Mingwei Lin

Papers

Total Citations

115

H-Index

About

Mingwei Lin is a leading researcher in autonomous navigation and robotics, with a primary focus on advancing simultaneous localization and mapping (SLAM) for mobile and underwater robots. His major contributions lie in improving the accuracy and robustness of FastSLAM algorithms, a cornerstone of robot navigation. In his highly cited 2018 work, "An Improved Transformed Unscented FastSLAM With Adaptive Genetic Resampling" (51 citations), Lin introduced a novel fuzzy-based importance sampling method that significantly enhances localization performance. He further refined these techniques in his 2019 paper, "Intelligent Filter-Based SLAM for Mobile Robots With Improved Localization Performance" (22 citations), addressing critical issues like particle impoverishment and degeneracy in particle filters. Expanding into underwater robotics, Lin’s 2024 study on an "Underwater fluid-driven soft dock for dynamic recovery of AUVs" (42 citations) demonstrates his innovative approach to improving pose tolerance for autonomous underwater vehicle recovery. With over 115 citations across his top works, Lin’s research bridges theoretical advancements and practical applications, making him a key figure in the evolution of SLAM technology for real-world autonomous systems.