Cable manipulation with a tactile-reactive gripper

By Y. She, Shaoxiong Wang, Siyuan Dong, N. Sunil, Alberto Rodriguez, Edward H. Adelson. Robotics: Science and Systems Conference, 2019

319 citations recorded by the source corpus.

Cables are complex, high-dimensional, and dynamic objects. Standard approaches to manipulate them often rely on conservative strategies that involve long series of very slow and incremental deformations, or various mechanical fixtures such as clamps, pins, or rings. We are interested in manipulating freely moving cables, in real time, with a pair of robotic grippers, and with no added mechanical constraints. The main contribution of this paper is a perception and control framework that moves in that direction, and uses real-time tactile feedback to accomplish the task of following a dangling cable. The approach relies on a vision-based tactile sensor, GelSight, that estimates the pose of the cable in the grip, and the friction forces during cable sliding. We achieve the behavior by combining two tactile-based controllers: (1) cable grip controller, where a PD controller combined with a leaky integrator regulates the gripping force to maintain the frictional sliding forces close to a suitable value; and (2) cable pose controller, where an linear–quadratic regulator controller based on a learned linear model of the cable sliding dynamics keeps the cable centered and aligned on the fingertips to prevent the cable from falling from the grip. This behavior is possible with the use of reactive gripper fitted with GelSight-based high-resolution tactile sensors. The robot can follow 1 m of cable in random configurations within two to three hand regrasps, adapting to cables of different materials and thicknesses. We demonstrate a robot grasping a headphone cable, sliding the fingers to the jack connector, and inserting it. To the best of the authors’ knowledge, this is the first implementation of real-time cable following without the aid of mechanical fixtures. Videos are available at http://gelsight.csail.mit.edu/cable/

Subfields: Biomedical Engineering, Cognitive Neuroscience, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/babe0886437dd126e0462fa730c9df9473e5f113

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In Biomedical Engineering

  1. Jia Pan
  2. Jens Kober
  3. Wenzhen Yuan

In Cognitive Neuroscience

  1. Jia Pan
  2. Jens Kober
  3. Jan Peters
  4. Gerhard Neumann
  5. Sergey Levine

In Control and Systems Engineering

  1. Jia Pan
  2. Jens Kober
  3. Dmitry Berenson
  4. Fanny Ficuciello
  5. Wenzhen Yuan
  6. Sergey Levine
  7. Jan Peters
  8. Pieter Abbeel

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