A PROBABILISTIC APPROACH TO ROBOTIC NDE INSPECTION

Abstract

The application of wireless robotic inspection vehicles equipped with different NDE payloads has been introduced previously, with emphasis placed on inspection applications in hazardous and inaccessible environments. A particular challenge to the practical application of such robotic inspection lies in the localization of the devices. The authors here consider a probabilistic approach to both the positioning and defect problems by using the location of the robot and the NDE measurements (acquired from the onboard transducers) to make inference about defect existence and position. Using a particle filter approach running locally on the robots, the vehicle location is tracked by fusing noisy redundant data sets supplying positional information.