Papers
35
Total Citations
1,632
H-Index
17
About
Philip Dames is a prominent roboticist whose research sits at the intersection of multi-robot systems, autonomous exploration, and probabilistic estimation. Best known for his influential survey on aerial swarm robotics (2018, 634 citations), Dames has helped shape the foundational understanding of how coordinated drone swarms can tackle complex real-world challenges, from search-and-rescue to environmental monitoring. A central thread throughout his work is enabling teams of mobile robots to autonomously detect, localize, and track unknown numbers of targets under uncertainty — problems he addresses using sophisticated probabilistic frameworks such as the Probability Hypothesis Density (PHD) filter and information-theoretic approaches rooted in Shannon and Rényi entropy. His contributions to multi-robot information gathering in hazardous environments demonstrate a consistent focus on safety-aware, decentralized control policies that function even when individual sensors fail or data association is unreliable. More recently, Dames expanded into learning-based robot navigation, with his DRL-VO framework (2023, 121 citations) demonstrating strong generalizability for autonomous navigation through dense pedestrian crowds. Collectively, his work has accumulated over 1,300 citations, reflecting his sustained impact on autonomous robotics, swarm intelligence, and adaptive sensing systems.
Research Focus
Key Achievements
Top Papers
- 1A Survey on Aerial Swarm Robotics634 citations · 2018
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- 7Distributed multi-target search and tracking using the PHD filter70 citations · 2019
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