Papers
9
Total Citations
366
H-Index
8
About
James Paulos is a leading researcher in multi-robot systems, decentralized control, and autonomous maritime robotics. His most influential work tackles the grand challenge of self-assembling large floating structures using swarms of robotic boats. In his highly cited 2015 paper (93 citations), Paulos demonstrated how identical autonomous boats could autonomously dock together to form variable-stiffness platforms, a breakthrough with implications for temporary ports, disaster response, and offshore construction. He has since pioneered the use of Graph Neural Networks (GNNs) for multi-robot coordination, with two 67-citation papers showing how GNNs can learn decentralized controllers for robot swarms and solve coverage problems for inspection and search-and-rescue missions. Paulos also contributed to multi-agent pursuit-evasion games and communication-efficient robot teams. His open-source simulator, RotorPy (2023), provides a lightweight Python-based tool for aerial robotics education and research. With over 350 total citations across his portfolio, Paulos bridges theory and practice, advancing both the algorithms and the hardware that enable large-scale robot teams to work together in the real world.
Research Focus
Key Achievements
Top Papers
- 1
- 2Multi-Robot Coverage and Exploration using Spatial Graph Neural Networks67 citations · 2021
- 3
- 4Self-assembly of a swarm of autonomous boats into floating structures56 citations · 2014
- 5Team Composition for Perimeter Defense with Patrollers and Defenders39 citations · 2019
- 6Coverage Control in Multi-Robot Systems via Graph Neural Networks22 citations · 2022
- 7Learning Connectivity for Data Distribution in Robot Teams10 citations · 2021
- 8
- 9Decentralization of Multiagent Policies by Learning What to Communicate4 citations · 2019