A Probabilistic Model for AGV Mobile Robot Ultrasonic Sensor

An autonomous guided vehicle (AGV) is a multi-sensor mobile robot. The sensors of a multi-sensor robot system are characteristically complex and diverse. They supply observations, which are often difficult to compare or aggregate directly. To make efficient use of the sensory information, the capabilities of each sensor must be modeled to extract information from the environment. For this goal, a probability model of ultrasonic sensor (PMUS) is presented in this paper. The model provides a means of distributing decision making and integrating diverse opinions. Also, the paper illustrates that a series of performance factors affect the probability model as parameters. PMUS could be extended to other sensors as members of the multi-sensor team. Moreover, the sensor probability model explored is suitable for all multi-sensor mobile robots. It should provide a quantitative ability for analysis of sensor performance, and allow the development of robust decision procedures for integrating sensor information. The theoretical sensor model presented is a first step in understanding and expanding the performance of ultrasound systems. The significance of this paper lies in the theoretic integration of sensory information from the probabilistic point of view.