HATSDF SLAM - Hardware-accelerated tsdf slam for reconfigurable socs
Autor(en): | Eisoldt, M. Flottmann, M. Gaal, J. Buschermohle, P. Hinderink, S. Hillmann, M. Nitschmann, A. Hoffmann, P. Wiemann, T. Porrmann, M. |
Stichwörter: | Energy utilization; Optical radar; Programmable logic controllers; Robotics, 3D maps; Autonomous robotics; Computational power; Depth camera; Energy-consumption; Hardware-accelerated; Reconfigurable SoC; Signed distance function; Simultaneous localization and mapping; Velodyne, System-on-chip | Erscheinungsdatum: | 2021 | Herausgeber: | Institute of Electrical and Electronics Engineers Inc. | Journal: | 2021 10th European Conference on Mobile Robots, ECMR 2021 - Proceedings | Zusammenfassung: | Simultaneous Localization and Mapping (SLAM) is one of the fundamental problems in autonomous robotics. Over the years, many approaches to solve this problem for 6D poses and 3D maps based on LiDAR sensors or depth cameras have been proposed. One of the main drawbacks of the solutions found in the literature is the required computational power and corresponding energy consumption. In this paper, we present an approach for LiDAR-based SLAM that maintains a global truncated signed distance function (TSDF) to represent the map. It is implemented on a System On Chip (SoC) with an integrated FPGA accelerator. The proposed system is able to track the position of a Velodyne VLP-16 LiDAR in real time, while maintaining a global TSDF map that can be used to create a polygonal map of the environment. We show that our implementation delivers competitive results compared to state-of-the-art algorithms while drastically reducing the power consumption compared to classical CPU or GPU-based methods. © 2021 IEEE. |
Beschreibung: | Conference of 10th European Conference on Mobile Robots, ECMR 2021 ; Conference Date: 31 August 2021 Through 3 September 2021; Conference Code:173117 |
ISBN: | 9781665412131 | DOI: | 10.1109/ECMR50962.2021.9568815 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118982028&doi=10.1109%2fECMR50962.2021.9568815&partnerID=40&md5=171d58076542ffee80c0a7818ccac750 |
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