Mike Peasgood

Papers

Total Citations

156

H-Index

About

Mike Peasgood is a leading researcher in multi-robot coordination and scalable motion planning. His work focuses on developing algorithms that allow large teams of robots to navigate complex, shared environments without collisions—a critical challenge for applications like warehouse automation and search-and-rescue. Peasgood’s most influential contribution is his 2008 paper, *"A Complete and Scalable Strategy for Coordinating Multiple Robots Within Roadmaps,"* which has garnered 132 citations. This work introduced a novel approach that moves beyond traditional decoupled planning, offering a complete and scalable solution for finding collision-free trajectories for many robots with individual goals. He also made significant strides in localization for resource-constrained systems, as seen in his 2006 paper on *"Localization of multiple robots with simple sensors"* (10 citations), which presented a distributed particle filter algorithm enabling micro-robots with low-cost infrared sensors to determine their positions. Peasgood’s research is notable for its practical focus on scalability and sensor limitations, bridging the gap between theoretical completeness and real-world deployment in tunnel environments and micro-robot swarms.