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Representing and Manipulating Deformable Linear Objects

Introduction

This is the GitHub organization home page for the Representing and Manipulating Deformable Linear Objects (RMDLO) project from the Bretl Research Group at the University of Illinois at Urbana-Champaign (UIUC). The project studies robotic manipulation, grasp planning, tactile sensing, segmentation, simulation, and tracking of wires and ropes.

Our growing hardware stack comprises software for controlling two ABB IRB120 6DOF robotic manipulators, the Rethink Robotics Sawyer 7DOF manipulator, the OnRobot 2FG7 gripper, the Intel RealSense d435 camera, the ZED Mini camera, and the DIGIT tactile sensor. For any project-related inquiries or requests, please contact Holly Dinkel [[email protected]].

Collaborators

Hameed Abdul-Rashid, Timothy Bretl, Brian Coltin Holly Dinkel, Achintya Gahalaut, Naixiang (Gabe) Gao, Zikun (Tony) Liu, Raghavendra (Raghav) Navaratna, Yash Rathod, Fuad Samhouri, Trey Smith, Jingyi Xiang, Harry Zhao

References

H. Dinkel, J. Xiang, H. Zhao, B. Coltin, T. Smith, and T. Bretl (2022) "Wire Point Cloud Instance Segmentation from RGBD Imagery with Mask R-CNN", ICRA Workshop on Deformable Objects. [Paper] [Video]

Funding Acknowledgment

This work is supported through NASA Space Technology Graduate Research Opportunity award 80NSSC21K1292, U.S. Department of Education Graduate Assistance in Areas of National award P200A180050-19, Illinois Space Grant Consortium Undergraduate Research Opportunity Program, UIUC Promoting Undergraduate Research in Engineering, UIUC Office of Undergraduate Research, and the UIUC Department of Aerospace Engineering.


https://github.com/RMDLO