Papers
2
Total Citations
14
H-Index
2
About
Zhuoyi Lin is a rising researcher at the intersection of robotics, control systems, and human–robot interaction. His work focuses on two key areas: developing intelligent navigation policies for mobile robots in crowded human environments, and advancing control strategies for lower limb rehabilitation exoskeletons. In his highly cited 2023 paper on robot navigation, Lin introduced a novel framework that integrates deep reinforcement learning with gated graph convolutional networks, enabling robots to dynamically learn and prioritize social relations among pedestrians—a critical step toward safe and socially compliant autonomous navigation. This work has already garnered 8 citations, reflecting its timely impact. In parallel, Lin addresses the challenges of gait rehabilitation by proposing an event-triggered sliding mode impulsive control method for exoskeleton robots, achieving robust gait tracking despite disturbances and reducing actuator wear. This contribution, with 6 citations, holds promise for improving the quality of life for patients with lower limb movement disorders. Lin’s research not only pushes the boundaries of autonomous navigation and rehabilitation robotics but also demonstrates a commitment to translating complex control theory into practical, human-centered applications.
Research Focus
Key Achievements
Top Papers
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