Papers

3

Total Citations

12

H-Index

3

About

Xumei Lin is a robotics researcher whose work centers on autonomous navigation, path planning, and simultaneous localization and mapping (SLAM) for mobile and aerial robots. Her major contributions lie in developing hybrid algorithms that overcome the limitations of traditional methods. In her most cited work (2023, 6 citations), she fused an improved A* algorithm with the Timed Elastic Band (TEB) approach to create smoother, more stable paths for wheeled robots, addressing issues of curve roughness and jerky command outputs. She further advanced SLAM technology for indoor aerial robots (2024, 3 citations) by integrating multi-sensor fusion to enhance mapping stability in feature-degraded environments and improve vertical estimation accuracy. Earlier, Lin explored bio-inspired optimization with a Beetle Antennae Search (BAS)-based global path planner (2019, 3 citations), which boosted speed and adaptability in obstacle avoidance. Her work demonstrates a consistent focus on practical, real-world improvements to autonomous navigation systems, making her research valuable for students and engineers working on robot autonomy, particularly in challenging indoor and unstructured environments.

Research Focus

Key Achievements

3
H-Index
3
Papers
12
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Path Planning for Wheeled Robots Based on the Fusion of Improved A* and TEB Algorithms
6 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Qingdao University of Science and Technology, Qingdao University of Technology

Top Papers

  1. 1
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  3. 3

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago