Abstract
In this paper, we present a three-dimensional mapping system for mobile robots using laser range sensors. Our system provides sensor preprocessing, efficient local mapping for reliable obstacle perception, and allocentric mapping with real-time localization for autonomous navigation. The software is available as open-source ROS-based package and has been successfully employed on different robotic platforms, such as micro aerial vehicles and ground robots in different research projects and robot competitions. Core of our approach are local multiresolution grid maps and an efficient surfel-based registration method to aggregate measurements from consecutive laser scans. By using local multiresolution grid maps as central data structure in our system, we gain computational efficiency by having high resolution in the near vicinity of the robot and lower resolution with increasing distance. Furthermore, local multiresolution grid maps provide a probabilistic representation of the environment—allowing us to address dynamic objects and to distinguish between occupied, free, and unknown areas. Spatial relations between local maps are modeled in a graph-based structure, enabling allocentric mapping and localization.
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