Run-time Self-classification of External Force using Virtual Point Mass Approximation for Object Manipulation

Title
Run-time Self-classification of External Force using Virtual Point Mass Approximation for Object Manipulation
Authors
배지훈김도익
Keywords
classification; external force; force sensor; object manipulation; virtual point mass
Issue Date
2014-01
Publisher
International Journal of Control, Automation and Systems
Citation
VOL 12, NO 1, 137-146
Abstract
Many tasks assigned to a manipulator include interactions with its operating environment or manipulating objects, which are detected as forces and moments by the force sensor. It is, however, not easy to detect when a pure external wrench occurred in interactions or manipulations since signals measured by the force sensor consist of the inertial effect of the end-effector and manipulating objects as well as the effect of interactions. In order to separate these combined effects, a self-classification method for the 6-axis force sensor is proposed in this paper by relating the wrench and the virtual point mass. With the proposed method, wrenches due to the end-effector and objects can be classified in runtime without any prior information for them, and thus a pure external wrench can also be distinguished from them. The effectiveness of the proposed self-classification method is verified through experiments.
URI
http://pubs.kist.re.kr/handle/201004/47569
ISSN
15986446
Appears in Collections:
KIST Publication > Article
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