Sensor fusion for the navigation of Autonomous Guided Vehicle using neural networks

A sensor fusion method for navigation of an Autonomous Guided Vehicle (AGV) robot using Artificial Neural Network (ANN) is described. Robot navigation is defined as the guiding of a mobile robot to a desired destination or along a desired path in an environment characterized by a terrain and a set of distinct objects, such as obstacles and landmarks. The low-level sensor fusion technique is used for direct integration of sensory data, resulting in parameter and state estimates. The multi-layered perceptron, with a single hidden layer in neural network structure, and the back-propagation algorithm are employed for the mobile robot's navigation and for obstacle avoidance. The significance of this work lies in the development of a new estimation method for mobile robot obstacle avoidance and guidance.