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Journal articles on the topic 'Backpack laser mapping'
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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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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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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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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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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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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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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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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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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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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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Salgues, H., H. Macher, and T. Landes. "EVALUATION OF MOBILE MAPPING SYSTEMS FOR INDOOR SURVEYS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIV-4/W1-2020 (September 3, 2020): 119–25. http://dx.doi.org/10.5194/isprs-archives-xliv-4-w1-2020-119-2020.
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Abstract. With their high recording rate of hundreds of thousands of points acquired per second, speed of execution and a remote acquisition mode, SLAM based mobile mapping systems (MMS) are a very powerful solution for capturing 3D point clouds in real time, simply by walking in the area of interest. Regarding indoor surveys, these MMS have been integrated in handheld or backpack solutions and become fast scanning sensors. Despite their advantages, the geometric accuracy of 3D point clouds guaranteed with these sensors is lower than the one reachable with static TLS. In this paper the effectiveness of two recent mobile mapping systems namely the GeoSLAM ZEB-REVO RT and the more recent GreenValley LiBackPack C50 is investigated for indoor surveys. In order to perform a reliable assessment study, several datasets produced with each sensor are compared to the high-cost georeferenced point cloud obtained with static laser scanning target-based technique.
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Masiero, Andrea, Francesca Fissore, Alberto Guarnieri, Francesco Pirotti, Domenico Visintini, and Antonio Vettore. "Performance Evaluation of Two Indoor Mapping Systems: Low-Cost UWB-Aided Photogrammetry and Backpack Laser Scanning." Applied Sciences 8, no. 3 (March 11, 2018): 416. http://dx.doi.org/10.3390/app8030416.
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Holmgren, J., H. M. Tulldahl, J. Nordlöf, M. Nyström, K. Olofsson, J. Rydell, and E. Willén. "ESTIMATION OF TREE POSITION AND STEM DIAMETER USING SIMULTANEOUS LOCALIZATION AND MAPPING WITH DATA FROM A BACKPACK-MOUNTED LASER SCANNER." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W3 (October 19, 2017): 59–63. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w3-59-2017.
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A system was developed for automatic estimations of tree positions and stem diameters. The sensor trajectory was first estimated using a positioning system that consists of a low precision inertial measurement unit supported by image matching with data from a stereo-camera. The initial estimation of the sensor trajectory was then calibrated by adjustments of the sensor pose using the laser scanner data. Special features suitable for forest environments were used to solve the correspondence and matching problems. Tree stem diameters were estimated for stem sections using laser data from individual scanner rotations and were then used for calibration of the sensor pose. A segmentation algorithm was used to associate stem sections to individual tree stems. The stem diameter estimates of all stem sections associated to the same tree stem were then combined for estimation of stem diameter at breast height (DBH). The system was validated on four 20&thinsp;m radius circular plots and manual measured trees were automatically linked to trees detected in laser data. The DBH could be estimated with a RMSE of 19&thinsp;mm (6&thinsp;%) and a bias of 8&thinsp;mm (3&thinsp;%). The calibrated sensor trajectory and the combined use of circle fits from individual scanner rotations made it possible to obtain reliable DBH estimates also with a low precision positioning system.
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Hyyppä, Eric, Xiaowei Yu, Harri Kaartinen, Teemu Hakala, Antero Kukko, Mikko Vastaranta, and Juha Hyyppä. "Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests." Remote Sensing 12, no. 20 (October 13, 2020): 3327. http://dx.doi.org/10.3390/rs12203327.
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In this work, we compared six emerging mobile laser scanning (MLS) technologies for field reference data collection at the individual tree level in boreal forest conditions. The systems under study were an in-house developed AKHKA-R3 backpack laser scanner, a handheld Zeb-Horizon laser scanner, an under-canopy UAV (Unmanned Aircraft Vehicle) laser scanning system, and three above-canopy UAV laser scanning systems providing point clouds with varying point densities. To assess the performance of the methods for automated measurements of diameter at breast height (DBH), stem curve, tree height and stem volume, we utilized all of the six systems to collect point cloud data on two 32 m-by-32 m test sites classified as sparse (n = 42 trees) and obstructed (n = 43 trees). To analyze the data collected with the two ground-based MLS systems and the under-canopy UAV system, we used a workflow based on our recent work featuring simultaneous localization and mapping (SLAM) technology, a stem arc detection algorithm, and an iterative arc matching algorithm. This workflow enabled us to obtain accurate stem diameter estimates from the point cloud data despite a small but relevant time-dependent drift in the SLAM-corrected trajectory of the scanner. We found out that the ground-based MLS systems and the under-canopy UAV system could be used to measure the stem diameter (DBH) with a root mean square error (RMSE) of 2–8%, whereas the stem curve measurements had an RMSE of 2–15% that depended on the system and the measurement height. Furthermore, the backpack and handheld scanners could be employed for sufficiently accurate tree height measurements (RMSE = 2–10%) in order to estimate the stem volumes of individual trees with an RMSE of approximately 10%. A similar accuracy was obtained when combining stem curves estimated with the under-canopy UAV system and tree heights extracted with an above-canopy flying laser scanning unit. Importantly, the volume estimation error of these three MLS systems was found to be of the same level as the error corresponding to manual field measurements on the two test sites. To analyze point cloud data collected with the three above-canopy flying UAV systems, we used a random forest model trained on field reference data collected from nearby plots. Using the random forest model, we were able to estimate the DBH of individual trees with an RMSE of 10–20%, the tree height with an RMSE of 2–8%, and the stem volume with an RMSE of 20–50%. Our results indicate that ground-based and under-canopy MLS systems provide a promising approach for field reference data collection at the individual tree level, whereas the accuracy of above-canopy UAV laser scanning systems is not yet sufficient for predicting stem attributes of individual trees for field reference data with a high accuracy.
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Marotta, Federica, Simone Teruggi, Cristiana Achille, Giorgio Paolo Maria Vassena, and Francesco Fassi. "Integrated Laser Scanner Techniques to Produce High-Resolution DTM of Vegetated Territory." Remote Sensing 13, no. 13 (June 26, 2021): 2504. http://dx.doi.org/10.3390/rs13132504.
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The paper presents the first part of a research project concerning the creation of 3D terrain models useful to understand landslide movements. Thus, it illustrates the creation process of a multi-source high-resolution Digital Terrain Model (DTM) in very dense vegetated areas obtained by integrating 3D data coming from three sources, starting from long and medium-range Terrestrial Laser Scanner up to a Backpack Indoor Mobile Mapping System. The point clouds are georeferenced by means of RKT GNSS points and automatically filtered using a Cloth Simulation Filter algorithm to separate points belonging to the ground. Those points are interpolated to produce the DTMs which are then mosaicked to obtain a unique multi-resolution DTM that plays a crucial role in the detection and identification of specific geological features otherwise visible. Standard deviation of residuals of the DTM varies from 0.105 m to 0.176 m for Z coordinate, from 0.065 m to 0.300 m for X and from 0.034 m to 0.175 m for Y. The area under investigation belongs to the Municipality of Piuro (SO) and includes both the town and surrounding valley. It was affected by a dramatic landslide in 1618 that destroyed the entire village. Numerous challenges have been faced, caused both by the characteristics of the area and the processed data. The complexity of the case study turns out to be an excellent test bench for the employed technologies, providing the opportunity to precisely identify the needed direction to obtain future promising results.
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Sánchez-Aparicio, L. J., B. Conde, M. A. Maté-González, R. Mora, M. Sánchez-Aparicio, J. García-Álvarez, and D. González-Aguilera. "A COMPARATIVE STUDY BETWEEN WMMS AND TLS FOR THE STABILITY ANALYSIS OF THE SAN PEDRO CHURCH BARREL VAULT BY MEANS OF THE FINITE ELEMENT METHOD." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W15 (August 26, 2019): 1047–54. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w15-1047-2019.
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<p><strong>Abstract.</strong> Stability of masonry constructions is highly conditioned by the geometric disposition of its elements due to its low tensile strength and great compressive mechanical properties. Under this framework, this paper attempts to evaluate the suitability of a wearable mobile mapping solution, equipped in a backpack and based on the well-known simultaneous location and mapping paradigm, for the structural diagnosis of historical constructions. To evaluate the suitability of this device, the structural analysis obtained is compared with a high precision terrestrial laser scanner, which is considered as ground truth. The Romanesque church of San Pedro (Becerril del Carpio, Spain) was selected as a study case. This construction, initially conceived in the XIII<sup>th</sup> century, has experimented in the past a soil settlement promoting the leaning of the north wall, several plastic hinges in its barrel vault and a visible geometrical deformation. The comparison of both techniques was carried out at different levels: i) an evaluation of the time needed to obtain the point cloud of the church; ii) an accuracy assessment based on the comparison of a terrestrial network using artificial spheres as checkpoints and; iii) an evaluation of the discrepancies, in terms of safety factor and collapse topology, found during the advance numerical evaluation of the barrel vault by means of the finite element method. This comparison places this wearable mobile mapping solution as an interesting tool for the creation of advanced numerical simulations to evaluate the structural stability of historical constructions.</p>
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Blaser, S., S. Nebiker, and D. Wisler. "PORTABLE IMAGE-BASED HIGH PERFORMANCE MOBILE MAPPING SYSTEM IN UNDERGROUND ENVIRONMENTS – SYSTEM CONFIGURATION AND PERFORMANCE EVALUATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5 (May 29, 2019): 255–62. http://dx.doi.org/10.5194/isprs-annals-iv-2-w5-255-2019.
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<p><strong>Abstract.</strong> The progression in urbanization increases the need for different types of underground infrastructure. Consequently, infrastructure and life cycle management are rapidly gaining in importance. Mobile reality capturing systems and cloud-based services exploiting georeferenced metric 3D imagery are already extensively used for infrastructure management in outdoor environments. These services minimise dangerous and expensive field visits or measurement campaigns. In this paper, we introduce the BIMAGE Backpack, a portable image-based mobile mapping system for 3D data acquisition in indoor environments. The system consists of a multi-head panorama camera, two multi-profile laser scanners and an inertial measurement unit. With this system, we carried out underground measurement campaigns in the Hagerbach Test Gallery, located in Flums Hochwiese, Switzerland. For our performance evaluations in two different tunnel sections, we employed LiDAR SLAM as well as advanced image-based georeferencing. The obtained absolute accuracies were in the range from 6.2 to 7.4&thinsp;cm. The relative accuracy, which for many applications is even more important, was in the range of 2&ndash;6&thinsp;mm. These figures demonstrate an accuracy improvement of the subsequent image-based georeferencing over LiDAR SLAM by about an order of magnitude. The investigations show the application potential of image-based portable mobile mapping systems for infrastructure inventory and management in large underground facilities.</p>
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Fissore, F., F. Pirotti, and A. Vettore. "OPEN SOURCE WEB TOOL FOR TRACKING IN A LOWCOST MOBILE MAPPING SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W8 (November 13, 2017): 99–104. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w8-99-2017.
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During the last decade several Mobile Mapping Systems (MMSs), i.e. systems able to acquire efficiently three dimensional data using moving sensors (Guarnieri et al., 2008, Schwarz and El-Sheimy, 2004), have been developed. Research and commercial products have been implemented on terrestrial, aerial and marine platforms, and even on human-carried equipment, e.g. backpack (Lo et al., 2015, Nex and Remondino, 2014, Ellum and El-Sheimy, 2002, Leica Pegasus backpack, 2016, Masiero et al., 2017, Fissore et al., 2018).<br><br> Such systems are composed of an integrated array of time-synchronised navigation sensors and imaging sensors mounted on a mobile platform (Puente et al., 2013, Tao and Li, 2007). Usually the MMS implies integration of different types of sensors, such as GNSS, IMU, video camera and/or laser scanners that allow accurate and quick mapping (Li, 1997, Petrie, 2010, Tao, 2000). The typical requirement of high-accuracy 3D georeferenced reconstruction often makes such systems quite expensive. Indeed, at time of writing most of the terrestrial MMSs on the market have a cost usually greater than 50000, which might be expensive for certain applications (Ellum and El-Sheimy, 2002, Piras et al., 2008). In order to allow best performance sensors have to be properly calibrated (Dong et al., 2007, Ellum and El-Sheimy, 2002).<br><br> Sensors in MMSs are usually integrated and managed through a dedicated software, which is developed ad hoc for the devices mounted on the mobile platform and hence tailored for the specific used sensors. Despite the fact that commercial solutions are complete, very specific and particularly related to the typology of survey, their price is a factor that restricts the number of users and the possible interested sectors.<br><br> This paper describes a (relatively low cost) terrestrial Mobile Mapping System developed at the University of Padua (TESAF, Department of Land Environment Agriculture and Forestry) by the research team in CIRGEO, in order to test an alternative solution to other more expensive MMSs. The first objective of this paper is to report on the development of a prototype of MMS for the collection of geospatial data based on the assembly of low cost sensors managed through a web interface developed using open source libraries. The main goal is to provide a system accessible by any type of user, and flexible to any type of upgrade or introduction of new models of sensors or versions thereof. After a presentation of the hardware components used in our system, a more detailed description of the software developed for the management of the MMS will be provided, which is the part of the innovation of the project. According to the worldwide request for having big data available through the web from everywhere in the world (Pirotti et al., 2011), the proposed solution allows to retrieve data from a web interface Figure 4. Actually, this is part of a project for the development of a new web infrastructure in the University of Padua (but it will be available for external users as well), in order to ease collaboration between researchers from different areas.<br><br> Finally, strengths, weaknesses and future developments of the low cost MMS are discussed.
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Peter, M., S. R. U. N. Jafri, and G. Vosselman. "LINE SEGMENTATION OF 2D LASER SCANNER POINT CLOUDS FOR INDOOR SLAM BASED ON A RANGE OF RESIDUALS." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W4 (September 14, 2017): 363–69. http://dx.doi.org/10.5194/isprs-annals-iv-2-w4-363-2017.
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Indoor mobile laser scanning (IMLS) based on the Simultaneous Localization and Mapping (SLAM) principle proves to be the preferred method to acquire data of indoor environments at a large scale. In previous work, we proposed a backpack IMLS system containing three 2D laser scanners and an according SLAM approach. The feature-based SLAM approach solves all six degrees of freedom simultaneously and builds on the association of lines to planes. Because of the iterative character of the SLAM process, the quality and reliability of the segmentation of linear segments in the scanlines plays a crucial role in the quality of the derived poses and consequently the point clouds. The orientations of the lines resulting from the segmentation can be influenced negatively by narrow objects which are nearly coplanar with walls (like e.g. doors) which will cause the line to be tilted if those objects are not detected as separate segments. State-of-the-art methods from the robotics domain like Iterative End Point Fit and Line Tracking were found to not handle such situations well. Thus, we describe a novel segmentation method based on the comparison of a range of residuals to a range of thresholds. For the definition of the thresholds we employ the fact that the expected value for the average of residuals of <i>n</i> points with respect to the line is <i>σ</i>&thinsp;/&thinsp;&radic;<i>n</i>. Our method, as shown by the experiments and the comparison to other methods, is able to deliver more accurate results than the two approaches it was tested against.
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Holland, D. A., C. Pook, D. Capstick, and A. Hemmings. "THE TOPOGRAPHIC DATA DELUGE – COLLECTING AND MAINTAINING DATA IN A 21ST CENTURY MAPPING AGENCY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 727–31. http://dx.doi.org/10.5194/isprsarchives-xli-b4-727-2016.
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In the last few years, the number of sensors and data collection systems available to a mapping agency has grown considerably. In the field, in addition to total stations measuring position, angles and distances, the surveyor can choose from hand-held GPS devices, multi-lens imaging systems or laser scanners, which may be integrated with a laptop or tablet to capture topographic data directly in the field. These systems are joined by mobile mapping solutions, mounted on large or small vehicles, or sometimes even on a backpack carried by a surveyor walking around a site. Such systems allow the raw data to be collected rapidly in the field, while the interpretation of the data can be performed back in the office at a later date. In the air, large format digital cameras and airborne lidar sensors are being augmented with oblique camera systems, taking multiple views at each camera position and being used to create more realistic 3D city models. Lower down in the atmosphere, Unmanned Aerial Vehicles (or Remotely Piloted Aircraft Systems) have suddenly become ubiquitous. Hundreds of small companies have sprung up, providing images from UAVs using ever more capable consumer cameras. It is now easy to buy a 42 megapixel camera off the shelf at the local camera shop, and Canon recently announced that they are developing a 250 megapixel sensor for the consumer market. While these sensors may not yet rival the metric cameras used by today’s photogrammetrists, the rapid developments in sensor technology could eventually lead to the commoditization of high-resolution camera systems. With data streaming in from so many sources, the main issue for a mapping agency is how to interpret, store and update the data in such a way as to enable the creation and maintenance of the end product. This might be a topographic map, ortho-image or a digital surface model today, but soon it is just as likely to be a 3D point cloud, textured 3D mesh, 3D city model, or Building Information Model (BIM) with all the data interpretation and modelling that entails. In this paper, we describe research/investigations into the developing technologies and outline the findings for a National Mapping Agency (NMA). We also look at the challenges that these new data collection systems will bring to an NMA, and suggest ways that we may work to meet these challenges and deliver the products desired by our users.
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Holland, D. A., C. Pook, D. Capstick, and A. Hemmings. "THE TOPOGRAPHIC DATA DELUGE – COLLECTING AND MAINTAINING DATA IN A 21ST CENTURY MAPPING AGENCY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 727–31. http://dx.doi.org/10.5194/isprs-archives-xli-b4-727-2016.
Full textAbstract:
In the last few years, the number of sensors and data collection systems available to a mapping agency has grown considerably. In the field, in addition to total stations measuring position, angles and distances, the surveyor can choose from hand-held GPS devices, multi-lens imaging systems or laser scanners, which may be integrated with a laptop or tablet to capture topographic data directly in the field. These systems are joined by mobile mapping solutions, mounted on large or small vehicles, or sometimes even on a backpack carried by a surveyor walking around a site. Such systems allow the raw data to be collected rapidly in the field, while the interpretation of the data can be performed back in the office at a later date. In the air, large format digital cameras and airborne lidar sensors are being augmented with oblique camera systems, taking multiple views at each camera position and being used to create more realistic 3D city models. Lower down in the atmosphere, Unmanned Aerial Vehicles (or Remotely Piloted Aircraft Systems) have suddenly become ubiquitous. Hundreds of small companies have sprung up, providing images from UAVs using ever more capable consumer cameras. It is now easy to buy a 42 megapixel camera off the shelf at the local camera shop, and Canon recently announced that they are developing a 250 megapixel sensor for the consumer market. While these sensors may not yet rival the metric cameras used by today’s photogrammetrists, the rapid developments in sensor technology could eventually lead to the commoditization of high-resolution camera systems. With data streaming in from so many sources, the main issue for a mapping agency is how to interpret, store and update the data in such a way as to enable the creation and maintenance of the end product. This might be a topographic map, ortho-image or a digital surface model today, but soon it is just as likely to be a 3D point cloud, textured 3D mesh, 3D city model, or Building Information Model (BIM) with all the data interpretation and modelling that entails. In this paper, we describe research/investigations into the developing technologies and outline the findings for a National Mapping Agency (NMA). We also look at the challenges that these new data collection systems will bring to an NMA, and suggest ways that we may work to meet these challenges and deliver the products desired by our users.
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Rutzinger, M., B. Höfle, R. Lindenbergh, S. Oude Elberink, F. Pirotti, R. Sailer, M. Scaioni, J. Stötter, and D. Wujanz. "CLOSE-RANGE SENSING TECHNIQUES IN ALPINE TERRAIN." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-6 (June 6, 2016): 15–22. http://dx.doi.org/10.5194/isprsannals-iii-6-15-2016.
Full textAbstract:
Early career researchers such as PhD students are a main driving force of scientific research and are for a large part responsible for research innovation. They work on specialized topics within focused research groups that have a limited number of members, but might also have limited capacity in terms of lab equipment. This poses a serious challenge for educating such students as it is difficult to group a sufficient number of them to enable efficient knowledge transfer. To overcome this problem, the Innsbruck Summer School of Alpine Research 2015 on close-range sensing techniques in Alpine terrain was organized in Obergurgl, Austria, by an international team from several universities and research centres. Of the applicants a group of 40 early career researchers were selected with interest in about ten types of specialized surveying tools, i.e. laser scanners, a remotely piloted aircraft system, a thermal camera, a backpack mobile mapping system and different grade photogrammetric equipment. During the one-week summer school, students were grouped according to their personal preference to work with one such type of equipment under guidance of an expert lecturer. All students were required to capture and process field data on a mountain-related theme like landslides or rock glaciers. The work on the assignments lasted the whole week but was interspersed with lectures on selected topics by invited experts. The final task of the summer school participants was to present and defend their results to their peers, lecturers and other colleagues in a symposium-like setting. Here we present the framework and content of this summer school which brought together scientists from close-range sensing and environmental and geosciences.
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Rutzinger, M., B. Höfle, R. Lindenbergh, S. Oude Elberink, F. Pirotti, R. Sailer, M. Scaioni, J. Stötter, and D. Wujanz. "CLOSE-RANGE SENSING TECHNIQUES IN ALPINE TERRAIN." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences III-6 (June 6, 2016): 15–22. http://dx.doi.org/10.5194/isprs-annals-iii-6-15-2016.
Full textAbstract:
Early career researchers such as PhD students are a main driving force of scientific research and are for a large part responsible for research innovation. They work on specialized topics within focused research groups that have a limited number of members, but might also have limited capacity in terms of lab equipment. This poses a serious challenge for educating such students as it is difficult to group a sufficient number of them to enable efficient knowledge transfer. To overcome this problem, the Innsbruck Summer School of Alpine Research 2015 on close-range sensing techniques in Alpine terrain was organized in Obergurgl, Austria, by an international team from several universities and research centres. Of the applicants a group of 40 early career researchers were selected with interest in about ten types of specialized surveying tools, i.e. laser scanners, a remotely piloted aircraft system, a thermal camera, a backpack mobile mapping system and different grade photogrammetric equipment. During the one-week summer school, students were grouped according to their personal preference to work with one such type of equipment under guidance of an expert lecturer. All students were required to capture and process field data on a mountain-related theme like landslides or rock glaciers. The work on the assignments lasted the whole week but was interspersed with lectures on selected topics by invited experts. The final task of the summer school participants was to present and defend their results to their peers, lecturers and other colleagues in a symposium-like setting. Here we present the framework and content of this summer school which brought together scientists from close-range sensing and environmental and geosciences.
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Wen, C., Y. Xia, Y. Lian, Y. Dai, J. Tan, C. Wang, and J. Li. "MOBILE LASER SCANNING SYSTEMS FOR GPS/GNSS-DENIED ENVIRONMENT MAPPING." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1 (September 26, 2018): 457–60. http://dx.doi.org/10.5194/isprs-archives-xlii-1-457-2018.
Full textAbstract:
<p><strong>Abstract.</strong> Indoor 3D mapping provides a useful three-dimensional structure via an indoor map for many applications. To acquire highly efficient and relatively accurate mapping for large-scale GPS/GNSS-denied scene, we present an upgraded backpacked laser scanning system and a car-mounted indoor mobile laser scanning system. The systems provide both 3D laser scanning point cloud and camera images. In this paper, a simultaneous extrinsic calibration approach for multiple multi-beam LIDAR and multiple cameras is also proposed using the Simultaneous Localization and Mapping (SLAM)-based algorithm. The proposed approach uses the SLAM-based algorithm to achieve a large calibration scene using mobile platforms, registers an acquired multi-beam LIDAR point cloud to the terrestrial LIDAR point cloud to acquire denser points for corner feature extraction, and finally achieves simultaneous calibration. With the proposed mapping and calibration algorithms, we can provide centimetre-lever coloured point cloud with relatively high efficiency and accuracy.</p>