Mobile service robot multi-floor navigation using visual detection and recognition of elevator features(ICCAS 2020)

Mobile service robot multi-floor navigation is a challenging issue for in indoor robot navigation, especially when moving between floors, entering and leaving elevator. So, in this paper we propose detection and recognition method of elevator features and robot navigation for entering and leaving the elevator. Thus, in this paper we propose a method which uses deep learning. Based image recognition system to identify particular floor from an elevator display. Using this method robot determines whether particular floor has reached. We proposed two-fold methods to accomplish our goal. On the first method we performed the extraction of elevator button coordinates through traditional feature extractor such as adaptive thresholding, blob detection, template matching. The next part of our approach is by using DL- based recognition, done by YOLO 9000 on the floor count display panel of the elevator. From our analysis of these above mentioned methods we discovered that the feature extractor out-performs the DL-based recognition system even in the tricky conditions. Such as lighter reflection, motion blur etc. and proves to be more robust system for detection and recognition.