Papers
10
Total Citations
132
H-Index
5
About
Xuelong Li is a robotics and artificial intelligence researcher whose work spans autonomous robot systems, robotic manipulation, medical imaging, and reinforcement learning. Best known for his contributions to motion planning and control, Li's 2021 paper on Model Predictive Control-based high-speed trajectory tracking for four-wheel independent steering robots has garnered 80 citations, establishing him as a notable voice in mobile robot navigation. His research extends into amphibious robotics, where he developed a multimode robot designed for practical applications such as beach patrol and garbage collection in land-water transition zones, reflecting a commitment to real-world impact. Li has also made meaningful contributions to medical robotics, designing robotic arm-based ultrasound scanning systems capable of three-dimensional quasi-static strain imaging — technology with direct implications for non-invasive clinical diagnostics. More recently, his work has shifted toward intelligent robotic manipulation, exploring affordance-driven next-best-view planning for grasping occluded objects, depth-enhanced policy learning, and cross-domain policy adaptation. His 2025 research on lifelong robot manipulation through primitive prompt learning signals a growing interest in continual learning for adaptive robotic systems. Collectively, Li's portfolio reflects a researcher bridging foundational robotics engineering with cutting-edge machine learning methodologies.
Research Focus
Key Achievements
Top Papers
- 1MPC-based high-speed trajectory tracking for 4WIS robot80 citations · 2021
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- 4Automatic ultrasound scanning system based on robotic arm9 citations · 2019
- 5Affordance-Driven Next-Best-View Planning for Robotic Grasping6 citations · 2023
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- 8Pattern Recognition3 citations · 2016
- 9Cross-Domain Policy Adaptation via Value-Guided Data Filtering3 citations · 2023
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