666", GROUP="plugdev"
ATTRS{idVendor}=="045e", ATTRS{idProduct}=="097c", MODE="0666", GROUP="plugdev"
ATTRS{idVendor}=="045e", ATTRS{idProduct}=="097d", MODE="0666", GROUP="plugdev"
ATTRS{idVendor}=="045e", ATTRS{idProduct}=="097e", MODE="0666", GROUP="plugdev"
LABEL="k4a_logic_rules_end"
Replace source file for Azure_Kinect_ROS_Driver with the one provided in config folder and replace config yaml files for the dlio and elevation mapping cupy with the one provided in respective folder
cd catkin_ws; catkin build; source devel/setup.bash
In terminal 1: roslaunch navstack_pub runCAR.launch
Open_loop launch:
In terminal 2: roslaunch navstack_pub open_loop.launch
Rule_based launch:
In terminal 2: roslaunch navstack_pub rule_based.launch
Neural Network Behavior cloning launch:
In terminal 2: cd catkin_ws/src/navstack_pub/src; python3 action_generator.py
All training data can be found at GMU Dataverse
Launch packages
In terminal 1: roslaunch navstack_pub runCAR_all.launch
Launch planner
In terminal 2: cd catkin_ws/src/WM-VCT; python3 CustromPlanner.py