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Multi-objective optimization in autonomous foraging using swarm robots
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AI
DOI：10.1016/j.swevo.2026.102294.png)
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Abstract
En 中文
Swarm robotics is an innovative field focused on developing collective behaviors through local interactions among simple robots, enabling scalability and flexibility across a wide range of tasks. This study presents a behavioral model for collective foraging based on RAOI (repulsion, attraction, orientation, and influence) parameters, and investigates how their tuning affects multi-objective performance in robot swarms. Our approach explores the relationship between RAOI parameter configurations and task-level performance metrics, allowing systematic analysis of emergent swarm behaviors in dynamic environments.
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