Linkless octree using multi-level perfect hashing

The standard C/C++ implementation of a spatial partitioning data structure, such as octree and quadtree, is often inefficient in terms of storage requirements particularly when the memory overhead for maintaining parent-to-child pointers is significant with respect to the amount of actual data in each tree node. In this work, we present a novel data structure that implements uniform spatial partitioning without storing explicit parent-to-child pointer links. Our linkless tree encodes the storage locations of subdivided nodes using perfect hashing while retaining important properties of uniform spatial partitioning trees, such as coarse-to-fine hierarchical representation, efficient storage usage, and efficient random accessibility. We demonstrate the performance of our linkless trees using image compression and path planning examples.postprin

Incremental Construction of Generalized Voronoi Diagrams on Pointerless Quadtrees

In robotics, Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent the spatial topologies of their surrounding area. In this paper we consider the problem of constructing GVDs on discrete environments. Several algorithms that solve this problem exist in the literature, notably the Brushfire algorithm and its improved versions which possess local repair mechanism. However, when the area to be processed is very large or is of high resolution, the size of the metric matrices used by these algorithms to compute GVDs can be prohibitive. To address this issue, we propose an improvement on the current algorithms, using pointerless quadtrees in place of metric matrices to compute and maintain GVDs. Beyond the construction and reconstruction of a GVD, our algorithm further provides a method to approximate roadmaps in multiple granularities from the quadtree based GVD. Simulation tests in representative scenarios demonstrate that, compared with the current algorithms, our algorithm generally makes an order of magnitude improvement regarding memory cost when the area is larger than 210×210. We also demonstrate the usefulness of the approximated roadmaps for coarse-to-fine pathfinding tasks

Hash-based hierarchical caching and layered filtering for interactive previews in global illumination rendering

Copyright © 2020 by the authors. Modern Monte-Carlo-based rendering systems still suffer from the computational complexity involved in the generation of noise-free images, making it challenging to synthesize interactive previews. We present a framework suited for rendering such previews of static scenes using a caching technique that builds upon a linkless octree. Our approach allows for memory-efficient storage and constant-time lookup to cache diffuse illumination at multiple hitpoints along the traced paths. Non-diffuse surfaces are dealt with in a hybrid way in order to reconstruct view-dependent illumination while maintaining interactive frame rates. By evaluating the visual fidelity against ground truth sequences and by benchmarking, we show that our approach compares well to low-noise path-traced results, but with a greatly reduced computational complexity, allowing for interactive frame rates. This way, our caching technique provides a useful tool for global illumination previews and multi-view rendering.German Federal Ministry for Economic Affairs and Energy (BMWi), funding the MoVISO ZIM-project under Grant No.: ZF4120902

Environment Perception for Driver Assistance Systems Using Hierarchical Occupancy Grids

Die Zahl der im Straßenverkehr Verunglückten in Deutschland ist rückläufig. Die Fahrzeughersteller tragen ihren Teil zur Sicherheit im Straßenverkehr bei, indem sie Fahrern immer komplexere Fahrerassistenz- und Sicherheitssysteme anbieten, um sicher und entspannt ans Ziel zu kommen. Für moderne Fahrerassistenzsysteme ist eine zuverlässige und umfassende Umgebungserfassung unerlässlich. Um möglichst viele unterschiedliche Systeme mit einer gemeinsamen Umgebungserfassung bedienen zu können, ist es notwendig, dass diese eine möglichst sensorunabhängige, anwendungsübergreifende, konsistente und umfassende Repräsentation der Umgebung liefert. Belegungskarten ermöglichen die Analyse von Freiraum, die Fahrbahnverlaufsschätzung, die Detektion bewegter Objekte und die Selbstlokalisierung. In dieser Arbeit wird daher eine dreidimensionale Belegungskarte zur Umgebungsmodellierung für Fahrerassistenzsysteme eingesetzt. Um den effizienten Einsatz von dreidimensionalen Karten zu ermöglichen wird ein Verfahren vorgestellt, mit dem sich der Detaillierungsgrad der Umgebungsmodellierung dynamisch und anwendungsgesteuert anpassen lässt. Um die Umgebungserfassung zu vervollständigen wird sowohl die rasterbasierte Selbstlokalisierung in zwei und drei Dimensionen als auch die Detektion und Verfolgung bewegter Objekte behandelt. Als weitere Anwendungen für die vorgeschlagene Umgebungsrepräsentation werden eine Laserscanner-basierte Höhenschätzung für Brücken und eine Parklückendetektion und -vermessung beschrieben und evaluiert.The number of casualties from road traffic is decreasing in Germany. Vehicle manufacturers contribute to safety by providing drivers with more and more complex driver assistance and safety systems, making driving safer and more relaxing. A reliable and comprehensive environment perception is essential for modern driver assistance systems. To support as many different applications as possible with a single environment representation, a sensor-independent and application-independent consistent environment representation must be applied. Occupancy grids enable free space analysis, road course estimation, detection of moving objects and self-localization among other things. Therefore, this thesis uses a three-dimensional occupancy grid to model the environment for driver assistance systems. To allow for an efficient application of three-dimensional occupancy grids, a dynamic method to control the occupancy grid detail level is proposed. The desired resolution is controlled by the applications. To complete the environment perception, a grid-based simultaneous self-localization and mapping approach for two and three dimensions as well as the detection and tracking of moving objects are described and evaluated. In addition, exemplary applications for the proposed environment representation are characterized and analyzed: lidar-based height estimation for bridges and parking spot detection and measuring