Knot planning from observation

Author

Morita, Takuma ; Takamatsu, Jun ; Ogawara, Koichi ; Kimura, Hiroshi ; Ikeuchi, Katsushi

Author_Institution

Inst. of Ind. Sci., Tokyo Univ., Japan

Volume

3

fYear

2003

fDate

14-19 Sept. 2003

Firstpage

3887

Abstract

Learning from Observation (LFO) has been widely applied in various types of robot system. It helps reduce the work of the programmer. But the available systems have application limited to rigid objects. Deformable objects are not considered because: 1) it is difficult to describe their state, and 2) too many operations are possible on them. In this paper, we choose the knot tying as case study for operating on nonrigid bodies, because a "knot theory" is available and the type of operations is limited. We describe the Knot Planning from Observation (KPO) paradigm, KPO theory and KPO system.

Keywords

learning (artificial intelligence); manipulators; object recognition; planning (artificial intelligence); robot vision; task analysis; KPO; LFO; deformable objects; knot planning from observation system; knot theory; knot tying task; learning from observation; nonrigid bodies; robot programming; robot system; robot vision; Cameras; Humans; Image recognition; Machine vision; Programming profession; Robot vision systems; Robotic assembly; Robotics and automation; Service robots; Transmission line measurements;

fLanguage

English

Publisher

ieee

Conference_Titel

Robotics and Automation, 2003. Proceedings. ICRA '03. IEEE International Conference on

ISSN

1050-4729

Print_ISBN

0-7803-7736-2

Type

conf

DOI

10.1109/ROBOT.2003.1242193

Filename

1242193