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Robust and safe traversal of doors is an important task for autonomous mobile robots. This paper presents a robust and inexpensive approach for recognizing and localizing doors based on monocular grey-level images and minimalistic models. The traversal is achieved by servoing the robot with respect to the door-hypothesis. Robustness against pose errors, scene complexity, and sensing conditions is obtained by combining indexing on significant aggregated features with a multi-view approach that employs consistency over time: pose-hypotheses are filtered via the motion of the robot to reject incorrect ones. The traversal is implemented as a behavior and was evaluated in 150 experiments at different doors under different conditions.
Eberst et al. (Thu,) studied this question.