Xinchen Tang
Papers
1
Total Citations
14
H-Index
1
About
Xinchen Tang is a rising researcher in autonomous robotics, whose work centers on intelligent path planning and multi-robot coordination in complex, dynamic environments. Tang’s most significant contribution is the development of a dual-layer symmetric path planning system, which integrates an improved Glasius bio-inspired neural network with the Dynamic Window Approach (DWA) algorithm. This innovative framework addresses critical challenges in real-time collision avoidance and efficient navigation for multi-robot systems, offering a robust solution that balances global path optimization with local reactive control. The foundational paper on this work, published in 2025, has already garnered 14 citations, signaling its immediate impact and relevance in the field. Tang’s research is particularly notable for its practical application in scenarios requiring high reliability and adaptability, such as warehouse automation and search-and-rescue operations. By advancing the capabilities of neural network-based planning in symmetric, cooperative settings, Tang is helping to push the boundaries of how autonomous systems can safely and effectively operate alongside one another.
Research Focus
Key Achievements
Top Papers
- 1