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Challenges of SLAM in Extremely Unstructured Environments: The DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset

Giubilato, Riccardo and Stürzl, Wolfgang and Wedler, Armin and Triebel, Rudolph (2022) Challenges of SLAM in Extremely Unstructured Environments: The DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset. IEEE Robotics and Automation Letters, 7 (4), pp. 8721-8728. IEEE - Institute of Electrical and Electronics Engineers. doi: 10.1109/LRA.2022.3188118. ISSN 2377-3766.

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Abstract

We present the DLR Planetary Stereo, Solid-State LiDAR, Inertial (S3LI) dataset, recorded on Mt. Etna, Sicily, an environment analogous to the Moon and Mars, using a hand-held sensor suite with attributes suitable for implementation on a space-like mobile rover. The environment is characterized by challenging conditions regarding both the visual and structural appearance: severe visual aliasing poses significant limitations to the ability of visual SLAM systems to perform place recognition, while the absence of outstanding structural details, joined with the limited Field-of-View of the utilized Solid-State LiDAR sensor, challenges traditional LiDAR SLAM for the task of pose estimation using point clouds alone. With this data, that covers more than 4 kilometers of travel on soft volcanic slopes, we aim to: 1) provide a tool to expose limitations of state-of-the-art SLAM systems with respect to environments, which are not present in widely available datasets and 2) motivate the development of novel localization and mapping approaches, that rely efficiently on the complementary capabilities of the two sensors. The dataset is accessible at the following url: https://rmc.dlr.de/s3li_dataset

Item URL in elib:https://elib.dlr.de/187610/
Document Type:Article
Title:Challenges of SLAM in Extremely Unstructured Environments: The DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Giubilato, RiccardoRiccardo.Giubilato (at) dlr.dehttps://orcid.org/0000-0002-3161-3171
Stürzl, WolfgangWolfgang.Stuerzl (at) dlr.dehttps://orcid.org/0000-0003-2440-5857
Wedler, ArminArmin.Wedler (at) dlr.dehttps://orcid.org/0000-0001-8641-0163
Triebel, RudolphRudolph.Triebel (at) dlr.dehttps://orcid.org/0000-0002-7975-036X
Date:October 2022
Journal or Publication Title:IEEE Robotics and Automation Letters
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:7
DOI :10.1109/LRA.2022.3188118
Page Range:pp. 8721-8728
Publisher:IEEE - Institute of Electrical and Electronics Engineers
ISSN:2377-3766
Status:Published
Keywords:Datasets for SLAM, field robots, space robotics and automation
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Robotics
DLR - Research area:Raumfahrt
DLR - Program:R RO - Robotics
DLR - Research theme (Project):R - E3D: Algorithms and Application (RM) [RO], R - Multisensory World Modelling (RM) [RO]
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition
Deposited By: Giubilato, Riccardo
Deposited On:22 Jul 2022 14:14
Last Modified:22 Jul 2022 14:14

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