Genetic algorithm based 3D motion planning for unmanned aerial vehicle
College
Gokongwei College of Engineering
Department/Unit
Electronics And Communications Engg
Document Type
Conference Proceeding
Source Title
2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019
Publication Date
11-1-2019
Abstract
Development of Unmanned Aerial Vehicle (UAV) is now a popular field in research. In most of its applications, a pathfinding algorithm is needed in order to find the optimal path and avoid obstacles. In this paper, a genetic algorithm is implemented in order to determine the optimal path for a UAV that will avoid obstacles along the way. The genetic algorithm implemented uses variable-length chromosomes to solve the problem. The results of the simulation of the system yield an average of 29 generations and avoided 53, 500 collisions to find the best path. © 2019 IEEE.
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Digitial Object Identifier (DOI)
10.1109/HNICEM48295.2019.9072878
Recommended Citation
Rivera, M. C., Del Rosario, J. B., & Bandala, A. A. (2019). Genetic algorithm based 3D motion planning for unmanned aerial vehicle. 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2019 https://doi.org/10.1109/HNICEM48295.2019.9072878
Disciplines
Electrical and Computer Engineering | Electrical and Electronics
Keywords
Drone aircraft in remote sensing; Drone aircraft; Genetic algorithms
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