Planning robust displacement missions by means of robot-tasks and local maps

This paper introduces a mobile robot mission planning method based on the robot-task concept. Missions are performed by a sequence of closed-loop mechanisms and are thus more robust with respect to the unavoidable differences between reality and the model used by the planner. A displacement mission is defined as the combination of a path and of a description of the observations expected along the way, enabling thus to control/check its comet execution. These observations are obtained by the use of local maps defined as coherent sets of landmarks or beacons detectable by the on-board sensing devices. The considered vehicle is a car like one endowed with a rotative telemeter. The environment is 2D and is structured by polygonal obstacles and landmarks. Robot-task generation is carried out in three phases. The first phase consists in defining a path as a set of configurations. Each of these configurations is attached to the list of map primitives providing the robot with the best localization information. This part is a compromise between length, safety conditions and complexity of vehicle control. The second phase applies a data analysis method to the path, in order to dynamically group path configurations associated to the same list of primitives called local maps. The third phase precisely deals with robot-task definition. It first consists in defining a smooth path (Bezier curve) from each group of configurations. The robot-task sequence corresponds to the ordered list of these paths associated with their respective local maps.