Title :
Neural network approach for obstacle avoidance in 3-D environments for UAVs
Author :
Yadav, Vivek ; Wang, Xiaohua ; Balakrishnan, S.N.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Missouri Univ., Rolla, MO
Abstract :
In this paper a controller design is proposed to get obstacle free trajectories in a three dimensional urban environment for unmanned air vehicles (UAVs). The controller has a two-layer architecture. In the upper layer, vision-inspired Grossberg neural network is proposed to get the shortest distance paths. In the bottom layer, a model predictive control (MPC) based controller is used to obtain dynamically feasible trajectories. Simulation results are presented for to demonstrate the potential of the approach
Keywords :
aerospace control; collision avoidance; control engineering computing; neural nets; predictive control; remotely operated vehicles; controller design; model predictive control based controller; obstacle avoidance; obstacle free trajectories; unmanned air vehicles; vision-inspired Grossberg neural network; Aerospace engineering; Intelligent networks; Neural networks; Neurons; Path planning; Predictive control; Predictive models; Road transportation; Trajectory; Unmanned aerial vehicles;
Conference_Titel :
American Control Conference, 2006
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-0209-3
Electronic_ISBN :
1-4244-0209-3
DOI :
10.1109/ACC.2006.1657288
