Papers
1
Total Citations
3
H-Index
1
About
Dr. Qi Lei is a leading researcher in intelligent robotic disassembly and remanufacturing, with a focus on automation and adaptive control strategies for end-of-life product processing. Their most notable contribution is the development of a peg-hole robotic disassembly compliant strategy using the Soft Actor-Critic (SAC) algorithm, a cutting-edge reinforcement learning approach that enables robots to dynamically adjust disassembly forces and avoid damage during complex extraction tasks. This work, published in 2024, addresses a critical bottleneck in remanufacturing efficiency by allowing robots to handle the high variability and force constraints inherent in peg-hole joints—a common but challenging disassembly scenario. With 3 citations to date, this paper has already garnered attention for its practical application of deep reinforcement learning to industrial automation. Dr. Lei’s research bridges the gap between theoretical control algorithms and real-world manufacturing challenges, offering scalable solutions for sustainable production. Their work is particularly valuable for students and engineers interested in robotics, AI-driven manufacturing, and circular economy technologies, demonstrating how intelligent systems can transform waste reduction and resource recovery.
Research Focus
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Top Papers
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