Multi-agent Path Planning
Multi-Agent Path Planning is a computational framework within multi-robot scheduling that determines collision-free trajectories for multiple autonomous agents by coordinating their movements from initial positions to designated goals while optimizing path efficiency and respecting spatial and temporal constraints.
579
Publications
32.5K
Citations
1.4K
Authors
454
Institutions
Publications per year
2017–2026
320
Variants
Mapp
Parents
579
Conflict-based search for optimal multi-agent pathfinding
Guni Sharon, Roni Stern, Ariel Felner et al. · Artificial Intelligence · 2014 · 1.2K citations
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454
University of Southern California
Los Angeles, United States
33 h-index
165 publications
12K citations
California Southern University
Chandler, United States
28 h-index
131 publications
9.6K citations
Ben-Gurion University of the Negev
Beersheba, Israel
25 h-index
80 publications
11.1K citations
Carnegie Mellon University
Pittsburgh, United States
20 h-index
71 publications
3.2K citations

Monash University
Melbourne, Australia
15 h-index
47 publications
2.7K citations
Massachusetts Institute of Technology
Cambridge, United States
15 h-index
38 publications
1.9K citations
Simon Fraser University
Burnaby, Canada
13 h-index
23 publications
990 citations
Australian Regenerative Medicine Institute
Clayton, Australia
12 h-index
31 publications
1.3K citations
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Conference · 24 publications · 2.2K citations
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22 publications · 1.4K citations
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21 publications · 1.4K citations
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Repository · 23 publications · 885 citations
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17 publications · 820 citations
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