Jincan Li
Papers
2
Total Citations
8
H-Index
2
About
Jincan Li is a researcher focused on advancing multi-robot systems through intelligent path planning and optimization algorithms. Their primary research areas include multi-robot path planning (MRPP), swarm intelligence, and task allocation in complex environments. Li’s major contributions lie in developing novel algorithms that address critical challenges in coordinating multiple robots, such as path conflicts, suboptimal task allocation, and computational inefficiency. Their most notable work, "Hybrid Clustering-Enhanced Brain Storm Optimization Algorithm for Efficient Multi-Robot Path Planning" (2025), introduces the HC-BSO algorithm, which significantly improves solution quality and convergence speed compared to traditional methods. This work has already garnered 4 citations, demonstrating its early impact. Li’s earlier paper, "Path Planning for Unified Scheduling of Multi-Robot Based on BSO Algorithm" (2023), also with 4 citations, laid the groundwork by adapting the Brain Storm Optimization algorithm for unified multi-robot scheduling, tackling collision avoidance and optimal path generation. Together, these contributions offer scalable, efficient solutions for real-world applications like warehouse automation and search-and-rescue operations, marking Li as a promising voice in the field of multi-robot coordination.
Research Focus
Key Achievements
Top Papers
- 1
- 2