Lianzheng Ge
Papers
13
Total Citations
120
H-Index
6
About
Lianzheng Ge is a leading researcher in human-robot collaboration and industrial robotics, with a focus on enhancing the safety, precision, and autonomy of robotic systems. His work spans human-robot interaction, kinematic calibration, and dynamic performance optimization, addressing critical challenges in both collaborative and autonomous robots. Ge’s most cited paper, "An Augmented Discrete‐Time Approach for Human‐Robot Collaboration" (2016, 29 citations), pioneers methods to improve interactive performance between humans and robots, a cornerstone of next-generation robotics. He also developed a novel calibration method combining Levenberg-Marquardt and particle filter algorithms for industrial robots (2020, 18 citations), significantly boosting absolute positioning accuracy. His research extends to mobile robotics, including abnormal pedestrian trajectory detection for public safety (2021, 11 citations) and target recognition using monocular PTZ cameras (2019, 9 citations). Ge’s contributions have practical implications for manufacturing, service robotics, and security, with cumulative citations exceeding 100. His work on redundancy resolution for mobile dual-arm robots (2016, 8 citations) and motion optimization for humanoid robots (2021, 6 citations) further underscores his impact on advancing robotic dexterity and adaptability.
Research Focus
Key Achievements
Top Papers
- 1An Augmented Discrete‐Time Approach for Human‐Robot Collaboration29 citations · 2016
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- 7Motion optimization of humanoid mobile robot with high redundancy6 citations · 2021
- 8A Hybrid SLAM method for service robots in Indoor Environment5 citations · 2011
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