The Grasp Loop Signature: A Topological Representation for Manipulation Planning with Ropes and Cables

Presented at ICRA 2024

Abstract

This paper studies robotic manipulation of deformable, one-dimensional objects (DOOs) like ropes or cables, which has important potential applications in manufacturing, agriculture, and surgery. In such environments, the task may involve threading through or avoiding becoming tangled with other objects. Grasping with multiple grippers can create closed loops between the robot and DOO, and if an obstacle lies within this loop, it may be impossible to reach the goal. However, prior work has only considered the topology of the DOO in isolation, ignoring the arms that are manipulating it. Searching over possible grasps to accomplish the task without considering such topological information is very inefficient, as many grasps will not lead to progress on the task due to topological constraints. Therefore, we propose the GL-Signature which categorizes the topology of these grasp loops and show how it can be used to guide planning. We perform experiments in simulation on two DOO manipulation tasks to show that using the GL-Signature is faster and more successful than methods that rely on local geometry or additional finite-horizon planning. Finally, we demonstrate using the GL-Signature in a real-world dual-arm cable manipulation task. 

Paper

       The ICRA version will be published on IEEE Explore soon, please cite that version.

https://arxiv.org/abs/2403.01611

Code

https://github.com/UM-ARM-Lab/mjregrasping (now public!)

Video

https://www.youtube.com/watch?v=zLeeZEsIT34

Here are some more figures and animations to help explain the GL-signature!