Robot learning of everyday object manipulations via human demonstration

Articles:

Title:: Robot learning of everyday object manipulations via human demonstration
Author(s):: Dang, Hao
Allen, Peter K.
Date:: 2010
Type:: Articles
Department:: Computer Science
Permanent URL:: http://hdl.handle.net/10022/AC:P:15083
Book/Journal Title:: The IEEE/RSJ International Conference on Intelligent Robots and Systems: IROS 2010: Taipei International Convention Center, Taipei, Taiwan, October 18-22, 2010: conference proceedings
Publisher:: IEEE
Publisher Location:: Piscataway, N.J.
Abstract:: We deal with the problem of teaching a robot to manipulate everyday objects through human demonstration. We first design a task descriptor which encapsulates important elements of a task. The design originates from observations that manipulations involved in many everyday object tasks can be considered as a series of sequential rotations and translations, which we call manipulation primitives. We then propose a method that enables a robot to decompose a demonstrated task into sequential manipulation primitives and construct a task descriptor. We also show how to transfer a task descriptor learned from one object to similar objects. In the end, we argue that this framework is highly generic. Particularly, it can be used to construct a robot task database that serves as a manipulation knowledge base for a robot to succeed in manipulating everyday objects.
Subject(s):: Robotics
DOI:: http://dx.doi.org/10.1109/IROS.2010.5651244