Peter J. Stuckey

Monash University, Australian Research Council, Australian Regenerative Medicine Institute

Papers

Total Citations

265

H-Index

About

Peter J. Stuckey is a prominent researcher whose work sits at the intersection of combinatorial optimization, robotics, and artificial intelligence, with a particular focus on multi-agent path finding (MAPF) and multi-agent pickup and delivery (MAPD) problems. His research addresses some of the most pressing challenges in autonomous systems, including how teams of robots can efficiently navigate shared environments without collisions while completing real-world logistical tasks. Stuckey's most influential contribution, "Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery" (2021, 184 citations), tackles the complex industrial problem of coordinating robot fleets in warehouse logistics and mail sortation systems — domains with enormous economic relevance. His branch-and-cut-and-price framework for MAPF (2022, 58 citations) demonstrates his expertise in bringing rigorous mathematical programming techniques to bear on robot coordination problems. More recently, his work on traffic flow optimization for lifelong MAPF addresses a critical scalability bottleneck that hampers existing algorithms as agent counts grow. Through innovative algorithmic contributions spanning temporal obstacle handling and large-scale path planning, Stuckey has established himself as a key figure in advancing autonomous multi-robot systems, with his work informing both academic research and practical deployment in modern automated logistics environments.