Jingwen Huang
Papers
1
Total Citations
13
H-Index
1
About
Jingwen Huang is a robotics researcher whose work centers on multi-robot systems, swarm intelligence, and autonomous navigation. Her most-cited paper, "Source-seeking multi-robot team simulator as container of nature-inspired metaheuristic algorithms and Astar algorithm" (2023, 13 citations), introduces a novel simulation framework that integrates nature-inspired metaheuristic algorithms—such as particle swarm optimization and genetic algorithms—with the classic A* pathfinding approach. This contribution is significant because it provides a modular, containerized platform for testing and comparing diverse algorithms in source-seeking tasks, enabling more efficient coordination of robot teams in unknown or hazardous environments. By bridging metaheuristic optimization with traditional path planning, Huang’s work offers a practical tool for researchers and engineers developing autonomous systems for applications like environmental monitoring, search-and-rescue, and exploration. Her research demonstrates a clear impact in advancing scalable, adaptive multi-robot coordination, and her simulator serves as a valuable benchmark for future studies in swarm robotics and algorithm hybridization.
Research Focus
Key Achievements
Top Papers
- 1