Title :
Path planning based on Genetic Algorithms and the Monte-Carlo method to avoid aerial vehicle collisions under uncertainties
Author :
Cobano, J.A. ; Conde, R. ; Alejo, D. ; Ollero, A.
Author_Institution :
Univ. of Seville, Seville, Spain
Abstract :
This paper presents a collision-free path planning method for an aerial vehicle sharing airspace with other aerial vehicles. It is based on grid models and genetic algorithms to find safe trajectories. Monte-Carlo method is used to evaluate the best predicted trajectories considering different sources of uncertainty such as the wind, the inaccuracies in the vehicle model and limitations of on-board sensors and control system.
Keywords :
Monte Carlo methods; aircraft control; collision avoidance; genetic algorithms; sensors; Monte Carlo method; aerial vehicle collision; collision-free path planning; genetic algorithm; grid model; on-board sensor; Atmospheric modeling; Computational modeling; Genetic algorithms; Prediction algorithms; Trajectory; Uncertainty;
Conference_Titel :
Robotics and Automation (ICRA), 2011 IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-61284-386-5
DOI :
10.1109/ICRA.2011.5980246
