Yuming Ning
Papers
6
Total Citations
68
H-Index
3
About
Yuming Ning is a robotics researcher whose work focuses on advancing autonomous multi-robot systems, intelligent manipulation, and robot skill learning. His major contributions lie in developing novel algorithms and frameworks that enable robots to operate more efficiently and safely in complex, unstructured environments. Notably, his highly cited paper "HMS-RRT" (33 citations) introduces a hybrid multi-strategy rapidly-exploring random tree algorithm for multi-robot collaborative exploration, significantly improving coordination and coverage in unknown terrains. Another influential work, "Inverse kinematics and planning/control co-design method of redundant manipulator for precision operation" (27 citations), addresses the challenge of precise manipulation by integrating kinematics and control design. Ning has also pioneered learning-based approaches, such as the MT-RSL framework, which leverages continuous dynamic movement primitives to enhance the efficiency and quality of robot-based intelligent operations. His research on robot imitation learning, including TS-RIL and H-RIL, tackles real-world obstacles and modular assembly tasks. With a growing citation impact and a focus on bridging theory and practical deployment, Yuming Ning is shaping the future of intelligent robotics.
Research Focus
Key Achievements
Top Papers
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- 4A robot motion skills method with explicit environmental constraints2 citations · 2024
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