Probabilistic Coverage Control
Probabilistic Coverage Control is a coverage control framework that distinguishes itself by incorporating probabilistic models to govern sensor placement and sensing performance, accounting for uncertainty in environment representation, sensor measurements, or actuation, thereby optimizing coverage in stochastic or partially known environments.
23
Publications
2.6K
Citations
65
Authors
34
Institutions
Publications per year
2017–2026
2
Parents
23
On k-coverage in a mostly sleeping sensor network
Santosh Kumar, Ten H. Lai, József Balogh · 2004 · 643 citations
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34
Japan Science and Technology Agency
Tokyo, Japan
2 h-index
4 publications
128 citations
Tokyo Institute of Technology
Tokyo, Japan
2 h-index
6 publications
298 citations
Boston University
Boston, United States
2 h-index
4 publications
456 citations
Kyushu University
Fukuoka, Japan
2 h-index
2 publications
64 citations

University of North Carolina at Charlotte
Charlotte, United States
2 h-index
7 publications
620 citations

Nara Institute of Science and Technology
Ikoma, Japan
2 h-index
6 publications
192 citations
William & Mary
Williamsburg, United States
1 h-index
5 publications
185 citations

Oak Ridge National Laboratory
Oak Ridge, United States
1 h-index
2 publications
34 citations
1–8 of 34
TMCCI · 2 publications · 88 citations
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1 publications · 43 citations
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1 publications · 13 citations
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1 publications · 11 citations
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1 publications · 201 citations
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