Papers
87
Total Citations
2,134
H-Index
22
About
Junzheng Wang is a prominent robotics researcher whose work sits at the intersection of mobile robot control, legged locomotion, and autonomous navigation. His research has made significant contributions to the development of wheel-legged robotic systems, focusing on achieving stable, adaptive motion across unstructured and challenging real-world terrains. Wang's pioneering work on six and four wheel-legged robots has advanced the field considerably, with innovations in gait transition, payload transportation, and flexible motion frameworks that address critical demands in emergency rescue, exploration, and industrial transportation applications. Among his most celebrated contributions is his development of advanced control strategies, including fuzzy-torque approximation-enhanced sliding mode control (196 citations) and neural fuzzy approximation methods (138 citations), which substantially improve lateral stability and trajectory tracking under uncertain physical interactions. His integration of OpenStreetMap-based navigation with 3D LiDAR and CCD camera systems (172 citations) has pushed the boundaries of outdoor autonomous robot navigation. Wang's research into 3D semantic mapping and adaptive impedance control further demonstrates his broad expertise across perception and control domains. Collectively, his publications have accumulated over 1,200 citations, reflecting deep and growing influence on the robotics community and inspiring new generations of researchers tackling complex real-world autonomy challenges.
Research Focus
Key Achievements
Top Papers
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- 4Control strategy of stable walking for a hexapod wheel-legged robot118 citations · 2020
- 5Building and optimization of 3D semantic map based on Lidar and camera fusion101 citations · 2020
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