Phillip G. Holloway
Papers
1
Total Citations
19
H-Index
1
About
Phillip G. Holloway is a researcher whose work lies at the intersection of swarm intelligence and collective robotics, with a particular focus on distributed decision-making and obstacle avoidance in autonomous systems. His most influential contribution, the 2006 paper "Obstacle Avoidance in Collective Robotic Search Using Particle Swarm Optimization," has garnered 19 citations and remains a foundational reference for applying bio-inspired algorithms to multi-robot coordination. In this work, Holloway demonstrated how particle swarm optimization (PSO) could be adapted to enable a team of robots to navigate unknown environments while avoiding obstacles, effectively merging principles from computational intelligence with real-world robotic constraints. This research not only advanced theoretical understanding of emergent behavior in swarms but also provided practical pathways for deploying low-cost, decentralized robotic teams in search-and-rescue and environmental monitoring missions. Holloway’s work is notable for its clarity in bridging algorithmic development with experimental validation, making it a valuable resource for students and researchers exploring adaptive robotics. Through his focused contributions, Holloway has helped shape how engineers think about scalability and robustness in collective autonomous systems.
Research Focus
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Top Papers
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