Planning of observation and motion for interpretation of road intersection scenes considering uncertainty

Describes a method of planning of observation and motion for a mobile robot to interpret a road intersection scene and to reach the intersection as soon as possible considering the uncertainty of interpretation. From a monocular color image, candidate regions are extracted for objects which are related to the intersection type. The probabilities of the regions coming from the objects are calculated from probabilistic models of the objects. From the probabilities of the regions and the relation between the intersection type and the objects, the current probability of intersection types is calculated. If the intersection type is ambiguous, the robot plans the observation and motion which minimize the expectation of the cost (time) to complete the task. The robot takes these actions and tries to determine the intersection type again. This process is iterated until the task is completed. The experimental result is shown for an actual intersection scene