Pattern Recognition and Text-Dependent Recognition for a Mobile Robot

Pattern Recognition and Audio Processing are important aspects in the control and behavior of mobile robots. Mobile robot´s action depends on the recognition of visual and audio stimuli in order to reflect intelligent behavior of the robot. This work presents two recognition systems developed using morphological operations and Linear Predictive Coding (LPC) with Backpropagation Neural Networks (BNN) to process visual and audio data respectively. The objective is to design a person tracking system for a mobile robot with text dependent pitch recognition and a visual pattern recognition mechanism. The BNN will awake the robot from the idle position, while the visual stimulation will be used to track the person given the command.