Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools.

För att kunna konkurrera inom dagens fordonsindustri krävs effektiv produktutveckling. Det är under designprocessen som det finns störst möjlighet att påverka slutprodukten till det bättre. Ett sätt att åstadkomma effektivare produktutveckling är att tillämpa ny teknik. För att generera digitaliserade vägmodeller som används i simuleringar kan laserskanning appliceras. I dessa simuleringar kan fordonen testköras virtuellt och därigenom förkorta dimensioneringsprocessen. Laserskanning av kuperad terräng är komplex och därför saknas det underlag av kuperade testbanor i simuleringar. Denna studie syftar till att presentera olika laserskanningstekniker samt att utöka underlaget för virtuella simuleringar inom dimensioneringsprocessen av dumprar. Målet med arbetet är att skapa virtuella vägsektioner som kan användas i simuleringsmodeller.  Tre huvudtekniker inom laserskanning presenteras i teorikapitlet. Vidare har terrest laserskanning utförts på Volvos testbana i Målajord och med skanningsdata som underlag har en vägmodell som kan användas i fordonssimuleringar skapats i Matlab. Vägmodellen som skapats representerar väl den verkliga körbanan, vilket indikerar att terrest laserskanning är en väl fungerande metod för detta ändamål. / Product development is necessary to compete in today´s vehicle industry. During the design process the largest possibility to affect the end product to the better exists. One way to achieve product development is to apply new technology. Through application of terrestrial laser scanning digitalized road models can be achieved and be used in simulations. In these simulations, vehicles can virtually do a trial run and thereby shorten the dimensionprocess. Laser scanning of hilly terrain is complex and therefore groundwork of hilly roadways in simulations is missing.  This study refers to present different types of laser scanning methods and expand the groundwork for virtual simulations in the dimensionprocess of dumpers. The vision is to create virtual roadways which can be used in simulation models. Three main techniques of laser scanning are presented in the theory chapter. Further on terrestrial laser scanning has been used on Volvos test track in Målajord and with this scanning data as groundwork a road model, which can be used in vehicle simulations, has been created in Matlab. The road model is well representing the real roadway, which indicates that terrestrial laser scanning is a well working method for this purpose.

A mobile laser scanning (MLS) system equipped with a lidar, inertial navigation system and satellite positioning can be used to reconstruct georeferenced point-based models of the surveyed environments. Ideal reconstruction requires accurate trajectories that are challenging to obtain in forests. Satellite signals are heavily degraded under the forest canopy, while lidar-based positioning is often inefficient due to the forest’s unstructured and complex nature. Most forestry-related solutions compute or improve the trajectory in post-processing, focusing on accuracy rather than the possibility of real-time operation. On the other hand, real-time solutions exist, but they are primarily tested and evaluated in urban environments, and the forest’s effect on them is less known. In this study, high-quality, real-time point-based forest model generation was considered by applying techniques from the field of robotics. Forest data were collected with an MLS system mounted 1) on a stick carried by a person and 2) mounted on a forest harvester while performing thinning operations. The system’s trajectory was computed using lidar-inertial-based smoothing and mapping algorithms with real-time limitations. In addition, satellite measurements were either fused into the smoothing algorithm contributing to the trajectory estimation or were used to georeference the trajectory in a post-processing manner. Collecting reliable reference trajectories is difficult in forests. Therefore, this study mainly contains qualitative and relative evaluation. The results indicate that real-time and onboard processing is feasible for forest data with adequate accuracy. State-of-the-art edge and planar feature-based lidar odometry was the most accurate but could not fully maintain real-time operation. On the other hand, the normal distributions transform-based odometry can maintain fast and constant computation with slightly lower accuracy. Fusing the satellite positioning for the mapping reduced the internal integrity of the reconstructed point cloud models, and it is suggested to use it for post-processed georeferencing instead. / Ett mobilt laserskanningssystem (MLS) utrustat med ett lidar, tröghetsnavigeringssystem och satellitpositionering kan användas för att rekonstruera georefererade punktbaserade modeller av de undersökta miljöerna. Idealisk återuppbyggnad kräver exakta banor som är utmanande att uppnå i skogar. Satellitsignaler är kraftigt försämrade under skogens tak, medan lidarbaserad positionering ofta är ineffektiv på grund av skogens ostrukturerade och komplexa natur. De flesta skogsbruksrelaterade lösningar beräknar eller förbättrar banan i efterbearbetning, med fokus på noggrannhet snarare än möjligheten till drift i realtid. Å andra sidan finns realtidslösningar, men de är främst testade och utvärderade i stadsmiljöer och skogens påverkan på dem är mindre känd. I denna studie övervägdes högkvalitativ, punktbaserad skogsmodellgenerering i realtid genom att tillämpa tekniker från robotteknikområdet. Skogsdata samlades in med ett MLS-system monterat 1) på en pinne som bärs av en person och 2) monterad på en skogsskördare under gallringsoperationer. Systemets bana beräknades med hjälp av lidar-tröghetsbaserade utjämnings- och kartläggningsalgoritmer med realtidsbegränsningar. Dessutom fuserades satellitmätningar antingen in i utjämningsalgoritmen som bidrog till banuppskattningen eller användes för att georeferera banan på ett efterbearbetningssätt. Att samla pålitliga referensbanor är svårt i skogar. Därför innehåller denna studie främst kvalitativ och relativ utvärdering. Resultaten indikerar att bearbetning i realtid och ombord är möjlig för skogsdata med tillräcklig noggrannhet. Toppmodern kant- och planfunktionsbaserad lidarodometri var den mest exakta men kunde inte helt upprätthålla realtidsdrift. Å andra sidan kan normalfördelningstransformationsbaserad odometri upprätthålla snabb och konstant beräkning med något lägre noggrannhet. Att sammansmälta satellitpositioneringen för kartläggningen minskade den interna integriteten hos de rekonstruerade punktmolnmodellerna, och det föreslås att man istället använder den för efterbehandlad georeferens.