Relevant bibliographies by topics / Backpack laser mapping

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Academic literature on the topic 'Backpack laser mapping'

Author: Grafiati
Published: 28 June 2021
Last updated: 1 February 2022

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Journal articles on the topic "Backpack laser mapping"

1

Lauterbach, H. A., D. Borrmann, A. Nüchter, A. P. Rossi, V. Unnithan, P. Torrese, and R. Pozzobon. "MOBILE MAPPING OF THE LA CORONA LAVATUBE ON LANZAROTE." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (May 29, 2019): 381–87. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-381-2019.

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<p><strong>Abstract.</strong> Planetary surfaces consist of rough terrain and cave-like environments. Future planetary exploration demands for accurate mapping. However, recent backpack mobile mapping systems are mostly tested in structured, indoor environments. This paper evaluates the use of a backpack mobile mapping system in a cave-like environment. The experiments demonstrate the abilities of an continuous-time optimization approach by mapping part of a lavatube of the La Corona volcano system on Lanzarote. We compare two strategies for trajectory estimation relying either on 2D or 3D laser scanners and show that a 3D laser scanner substantially improved the final results.</p>
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2

Shao, J., W. Zhang, L. Luo, S. Cai, and H. Jiang. "SLAM-BASED BACKPACK LASER SCANNING FOR FOREST PLOT MAPPING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2020 (August 3, 2020): 267–71. http://dx.doi.org/10.5194/isprs-annals-v-2-2020-267-2020.

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Abstract. Acquisition of three-dimensional (3D) structural information is significant for forest measurements. To achieve faster data collection in forests, we design a backpack laser scanning (BLS) system using a single mobile laser scanning (MLS) scanner and specific to forest environments. The simultaneous localization and mapping (SLAM) approach based on the natural geometric characteristics of trees is used for BLS-based forest mapping, in which the skeleton line of the individual tree is extracted for scan matching and the incremental maps are adopted for global optimization of all the BLS point clouds. The final experimental results show that the SLAM-based BLS system achieves accurate forest plots mapping and allows reaching low mapping errors, in which the mean errors are approximately 3 cm in the horizontal and 2 cm in the vertical direction.
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3

Lovas, T., K. Hadzijanisz, V. Papp, and A. J. Somogyi. "INDOOR BUILDING SURVEY ASSESSMENT." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 251–57. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-251-2020.

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Abstract. There are multiple emerging technologies, devices and integrated equipment to support indoor mapping. The two main categories are the wearable/portable (e.g. hand-held or backpack devices) and the trolley based devices. The most widely used sensors of the integrated systems are the laser scanners (usually profile scanners), camera(s) and the IMU unit. Compared to outdoor mobile mapping systems the main difference is the lack of GNSS signals; localization is usually supported by SLAM (Simultaneous Localization and Mapping) technology, using Kalman-filtering. Current paper discusses the assessment of the potential of trolley-based indoor mobile mapping systems (MMS) by surveying a building part by multiple technologies. Besides conventional land surveying measurements, terrestrial lasers scanning and a backpack-based mobile survey have been carried out. The analysis included cloud-to-cloud comparison as well as CAD-based evaluation focusing on the geometric accuracy of the point clouds. The paper also presents the surveying workflow; on its resource-needs and potential application fields. The paper discusses the data acquisition technologies and procedures and the different quality assessment methods and results. Since an experimental survey was conducted with a backpack-based unit in the same study area, the paper gives a brief overview on how the two different mobile mapping technologies can be applied indoor, and presents the main differences, advantages and drawbacks.
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4

Velas, Martin, Michal Spanel, Tomas Sleziak, Jiri Habrovec, and Adam Herout. "Indoor and Outdoor Backpack Mapping with Calibrated Pair of Velodyne LiDARs." Sensors 19, no. 18 (September 12, 2019): 3944. http://dx.doi.org/10.3390/s19183944.

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This paper presents a human-carried mapping backpack based on a pair of Velodyne LiDAR scanners. Our system is a universal solution for both large scale outdoor and smaller indoor environments. It benefits from a combination of two LiDAR scanners, which makes the odometry estimation more precise. The scanners are mounted under different angles, thus a larger space around the backpack is scanned. By fusion with GNSS/INS sub-system, the mapping of featureless environments and the georeferencing of resulting point cloud is possible. By deploying SoA methods for registration and the loop closure optimization, it provides sufficient precision for many applications in BIM (Building Information Modeling), inventory check, construction planning, etc. In our indoor experiments, we evaluated our proposed backpack against ZEB-1 solution, using FARO terrestrial scanner as the reference, yielding similar results in terms of precision, while our system provides higher data density, laser intensity readings, and scalability for large environments.
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5

Yu, Peidong, Mengke Wang, and Huanjian Chen. "Integration and evaluation of SLAM-based backpack mobile mapping system." E3S Web of Conferences 206 (2020): 03014. http://dx.doi.org/10.1051/e3sconf/202020603014.

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Mobile mapping is an efficient technology to acquire spatial data of the environment. As a supplement of vehicle-borne and air-borne methods, Backpack mobile mapping system (MMS) has a wide application prospect in indoor and underground space. High-precision positioning and attitude determination are the key to MMS. Usually, GNSS/INS integrated navigation system provides reliable pose information. However, in the GNSS-denied environments, there is no effective long-term positioning method. With the development of simultaneous localization and mapping (SLAM) algorithm, it provides a new solution for indoor mobile mapping. This paper develops a portable backpack mobile mapping system, which integrates multi-sensor such as LiDAR, IMU, GNSS and panoramic camera. The 3D laser SLAM algorithm is applied to the mobile mapping to realize the acquisition of geographic information data in various complex environments. The experimental results in typical indoor and outdoor scenes show that the system can achieve high-precision and efficient acquisition of 3D information, and the relative precision of point cloud is 2~4cm, which meets the requirements of scene mapping and reconstruction.
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6

Nüchter, A., D. Borrmann, P. Koch, M. Kühn, and S. May. "A MAN-PORTABLE, IMU-FREE MOBILE MAPPING SYSTEM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences II-3/W5 (August 19, 2015): 17–23. http://dx.doi.org/10.5194/isprsannals-ii-3-w5-17-2015.

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Mobile mapping systems are commonly mounted on cars, ships and robots. The data is directly geo-referenced using GPS data and expensive IMU (inertial measurement systems). Driven by the need for flexible, indoor mapping systems we present an inexpensive mobile mapping solution that can be mounted on a backpack. It combines a horizontally mounted 2D profiler with a constantly spinning 3D laser scanner. The initial system featuring a low-cost MEMS IMU was revealed and demonstrated at <i>MoLaS: Technology Workshop Mobile Laser Scanning at Fraunhofer IPM</i> in Freiburg in November 2014. In this paper, we present an IMU-free solution.
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7

Khoshelham, K., H. Tran, and D. Acharya. "INDOOR MAPPING EYEWEAR: GEOMETRIC EVALUATION OF SPATIAL MAPPING CAPABILITY OF HOLOLENS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 5, 2019): 805–10. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-805-2019.

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<p><strong>Abstract.</strong> Existing indoor mapping systems have limitations in terms of time efficiency and flexibility in complex environments. While backpack and handheld systems are more flexible and can be used for mapping multi-storey buildings, in some application scenarios, e.g. emergency response, a light-weight indoor mapping eyewear or head-mounted system has practical advantages. In this paper, we investigate the spatial mapping capability of Microsoft Hololens mixed reality eyewear for 3D mapping of large indoor environments. We provide a geometric evaluation of 3D mesh data captured by the Hololens in terms of local precision, coverage, and global correctness in comparison with terrestrial laser scanner data and a reference 3D model. The results indicate the high efficiency and flexibility of Hololens for rapid mapping of relatively large indoor environments with high completeness and centimetre level accuracy.</p>
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8

Karam, Samer, George Vosselman, Michael Peter, Siavash Hosseinyalamdary, and Ville Lehtola. "Design, Calibration, and Evaluation of a Backpack Indoor Mobile Mapping System." Remote Sensing 11, no. 8 (April 13, 2019): 905. http://dx.doi.org/10.3390/rs11080905.

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Indoor mobile mapping systems are important for a wide range of applications starting from disaster management to straightforward indoor navigation. This paper presents the design and performance of a low-cost backpack indoor mobile mapping system (ITC-IMMS) that utilizes a combination of laser range-finders (LRFs) to fully recover the 3D building model based on a feature-based simultaneous localization and mapping (SLAM) algorithm. Specifically, we use robust planar features. These are advantageous, because oftentimes the final representation of the indoor environment is wanted in a planar form, and oftentimes the walls in an indoor environment physically have planar shapes. In order to understand the potential accuracy of our indoor models and to assess the system’s ability to capture the geometry of indoor environments, we develop novel evaluation techniques. In contrast to the state-of-the-art evaluation methods that rely on ground truth data, our evaluation methods can check the internal consistency of the reconstructed map in the absence of any ground truth data. Additionally, the external consistency can be verified with the often available as-planned state map of the building. The results demonstrate that our backpack system can capture the geometry of the test areas with angle errors typically below 1.5° and errors in wall thickness around 1 cm. An optimal configuration for the sensors is determined through a set of experiments that makes use of the developed evaluation techniques.
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9

Hu, Shaoxing, Shen Xiao, Aiwu Zhang, Yiming Deng, and Bingke Wang. "Continuous-Time Laser Frames Associating and Mapping via Multilayer Optimization." Sensors 21, no. 1 (December 25, 2020): 97. http://dx.doi.org/10.3390/s21010097.

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To achieve the ability of associating continuous-time laser frames is of vital importance but challenging for hand-held or backpack simultaneous localization and mapping (SLAM). In this study, the complex associating and mapping problem is investigated and modeled as a multilayer optimization problem to realize low drift localization and point cloud map reconstruction without the assistance of the GNSS/INS navigation systems. 3D point clouds are aligned among consecutive frames, submaps, and closed-loop frames using the normal distributions transform (NDT) algorithm and the iterative closest point (ICP) algorithm. The ground points are extracted automatically, while the non-ground points are automatically segmented to different point clusters with some noise point clusters omitted before 3D point clouds are aligned. Through the three levels of interframe association, submap matching and closed-loop optimization, the continuous-time laser frames can be accurately associated to guarantee the consistency of 3D point cloud map. Finally, the proposed method was evaluated in different scenarios, the experimental results showed that the proposed method could not only achieve accurate mapping even in the complex scenes, but also successfully handle sparse laser frames well, which is critical for the scanners such as the new Velodyne VLP-16 scanner’s performance.
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10

Karam, S., V. Lehtola, and G. Vosselman. "INTEGRATING A LOW-COST MEMS IMU INTO A LASER-BASED SLAM FOR INDOOR MOBILE MAPPING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17 (November 29, 2019): 149–56. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w17-149-2019.

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Abstract. Indoor mapping techniques are highly important in many applications, such as human navigation and indoor modelling. As satellite positioning systems do not work in indoor applications, several alternative navigational sensors and methods have been used to provide accurate indoor positioning for mapping purposes, such as inertial measurement units (IMUs) and simultaneous localisation and mapping algorithms (SLAM). In this paper, we investigate the benefits that the integration of a low-cost microelectromechanical system (MEMS) IMU can bring to a feature-based SLAM algorithm. Specifically, we utilize IMU data to predict the pose of our backpack indoor mobile mapping system to improve the SLAM algorithm. The experimental results show that using the proposed IMU integration method leads into a more robust data association between the measured points and the model planes. Notably, the number of points that are assigned to the model planes is increased, and the root mean square error (RMSE) of the residuals, i.e. distances between these measured points and the model planes, is decreased significantly from 1.8 cm to 1.3 cm.
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