Learning to traverse doors using visual information
Mobile robots need to navigate in their environment in order to perform useful tasks. Doors appear in almost every office-like indoor environment and they have to be crossed often during the navigation process. We present in this paper a new approach that uses visual information to anticipate that a door has to be crossed. Combining then visual information with ultrasonic sensors, the robot approaches the door until an adequate distance is reached. Door traversing is then performed using sonar sensors. This paper describes the control architecture and the behaviors that have been implemented to obtain the door traversing behavior. Results and performance issues are explained. The experiments have been carried out with a B21 mobile robot. (C) 2002 IMACS. Published by Elsevier Science B.V. All rights reserved.
mobile robots door traversing behavior neural networks visual door detection