A genetic algorithm for robust motion planning
This paper proposes a solution by genetic algorithms to the problem of planning a robust and suboptimal trajectory in the velocity space of a mobile robot. Robust trajectories are obtained introducing cumulative noise in the evaluation of the fitness function and introducing modifications in the genetic algorithm to taking into account this new feature. Results are presented that show the performance of the algorithm in different environments and the influence of the noise in the planned trajectories.
Keywordsnonholonomic motion planning robust robot motion evolutionary computation in noisy environments
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