Vision based navigation system considering error recovery for autonomous mobile robot

We present a vision based navigation system which has an error recovery function for an autonomous mobile robot. A misrecognition of landmark causes the robot to mislocate itself. When this happens, the robot is unable to perform its primary objective. In order to solve this kind of problem, we have proposed a hierarchical control architecture "HALAS" (hierarchical adaptive and learning architecture system). This consists of some modules which are arranged hierarchically and each module means a single function of this robot. When one module fails in its aim, the upper module detects the error and recovers from it using other useful information from its knowledge data base. We show experimentally that the robot gets a higher reliability in autonomous mobility because the map correspondence module finds the error which has been caused by an anemo perception module (landmark recognition module) and it corrects the error utilizing its map information.