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This chapter covers the essentials regarding indoor 3D data, from scanning to reconstruction. It is aimed for education and professionals. The order of presentation is background, history in measurement method development, sensors, sensor systems, positioning algorithms, reconstruction, and applications. The authors’ backgrounds are in indoor 3D, mobile laser scanning, indoor reconstruction, and robotics. In order to maintain a coherence in the text and provide some useful tools for the reader, we have selected to focus solely on the ICP version of simultaneous localization and mapping (SLAM). Regardless, this should give a solid base for the reader to understand other (e.g. probabilistic) indoor SLAM methods as well. Reconstruction algorithms (starting from room segmentation and opening detection) are discussed with the help of abundant figures. At the very end, we discuss future trends with a connection to the current applications and propose some exercise questions for students.
Ville V. Lehtola; Shayan Nikoohemat; Andreas Nüchter. Indoor 3D: Overview on Scanning and Reconstruction Methods. Handbook of Big Geospatial Data 2020, 55 -97.
AMA StyleVille V. Lehtola, Shayan Nikoohemat, Andreas Nüchter. Indoor 3D: Overview on Scanning and Reconstruction Methods. Handbook of Big Geospatial Data. 2020; ():55-97.
Chicago/Turabian StyleVille V. Lehtola; Shayan Nikoohemat; Andreas Nüchter. 2020. "Indoor 3D: Overview on Scanning and Reconstruction Methods." Handbook of Big Geospatial Data , no. : 55-97.
Tiago De Oliveira Marques; Maija Mäkelä; Leslie Montloin; Terhi Lehtola; Sarang Thombre; Ville Lehtola. Towards tropospheric delay estimation using GNSS smartphone receiver network. Advances in Space Research 2020, 1 .
AMA StyleTiago De Oliveira Marques, Maija Mäkelä, Leslie Montloin, Terhi Lehtola, Sarang Thombre, Ville Lehtola. Towards tropospheric delay estimation using GNSS smartphone receiver network. Advances in Space Research. 2020; ():1.
Chicago/Turabian StyleTiago De Oliveira Marques; Maija Mäkelä; Leslie Montloin; Terhi Lehtola; Sarang Thombre; Ville Lehtola. 2020. "Towards tropospheric delay estimation using GNSS smartphone receiver network." Advances in Space Research , no. : 1.
Autonomous ships are expected to improve the level of safety and efficiency in future maritime navigation. Such vessels need perception for two purposes: to perform autonomous situational awareness and to monitor the integrity of the sensor system itself. In order to meet these needs, the perception system must fuse data from novel and traditional perception sensors using Artificial Intelligence (AI) techniques. This article overviews the recognized operational requirements that are imposed on regular and autonomous seafaring vessels, and then proceeds to consider suitable sensors and relevant AI techniques for an operational sensor system. The integration of four sensors families is considered: sensors for precise absolute positioning (Global Navigation Satellite System (GNSS) receivers and Inertial Measurement Unit (IMU)), visual sensors (monocular and stereo cameras), audio sensors (microphones), and sensors for remote-sensing (RADAR and LiDAR). Additionally, sources of auxiliary data, such as Automatic Identification System (AIS) and external data archives are discussed. The perception tasks are related to well-defined problems, such as situational abnormality detection, vessel classification, and localization, that are solvable using AI techniques. Machine learning methods, such as deep learning and Gaussian processes, are identified to be especially relevant for these problems. The different sensors and AI techniques are characterized keeping in view the operational requirements, and some example state-of-the-art options are compared based on accuracy, complexity, required resources, compatibility and adaptability to maritime environment, and especially towards practical realization of autonomous systems.
Sarang Thombre; Zheng Zhao; Henrik Ramm-Schmidt; Jose M. Vallet Garcia; Tuomo Malkamaki; Sergey Nikolskiy; Toni Hammarberg; Hiski Nuortie; M. Zahidul H. Bhuiyan; Simo Sarkka; Ville V. Lehtola. Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review. IEEE Transactions on Intelligent Transportation Systems 2020, PP, 1 -20.
AMA StyleSarang Thombre, Zheng Zhao, Henrik Ramm-Schmidt, Jose M. Vallet Garcia, Tuomo Malkamaki, Sergey Nikolskiy, Toni Hammarberg, Hiski Nuortie, M. Zahidul H. Bhuiyan, Simo Sarkka, Ville V. Lehtola. Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review. IEEE Transactions on Intelligent Transportation Systems. 2020; PP (99):1-20.
Chicago/Turabian StyleSarang Thombre; Zheng Zhao; Henrik Ramm-Schmidt; Jose M. Vallet Garcia; Tuomo Malkamaki; Sergey Nikolskiy; Toni Hammarberg; Hiski Nuortie; M. Zahidul H. Bhuiyan; Simo Sarkka; Ville V. Lehtola. 2020. "Sensors and AI Techniques for Situational Awareness in Autonomous Ships: A Review." IEEE Transactions on Intelligent Transportation Systems PP, no. 99: 1-20.
Indoor 3D models are digital representations of building interiors reconstructed from scanned data acquired by laser scanners, digital depth (RGBD) cameras, and CAD drawings. Consequently, there is noise in the source data and a notable variety in the methods used to treat the noise and to process these data into reconstructed models. Alas, the correctness of these reconstructions and thus their suitability for a given application are uncertain. There is a lack of a robust base logic that would allow for controlling the consistency of these (automatically) generated models. Fortunately, correctness criteria are well‐defined through existing international standards. Hence, we propose a conceptual framework based on formal grammars to check the semantic, geometric, and topological consistency of a reconstructed 3D model. The proposed method proceeds in three steps to validate the model: (1) correctness checking of individual components; (2) consistency verification of instances’ interactions; and (3) model consistency check for targeted applications. Our method identifies the components in the model that violate the given rules derived from the current standards and expert knowledge. Ultimately, we propose a quantified formulation of our method that may be straightforwardly integrated into industrial‐level model checkers. The approach is independent of level of details and reconstruction method.
Shayan Nikoohemat; Abdoulaye A. Diakité; Ville Lehtola; Sisi Zlatanova; George Vosselman. Consistency grammar for 3D indoor model checking. Transactions in GIS 2020, 25, 189 -212.
AMA StyleShayan Nikoohemat, Abdoulaye A. Diakité, Ville Lehtola, Sisi Zlatanova, George Vosselman. Consistency grammar for 3D indoor model checking. Transactions in GIS. 2020; 25 (1):189-212.
Chicago/Turabian StyleShayan Nikoohemat; Abdoulaye A. Diakité; Ville Lehtola; Sisi Zlatanova; George Vosselman. 2020. "Consistency grammar for 3D indoor model checking." Transactions in GIS 25, no. 1: 189-212.
In recent years, the importance of indoor mapping increased in a wide range of applications, such as facility management and mapping hazardous sites. The essential technique behind indoor mapping is simultaneous localization and mapping (SLAM) because SLAM offers suitable positioning estimates in environments where satellite positioning is not available. State-of-the-art indoor mobile mapping systems employ Visual-based SLAM or LiDAR-based SLAM. However, Visual-based SLAM is sensitive to textureless environments and, similarly, LiDAR-based SLAM is sensitive to a number of pose configurations where the geometry of laser observations is not strong enough to reliably estimate the six-degree-of-freedom (6DOF) pose of the system. In this paper, we present different strategies that utilize the benefits of the inertial measurement unit (IMU) in the pose estimation and support LiDAR-based SLAM in overcoming these problems. The proposed strategies have been implemented and tested using different datasets and our experimental results demonstrate that the proposed methods do indeed overcome these problems. We conclude that IMU observations increase the robustness of SLAM, which is expected, but also that the best reconstruction accuracy is obtained not with a blind use of all observations but by filtering the measurements with a proposed reliability measure. To this end, our results show promising improvements in reconstruction accuracy.
S. Karam; Ville Lehtola; G. Vosselman. STRATEGIES TO INTEGRATE IMU AND LIDAR SLAM FOR INDOOR MAPPING. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2020, V-1-2020, 223 -230.
AMA StyleS. Karam, Ville Lehtola, G. Vosselman. STRATEGIES TO INTEGRATE IMU AND LIDAR SLAM FOR INDOOR MAPPING. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2020; V-1-2020 ():223-230.
Chicago/Turabian StyleS. Karam; Ville Lehtola; G. Vosselman. 2020. "STRATEGIES TO INTEGRATE IMU AND LIDAR SLAM FOR INDOOR MAPPING." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-1-2020, no. : 223-230.
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.
S. Karam; Ville Lehtola; G. Vosselman. INTEGRATING A LOW-COST MEMS IMU INTO A LASER-BASED SLAM FOR INDOOR MOBILE MAPPING. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2019, XLII-2/W17, 149 -156.
AMA StyleS. Karam, Ville Lehtola, G. Vosselman. INTEGRATING A LOW-COST MEMS IMU INTO A LASER-BASED SLAM FOR INDOOR MOBILE MAPPING. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019; XLII-2/W17 ():149-156.
Chicago/Turabian StyleS. Karam; Ville Lehtola; G. Vosselman. 2019. "INTEGRATING A LOW-COST MEMS IMU INTO A LASER-BASED SLAM FOR INDOOR MOBILE MAPPING." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17, no. : 149-156.
Single photon lidars (in solid state form) offer several benefits over pulsed lidars, such as independence of micro-mechanical moving parts or rotating joints, lower power consumption, faster acquisition rate, and reduced size. When mass produced, they will be cheaper and smaller and thus very attractive for mobile laser scanning applications. However, as these lidars operate by receiving single photons, they are very susceptible to background illumination such as sunlight. In other words, the observations contain a significant amount of noise, or to be specific, outliers. This causes trouble for measurements done in motion, as the sampling rate (i.e. the measurement frequency) should be low and high at the same time. It should be low enough so that target detection is robust, meaning that the targets can be distinguished from the single-photon avalanche diode (SPAD) triggings caused by the background photons. On the other hand, the sampling rate should be high enough to allow for measurements to be done from motion. Quick sampling reduces the probability that a sample gathered during motion would contain data from more than a single target at a specific range. Here, we study the exploitation of spatial correlations that exist between the observations as a mean to overcome this sampling rate paradox. We propose computational methods for short and long range. Our results indicate that the spatial correlations do indeed allow for faster and more robust sampling of measurements, which makes single photon lidars more attractive in (daylight) mobile laser scanning.
V. V. Lehtola; H. Hyyti; P. Keränen; J. Kostamovaara. SINGLE PHOTON LIDAR IN MOBILE LASER SCANNING: THE SAMPLING RATE PROBLEM AND INITIAL SOLUTIONS VIA SPATIAL CORRELATIONS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2019, XLII-2/W18, 91 -97.
AMA StyleV. V. Lehtola, H. Hyyti, P. Keränen, J. Kostamovaara. SINGLE PHOTON LIDAR IN MOBILE LASER SCANNING: THE SAMPLING RATE PROBLEM AND INITIAL SOLUTIONS VIA SPATIAL CORRELATIONS. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019; XLII-2/W18 ():91-97.
Chicago/Turabian StyleV. V. Lehtola; H. Hyyti; P. Keränen; J. Kostamovaara. 2019. "SINGLE PHOTON LIDAR IN MOBILE LASER SCANNING: THE SAMPLING RATE PROBLEM AND INITIAL SOLUTIONS VIA SPATIAL CORRELATIONS." The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W18, no. : 91-97.
Point clouds obtained from mobile and terrestrial laser scanning are imperfect as data is typically missing due to occlusions. This problem is often encountered in 3D reconstruction and is especially troublesome for 3D visualization applications. The missing data may be recovered by intensifying the scanning mission, which may be expensive, or to some extent, by computational means. Here, we present an inpainting technique that covers these occlusion holes in 3D built environment point clouds. The proposed technique uses two neural networks with an identical architecture, applied separately for geometry and colors.
P. Väänänen; V. Lehtola. INPAINTING OCCLUSION HOLES IN 3D BUILT ENVIRONMENT POINT CLOUDS. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2019, XLII-2/W17, 393 -398.
AMA StyleP. Väänänen, V. Lehtola. INPAINTING OCCLUSION HOLES IN 3D BUILT ENVIRONMENT POINT CLOUDS. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019; XLII-2/W17 ():393-398.
Chicago/Turabian StyleP. Väänänen; V. Lehtola. 2019. "INPAINTING OCCLUSION HOLES IN 3D BUILT ENVIRONMENT POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W17, no. : 393-398.
Safety in ice-covered polar waters can be optimised via the choice of a ship's route. This is of utmost importance for conventional as well as autonomous ships. However, the current state of the art in e-Navigation tools has left two open questions. First, what essential information are these tools still missing, and second, how they are seen by sea captains. In order to address these questions, we organised an ice navigation workshop to systematically collect routing justifications given by and waypoints planned by experienced sea captains that are particularly seasoned in ice navigation. Here, we report the outcome of that workshop. Our key findings include the reasoning and the commentary of the participants in looking for a better and safer route. These comments shed light upon both the official and unofficial code of conduct in open waters and boil down into a list of additional prerequisite information if further steps towards system autonomy are sought. Finally, the expert-planned waypoints are to be published alongside this paper to act as a benchmark for future maritime studies.
Ville V. Lehtola; Jakub Montewka; Johanna Salokannel. Sea Captains’ Views on Automated Ship Route Optimization in Ice-covered Waters. Journal of Navigation 2019, 73, 364 -383.
AMA StyleVille V. Lehtola, Jakub Montewka, Johanna Salokannel. Sea Captains’ Views on Automated Ship Route Optimization in Ice-covered Waters. Journal of Navigation. 2019; 73 (2):364-383.
Chicago/Turabian StyleVille V. Lehtola; Jakub Montewka; Johanna Salokannel. 2019. "Sea Captains’ Views on Automated Ship Route Optimization in Ice-covered Waters." Journal of Navigation 73, no. 2: 364-383.
GNSS receiver data crowdsourcing is of interest for multiple applications, e.g., weather monitoring. The bottleneck in this technology is the quality of the GNSS receivers. Therefore, we lay out in an introductory manner the steps to estimate the performance of an arbitrary GNSS receiver via the measurement errors related to its instrumentation. Specifically, we do not need to know the position of the receiver antenna, which allows also for the assessment of smartphone GNSS receivers having integrated antennas. Moreover, the method is independent of atmospheric errors so that no ionospheric or tropospheric correction services provided by base stations are needed. Error models for performance evaluation can be calculated from receiver RINEX (receiver independent exchange format)data using only ephemeris corrections. For the results, we present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications. Currently, the typical positioning precision for the latest smartphone receivers is around the decimeter level, while for a professional-grade receiver, it is within a few millimeters.
Ville V. Lehtola; Stefan Söderholm; Michelle Koivisto; Leslie Montloin. Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance. Sensors 2019, 19, 3018 .
AMA StyleVille V. Lehtola, Stefan Söderholm, Michelle Koivisto, Leslie Montloin. Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance. Sensors. 2019; 19 (13):3018.
Chicago/Turabian StyleVille V. Lehtola; Stefan Söderholm; Michelle Koivisto; Leslie Montloin. 2019. "Exploring GNSS Crowdsourcing Feasibility: Combinations of Measurements for Modeling Smartphone and Higher End GNSS Receiver Performance." Sensors 19, no. 13: 3018.
Safety for conventional and autonomous navigation in ice-covered waters is a topic of rising importance. Here, we propose a generic extendable framework to provide the optimal route from multiple route planning objectives. These objectives are attained by an evaluation of multi-source input data, including state-of-the-art model data for ice conditions, for bathymetric knowledge, and for ship-ice interaction. Additionally, we model the ship-ship interactions statistically using a mean-field, to account for ships (indirectly) assisting each other via artificial ice channels. For the subsequent pathfinding problem, we propose a new A*-based algorithm that yields output which is not dependent on the grid format of the input data but instead consists of a path that follows the Earth's curvature. The outputs of the algorithm are a set of waypoints (representing the optimal route), the travel costs (expressed in time), and the additional travel cost estimates caused by route deviation, should the optimal route be altered in any way. The steaming speeds, the optimal route, and the deviation times are represented with two-dimensional (2D) maps. Finally, we provide a model implementation of our framework as a Matlab-package, ICEPATHFINDER, that is suitable for both operational and strategic ship route optimization.
Ville Lehtola; Jakub Montewka; Floris Goerlandt; Robert Guinness; Mikko Lensu. Finding safe and efficient shipping routes in ice-covered waters: A framework and a model. Cold Regions Science and Technology 2019, 165, 102795 .
AMA StyleVille Lehtola, Jakub Montewka, Floris Goerlandt, Robert Guinness, Mikko Lensu. Finding safe and efficient shipping routes in ice-covered waters: A framework and a model. Cold Regions Science and Technology. 2019; 165 ():102795.
Chicago/Turabian StyleVille Lehtola; Jakub Montewka; Floris Goerlandt; Robert Guinness; Mikko Lensu. 2019. "Finding safe and efficient shipping routes in ice-covered waters: A framework and a model." Cold Regions Science and Technology 165, no. : 102795.
Z. Kang; K. Khoshelham; L. Díaz-Vilariño; S. Dalyot; C. Wang; S. Nebiker; Ville Lehtola; K. W. Chiang; K.-J. Li; B. De Lathouwer. PREFACE – ISPRS WORKSHOP INDOOR 3D 2019. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2019, IV-2/W5, 245 -245.
AMA StyleZ. Kang, K. Khoshelham, L. Díaz-Vilariño, S. Dalyot, C. Wang, S. Nebiker, Ville Lehtola, K. W. Chiang, K.-J. Li, B. De Lathouwer. PREFACE – ISPRS WORKSHOP INDOOR 3D 2019. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2019; IV-2/W5 ():245-245.
Chicago/Turabian StyleZ. Kang; K. Khoshelham; L. Díaz-Vilariño; S. Dalyot; C. Wang; S. Nebiker; Ville Lehtola; K. W. Chiang; K.-J. Li; B. De Lathouwer. 2019. "PREFACE – ISPRS WORKSHOP INDOOR 3D 2019." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W5, no. : 245-245.
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.
Samer Karam; George Vosselman; Michael Peter; Siavash Hosseinyalamdary; Ville Lehtola. Design, Calibration, and Evaluation of a Backpack Indoor Mobile Mapping System. Remote Sensing 2019, 11, 905 .
AMA StyleSamer Karam, George Vosselman, Michael Peter, Siavash Hosseinyalamdary, Ville Lehtola. Design, Calibration, and Evaluation of a Backpack Indoor Mobile Mapping System. Remote Sensing. 2019; 11 (8):905.
Chicago/Turabian StyleSamer Karam; George Vosselman; Michael Peter; Siavash Hosseinyalamdary; Ville Lehtola. 2019. "Design, Calibration, and Evaluation of a Backpack Indoor Mobile Mapping System." Remote Sensing 11, no. 8: 905.
Crane posture estimation is the stepping stone to forest machine automation. Here, we introduce a robust minimal perception solution, that is, one that uses minimal constraints for maximal benefits. Specifically, we introduce a robust particle‐filter‐based method to estimate and track the posture of a flexible hydraulic crane by using only low‐cost equipment, namely, a two‐dimensional (2D) laser scanner, two short magnetically attached metal tubes as targets, and an angle sensor. An important feature of our method is that it incorporates control signals for hydraulic actuators. In contrast to the previous works employing laser scanners, we do not use the full shape of the crane to estimate the crane posture, but, instead, we use only two small targets in the field of view of the laser scanner. Thus, a large share of the range data is useful for other purposes, for example, to map the surrounding environment. We test the proposed method in a challenging forest environment and show that the particle filter is able to estimate the posture of the hydraulic crane efficiently and reliably in the presence of occlusions and obstructions. During our comprehensive testing, the tip position was measured with average errors smaller than 4.3 cm whereas the absolute maximum error was 15 cm.
Heikki Hyyti; Ville V. Lehtola; Arto Visala. Forestry crane posture estimation with a two-dimensional laser scanner. Journal of Field Robotics 2018, 35, 1025 -1049.
AMA StyleHeikki Hyyti, Ville V. Lehtola, Arto Visala. Forestry crane posture estimation with a two-dimensional laser scanner. Journal of Field Robotics. 2018; 35 (7):1025-1049.
Chicago/Turabian StyleHeikki Hyyti; Ville V. Lehtola; Arto Visala. 2018. "Forestry crane posture estimation with a two-dimensional laser scanner." Journal of Field Robotics 35, no. 7: 1025-1049.
Matti Vaaja; Mikko Maksimainen; Juho-Pekka Virtanen; Antero Kukko; Ville Lehtola; Juha Hyyppä; Hannu Hyyppä. Mobile mapping of night-time road environment lighting conditions. The Photogrammetric Journal of Finland 2018, 26, 1 -17.
AMA StyleMatti Vaaja, Mikko Maksimainen, Juho-Pekka Virtanen, Antero Kukko, Ville Lehtola, Juha Hyyppä, Hannu Hyyppä. Mobile mapping of night-time road environment lighting conditions. The Photogrammetric Journal of Finland. 2018; 26 (1):1-17.
Chicago/Turabian StyleMatti Vaaja; Mikko Maksimainen; Juho-Pekka Virtanen; Antero Kukko; Ville Lehtola; Juha Hyyppä; Hannu Hyyppä. 2018. "Mobile mapping of night-time road environment lighting conditions." The Photogrammetric Journal of Finland 26, no. 1: 1-17.
Mobile laser scanning (MLS) provides kinematic means to collect three dimensional data from surroundings for various mapping and environmental analysis purposes. Vehicle based MLS has been used for road and urban asset surveys for about a decade. The equipment to derive the trajectory information for the point cloud generation from the laser data is almost without exception based on GNSS-IMU (Global Navigation Satellite System – Inertial Measurement Unit) technique. That is because of the GNSS ability to maintain global accuracy, and IMU to produce the attitude information needed to orientate the laser scanning and imaging sensor data. However, there are known challenges in maintaining accurate positioning when GNSS signal is weak or even absent over long periods of time. The duration of the signal loss affects the severity of degradation of the positioning solution depending on the quality/performance level of the IMU in use. The situation could be improved to a certain extent with higher performance IMUs, but increasing system expenses make such approach unsustainable in general. Another way to tackle the problem is to attach additional sensors to the system to overcome the degrading position accuracy: such that observe features from the environment to solve for short term system movements accurately enough to prevent the IMU solution to drift. This results in more complex system integration with need for more calibration and synchronization of multiple sensors into an operational approach. In this paper we study operation of an ATV (All -terrain vehicle) mounted, GNSS-IMU based single scanner MLS system in boreal forest conditions. The data generated by RoamerR2 system is targeted for generating 3D terrain and tree maps for optimizing harvester operations and forest inventory purposes at individual tree level. We investigate a process-flow and propose a graph optimization based method which uses data from a single scanner MLS for correcting the post-processed GNSS-IMU trajectory for positional drift under mature boreal forest canopy conditions. The result shows that we can improve the internal conformity of the data significantly from 0.7 m to 1 cm based on tree stem feature location data. When the optimization result is compared to reference at plot level we reach down to 6 cm mean error in absolute tree stem locations. The approach can be generalized to any MLS point cloud data, and provides as such a remarkable contribution to harness MLS for practical forestry and high precision terrain and structural modeling in GNSS obstructed environments.Peer reviewe
Antero Kukko; Risto Kaijaluoto; Harri Kaartinen; Ville Lehtola; Anttoni Jaakkola; Juha Hyyppä. Graph SLAM correction for single scanner MLS forest data under boreal forest canopy. ISPRS Journal of Photogrammetry and Remote Sensing 2017, 132, 199 -209.
AMA StyleAntero Kukko, Risto Kaijaluoto, Harri Kaartinen, Ville Lehtola, Anttoni Jaakkola, Juha Hyyppä. Graph SLAM correction for single scanner MLS forest data under boreal forest canopy. ISPRS Journal of Photogrammetry and Remote Sensing. 2017; 132 ():199-209.
Chicago/Turabian StyleAntero Kukko; Risto Kaijaluoto; Harri Kaartinen; Ville Lehtola; Anttoni Jaakkola; Juha Hyyppä. 2017. "Graph SLAM correction for single scanner MLS forest data under boreal forest canopy." ISPRS Journal of Photogrammetry and Remote Sensing 132, no. : 199-209.
Accurate three-dimensional (3D) data from indoor spaces are of high importance for various applications in construction, indoor navigation and real estate management. Mobile scanning techniques are offering an efficient way to produce point clouds, but with a lower accuracy than the traditional terrestrial laser scanning (TLS). In this paper, we first tackle the problem of how the quality of a point cloud should be rigorously evaluated. Previous evaluations typically operate on some point cloud subset, using a manually-given length scale, which would perhaps describe the ranging precision or the properties of the environment. Instead, the metrics that we propose perform the quality evaluation to the full point cloud and over all of the length scales, revealing the method precision along with some possible problems related to the point clouds, such as outliers, over-completeness and misregistration. The proposed methods are used to evaluate the end product point clouds of some of the latest methods. In detail, point clouds are obtained from five commercial indoor mapping systems, Matterport, NavVis, Zebedee, Stencil and Leica Pegasus: Backpack, and three research prototypes, Aalto VILMA , FGI Slammer and the Würzburg backpack. These are compared against survey-grade TLS point clouds captured from three distinct test sites that each have different properties. Based on the presented experimental findings, we discuss the properties of the proposed metrics and the strengths and weaknesses of the above mapping systems and then suggest directions for future research.
Ville V. Lehtola; Harri Kaartinen; Andreas Nüchter; Risto Kaijaluoto; Antero Kukko; Paula Litkey; Eija Honkavaara; Tomi Rosnell; Matti T. Vaaja; Juho-Pekka Virtanen; Matti Kurkela; Aimad El Issaoui; Lingli Zhu; Anttoni Jaakkola; Juha Hyyppä. Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods. Remote Sensing 2017, 9, 796 .
AMA StyleVille V. Lehtola, Harri Kaartinen, Andreas Nüchter, Risto Kaijaluoto, Antero Kukko, Paula Litkey, Eija Honkavaara, Tomi Rosnell, Matti T. Vaaja, Juho-Pekka Virtanen, Matti Kurkela, Aimad El Issaoui, Lingli Zhu, Anttoni Jaakkola, Juha Hyyppä. Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods. Remote Sensing. 2017; 9 (8):796.
Chicago/Turabian StyleVille V. Lehtola; Harri Kaartinen; Andreas Nüchter; Risto Kaijaluoto; Antero Kukko; Paula Litkey; Eija Honkavaara; Tomi Rosnell; Matti T. Vaaja; Juho-Pekka Virtanen; Matti Kurkela; Aimad El Issaoui; Lingli Zhu; Anttoni Jaakkola; Juha Hyyppä. 2017. "Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods." Remote Sensing 9, no. 8: 796.
Due to a mistake during the production process, the J. Imaging Editorial Office and the authors wish to make this correction to the paper written by Lehtola et al. [1].
Ville V. Lehtola; Matti Kurkela; Petri Rönnholm. Erratum: Ville V. Lehtola, et al. Radial Distortion from Epipolar Constraint for Rectilinear Cameras. J. Imaging 2017, 3, 8. Journal of Imaging 2017, 3, 23 .
AMA StyleVille V. Lehtola, Matti Kurkela, Petri Rönnholm. Erratum: Ville V. Lehtola, et al. Radial Distortion from Epipolar Constraint for Rectilinear Cameras. J. Imaging 2017, 3, 8. Journal of Imaging. 2017; 3 (3):23.
Chicago/Turabian StyleVille V. Lehtola; Matti Kurkela; Petri Rönnholm. 2017. "Erratum: Ville V. Lehtola, et al. Radial Distortion from Epipolar Constraint for Rectilinear Cameras. J. Imaging 2017, 3, 8." Journal of Imaging 3, no. 3: 23.
Lens distortion causes difficulties for 3D reconstruction, when uncalibrated image sets with weak geometry are used. We show that the largest part of lens distortion, known as the radial distortion, can be estimated along with the center of distortion from the epipolar constraint separately and before bundle adjustment without any calibration rig. The estimate converges as more image pairs are added. Descriptor matched scale-invariant feature (SIFT) point pairs that contain false matches can readily be given to our algorithm, EPOS (EpiPOlar-based Solver), as input. The processing is automated to the point where EPOS solves the distortion whether its type is barrel or pincushion or reports if there is no need for correction.
Ville V. Lehtola; Matti Kurkela; Petri Rönnholm. Radial Distortion from Epipolar Constraint for Rectilinear Cameras. Journal of Imaging 2017, 3, 8 .
AMA StyleVille V. Lehtola, Matti Kurkela, Petri Rönnholm. Radial Distortion from Epipolar Constraint for Rectilinear Cameras. Journal of Imaging. 2017; 3 (1):8.
Chicago/Turabian StyleVille V. Lehtola; Matti Kurkela; Petri Rönnholm. 2017. "Radial Distortion from Epipolar Constraint for Rectilinear Cameras." Journal of Imaging 3, no. 1: 8.
Ville Lehtola; Juho-Pekka Virtanen; Matti T. Vaaja; Hannu Hyyppä; Andreas Nuechter. Localization of a mobile laser scanner via dimensional reduction. ISPRS Journal of Photogrammetry and Remote Sensing 2016, 121, 48 -59.
AMA StyleVille Lehtola, Juho-Pekka Virtanen, Matti T. Vaaja, Hannu Hyyppä, Andreas Nuechter. Localization of a mobile laser scanner via dimensional reduction. ISPRS Journal of Photogrammetry and Remote Sensing. 2016; 121 ():48-59.
Chicago/Turabian StyleVille Lehtola; Juho-Pekka Virtanen; Matti T. Vaaja; Hannu Hyyppä; Andreas Nuechter. 2016. "Localization of a mobile laser scanner via dimensional reduction." ISPRS Journal of Photogrammetry and Remote Sensing 121, no. : 48-59.