Papers
11
Total Citations
85
H-Index
6
About
Yongquan Zhang’s research lies at the critical intersection of robotic automation, sustainable manufacturing, and intelligent sensing. His most impactful work addresses the pressing challenge of disassembling electric vehicle (EV) batteries—a task fraught with uncertainty due to varying battery designs and conditions. In his highly cited 2024 paper, Zhang systematically surveys robotic technologies and opportunities for EV battery disassembly, highlighting the urgent need for smart, adaptive automation to enable efficient recycling and remanufacturing. He further advances this domain by developing reinforcement learning methods that inject external knowledge to accelerate robotic disassembly skill acquisition, tackling real-world inefficiencies. Beyond disassembly, Zhang has made notable contributions to precision manufacturing: his work on dual-drive gantry-type machine tools introduces a non-delay error compensation method based on the drive-at-center-of-gravity principle, improving accuracy in CNC machines and industrial robots. He also explores multimodal tactile sensing for space extravehicular operations, demonstrating versatility in sensor design. With papers accumulating citations across robotics, manufacturing, and sensing, Zhang’s research is shaping the future of automated disassembly and high-precision robotic systems, offering practical solutions for industry and sustainability.
Research Focus
Key Achievements
Top Papers
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- 5Dynamic characteristics and research on the dual-drive feed mechanism7 citations · 2021
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