Zhouyi Zheng
Papers
2
Total Citations
22
H-Index
1
About
Zhouyi Zheng is a researcher advancing the frontier of robotic manipulation, with a focus on force-relevant skill learning and adaptive control for industrial applications. Their work centers on enabling robots to acquire, generalize, and autonomously tune complex contact tasks—particularly robotic polishing—where environmental uncertainty poses significant challenges. Zheng’s major contribution, the AL-ProMP framework (cited 21 times), introduces a novel method for learning and generalizing force-based skills, allowing robots to adaptively refine their polishing motions in response to real-time force feedback. This approach bridges the gap between human skill acquisition and robotic execution, offering a practical solution for continuous contact tasks in manufacturing. Additionally, their research on adaptive tuning of polishing skills, grounded in force feedback models, demonstrates how robots can dynamically modify learned behaviors to maintain performance in uncertain environments. By integrating human-inspired skill models with adaptive control, Zheng is paving the way for more dexterous and resilient robotic systems in precision manufacturing. Their work holds significant promise for industries seeking to automate complex, force-sensitive processes with greater reliability and efficiency.
Research Focus
Key Achievements
Top Papers
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- 2