Robot_Manipulator_Control

This is a developing ROS robot manipulator project, involved in using a UR10, 'self-made' dynamixel gripper. The main idea of this package is to enable fast configure on the UR10 motion sequence within in a short period of time. This is done by just edit the motion_config.yaml file, without changing the source code.

Here, step-by-step instructions are listed here to guide user on how to setup the environment to: (1) Run it on Rviz (2) Run it on a real UR10 Robot!!!!! Have fun people!!

Table Of Contents

1. Environment Setup
2. Run Demo Script on Rviz
3. Run On UR10 hardware
4. Understand motion_config.yaml
5. Brief Code Explanation
6. TODO

1. Environment Setup

a) Install ROS

b) Install Moveit and ur10_moveit_config

ROS MOVEIT! is used for motion planning. UR10 moveit pkg is here.

sudo apt-get install ros-kinetic-moveit
sudo apt-get install ros-kinetic-ur10-moveit-config

c) Install current ROS Package

catkin_make
roscd ur10_rmf/scripts
chmod +x robot_manipulator_control.py
source ~/xxx/devel/setup.bash

• If Dynamixel Gripper is used: Refer to the README.md in to dynamixel_gripper pkg.

** d) If Interfacing with UR10 hardware

Install Some UR hardware dependencies

sudo apt-get install ros-kinetic-ur-msgs    # to interface with hardware
sudo apt-get install ros-kinetic-controller-manager
sudo apt-get install ros-kinetic-industrial-msgs

Install ur_modern_driver

git clone https://github.com/ros-industrial/ur_modern_driver/
git checkout kinetic-devel`             # if using kenetic
catkin_make --pkg ur_modern_driver      # here apt-get all relevent dependencies of ur_modern_driver

** e) Configure IP for UR10 hardware and PC Network Connection

# FIRST CREATE A LOCAL IP TO COMMUNICATE WITH THE HARDWARE DEPENDING ON IP AND MASK
ping 192.168.88.70 #depends on $UR10_IP

** g) If Dynamic Dynamic cartesian planning is used (optional):

• Urg_node: Optional hardware intergration with hokoyu lidar, package is Here
• Object Pose Estimation: Optional detection of target object's pose respective to lidar, package is Here

2. Run Demo Script on Rviz

This is to run UR on Rviz, without a hardware setup.

a) Run Movegroup and Rviz

Robot’s config file

roslaunch ur10_rmf ur10_test.launch
# or default .launch file
roslaunch ur10_moveit_config demo.launch

b) Motion Planning Python Script

To program a series of motion , edit the yaml file at config/motion_config.yaml. Once done, run the script to visualize the motion control.

rosrun ur10_rmf robot_manipulator_control.py

c) Optional Dynamic Planning on target (with hokoyu)

roslaunch urg_node urg_lidar.launch                         # pls configure hokoyu's ip
rosrun object_pose_estimation object_pose_estimation_ros

Notes

• uncomment joint_state_publisher node in ur10_test.launch will enable rviz ur10 to run without UR10 hardware
• Change planning between: STOMP, CHOMP, OMPL
• If select STOMP planner, build package from industrial moveit
• For 'ur_modern_driver' bringup, Arg servoj_time happened to be related to the network between arm and pc, increase to prevent congestion, or maybe some jerking motion

3. Run On UR10 hardware

Here, Hokoyu Lidar is used for pose estimation of the target object. Refer to object_pose_estimation ros pkg for reference.

a) Launch MoveGroup, Rviz, Urg_node, Ur10 Hardware BringUp

roslaunch ur10_rmf ur10_hardware.launch

Here, you will be able to see the current ur10 hardware pose on Rviz. If dynamic cartesian planning is not used, user can comment out urg_node, object_pose_estimation pkg.

b) Enable Moveit Execution on hardware

roslaunch ur10_moveit_config ur10_moveit_planning_execution.launch limited:=true

• Steps 1 and 2 combined: roslaunch ur10_rmf ur10_hardware_combined.launch

c) Run and Test Script

rosrun ur10_rmf robot_manipulator_control.py
rostopic pub /ur10/motion_group_id std_msgs/String "INPUT" #INPUT: G1, G2... 

*To know current pose and joint angle, check printout after each motion

4. Understand motion_config.yaml

All defination and setting of motion is configure on config/motion_config.yaml. User just need to change the config file to configure each request motion.

• 4 types of motion: cartesian, joint_goal, pose_goal, 2d_dynamic_cartesian
• 2 types of gripper motion: eef_grip_obj, eef_release_obj
• Edit enable_gripper in .yaml file to True to enable usage of gripper
• In the yaml file, the hierachy of each is: motion_group > motion > cartesian_motion.
• Use execute_motion_group_service to check printout of current 6 joints and current eef pose, this helps in configuring the motion yaml
• adding a Coefficeient, e.g. '3', '-2', on each motion_id or cartesian_motion_id is supported in the yaml file.

Working with Pose Estimation

• To have dynamic cartesian planning, use 2d_dynamic_cartesian in yaml file motion type.
• Pose input of the target_pose is via ROSTOPIC /ur10/target_pose with [x, y, theta] info
• RosMsg for pose is from a pose estimation node, e.g: lidar point cloud pose estimation.
• input 2D info of fix_laser_pose, target, tolerance
• Here is my own lidar pose estimation ros node

Working with Gripper

• If wanna run with the gripper, pls refer to the package readme.md to run the launch file: roslaunch dynamixel_gripper gripper_manager.roslaunch
• In yaml file, enable_gripper: False, and use eef_grip_obj, eef_release_obj.
• ur10 control is a higher level control of dynamixel gripper

Error Msg

• enable log_motion_error with True, this will record all unsuccessfull motion, which can be in planning or execution phase
• the file error_log.txt will be generated in the current working directory

5. Brief Code Explanation

ManipulatorControl Class

Class ManipulatorControl simplfied the use of typing code to control the robot manipulator. This helps user to create a series of motion just by edit the motion_config.yaml file. 3 useful functions in this class are:

• execute_all_motion_group(),
• execute_motion_group(string motion_group_id) return True/False, True: success, False: fail
• execute_motion(string motion_id) return True/False, True: success, False: fail
• execute_motion_group_service() ros service by getting request of motion group

ArmManipulation Class

This class directly interact with the ROS moveit package.

• go_to_joint_state(joint_goal, time_factor) return bool (success anot)
• go_to_pose_goal(self, pose_list, time_factor ) return bool (success anot)
• plan_cartesian_path(self, motion_list, time_factor) return obj, float (planned trajectory, success fraction, 1.0)
• execute_plan(self, plan) return bool (success anot)

Pub Sub for execute_group_service()

Use ur10.execute_motion_group_service() to start ros service, which request group_id to user. This will activate ros pub sub mentioned below:

• /ur10/motion_group_id: Group ID (string) Sub
• /ur10/manipulator_state: State of arm and gripper (custom msg) Pub
• /ur10/rm_bridge_state: same as above's state, temp solution to feed to ros bridge (float32_array) Pub

Other Pub Sub Being used:

• /gripper/state: gripper status (grip_state msg) Sub
• /gripper/command: command gripper on ros1 (Int32) Pub
• /ur10/target_pose: 2D Pose from pose estimation (Pose2D) msg Sub

6. TODO

• update scene obstacle creation
• stop execution feature, maybe with asyncExecute()
• cleanup transformation of dynamic cartesian planning
• robustness
• Adjust dynamic planning tolerance, chg to when hit limit, stop execution
• Handle pub of error_flag