Combined grid and feature-based occupancy map building in large outdoor environments

Abstract

This paper presents an approach to create three-dimensional occupancy maps from an aerial vehicle with stereo vision. The main idea is to create an occupancy grid that moves along with the vehicle and extract features into a fixed global map. Vice versa, global features or a-priori knowledge can be inserted into the grid. The maps are calculated onboard to be used for autonomous behavior like path planning and obstacle avoidance. With the described method, maps are created and updated in real-time, and due to its flexibility, the vehicle is not restricted to a pre-defined area. The developed approach has been demonstrated in flights with a small unmanned helicopter.