Chenyuan He
Papers
2
Total Citations
55
H-Index
2
About
Chenyuan He is a leading researcher in autonomous robotics and intelligent control, with a primary focus on multi-robot coordination, path planning, and reinforcement learning under uncertainty. His most influential work, "Integral Reinforcement Learning-Based Multi-Robot Minimum Time-Energy Path Planning Subject to Collision Avoidance and Unknown Environmental Disturbances" (2020, 40 citations), introduces a groundbreaking online adaptive framework that enables multiple robots to simultaneously minimize travel time and energy consumption while navigating unknown, dynamic environments. This work is pivotal for energy-constrained robotic platforms, as it addresses the critical challenge of collision avoidance without prior environmental knowledge. He further advances this paradigm in "Integral reinforcement learning‐based approximate minimum time‐energy path planning in an unknown environment" (15 citations), which provides a foundational solution for single-robot systems facing uncertain disturbances like wind. By integrating integral reinforcement learning with optimal control theory, He’s contributions offer scalable, real-time solutions that significantly improve the efficiency and safety of autonomous systems. His research has substantial implications for applications ranging from drone swarms to planetary exploration, establishing him as a key innovator in adaptive, disturbance-aware robotic navigation.
Research Focus
Key Achievements
Top Papers
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