Learning Nullspace Policies

Chris Towell, Matthew Howard, Sethu Vijayakumar

Research output: Chapter in Book/Report/Conference proceedingConference paper

19 Citations (Scopus)

Abstract

Many everyday tasks performed by people, such as reaching, pointing or drawing, resolve redundant degrees of freedom in the arm in a similar way. In this paper we present a novel method for learning the strategy used to resolve redundancy by exploiting the variability in multiple observations of different tasks. We demonstrate the effectiveness of this method on three simulated plants: a toy example, a three link planar arm, and the KUKA lightweight arm.
Original languageEnglish
Title of host publication2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
PublisherIEEE
Pages241-248
Number of pages8
ISBN (Print)978-1-4244-6674-0
DOIs
Publication statusPublished - 2010

Fingerprint

Dive into the research topics of 'Learning Nullspace Policies'. Together they form a unique fingerprint.

Cite this