Yanbiao Li
Papers
16
Total Citations
361
H-Index
11
About
Yanbiao Li is a leading researcher at the intersection of biomimetic robotics, humanoid mechanisms, and soft actuation. His work spans fish-inspired underwater robots, serial-parallel hybrid humanoid arms, and innovative soft robotics. Li’s major contributions include developing multi-objective trajectory planning methods for robotic manipulators—his 2022 paper on an improved elitist non-dominated sorting genetic algorithm (41 citations) and his 2021 work on a 7-DOF hybrid humanoid arm (50 citations) are widely cited. He has advanced inverse kinematics and dynamic load distribution for hybrid mechanisms, with his 2020 paper on inverse displacement analysis of a novel humanoid arm garnering 47 citations. Li also pioneers soft robotics, creating high-performance PVC gel actuators for lightweight humanoid facial robots (2024, 15 citations) and fiber-constrained actuators (2023, 23 citations). His comprehensive review on fish-inspired robots (2022, 63 citations) and his review on humanoid robot heads for human-robot interaction (2023, 17 citations) are essential references. Notably, Li applies reinforcement learning to quadruped gait planning (2023, 15 citations) and uses screw theory for generalized kinematics analysis (2021, 18 citations). With over 325 citations across his top works, Li’s research is shaping the future of adaptive, bio-inspired, and human-friendly robotic systems.
Research Focus
Key Achievements
Top Papers
- 1A comprehensive review on fish-inspired robots63 citations · 2022
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- 3Inverse displacement analysis of a novel hybrid humanoid robotic arm47 citations · 2020
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- 8Humanoid robot heads for human-robot interaction: A review17 citations · 2023
- 9A Hierarchical Framework for Quadruped Robots Gait Planning Based on DDPG15 citations · 2023
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