Indoor navigation of mobile robots based on visual memory and image-based visual servoing

摘要

This thesis presents a method for appearance-based navigation from an image memory by Image-Based Visual Servoing (IBVS). The entire navigation process is based on 2D image information without using any 3D information at all. The environment is represented by a set of reference images with overlapping landmarks, which are selected automatically during a prior learning phase. These reference images define the path to follow during the navigation. The switching of reference images during navigation is done by comparing the current acquired image with nearby reference images. Based on the current image and two succeeding key images, the rotational velocity of a mobile robot is computed under IBVS control law. First, we have used the entire image as a feature, where mutual information between reference images and the current view is exploited. Then, we have used line segments for the indoor navigation, where we have shown that line segments are better features for the structured indoor environment. Finally, we combinedline segments with point-based features for increasing the application of the method to a wide range of indoor scenarios with smooth motion. Real-time navigation with a Pioneer 3DX equipped with an on-board perspective camera has been performed in the indoor environment. The obtained results confirm the viability of our approach and verify that accurate mapping and localization are not mandatory for a useful indoor navigation.