A fully integrated system for hardware-accelerated TSDF SLAM with LiDAR sensors (HATSDF SLAM)
DC Element | Wert | Sprache |
---|---|---|
dc.contributor.author | Eisoldt, Marc | |
dc.contributor.author | Gaal, Julian | |
dc.contributor.author | Wiemann, Thomas | |
dc.contributor.author | Flottmann, Marcel | |
dc.contributor.author | Rothmann, Marc | |
dc.contributor.author | Tassemeier, Marco | |
dc.contributor.author | Porrmann, Mario | |
dc.date.accessioned | 2023-02-17T11:33:29Z | - |
dc.date.available | 2023-02-17T11:33:29Z | - |
dc.date.issued | 2022 | |
dc.identifier.issn | 0921-8890 | |
dc.identifier.uri | http://osnascholar.ub.uni-osnabrueck.de/handle/unios/65358 | - |
dc.description.abstract | 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 state-of-the-art LiDARs 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.(c) 2022 Elsevier B.V. All rights reserved. | |
dc.description.sponsorship | Ministry of Science and Culture of Lower Saxony; Volk- swagenStiftung; The DFKI Niedersachsen Lab (DFKI NI) is sponsored by the Ministry of Science and Culture of Lower Saxony and the Volk- swagenStiftung. | |
dc.language.iso | en | |
dc.publisher | ELSEVIER | |
dc.relation.ispartof | ROBOTICS AND AUTONOMOUS SYSTEMS | |
dc.subject | 3D mapping | |
dc.subject | Automation & Control Systems | |
dc.subject | Computer Science | |
dc.subject | Computer Science, Artificial Intelligence | |
dc.subject | FPGA programming | |
dc.subject | Hardware acceleration | |
dc.subject | Robotics | |
dc.subject | SLAM | |
dc.title | A fully integrated system for hardware-accelerated TSDF SLAM with LiDAR sensors (HATSDF SLAM) | |
dc.type | journal article | |
dc.identifier.doi | 10.1016/j.robot.2022.104205 | |
dc.identifier.isi | ISI:000843552500007 | |
dc.description.volume | 156 | |
dc.identifier.eissn | 1872-793X | |
dc.publisher.place | RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS | |
dcterms.isPartOf.abbreviation | Robot. Auton. Syst. | |
local.import.remains | affiliations : University Osnabruck; University Osnabruck | |
local.import.remains | web-of-science-index : Science Citation Index Expanded (SCI-EXPANDED) | |
crisitem.author.dept | FB 06 - Mathematik/Informatik | - |
crisitem.author.dept | FB 06 - Mathematik/Informatik | - |
crisitem.author.deptid | fb06 | - |
crisitem.author.deptid | fb06 | - |
crisitem.author.orcid | 0000-0003-0710-872X | - |
crisitem.author.orcid | 0000-0003-1005-5753 | - |
crisitem.author.parentorg | Universität Osnabrück | - |
crisitem.author.parentorg | Universität Osnabrück | - |
crisitem.author.netid | WiTh428 | - |
crisitem.author.netid | PoMa309 | - |
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geprüft am 07.06.2024