Abstract
A lot of research work deals with the building of 3D environment models, e.g. by lidar-based 6D SLAM on ground vehicles. Because these single vehicle approaches always are afflicted by partial occlusion of the environment, we propose to fuse point cloud data taken by ground and aerial vehicles. Therefore, we use manually steered ground and aerial vehicles equipped with localization sensors and laser scanners to record point cloud data. The point cloud data is fused predominantly by existing state-of-the-art algorithms and data formats in ROS. Finally, Octomaps are calculated as common environment models. Two real world experiments in structured and unstructured outdoor environments are presented. The resulting point clouds and maps are evaluated qualitatively and quantitatively.
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Acknowledgments
This work has been supported by the Federal Office of Bundeswehr Equipment, Information Technology and In-Service Support (BAAINBw).
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Langerwisch, M., Steven Krämer, M., Kuhnert, KD., Wagner, B. (2016). Construction of 3D Environment Models by Fusing Ground and Aerial Lidar Point Cloud Data. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds) Intelligent Autonomous Systems 13. Advances in Intelligent Systems and Computing, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-319-08338-4_35
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DOI: https://doi.org/10.1007/978-3-319-08338-4_35
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