Kecheng Sun
Papers
1
Total Citations
4
H-Index
1
About
Kecheng Sun is a robotics researcher whose work focuses on advancing multi-robot motion planning (MRMP) by bridging the gap between global path consistency and real-time local execution. His most-cited paper, "A*-TEB: An Improved A* Algorithm Based on the TEB Strategy for Multi-Robot Motion Planning" (2025, 4 citations), proposes a novel hybrid framework that integrates the global optimality of the A* algorithm with the local dynamic adaptability of the Timed Elastic Band (TEB) strategy. This approach directly addresses a critical limitation in existing MRMP research: the failure to simultaneously ensure strong local planning capabilities and global coordination, which often leads to path conflicts during execution. By fusing these two paradigms, Sun’s work enables robots to maintain efficient, collision-free trajectories in complex, dynamic environments. His contributions are particularly significant for applications in warehouse logistics, autonomous fleets, and collaborative manufacturing, where multiple robots must operate in close proximity without centralized control. Though early in his career, Sun’s research has already garnered attention for its practical impact, offering a scalable solution to one of the most persistent challenges in multi-agent systems.
Research Focus
Key Achievements
Top Papers
- 1