Sensor fusion for prediction of orientation and position from obstacle using multiple IR sensors an approach based on Kalman filter

Abstract

Kalman filters have gained immense research attention in robotics, throughout the last decades. Among the applications, localization of robots through Kalman filters proved promising results. This paper presents an application of sensor fusion for prediction of orientation and depth to wall/obstacle by fusing the inputs from three IR range finders. The experimental result demonstrates the capability of Kalman filter to predict the parameters precisely, from noisy sensor inputs. The technique find application in determining the position and orientation from wall which will be helpful in obstacle avoidance decision making, automatic parking of automobiles etc.