REACH ROS Plugins

This package contains the ROS1-based plugin implemenations of REACH kinematics, evaluation, and display interfaces

Installation

First, clone the repository into a catkin workspace

cd ~/reach_ws/src
git clone https://github.com/ros-industrial/reach_ros.git
cd ..

Install the dependencies

vcs import src < src/reach_ros/dependencies.repos
rosdep install --from-paths src --ignore-src -r -y

Build the repository

catkin build

Demo

A simple demonstration of the capability of this repository is provided in the demo sub-directory. See the instructions for details on how to run the demo.

Usage

Use the following steps to run a reach study with a robot using the ROS1 infrastructure and plugins.

1. Create a URDF of your robot system
2. Create a launch file to load the URDF, SRDF, and other required parameters (e.g. related to kinematics, joint, limits) to the parameter server (see this demo example file)
3. Create a mesh model of the workpiece

   Note: the origin of this model should align with the kinematic base frame of the robot

4. Create a point cloud of the target points on the workpiece
   • This point cloud can be generated using a command line tool from PCL 1.8:

      pcl_mesh_sampling <workpiece_mesh>.ply <output_cloud>.pcd -n_samples <number of samples> -leaf_size <leaf_size> -write_normals true
      

1. Create a configuration YAML file defining the parameters of the reach study and the configuration of the interface plugins (see this demo example)
2. Run the setup launch file

    roslaunch reach_ros setup.launch robot:=<load_robot_parameters>.launch
    

1. Run the reach study analysis

    roslaunch reach_ros start.launch config_file:=<config_file.yaml> config_name:=<arbitrary_config>
    

Evaluation Plugins

Manipulability

This plugin uses MoveIt! to calculate the manipulability of a robot pose. Higher manipulability results in a higher pose score. Range: [0, inf)

Parameters:

• planning_group
  • The name of the planning group with which to evaluate the manipulability of a given robot pose
• jacobian_row_subset (optional)
  • The indices of the rows of the Jacobian to use when evaluating the manipulability. The row indices should be on [0, 6) and correspond to the output space [x, y, z, rx, ry, rz]
  • Ex. jacobian_row_subset: [0, 1, 2] # position manipulability only

Manipulability Scaled

This plugin uses MoveIt! to calculate the manipulability of a robot pose divided by the characteristic length of the motion group. The characteristic length is computed by walking from the base link to the tip link of the motion group and summing the distances between adjacent links. Higher scaled manipulability results in a higher pose score. Range: [0, inf)

Parameters:

• planning_group
  • The name of the planning group with which to evaluate the manipulability of a given robot pose
• jacobian_row_subset (optional)
  • The indices of the rows of the Jacobian to use when evaluating the manipulability. The row indices should be on [0, 6) and correspond to the output space [x, y, z, rx, ry, rz]
  • Ex. jacobian_row_subset: [0, 1, 2] # position manipulability only
• excluded_links (optional)
  • The names of links contained in the motion group that should not contribute to the characteristic length

Manipulability Ratio

This plugin uses MoveIt! to calculate the manipulability of a robot pose and evaluate a score. The score is calculated as the ratio of the smallest manipulability value to the largest manipulability value. The larger this ratio, the more uniform the dexterity and the higher the score. Range [0, 1]

Parameters:

• planning_group
  • The name of the planning group with which to evaluate the manipulability of a given robot pose
• jacobian_row_subset (optional)
  • The indices of the rows of the Jacobian to use when evaluating the manipulability. The row indices should be on [0, 6) and correspond to the output space [x, y, z, rx, ry, rz]
  • Ex. jacobian_row_subset: [0, 1, 2] # position manipulability only

Distance Penalty

This plugin uses the MoveIt! collision environment to calculate the distance to closest collision for a robot pose. That distance value is then used to score the robot pose. Larger distance to closest collision

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