Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
412930 | Robotics and Autonomous Systems | 2008 | 12 Pages |
This work is about solving the global localization issue for mobile robots, operating in large and cooperative environments. It tackles the problem of estimating the pose of a robot, or team of robots in a map reference frame, given the map, the real-time data from the robot onboard sensors, and the real-time data coming from other robots or sensors in the environment. After a first step of position hypotheses generation, an efficient probabilistic active strategy selects an action, for a single lost robot case, or two joint actions when two lost robots are in a line of sight, so that the hypotheses set is best disambiguated. The action set is adapted to the multi-hypothesis situation, and action evaluation takes into account remote observations available in robot network systems. This paper presents the theoretical formulation for both non-cooperative, and cooperative cases. An implementation of the proposed strategy is discussed, and simulation results presented.