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Dynamic robot scheduling using a genetic algorithm

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1 Author(s)
Ellefsen, K.O. ; Dept. of Comput. & Inf. Sci., Norwegian Univ. of Sci. & Technol. (NTNU), Trondheim, Norway

This paper describes a genetic algorithm that was developed for optimizing plans in a robotic competition. The algorithm was used both as a static planner, making plans before matches, and as a dynamic replanner during matches, a task with much stricter demands of efficiency. The genetic algorithm was hybridized with a local search technique, which experiments proved essential to finding good solutions in this complex task. To enable rapid response under environmental changes, a heuristic for immediate response and a contingency planning module were also implemented. Experiments proved that the algorithm was able to generate good plans, and continuously modify them in light of a rapidly changing environment.

Published in:

Evolutionary Computation (CEC), 2011 IEEE Congress on

Date of Conference:

5-8 June 2011