Genetic algorithm for path planning of UAVs as a maze-solving problem
Manuel A. Gutierrez-Martinez, Luis E. Cabriales-Ramirez, Edgar Ulises Rojo-Rodríguez, Edmundo Javier Ollervides-Vazquez, P. Castillo, Octavio García Salazar · 2022 International Conference on Unmanned Aircraft Systems (ICUAS) · 2022
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.