Jonathan Smith

University of Hawaiʻi at Mānoa, University of Illinois Urbana-Champaign

Papers

Total Citations

162

H-Index

About

Jonathan Smith is a pioneering researcher in autonomous robotics and adaptive control systems, with his work bridging artificial intelligence and real-time robotic navigation. His most influential contribution is the development of genetic algorithm-based approaches for adaptive motion planning in autonomous mobile robots, as demonstrated in his landmark 2002 paper, which has garnered 156 citations. This work revolutionized how robots navigate unknown or time-varying environments by enabling both off-line and online path planning through evolutionary computation. The adaptive nature of his GA-based framework allows robots to dynamically adjust their trajectories without requiring complete environmental knowledge, making it particularly valuable for applications in search-and-rescue, exploration, and industrial automation. Beyond robotics, Smith has also contributed to quality-of-service management in multimedia feedback control systems, proposing novel admission control and scheduling algorithms for applications involving robot manipulators and cameras. His research demonstrates a consistent focus on creating robust, adaptive systems that can operate effectively under real-world constraints. Smith's work continues to influence modern autonomous systems, particularly in the integration of evolutionary algorithms for real-time decision-making in unpredictable environments.