A ROS package for controlling the Remote Direct-Drive Actuator (RDDA) with Universal Robots UR5/UR5e at Northeastern University, Boston.
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Setup ROS A master's IP:
export ROS_IP=192.168.0.151 -> .bashrc
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Setup ROS B master's IP in rdda_comm_bridge.py
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Setup
robot_type
androbot_ip
in control_core.py.
roslaunch rdda_ur5_control control_server.launch
rosservice call /rdda_ur5_control/set_rdda_stiffness -- finger1 finger2
rosservice call /rdda_ur5_control/init_rdda_stiffness
rosservice call /rdda_ur5_control/set_rdda_positions -- finger1 finger2
rosservice call /rdda_ur5_control/set_rdda_max_velocities -- finger1 finger2
rosservice call /rdda_ur5_control/set_rdda_max_efforts -- finger1 finger2
rosservice call /rdda_ur5_control/home_rdda
rosservice call /rdda_ur5_control/read_rdda_positions
rosservice call /rdda_ur5_control/read_rdda_lower_bounds
rosservice call /rdda_ur5_control/read_rdda_upper_bounds
rosservice call /rdda_ur5_control/read_rdda_origins
rosservice call /rdda_ur5_control/read_ur5_position
rosservice call /rdda_ur5_control/move_ur5 -- x y z roll pitch yaw velocity
rosservice call /rdda_ur5_control/move_ur5_trajectory -- step_size step_num velocity wait
rosservice call /rdda_ur5_control/move_ur5_linear -- axis target velocity wait
rosservice call /rdda_ur5_control/stop_ur5
rosservice call /rdda_ur5_control/home_ur5
Example: control_client_py3.py
NSF project: Controllable Compliance: A New Robotic Arm for Contact-Rich Manipulation
CoRL 2020: Belief-Grounded Networks for Accelerated Robot Learning under Partial (website)
This project uses the code from MoveIt! and the GitHub repository rdda_interface.