Xiangmin Wu
Papers
1
Total Citations
8
H-Index
1
About
Xiangmin Wu is a researcher in mobile robotics and autonomous navigation, with a primary focus on path planning and obstacle avoidance. Their most notable contribution is the development of an improved artificial potential field (APF) method for mobile robot path planning, which introduces a subgoal adaptive selection mechanism to overcome the traditional APF's limitations, such as local minima and goal non-reachability. This work, published in 2019, has garnered 8 citations, demonstrating its relevance in advancing practical solutions for real-time robot motion. Wu's research addresses critical challenges in dynamic environments, enhancing the efficiency and safety of autonomous systems. By refining classical algorithms with adaptive strategies, their work supports applications in service robotics, industrial automation, and autonomous vehicles. Wu's contributions are valuable for students and researchers seeking to understand and improve heuristic-based navigation techniques, offering a bridge between theoretical foundations and applied robotics.
Research Focus
Key Achievements
Top Papers
- 1