Eliot Winer

Papers

Total Citations

102

H-Index

About

Dr. Eliot Winer is a leading researcher in autonomous robotics and swarm intelligence, with a primary focus on developing algorithms for source-seeking tasks using multi-robot systems. His most influential work centers on applying Particle Swarm Optimization (PSO) to enable mobile robots to locate signal sources—such as electromagnetic or chemical emitters—in complex, non-differentiable environments where traditional gradient-based methods fail. His 2015 paper, "Particle Swarm Optimization-Based Source Seeking," which has garnered 99 citations, stands as a cornerstone contribution, demonstrating how swarm-based approaches can effectively solve the source-seeking problem by treating each robot as a particle in the optimization algorithm. This work has significant implications for applications ranging from environmental monitoring to search-and-rescue operations. Additionally, his related study on implementing Standard Particle Swarm Optimization (SPSO) with physical robots provides practical validation of these theoretical concepts, bridging the gap between simulation and real-world deployment. Through his research, Dr. Winer has advanced the field of autonomous navigation and collective robotics, offering scalable, robust solutions for locating unknown sources in dynamic, unstructured environments.