Viewpoint Planning for Object Identification Using Visual Experience According to Long-Term Activity | Zendy

Kimitoshi Yamazaki | Zendy; Kazuki Nogami | Zendy; Kotaro Nagahama | Zendy

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Viewpoint Planning for Object Identification Using Visual Experience According to Long-Term Activity

Author(s) -

Kimitoshi Yamazaki,

Kazuki Nogami,

Kotaro Nagahama

Publication year - 2022

Publication title -

international journal of automation technology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.513

H-Index - 18

eISSN - 1883-8022

pISSN - 1881-7629

DOI - 10.20965/ijat.2022.p0197

Subject(s) - identification (biology) , object (grammar) , orientation (vector space) , computer science , selection (genetic algorithm) , artificial intelligence , term (time) , computer vision , motion planning , robot , mathematics , botany , geometry , physics , quantum mechanics , biology

In this paper, we propose a viewpoint planning method for object identification. We introduce the policy of maximizing the posterior probability of the orientation of an object observed after a robot moves its viewpoint and show a novel formulation of viewpoint planning. In addition, we propose criteria for viewpoint selection based on past sensing experience. Finally, we confirm the effectiveness of the proposed method via simulations using a mobile manipulator.

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