Design of a Low-cost Autonomous Mobile Robot

Abstract

Detection of obstacles during navigation of a mobile robot is considered difficult due to varying nature in terms of size, shape and location of the obstacle as well as ambient light that interferes with infra-red (IR) signals of the robot. In this paper, we propose a novel low-cost method that successfully guides a robot along a path using image processing and IR sensor circuits. A high continuous IR signal is converted into a low continuous IR signal by means of a demodulation circuit that enables a peripheral interface controller to receive this low continuous IR signal and take relevant decisions based on the signal. The images taken from a web camera are preprocessed to remove noise and detect edges. Subsequently, an image processing routine effectively calculates the angle to be rotated of the front wheels using a scan line algorithm. A minimum mean distance error of 2.45 was observed in tracking the path at a signal-to-nose ratio of 26.50. The accuracy of speech recognition was 92% for two voice training sessions.