Papers

3

Total Citations

31

H-Index

2

About

Wankai Li is an emerging researcher whose work spans robotics, autonomous systems, and computational optimization. Li's most significant contribution lies in the domain of indoor robot localization, where their research tackles the persistent challenge of single-sensor positioning limitations in wheeled robots. By developing a sophisticated multi-sensor fusion approach that integrates wheel odometry dead reckoning, Inertial Measurement Unit data, and LiDAR-derived environmental mapping, Li has demonstrated a meaningful advancement in reliable indoor navigation — work that has already attracted 25 citations since its 2024 publication, reflecting strong community interest. Beyond robotics, Li has shown a creative aptitude for bio-inspired computation, introducing the Crown Growth Optimizer, a novel meta-heuristic algorithm modeled on the biological mechanics of tree crown development. This algorithm elegantly balances global exploration and local exploitation through simulated growing, sprouting, and pruning processes, with demonstrated applications in engineering optimization problems. Though still in the early stages of their research career, Li's interdisciplinary reach — bridging physical robotic systems and algorithmic innovation — signals a promising trajectory. Students interested in autonomous navigation or evolutionary computation would find Li's growing body of work both accessible and technically stimulating.

Research Focus

Key Achievements

2
H-Index
3
Papers
31
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Multi-sensor fusion based wheeled robot research on indoor positioning method
25 citations · 2024
📈 Most Prolific Year: 2024 (3 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Xiamen University of Technology, Shanghai University of Electric Power

Top Papers

  1. 1
  2. 2
  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago