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An Unknown Environment Exploration Strategy for Swarm Robotics Based on Brain Storm Optimization Algorithm

Li Gao, Dabu Zhang, Yuhui Shi

Year
2019
Citations
18

Abstract

In this paper, a distributed algorithm used to solve the swarm robotic exploration problem with communication constraint conditions is proposed. The swarm robotics exploration problem is represented as an optimization problem in this paper, and a modified Brain Storm Optimization algorithm is utilized to solve this problem. This swarm robotic exploration algorithm has several advantages compared to traditional strategies. Firstly, it is fully decentralized, which suits for swarm robotic application. What is more, it is easy to combine this algorithm with many existing frontier-based exploration methods to improve robots' cooperation ability. Finally, the proposed method has been tested in several different simulation environments, and the experimental results demonstrate its advantages over other approaches.

Keywords

Swarm behaviourSwarm roboticsComputer scienceArtificial intelligenceRoboticsRobotAnt roboticsConstraint (computer-aided design)Multi-swarm optimizationAlgorithm

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