Sensor-based navigation in cluttered environments

We present a new approach to sensor-based navigation in cluttered environments. In our system, tasks are specified in terms of visual goals, and obstacles are detected by a laser range finder. To effect task performance, we introduce a new gain scheduling visual servo controller. Our approach uses a diagonal gain matrix whose entries are adjusted during execution according to one of several proposed gain schedules. Obstacle avoidance is achieved by allowing the detected obstacles to generate artificial repulsive potential fields, which alter the motion of the mobile robot base. Since this motion affects the vision-based control, it is compensated by corresponding camera motions. Finally, we combine the obstacle avoiding and visual servo components of the system so that visual servo tasks can be performed as obstacles are avoided. We illustrate our approach with both simulations and real experiments using our experimental platform H/sup il/are2Bis.