Bayesian Search Planning is a search planning framework that employs Bayesian inference to iteratively update the probability of a target's location based on prior knowledge and newly acquired evidence, thereby optimizing search efforts under uncertainty.
17
Publications
850
Citations
41
Authors
18
Institutions
Publications per year
2017–2026
3
Parents
Publications
17
ChatGPT Research Group for Optimizing the Crystallinity of MOFs and COFs
Zhiling Zheng, Oufan Zhang, Ha L. Nguyen et al. · ACS Central Science · 2023 · 147 citations · Full text
Search and Rescue Optimal Planning System
Thomas M. Kratzke, Lawrence D. Stone, J R Frost · 2010 · 79 citations
1–5 of 17
Authors
41
- LDLawrence D. Stone
Daniel H. Wagner Associates (United States), United States
3 publications · 167 citations
3
h-index
- TF
3
h-index
- JR
2
h-index
- FB
2
h-index
- TM
2
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1–5 of 41
Institutions
18
The University of Sydney
Sydney, Australia
3 h-index
5 publications
290 citations
Oregon State University
Corvallis, United States
3 h-index
5 publications
150 citations
Metron (United States)
Reston, United States
2 h-index
6 publications
354 citations
Australian Centre for Robotic Vision
Brisbane, Australia
2 h-index
2 publications
158 citations
UNSW Sydney
Sydney, Australia
2 h-index
5 publications
420 citations
Washington State University
Pullman, United States
2 h-index
4 publications
240 citations
United States Coast Guard
Washington D.C., United States
2 h-index
2 publications
144 citations
Daniel H. Wagner Associates (United States)
Exton, United States
2 h-index
3 publications
121 citations
1–8 of 18
Venues
- Naval Research Logistics Quarterly
1 publications · 65 citations
1
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- IEEE Transactions on Control Systems Technology
1 publications · 19 citations
1
h-index
- Autonomous Robots
1 publications · 54 citations
1
h-index
- Polish Maritime Research
1 publications · 17 citations
1
h-index
- Proceedings of the International Conference on Automated Planning and Scheduling
1 publications · 10 citations
1
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1–5