Congbo Li

Chongqing University

Papers

3

Total Citations

72

H-Index

3

About

Congbo Li is a leading researcher at the intersection of intelligent robotics and sustainable manufacturing, with key contributions in robotic machining, human-robot interaction, and agricultural automation. His work addresses critical challenges in high-precision, energy-efficient robotic systems. Li’s most cited paper, “Energy-Saving Trajectory Planning for Robotic High-Speed Milling of Sculptured Surfaces” (34 citations), pioneers a method to optimize robot trajectories under complex curvature constraints, significantly reducing energy consumption in manufacturing. In the domain of safe human-robot collaboration, his paper “Toward Safe Human–Robot Interaction: A Fast-Response Admittance Control Method for Series Elastic Actuator” (27 citations) introduces a novel control strategy that mitigates time-delay issues, enabling faster, safer interactions with compliant robots. More recently, Li’s data-driven approach in “Data-driven Bayesian Gaussian mixture optimized anchor box model for accurate and efficient detection of green citrus” (11 citations) demonstrates his versatility, applying advanced machine learning to agricultural robotics for precise fruit detection. With a growing citation impact and a focus on bridging theoretical control methods with practical applications, Li’s work is shaping the future of autonomous, energy-aware, and human-safe robotic systems.

Research Focus

Key Achievements

3
H-Index
3
Papers
72
Total Citations
24
Avg Citations/Paper
🏆 Most Cited Paper
Energy-Saving Trajectory Planning for Robotic High-Speed Milling of Sculptured Surfaces
34 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 13
🏛 Institutions: Chongqing University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago