Hongyang Li
Papers
3
Total Citations
58
H-Index
2
About
Hongyang Li’s research lies at the intersection of robotics, optimal control, and embodied intelligence, with a focus on enabling robots to achieve dynamic, efficient, and generalizable locomotion and manipulation. His early work pioneered the use of discrete mechanics and optimal control (DMOC) for bipedal walking robots, introducing a superlinear convergent feasible sequential quadratic programming algorithm (FSQPA) that solved periodic gait optimization problems with provable efficiency and global convergence. This foundational contribution, published in 2015, has garnered 54 citations and remains a reference point for optimization-driven locomotion. Li further advanced this line of work with a smoothing penalty function method, enhancing the robustness of gait trajectory generation under constraints. More recently, he has turned his attention to robotic manipulation, proposing a dual-system framework that synergizes a generalist policy—trained on large, cross-embodiment data for broad adaptability—with a specialist module for precise, task-specific control. This 2024 work addresses the critical challenge of balancing generalization and specialization in real-world robotics. Across his career, Li’s contributions have been supported by national programs including the 863 Plan and the National Natural Science Foundation of China, underscoring his role in advancing both theoretical optimization and practical robotic systems.
Research Focus
Key Achievements
Top Papers
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