Daniel J. Warner

Papers

Total Citations

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About

Daniel J. Warner is a leading researcher in distributed robotics and autonomous systems, with a focus on the theoretical foundations of multi-robot coordination. His work centers on developing rigorous mathematical frameworks for analyzing and guaranteeing the behavior of mobile robot swarms, particularly in tasks like gathering and convergence. Warner’s most influential contributions include a novel approach for analyzing convergence algorithms for mobile robots (2011, 54 citations), which introduced a powerful new methodology for proving that distributed control strategies will reliably bring robots together. He also made a seminal contribution to the problem of collisionless gathering of robots with physical extent (2011, 43 citations), addressing a critical challenge in real-world robotics: ensuring that robots with non-zero size can assemble without collisions. These papers have become foundational references in the field, cited by researchers working on everything from swarm robotics to sensor networks. Warner’s work is notable for its elegant blend of geometry, control theory, and algorithmic analysis, providing both practical design principles and deep theoretical insights that continue to shape how engineers build reliable, scalable multi-robot systems.