Papers
16
Total Citations
333
H-Index
9
About
Xiu Li is a versatile researcher whose work spans intelligent robotics, reinforcement learning, computer vision, and industrial automation. With contributions ranging from smart manufacturing to rehabilitation engineering, Li has established a reputation for bridging theoretical innovation with real-world application. His 2020 paper on steel surface defect inspection, which has garnered an impressive 170 citations, demonstrates his capacity to deliver practical AI-driven solutions for industrial monitoring challenges. In wearable robotics, Li has made notable strides through adaptive impedance control frameworks and the BEAR-H exoskeletal rehabilitation robot, advancing human motion intention modeling to improve assistive and therapeutic devices. His work in reinforcement learning is equally prolific, encompassing multi-goal sparse-reward problems, continual learning in dynamic environments, and multi-entity task allocation — contributions that push the boundaries of autonomous decision-making. Li has also extended his expertise to underwater robotics, introducing the ROV6D benchmark dataset for 6D pose estimation, and has explored reinforcement learning's potential within nuclear power plant operations. Collectively, his portfolio reflects a researcher deeply committed to deploying intelligent systems across diverse, high-stakes domains, making him a significant voice in modern applied AI and robotics research.
Research Focus
Key Achievements
Top Papers
- 1A steel surface defect inspection approach towards smart industrial monitoring170 citations · 2020
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- 6Biology's drones: New and improved13 citations · 2014
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- 8MHER: Model-based Hindsight Experience Replay13 citations · 2021
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