Neural Network Navigation Technique for Unmanned Vehicle

Using a neural network (ANN) for the brain, we want a vehicle to drive by itself avoiding obstacles. We accomplish this by choosing the appropriate inputs/outputs and by carefully training the ANN. We feed the network with distances of the closest obstacles around the vehicle to imitate what a human driver would see. The output is the acceleration and steering of the vehicle. We also need to train the network with a set of strategic input-output. The result is impressive, for a couple of neurons! The unmanned vehicle (UV) drives around avoiding obstacles, but some improvement or modification can be done to make this software work for a specific purpose.

[1]  Samira Chouraqui,et al.  Trajectory Estimation and Control of Vehicle using Neuro-Fuzzy Technique , 2012 .

[2]  Ricardo Martínez-Soto,et al.  Optimization of Interval Type-2 Fuzzy Logic Controllers for a Perturbed Autonomous Wheeled Mobile Robot Using Genetic Algorithms , 2009, Soft Computing for Hybrid Intelligent Systems.

[3]  Karl Johan Åström,et al.  Adaptive Control , 1989, Embedded Digital Control with Microcontrollers.

[4]  Randal W. Beard,et al.  CLF-based tracking control for UAV kinematic models with saturation constraints , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).

[5]  Rajeeva Kumar,et al.  Adaptive control of UAVs in close-coupled formation flight , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[6]  Kimon P. Valavanis,et al.  A framework for fuzzy logic based UAV navigation and control , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[7]  Robert Babuska,et al.  Fuzzy algorithms for control , 1999 .

[8]  Alexander L. Fradkov,et al.  Combined adaptive autopilot for an UAV flight control , 2002, Proceedings of the International Conference on Control Applications.

[9]  Francisco Herrera,et al.  Ten years of genetic fuzzy systems: current framework and new trends , 2004, Fuzzy Sets Syst..

[10]  Narasimhan Sundararajan,et al.  Neuro-controller design for nonlinear fighter aircraft maneuver using fully tuned RBF networks , 2001, Autom..