Chupeng Su
Papers
4
Total Citations
26
H-Index
4
About
Chupeng Su is a rising researcher at the forefront of intelligent robotic manipulation, with a focus on making assembly and rehabilitation robotics more adaptive and human-centric. His work bridges deep reinforcement learning, multimodal perception, and imitation learning to tackle the fundamental challenge of generalization in semi-structured environments. Su’s most impactful contribution is the development of a task attention-based multimodal fusion framework combined with curriculum residual learning, which enables robots to generalize assembly skills across varying contexts—a critical step toward automating complex, labor-intensive manufacturing. His pioneering approach to shaping exploration space in deep reinforcement learning has also advanced force-controlled assembly, reducing the gap between simulation and real-world deployment. With over 26 citations across his top papers since 2021, Su’s research is gaining traction for its practical implications. Notably, he has extended his expertise to rehabilitation robotics, designing personalized passive training control strategies for lower limb exoskeletons that adapt to individual step lengths. Su’s work stands out for its dual impact: pushing the boundaries of robotic dexterity while addressing real-world needs in manufacturing and healthcare.
Research Focus
Key Achievements
Top Papers
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