We present a biologically inspired design for swarm foraging based on ant's pheromone deployment, where the swarm is assumed to have very restricted capabilities. The robots do not require global or relative position measurements and the swarm is fully decentralized and needs no infrastructure in place. Additionally, the system only requires one-hop communication over the robot network, we do not make any assumptions about the connectivity of the communication graph and the transmission of information and computation is scalable versus the number of agents. This is done by letting the agents in the swarm act as foragers or as guiding agents (beacons). We present experimental results computed for a swarm of Elisa-3 robots on a simulator, and show how the swarm self-organizes to solve a foraging problem over an unknown environment, converging to trajectories around the shortest path. At last, we discuss the limitations of such a system and propose how the foraging efficiency can be increased.
翻译：我们根据蚂蚁的外激素部署情况,提出了一种生物启发的群温迁移设计,假设群温的能力非常有限。机器人不需要全球或相对位置的测量,而群温完全分散,不需要基础设施。此外,系统只需要机器人网络的一杆通信,我们并不对通信图的连通性做出任何假设,信息传输和计算与代理人的数量相比是可缩放的。让群温中的代理人作为前锋或指导剂(beacons)来完成这项工作。我们为模拟器上的一群Elisa-3机器人计算了实验结果,并展示了暖热自我组织如何在未知环境中解决问题,在最短的路径周围凝聚到轨迹。最后,我们讨论了这种系统的局限性,并提出了如何提高捕捉效率的建议。
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