Multi-Robot Task Scheduling with Ant Colony Optimization in Antarctic Environments
Seokyoung Kim, Heoncheol Lee
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.
Topics & Concepts
Ant colony optimization algorithmsRobotScheduling (production processes)Computer scienceTask (project management)Real-time computingArtificial intelligenceDistributed computingEngineeringSystems engineeringOperations managementRobotic Path Planning AlgorithmsOptimization and Search ProblemsModular Robots and Swarm Intelligence