DISCONTINUATION OF PROJECT

This project will no longer be maintained by Intel.
Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project.
Intel no longer accepts patches to this project.
If you have an ongoing need to use this project, are interested in independently developing it, or would like to maintain patches for the open source software community, please create your own fork of this project.

Contact: [email protected]

ROS2 Grasp Library

A ROS2 intelligent visual grasp solution for advanced industrial usages, with OpenVINO™ grasp detection and MoveIt Grasp Planning.

Overview

ROS2 Grasp Library enables state-of-the-art CNN based deep learning grasp detection algorithms on ROS2 for intelligent visual grasp in industrial robot usage scenarios. This package provides ROS2 interfaces compliant with the open source MoveIt motion planning framework supported by most of the robot models in ROS industrial. This package delivers

• A ROS2 Grasp Planner providing grasp planning service, as an extensible capability of MoveIt (moveit_msgs::srv::GraspPlanning), translating grasp detection results into MoveIt Interfaces (moveit_msgs::msg::Grasp)
• A ROS2 Grasp Detctor abstracting interfaces for grasp detection results
• A ROS2 hand-eye calibration module generating transformation from camera frame to robot frame
• ROS2 example applications demonstrating how to use this ROS2 Grasp Library in advanced industrial usages for intelligent visual grasp

Grasp Detection Algorithms

Grasp detection back-end algorithms enabled by this ROS2 Grasp Library:

• Grasp Pose Detection detects 6-DOF grasp poses for a 2-finger grasp (e.g. a parallel jaw gripper) in 3D point clouds from RGBD sensor or PCD file. The grasp detection was enabled with Intel® DLDT toolkit and Intel® OpenVINO™ toolkit.

  

Tutorials

Refer to ROS2 Grasp Library Tutorials for how to

• Install, build, and launch the ROS2 Grasp Planner and Detector
• Use launch options to customize in a new workspace
• Bring up the intelligent visual grasp solution on a new robot
• Do hand-eye calibration for a new camera setup
• Launch the example applications

Example Applications

Random Picking (OpenVINO Grasp Detection)

Recognition Picking (OpenVINO Grasp Detection + OpenVINO Mask-rcnn Object Segmentation)

Known Issues

• Cloud camera failed at "Invalid sizes when resizing a matrix or array" when dealing with XYZRGBA pointcloud from ROS2 Realsenes, tracked as #6 of gpg, patch under review.
• 'colcon test' sometimes failed with test suite "tgrasp_ros2", due to ROS2 service request failure issue (reported ros2 examples issue #228 and detailed discussed in ros2 demo issue #304)
• Rviz2 failed to receive Static TF from camera due to transient_local QoS (expected in the coming ROS2 Eloquent, discussed in geometry2 issue #183), workaround patch available till the adaption to Eloquent

Contribute to This Project

It's welcomed to contribute to this project. Here're some recommended practices:

• When adding a new feature it's expected to add tests covering the new functionalities

  colcon test --packages-select <names_of_affected_packages>

• Before submitting a patch, it's recommended to pass all existing tests to avoid regression

  colcon test --packages-select <names_of_existing_packages>

Any security issue should be reported using process at https://01.org/security