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About

Stuart Baker is a leading researcher in multi-robot systems, with a primary focus on cooperative control, formation navigation, and collaborative manipulation. His most impactful work introduces a constrained optimization framework for multi-robot formation control in dynamic environments, enabling teams of robots to autonomously adjust their size and 3D orientation to avoid static and moving obstacles—a paper that has garnered 291 citations. Baker further advanced the field with a method for navigating robot formations using sequential convex programming (63 citations), allowing for local, real-time reconfigurations in complex 2D and 3D spaces. In collaborative assembly, he formulated multi-robot grasp planning as a constraint satisfaction problem (61 citations), enabling sequential assembly operations with collision-free transfers. His earlier work on GPU-accelerated ground segmentation from LIDAR point clouds for autonomous vehicles demonstrates a commitment to practical perception systems. With over 420 total citations across these key contributions, Baker’s research has significantly shaped how multi-robot teams operate safely and efficiently in cluttered, dynamic environments—a critical capability for applications ranging from warehouse logistics to autonomous construction.