Sensor-based local homing using Omnidirectional Range and Intensity Sensing System for indoor mobile robot navigation

Proposes a novel local homing algorithm for indoor mobile robot navigation. In the algorithm, we divide the whole navigation task into simple local tasks in order to reduce the computational burden and the required memory size. We develop a new environment model based on the omnidirectional sensor data obtained from the Omnidirectional Range and Intensity Sensing System (ORISS), which consists of a set of ultrasonic sensors and a vision sensor. In order to enhance the reliability of the sensor information, we fuse the sensor data by means of the characteristics of the indoor environment structure and the sensor model. To verify the proposed algorithm, experiments with a mobile robot are carried out in a corridor.