Papers

5

Total Citations

71

H-Index

4

About

Liming Li is a leading researcher in the field of robotics, with a primary focus on the comprehensive evaluation and performance optimization of robotic systems. Their work is distinguished by the innovative application of advanced statistical methods—such as modified principal component analysis and projection pursuit—to create robust, multi-index evaluation frameworks for robots operating in complex, dynamic environments. Li’s major contributions include developing holistic performance assessment systems for earthquake rescue robots and humanoid robot arms, addressing critical needs in disaster response and human-robot interaction. Notably, their 2020 paper on robotic global performance evaluation has garnered 50 citations, underscoring its foundational impact on the field. Li has also pioneered the integration of artificial emotion expression into robotic behaviors, enabling more natural and effective human-robot interactions. Their research on quadruped robot efficiency and motion similarity evaluation further demonstrates a sustained commitment to advancing robotic autonomy and task adaptability. Through these contributions, Li has established a rigorous, data-driven methodology for evaluating and enhancing robot performance, directly influencing the design and deployment of more capable, responsive machines in real-world applications.

Research Focus

Key Achievements

4
H-Index
5
Papers
71
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Comprehensive evaluation of robotic global performance based on modified principal component analysis
50 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Beijing University of Technology, Beijing Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago