Real-Time Door Detection Based on AdaBoost Learning Algorithm

Doors are important landmarks for robot self-localization and navigation in indoor environments. Existing algorithms of door detection are often limited for restricted environments. They do not consider the diversity and variety of doors. In this paper we present a camera- and laser-based approach, which allows finding more than 72% doors with a false- positive rate of 0.008 in static testdata. By using different door perspectives form a moving robot, we detect more than 90% of the doors with a very low false detection rate.