A Searching and Tracking Framework for Multi-Robot Observation of Multiple Moving Targets | Zendy

Zheng Liu | Zendy; Marcelo H. Ang | Zendy; Winston K.G. Seah | Zendy

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A Searching and Tracking Framework for Multi-Robot Observation of Multiple Moving Targets

Author(s) -

Zheng Liu,

Marcelo H. Ang,

Winston K.G. Seah

Publication year - 2004

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.172

H-Index - 20

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2004.p0014

Subject(s) - computer science , tracking (education) , robot , artificial intelligence , field (mathematics) , computer vision , table (database) , motion (physics) , collision avoidance , collision , data mining , psychology , pedagogy , mathematics , computer security , pure mathematics

The "museum problem" is a typical research topic on multi-robot observation of multiple moving targets. The objective of museum problem is to optimize the distribution of robots, such that the maximal moving targets can be observed. In this paper, we present our memory based searching and artificial potential field based tracking framework for museum problem. For searching, a memory table, either local or shared, can help shorten the searching time for targets. For tracking, our artificial potential field based motion control provides real-time tracking of moving targets with collision avoidance. Qualitative simulations demonstrate the capability of our searching and tracking framework.

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