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Genetic algorithm for path planning of UAVs as a maze-solving problem

Abstract : This research work addresses the problem of path planning for unmanned aerial vehicles (UAVs) in complex environments such as a maze. A genetic algorithm (GA) with variable chromosomes and gene change conditions is designed when the decision point criteria and a collision with a wall are presented; without considering large chromosomes. Our proposed GA obtains the sequence of minimum movements required to solve the maze. Then, the trajectories are generated by high-order polynomials. Finally, numerical simulations and real-time tests are carried out to validate the proposed algorithm.
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https://hal-cnrs.archives-ouvertes.fr/hal-03844521
Contributor : Pedro Castillo Garcia Connect in order to contact the contributor
Submitted on : Monday, November 21, 2022 - 5:44:27 PM
Last modification on : Tuesday, November 29, 2022 - 12:57:51 PM

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M A Gutierrez-Martinez, L E Cabriales-Ramirez, E U Rojo-Rodriguez, E J Ollervides-Vazquez, Pedro Castillo Garcia, et al.. Genetic algorithm for path planning of UAVs as a maze-solving problem. International Conference on Unmanned Aircraft Systems (ICUAS22), Jun 2022, Dubrovnik, Croatia. pp.881-890, ⟨10.1109/ICUAS54217.2022.9836048⟩. ⟨hal-03844521⟩

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