Yanpu Lei

Huazhong University of Science and Technology

Papers

Total Citations

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About

Yanpu Lei is a robotics researcher focused on advancing intelligent automation for manufacturing, with key contributions in variable impedance control, multi-robot collaboration, and vision-guided assembly. His work addresses critical challenges in industrial robotics, particularly for the high-precision demands of 3C (computer, communication, and consumer electronics) manufacturing. Lei’s most cited paper, “Variable Impedance Control of Manipulator Based on DQN” (2020, 4 citations), pioneers the use of deep reinforcement learning to dynamically adjust robot stiffness and damping, enabling safer and more adaptive human-robot interaction. In “Multi-robot Collaborative Assembly Research for 3C Manufacturing” (2019, 4 citations), he proposes a framework for coordinating multiple manipulators in complex tasks like server motherboard assembly, demonstrating practical scalability. His work “Vision-Based Position/Impedance Control for Robotic Assembly Task” (2019, 3 citations) integrates computer vision with impedance control to eliminate tedious manual target pose detection, streamlining real-world industrial processes. Though early in his career, Lei’s research bridges reinforcement learning, multi-agent systems, and sensor-based control, offering tangible solutions for next-generation smart factories. His contributions are particularly notable for their direct applicability to high-mix, low-volume production environments.