Agent-Based Simulations for Multi-Robot Systems Exploration of Tree-Like Environments

Abstract

In this paper, an agent-based simulation model is proposed to explore an unknown tree with arbitrary edge distances by a set of robots which are initially located at the root of the tree and expected to return back to the root after all nodes are explored. The proposed algorithm depends only on local information stored at nodes using a bookkeeping token left at nodes by robots. It is shown that the proposed algorithm with the Earliest Selection Policy (ESP) is superior to using Random Selection Policy (RSP). The proposed agents-based simulation can be used to study general cases of network and tree exploration problems by multiple robots.