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Multi-Robot Task Scheduling with Ant Colony Optimization in Antarctic Environments

Seokyoung Kim, Heoncheol Lee

Year
2023
Citations
17
Access
Open access

Abstract

This paper addresses the problem of multi-robot task scheduling in Antarctic environments. There are various algorithms for multi-robot task scheduling, but there is a risk in robot operation when applied in Antarctic environments. This paper proposes a practical multi-robot scheduling method using ant colony optimization in Antarctic environments. The proposed method was tested in both simulated and real Antarctic environments, and it was analyzed and compared with other existing algorithms. The improved performance of the proposed method was verified by finding more efficiently scheduled multiple paths with lower costs than the other algorithms.

Keywords

Ant colony optimization algorithmsRobotScheduling (production processes)Computer scienceTask (project management)Real-time computingArtificial intelligenceDistributed computingEngineeringSystems engineering

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