An autonomous manipulation system based on force control and optimization

  • Authors:

  • Ludovic Righetti;Mrinal Kalakrishnan;Peter Pastor;Jonathan Binney;Jonathan Kelly;Randolph C. Voorhies;Gaurav S. Sukhatme;Stefan Schaal

  • Affiliations:

  • Computer Science Department, University of Southern California, Los Angeles, USA 90089 and Autonomous Motion Department, Max-Planck-Institute for Intelligent Systems, Tübingen, Germany 72076;Computer Science Department, University of Southern California, Los Angeles, USA 90089;Computer Science Department, University of Southern California, Los Angeles, USA 90089;Computer Science Department, University of Southern California, Los Angeles, USA 90089;Institute for Aerospace Studies, University of Toronto, Toronto, Canada M3H 5T6;Computer Science Department, University of Southern California, Los Angeles, USA 90089;Computer Science Department, University of Southern California, Los Angeles, USA 90089;Computer Science Department, University of Southern California, Los Angeles, USA 90089 and Autonomous Motion Department, Max-Planck-Institute for Intelligent Systems, Tübingen, Germany 72076

  • Venue:
  • Autonomous Robots
  • Year:
  • 2014

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we present an architecture for autonomous manipulation. Our approach is based on the belief that contact interactions during manipulation should be exploited to improve dexterity and that optimizing motion plans is useful to create more robust and repeatable manipulation behaviors. We therefore propose an architecture where state of the art force/torque control and optimization-based motion planning are the core components of the system. We give a detailed description of the modules that constitute the complete system and discuss the challenges inherent to creating such a system. We present experimental results for several grasping and manipulation tasks to demonstrate the performance and robustness of our approach.