Papers
9
Total Citations
64
H-Index
5
About
Kiwon Yeom is a robotics researcher whose work spans autonomous navigation, swarm intelligence, and medical robotics. His primary contributions lie in developing intelligent control systems for mobile robots, particularly car-like platforms, where he has pioneered the integration of deep reinforcement learning and neural network-based model predictive control for collision-free autonomous driving. His 2022 paper on deep reinforcement learning for mobile robots has garnered 17 citations, while his work on neural network-based model predictive control has received 12 citations, demonstrating significant impact in the field of autonomous navigation. Yeom has also made notable contributions to swarm robotics, with his 2010 paper on artificial morphogenesis for arbitrary shape generation using multi-agent systems (5 citations) exploring how simple modular robots can self-organize into desired structures through evolutionary developmental methods. More recently, he has ventured into medical robotics, developing a robotic system for precise vascular access and autonomous venipuncture (2024, 4 citations), as well as an injection-point determination algorithm for intelligent injection robots (2023, 4 citations). His work on bio-inspired control synthesis for steerable robotic bars (2018, 5 citations) further showcases his versatility in applying biological principles to robotic design.
Research Focus
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