Learning Nullspace Policies
Proc. IEEE/RSJ Intl. Conf. on Intelligent Robots and Systems (IROS 2010), Taiwan (2010).
Date
2010Author
Towell, Christopher
Howard, Matthew
Vijayakumar, Sethu
Metadata
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.