3D LiDAR Point Cloud Processing Algorithms

In the race for autonomous vehicles and advanced driver assistance systems (ADAS), the automotive industry has energetically pursued research in the area of sensor suites to achieve such technological feats. Commonly used autonomous and ADAS sensor suites include multiples of cameras, radio detection and ranging (RADAR), light detection and ranging (LiDAR), and ultrasonic sensors. Great interest has been generated in the use of LiDAR sensors and the value added in an automotive application. LiDAR sensors can be used to detect and track vehicles, pedestrians, cyclists, and surrounding objects. A LiDAR sensor operates by emitting light amplification by stimulated emission of radiation (LASER) beams and receiving the reflected LASER beam to acquire relevant distance information. LiDAR reflections are organized in a three-dimensional environment known as a point cloud. A major challenge in modern autonomous automotive research is to be able to process the dimensional environmental data in real time. The LiDAR sensor used in this research is the Velodyne HDL 32E, which provides nearly 700,000 data points per second. The large amount of data produced by a LiDAR sensor must be processed in a highly efficient way to be effective. This thesis provides an algorithm to process the LiDAR data from the sensors user datagram protocol (UDP) packet to output geometric shapes that can be further analyzed in a sensor suite or utilized for Bayesian tracking of objects. The algorithm can be divided into three stages: Stage One - UDP packet extraction; Stage Two - data clustering; and Stage Three - shape extraction. Stage One organizes the LiDAR data from a negative to a positive vertical angle during packet extraction so that subsequent steps can fully exploit the programming efficiencies. Stage Two utilizes an adaptive breakpoint detector (ABD) for clustering objects based on a Euclidean distance threshold in the point cloud. Stage Three classifies each cluster into a shape that is either a point, line, L-shape, or a polygon using principal component analysis and shape fitting algorithms that have been modified to take advantage of the pre-organized data from Stage One. The proposed algorithm was written in the C language and the runtime was tested on a two Windows equipped machines where the algorithm completed the processing, on average, sparing 30% of the time between UDP data packets sent from the HDL32E. In comparison to related research, this algorithm performed over seven hundred and thirty-seven times faster

Combining Occupancy Grids with a Polygonal Obstacle World Model for Autonomous Flights

This chapter presents a mapping process that can be applied to autonomous systems for obstacle avoidance and trajectory planning. It is an improvement over commonly applied obstacle mapping techniques, such as occupancy grids. Problems encountered in large outdoor scenarios are tackled and a compressed map that can be sent on low-bandwidth networks is produced. The approach is real-time capable and works in full 3-D environments. The efficiency of the proposed approach is demonstrated under real operational conditions on an unmanned aerial vehicle using stereo vision for distance measurement

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

ARTIST-DRIVEN FRACTURING OF POLYHEDRAL SURFACE MESHES

This paper presents a robust and artist driven method for fracturing a surface polyhedral mesh via fracture maps. A fracture map is an undirected simple graph with nodes representing positions in UV-space and fracture lines along the surface of a mesh. Fracture maps allow artists to concisely and rapidly define, edit, and apply fracture patterns onto the surface of their mesh. The method projects a fracture map onto a polyhedral surface and splits its triangles accordingly. The polyhedral mesh is then segmented based on fracture lines to produce a set of independent surfaces called fracture components, containing the visible surface of each fractured mesh fragment. Subsequently, we utilize a Voronoi-based approximation of the input polyhedral mesh’s medial axis to derive a hidden surface for each fragment. The result is a new watertight polyhedral mesh representing the full fracture component. Results are aquired after a delay sufficiently brief for interactive design. As the size of the input mesh increases, the computation time has shown to grow linearly. A large mesh of 41,000 triangles requires approximately 3.4 seconds to perform a complete fracture of a complex pattern. For a wide variety of practices, the resulting fractures allows users to provide realistic feedback upon the application of extraneous forces

Sensor Signal and Information Processing II

In the current age of information explosion, newly invented technological sensors and software are now tightly integrated with our everyday lives. Many sensor processing algorithms have incorporated some forms of computational intelligence as part of their core framework in problem solving. These algorithms have the capacity to generalize and discover knowledge for themselves and learn new information whenever unseen data are captured. The primary aim of sensor processing is to develop techniques to interpret, understand, and act on information contained in the data. The interest of this book is in developing intelligent signal processing in order to pave the way for smart sensors. This involves mathematical advancement of nonlinear signal processing theory and its applications that extend far beyond traditional techniques. It bridges the boundary between theory and application, developing novel theoretically inspired methodologies targeting both longstanding and emergent signal processing applications. The topic ranges from phishing detection to integration of terrestrial laser scanning, and from fault diagnosis to bio-inspiring filtering. The book will appeal to established practitioners, along with researchers and students in the emerging field of smart sensors processing

Energy Consumption Improvement Through a Visualization Software

In the actual world frame, energy efficiency becomes a necessity. Since 1995, Kyoto protocol has highlighted that humans need to improve their energy consumption and reduce CO2 signature. Building consumption represent a third of the global energy consumption and Information Technology (IT) equipment is weighing heavily on energy expenses. For example

AGATA, Technical Proposal for an Advanced Gamma Tracking Array for the European Gamma Spectroscopy Community

International audienceAn Advanced GAmma-ray Tracking Array, AGATA, is proposed for high-resolution γ-ray spectroscopy with exotic beams. AGATA will employ highly segmented Ge detectors as well as fully digital electronics and relies on newly developed pulse-shape analysis and tracking methods. The array is being designed in a way that it provides optimal properties for nuclear structure experiments in a wide range of beam velocities (from stopped to v/c ≈ 50%), almost independent of beam quality and background conditions. Selectivity and sensitivity of AGATA will be superior to any existing γ-array by several orders of magnitude. Hence, it will be for a long time a rich source for nuclear structure physics providing the means for new discoveries and opening challenging new perspectives. This document is the initial proposal sent to the European Commission to obtain the necessary funds for the project

Interactive volume ray tracing

Die Visualisierung von volumetrischen Daten ist eine der interessantesten, aber sicherlich auch schwierigsten Anwendungsgebiete innerhalb der wissenschaftlichen Visualisierung. Im Gegensatz zu Oberflächenmodellen, repräsentieren solche Daten ein semi-transparentes Medium in einem 3D-Feld. Anwendungen reichen von medizinischen Untersuchungen, Simulation physikalischer Prozesse bis hin zur visuellen Kunst. Viele dieser Anwendungen verlangen Interaktivität hinsichtlich Darstellungs- und Visualisierungsparameter. Der Ray-Tracing- (Stahlverfolgungs-) Algorithmus wurde dabei, obwohl er inhärent die Interaktion mit einem solchen Medium simulieren kann, immer als zu langsam angesehen. Die meisten Forscher konzentrierten sich vielmehr auf Rasterisierungsansätze, da diese besser für Grafikkarten geeignet sind. Dabei leiden diese Ansätze entweder unter einer ungenügenden Qualität respektive Flexibilität. Die andere Alternative besteht darin, den Ray-Tracing-Algorithmus so zu beschleunigen, dass er sinnvoll für Visualisierungsanwendungen benutzt werden kann. Seit der Verfügbarkeit moderner Grafikkarten hat die Forschung auf diesem Gebiet nachgelassen, obwohl selbst moderne GPUs immer noch Limitierungen, wie beispielsweise der begrenzte Grafikkartenspeicher oder das umständliche Programmiermodell, enthalten. Die beiden in dieser Arbeit vorgestellten Methoden sind deshalb vollständig softwarebasiert, da es sinnvoller erscheint, möglichst viele Optimierungen in Software zu realisieren, bevor eine Portierung auf Hardware erfolgt. Die erste Methode wird impliziter Kd-Baum genannt, eine hierarchische und räumliche Beschleunigungstruktur, die ursprünglich für die Generierung von Isoflächen reguläre Gitterdatensätze entwickelt wurde. In der Zwischenzeit unterstützt sie auch die semi-transparente Darstellung, die Darstellung von zeitabhängigen Datensätzen und wurde erfolgreich für andere Anwendungen eingesetzt. Der zweite Algorithmus benutzt so genannte Plücker-Koordinaten, welche die Implementierung eines schnellen inkrementellen Traversierers für Datensätze erlauben, deren Primitive Tetraeder beziehungsweise Hexaeder sind. Beide Algorithmen wurden wesentlich optimiert, um eine interaktive Bildgenerierung volumetrischer Daten zu ermöglichen und stellen deshalb einen wichtigen Beitrag hin zu einem flexiblen und interaktiven Volumen-Ray-Tracing-System dar.Volume rendering is one of the most demanding and interesting topics among scientific visualization. Applications include medical examinations, simulation of physical processes, and visual art. Most of these applications demand interactivity with respect to the viewing and visualization parameters. The ray tracing algorithm, although inherently simulating light interaction with participating media, was always considered too slow. Instead, most researchers followed object-order algorithms better suited for graphics adapters, although such approaches often suffer either from low quality or lack of flexibility. Another alternative is to speed up the ray tracing algorithm to make it competitive for volumetric visualization tasks. Since the advent of modern graphic adapters, research in this area had somehow ceased, although some limitations of GPUs, e.g. limited graphics board memory and tedious programming model, are still a problem. The two methods discussed in this thesis are therefore purely software-based since it is believed that software implementations allow for a far better optimization process before porting algorithms to hardware. The first method is called implicit kd-tree, which is a hierarchical spatial acceleration structure originally developed for iso-surface rendering of regular data sets that now supports semi-transparent rendering, time-dependent data visualization, and is even used in non volume-rendering applications. The second algorithm uses so-called Plücker coordinates, providing a fast incremental traversal for data sets consisting of tetrahedral or hexahedral primitives. Both algorithms are highly optimized to support interactive rendering of volumetric data sets and are therefore major contributions towards a flexible and interactive volume ray tracing framework