Papers
51
Total Citations
503
H-Index
12
About
Guoyu Zuo is a robotics researcher whose work spans locomotion control, human-robot interaction, machine learning, and autonomous manipulation. With a career rooted in the study of legged and wheeled robotic systems, Zuo made early contributions to evolutionary computation-based gait optimization — a foundational challenge in mobile robotics — earning 70 citations for a comprehensive 2010 review that remains a key reference in the field. His parallel work on two-wheeled self-balancing robots and agricultural path planning demonstrated a breadth of applied robotics expertise. As his research evolved, Zuo pioneered a pneumatic tactile sensor for collaborative robots (56 citations), addressing the critical need for safe, intuitive human-robot interaction. More recently, he has embraced cutting-edge machine learning techniques, contributing notable work in generative adversarial imitation learning, sparse-reward reinforcement learning, and graph-based deep reinforcement learning for robotic grasping in complex, occluded environments. His 2023 work on Bayesian fuzzy broad learning for joint servo control reflects a continued push toward intelligent, adaptive robot systems. Collectively, his publications have accumulated over 300 citations, marking him as a versatile and impactful voice in modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1A Review of Gait Optimization Based on Evolutionary Computation70 citations · 2010
- 2A Pneumatic Tactile Sensor for Co-Operative Robots56 citations · 2017
- 3Deterministic generative adversarial imitation learning35 citations · 2020
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- 8Path planning algorithm based on sub-region for agricultural robot21 citations · 2010
- 9Multi-robot Formation Control Using Reinforcement Learning Method18 citations · 2010
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