Dynamic Robot Chain Networks for Swarm Foraging

Abstract

The objective of foraging robot swarms is to search for and collect resources in an unknown arena as quickly as possible. To avoid the congestion near the central collection zone, we previously proposed an extension to the multiple-place foraging in which robot chains are deployed dynamically so that foraging robots can deliver to the robot chains instead of the central collection zone. However, a robot chain can only reach one location at a time, and congestion can occur at the end of the robot chain. This paper presents an extension to dynamic robot chains called dynamic robot chain networks, which extends robot chains with branches, each of which reaches different resource clusters. We formulate the problem of finding the smallest dynamic robot chain networks as the Euclidean Steiner tree problem and explain how Steiner trees can be utilized to optimize the efficiency of the foraging operations. We implemented our foraging robot swarms in a simulator called ARGoS. Our experiments showed that dynamic robot chain networks can avoid obstacles and collect more resources when compared with the original robot chain design.