MOLISENS: MObile LIdar SENsor System to exploit the potential of small industrial lidar devices for geoscientific applications
-
Published:2022-08-02
Issue:2
Volume:11
Page:247-261
-
ISSN:2193-0864
-
Container-title:Geoscientific Instrumentation, Methods and Data Systems
-
language:en
-
Short-container-title:Geosci. Instrum. Method. Data Syst.
Author:
Goelles Thomas, Hammer Tobias, Muckenhuber StefanORCID, Schlager BirgitORCID, Abermann JakobORCID, Bauer Christian, Expósito Jiménez Víctor J., Schöner Wolfgang, Schratter Markus, Schrei Benjamin, Senger KimORCID
Abstract
Abstract. We propose a newly developed modular MObile LIdar SENsor System (MOLISENS) to enable new applications for small industrial lidar (light detection and ranging) sensors. The stand-alone modular setup supports both monitoring of dynamic processes and mobile mapping applications based on SLAM (Simultaneous Localization and Mapping) algorithms. The main objective of MOLISENS is to exploit newly emerging perception sensor technologies developed for the automotive industry for geoscientific applications. However, MOLISENS can also be used for other application areas, such as 3D mapping of buildings or vehicle-independent data collection for sensor performance assessment and sensor modeling. Compared to TLSs, small industrial lidar sensors provide advantages in terms of size (on the order of 10 cm), weight (on the order of 1 kg or less), price (typically between EUR 5000 and 10 000), robustness (typical protection class of IP68), frame rates (typically 10–20 Hz), and eye safety class (typically 1). For these reasons, small industrial lidar systems can provide a very useful complement to currently used TLS (terrestrial laser scanner) systems that have their strengths in range and accuracy performance. The MOLISENS hardware setup consists of a sensor unit, a data logger, and a battery pack to support stand-alone and mobile applications. The sensor unit includes the small industrial lidar Ouster OS1-64 Gen1, a ublox multi-band active GNSS (Global Navigation Satellite System) with the possibility for RTK (real-time kinematic), and a nine-axis Xsens IMU (inertial measurement unit). Special emphasis was put on the robustness of the individual components of MOLISENS to support operations in rough field and adverse weather conditions. The sensor unit has a standard tripod thread for easy mounting on various platforms. The current setup of MOLISENS has a horizontal field of view of 360∘, a vertical field of view with a 45∘ opening angle, a range of 120 m, a spatial resolution of a few centimeters, and a temporal resolution of 10–20 Hz. To evaluate the performance of MOLISENS, we present a comparison between the integrated small industrial lidar Ouster OS1-64 and the state-of-the-art high-accuracy and high-precision TLS Riegl VZ-6000 in a set of controlled experimental setups. We then apply the small industrial lidar Ouster OS1-64 in several real-world settings. The mobile mapping application of MOLISENS has been tested under various conditions, and results are shown from two surveys in the Lurgrotte cave system in Austria and a glacier cave in Longyearbreen on Svalbard.
Funder
Bundesministerium für Digitalisierung und Wirtschaftsstandort Bundesministeriums für Kunst, Kultur, öffentlichen Dienst und Sport Steirische Wirtschaftsförderungsgesellschaft Karl-Franzens-Universität Graz
Publisher
Copernicus GmbH
Subject
Atmospheric Science,Geology,Oceanography
Reference73 articles.
1. AccuPower Research, Development and Distribution Company (Ltd.): AccuPower
AkkuPacks,
https://www.accupower.at/produkt-kategorie/akkus/lithium/akkupacks/
(last access: 1 February 2022), 2022. a 2. Alexander, A., Obu, J., Schuler, T. V., Kääb, A., and Christiansen, H. H.: Subglacial permafrost dynamics and erosion inside subglacial channels driven by surface events in Svalbard, The Cryosphere, 14, 4217–4231, https://doi.org/10.5194/tc-14-4217-2020, 2020. a 3. Bălaşa, R. I., Olaru, G., Constantin, D., Ștefan, A., Bîlu, C. M.,
and Bălăceanu, M. B.: LIDAR based distance estimation for emergency
use terrestrial autonomous robot, 14th International Conference on
Electronics, Comp. Artif. Intell., 13, 1–4,
https://doi.org/10.1109/ECAI52376.2021.9515047, 2021. a, b 4. Behley, J. and Stachniss, C.: Efficient Surfel-Based SLAM using 3D Laser Range
Data in Urban Environments, in: Conference: Robotics: Science and Systems
2018, Pittsburgh, Pennsylvania, USA, https://doi.org/10.15607/RSS.2018.XIV.016, 2018.
a 5. Birkebak, M., Stearns, J., Durell, C., and Scharpf, D.: Radiometry 101
Calibrating with diffuse reflecting targets,
https://www.photonicsonline.com/doc/radiometry-calibrating-with-diffuse-reflecting-targets-0001 (last access: 28 July 2022),
2018. a
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|