Piyabhum Chaysri
Papers
3
Total Citations
17
H-Index
3
About
Piyabhum Chaysri is a researcher at the intersection of robotics, reinforcement learning, and autonomous systems, with a focus on making advanced robotics more accessible and intelligent. His work spans two key areas: the development of low-cost autonomous surface vehicles and the application of multi-agent reinforcement learning to robotic navigation. Chaysri’s most cited work, "Design and Implementation of a Low-Cost Intelligent Unmanned Surface Vehicle" (2024, 8 citations), demonstrates his commitment to democratizing robotics by building a functional USV for under EUR 1000, significantly lowering the barrier to entry for researchers and hobbyists. His earlier research on multi-agent systems, including "Multiple mini-robots navigation using a collaborative multiagent reinforcement learning framework" (2020, 6 citations) and "Navigation of inertial forces driven mini-robots using reinforcement learning" (2019, 3 citations), explores how reinforcement learning can enable autonomous coordination among small, vibration-driven robots. These contributions highlight his ability to combine practical engineering with cutting-edge AI, offering scalable solutions for swarm robotics and autonomous navigation. Chaysri’s work is particularly notable for its emphasis on cost-effectiveness and adaptability, making him a rising voice in accessible robotics research.
Research Focus
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Top Papers
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