A Stereovision-based navigation system for a mobile robot

This report describes the work at INRIA on obstacle avoidance and trajectory planning for a mobile robot using stereovision. Our mobile robot is equipped with a trinocular vision system that has been put into hardware and is be capable of delivering 3D maps of the environment at rates between 1 and 5 Hz. Those 3D maps contain line segments extracted from the images and reconstructed in three dimensions. They are used for a variety of tasks including obstacle avoidance and trajectory planning. For those two tasks, we project on the ground floor the 3D line segments to obtain a two-dimensional map, we simplify the map according to some simple geometric criteria and use the remaining 2D segments to construct a tessellation, more precisely a triangulation of the ground floor. This tessellation has several advantages : it is adapted to the structure of the environment since all stereo segments are edges of triangles in the tessellation - it can be efficiently computed (the algorithm we use for the triangulation has a complexity of O(log n) per update, if n is the number of points used - it is dynamic, in the sense that segments can be added or subtracted from an existing triangulation efficiently. We use this triangulation as a support for further processing. We first determine space, simply by marking those triangles which are empty, again a very simple processing and then use the graph formed by those triangles to generate collision free trajectories, when new sensory data are acquired the ground floor map is easily updated using the nice computational properties of the Delaunay triangulation and the process is iterated. We show examples in which our robot navigates freely in a real indoors environment using this system.