An intelligent remote maintenance and diagnostic system on mobile robot

This paper presents the design and implementation of an intelligent multisensor based mobile robot for remote maintenance and diagnostic system. We introduce four steps to achieve remote maintenance and diagnostic. Fisrt, we use a multisensor process to solve the problem from sensors. We equip various types of sensors properly in the mobile robot subsystem. Second, we build up a good database from these sensors. Third, we establish a statistical model of the maintenance and diagnostic system. We also use regression analysis to estimate these models parameters. Fourth, we use case-based reasoning (CBR), classification and regression trees (CART) to make a decision and find out which components are faulty. Finally, we implement the remote maintenance and diagnostic system in a driver system of the mobile robot.