Xinmin Chen
Papers
1
Total Citations
27
H-Index
1
About
Xinmin Chen is a leading researcher in mobile robotics and intelligent path planning, with a focus on optimizing autonomous navigation through hybrid algorithms. Their most impactful work introduces a jump point search improved ant colony hybrid optimization algorithm, which significantly enhances path accuracy and reduces unnecessary turns for mobile robots. By integrating jump point search to pre-distribute initial pheromone concentrations, Chen’s approach overcomes traditional ant colony optimization limitations, achieving smoother and more efficient routes. This contribution, cited 27 times since 2022, demonstrates Chen’s ability to merge computational intelligence with practical robotic challenges. Their research addresses critical issues in real-world deployment, such as energy efficiency and obstacle avoidance, making it valuable for students and engineers working on autonomous systems. Chen’s work stands out for its innovative hybridization of search and optimization techniques, offering a robust framework for future advancements in mobile robot navigation and swarm intelligence.
Research Focus
Key Achievements
Top Papers
- 1