A neural network-based navigation system for mobile robots

For mobile robots to be autonomous, they should have essential functional capabilities such as determination of their current location and heading angle, path control in order to follow the desired path and local path planning for uncertain environments. This paper deals with the above three issues and illustrates how the artificial neural network can be utilized to solve such problems. This neural network-based navigation system offers a method of determining the mobile robot´s position-a 3D landmark sensing system with neural estimator. It also offers a neural net-based feedforward controller designed to accurately track a desired path and a sensor-based local path planning capability to adapt to complex and changing environments. System software/hardware architecture to implement the above functional capabilities are discussed and some experimental and simulation results are illustrated to show the effectiveness of the proposed navigation system