Xuanyang Shi
Papers
13
Total Citations
98
H-Index
6
About
Xuanyang Shi is a robotics researcher whose work centers on the control and motion planning of legged and humanoid robots, with a particular focus on achieving dynamic, stable, and highly agile locomotion. His major contributions span the development of optimization-based control frameworks for complex maneuvers, including bipedal walking, vertical jumping, and disturbance recovery. Shi has pioneered the use of quadratic programming (QP) and model predictive control (MPC) to handle over-constrained control objectives in real time, enabling robots to perform tasks like upward jumping and precise stepping on stones. His most cited work, "A Multitasking-Oriented Robot Arm Motion Planning Scheme Based on Deep Reinforcement Learning and Twin Synchro-Control" (35 citations), integrates deep reinforcement learning with digital twin technology for humanoid arms, aligning with Industry 4.0 and Made in China 2025 initiatives. Additionally, his research on stiffness optimization and hierarchical quadratic programming for bipedal walking (12 citations) has advanced the application of spring-loaded inverted pendulum models. Shi’s work also extends to practical applications, such as multi-robot disaster information sensing and low-cost obstacle avoidance for miniature reconnaissance robots. With over 90 total citations, his research is shaping the future of dynamic, whole-body control in robotics.
Research Focus
Key Achievements
Top Papers
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- 3Vertical Jumping for Legged Robot Based on Quadratic Programming9 citations · 2021
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