Jiwei Hu
Papers
15
Total Citations
167
H-Index
8
About
Jiwei Hu is a leading researcher in intelligent robotics, with a primary focus on robotic disassembly, rehabilitation exoskeletons, and human-machine collaboration. His work bridges deep learning, predictive control, and digital twin technologies to create adaptive, autonomous robotic systems. Hu’s most impactful contributions include the development of a predictive exposure control framework for vision-based robotic disassembly, which integrates deep and predictive learning to enhance precision in complex tasks—a paper that has garnered 28 citations. He also designed a reconfigurable upper limb rehabilitation exoskeleton with soft modular joints, addressing the critical need for adaptable, patient-specific therapy devices (25 citations). His dual-loop architecture for deep active learning and human-machine collaboration in smart robot vision (24 citations) further showcases his innovation in real-time robotic adaptation. Additionally, Hu has advanced automatic disassembly with a two-stage screw detection framework using reflection feature regression (15 citations) and obstacle avoidance path planning through improved artificial potential fields and rapidly-exploring random trees (15 citations). With over 150 total citations across his top works, Hu’s research is pivotal for sustainable manufacturing, medical robotics, and intelligent automation, making him a key figure in next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
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- 5Obstacle Avoidance Path Planning Based on Improved APF and RRT15 citations · 2021
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- 7Digital Twin System of Object Location and Grasp Robot9 citations · 2020
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