Learning Nullspace Policies
Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010).
dc.contributor.author | Towell, Christopher | en |
dc.contributor.author | Howard, Matthew | en |
dc.contributor.author | Vijayakumar, Sethu | en |
dc.date.accessioned | 2010-08-18T15:39:29Z | |
dc.date.available | 2010-08-18T15:39:29Z | |
dc.date.issued | 2010 | |
dc.identifier.uri | http://hdl.handle.net/1842/3649 | |
dc.description.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. | en |
dc.language.iso | en | |
dc.subject | Informatics | en |
dc.subject | Computer Science | en |
dc.title | Learning Nullspace Policies | en |
dc.type | Conference Paper | en |
rps.title | Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010). | en |
dc.extent.noOfPages | 8 | en |
dc.date.updated | 2010-08-18T15:39:30Z |