Computer Science Faculty Publications
Document Type
Conference Proceeding
Publication Date
2025
Abstract
Swarm robotics offers robust and scalable solutions for tasks such as foraging, but congestion near central collection zones remains a critical challenge, especially with increasing swarm sizes. Traditional solutions, such as static path planning or local repulsion-based methods, often fail to prevent interrobot collisions or bottlenecks near the collection zones. This research presents a comparative study of three strategies to mitigate congestion when returning resources to the central collection zone. The research herein focuses on tightly packed environments where, in theory, robots should follow a preplanned spiral, either ad-hoc, square, or circular, with congestion detection as described in the first two strategies. Both spiral strategies integrate multiple entry points into the central collection zone and dynamic re-routing upon congestion detection. Experimental evaluation in the ARGoS simulation environment demonstrates significant improvements in task completion time, collision reduction, and system throughput. These results indicate that structured square and circular congestion-aware trajectories can significantly improve swarm foraging efficiency.
Recommended Citation
Gonzalez, Arturo, and Qi Lu. "Congestion Mitigation for Foraging Robot Swarms Using Spiral Path Strategies." In 2025 8th International Conference on Intelligent Robotics and Control Engineering (IRCE), pp. 14-19. IEEE, 2025. https://doi.org/10.1109/IRCE66030.2025.11203171
Publication Title
2025 8th International Conference on Intelligent Robotics and Control Engineering (IRCE)
DOI
10.1109/IRCE66030.2025.11203171
Comments
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