Papers
48
Total Citations
1,823
H-Index
20
About
Jiehao Li is a prominent robotics researcher whose work spans mobile robot control, autonomous navigation, and intelligent systems. His research has made significant contributions to the development of wheel-legged robots, advancing their stability, motion flexibility, and real-world applicability across challenging terrains and complex operational scenarios. Li's most impactful work focuses on control methodologies for lateral stability and trajectory tracking in mobile robots. His 2021 paper introducing fuzzy-torque approximation-enhanced sliding mode control has garnered 196 citations, reflecting its broad influence on the field. Complementing this, his neural fuzzy approximation framework for wheel-legged robots under uncertain physical interaction (138 citations) demonstrates his expertise in adaptive intelligent control strategies. His contributions to six wheel-legged robot design — covering flexible motion frameworks, gait transitions, and heavy-payload transportation — collectively represent a cohesive research program pushing the boundaries of hybrid locomotion systems. Beyond control theory, Li has made notable strides in autonomous navigation, developing OpenStreetMap-based outdoor navigation using 3D LiDAR and CCD cameras (172 citations), and advancing 3D semantic mapping through sensor fusion (101 citations). His more recent work on agricultural robotics, including a lightweight tea bud detection network achieving 132 citations, showcases his versatility. With over 1,000 cumulative citations, Li's research continues shaping the future of intelligent autonomous robots.
Research Focus
Key Achievements
Top Papers
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- 5Building and optimization of 3D semantic map based on Lidar and camera fusion101 citations · 2020
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