Truck backer-upper: an example of self-learning in neural networks

Derrick Nguyen; Bernard Widrow

doi:10.1117/12.21108

1 January 1990 Truck backer-upper: an example of self-learning in neural networks

Derrick Nguyen, Bernard Widrow

Proceedings Volume 1293, Applications of Artificial Intelligence VIII; (1990) https://doi.org/10.1117/12.21108
Event: 1990 Technical Symposium on Optics, Electro-Optics, and Sensors, 1990, Orlando, FL, United States

Abstract

Neural networks can he used to solve highly nonlinear control problems. A two-layer neural network containing 26 adaptive neural elements has learned to back up a computer simulated trailer truck to a loading dock, even when initially “jackknifed. ’’ It is not yet known how to design a controller to perform this steering task. Nevertheless, the neural net was able to learn of its own accord to do this, regardless of initial conditions. Experience gained with the truck backer upper should be applicable to a wide variety of nonlinear control problems.

Citation Download Citation

Derrick Nguyen and Bernard Widrow "Truck backer-upper: an example of self-learning in neural networks", Proc. SPIE 1293, Applications of Artificial Intelligence VIII, (1 January 1990); https://doi.org/10.1117/12.21108

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