Architectures for embedded multimodal sensor data fusion systems in the robotics : and airport traffic suveillance ; domain

Smaller autonomous robots and embedded sensor data fusion systems often suffer from limited computational and hardware resources. Many ‘Real Time’ algorithms for multi modal sensor data fusion cannot be executed on such systems, at least not in real time and sometimes not at all, because of the computational and energy resources needed, resulting from the architecture of the computational hardware used in these systems. Alternative hardware architectures for generic tracking algorithms could provide a solution to overcome some of these limitations. For tracking and self localization sequential Bayesian filters, in particular particle filters, have been shown to be able to handle a range of tracking problems that could not be solved with other algorithms. But particle filters have some serious disadvantages when executed on serial computational architectures used in most systems. The potential increase in performance for particle filters is huge as many of the computational steps can be done concurrently. A generic hardware solution for particle filters can relieve the central processing unit from the computational load associated with the tracking task. The general topic of this research are hardware-software architectures for multi modal sensor data fusion in embedded systems in particular tracking, with the goal to develop a high performance computational architecture for embedded applications in robotics and airport traffic surveillance domain. The primary concern of the research is therefore: The integration of domain specific concept support into hardware architectures for low level multi modal sensor data fusion, in particular embedded systems for tracking with Bayesian filters; and a distributed hardware-software tracking systems for airport traffic surveillance and control systems. Runway Incursions are occurrences at an aerodrome involving the incorrect presence of an aircraft, vehicle, or person on the protected area of a surface designated for the landing and take-off of aircraft. The growing traffic volume kept runway incursions on the NTSB’s ‘Most Wanted’ list for safety improvements for over a decade. Recent incidents show that problem is still existent. Technological responses that have been deployed in significant numbers are ASDE-X and A-SMGCS. Although these technical responses are a significant improvement and reduce the frequency of runway incursions, some runway incursion scenarios are not optimally covered by these systems, detection of runway incursion events is not as fast as desired, and they are too expensive for all but the biggest airports. Local, short range sensors could be a solution to provide the necessary affordable surveillance accuracy for runway incursion prevention. In this context the following objectives shall be reached. 1) Show the feasibility of runway incursion prevention systems based on localized surveillance. 2) Develop a design for a local runway incursion alerting system. 3) Realize a prototype of the system design using the developed tracking hardware.Kleinere autonome Roboter und eingebettete Sensordatenfusionssysteme haben oft mit stark begrenzter Rechenkapazität und eingeschränkten Hardwareressourcen zu kämpfen. Viele Echtzeitalgorithmen für die Fusion von multimodalen Sensordaten können, bedingt durch den hohen Bedarf an Rechenkapazität und Energie, auf solchen Systemen überhaupt nicht ausgeführt werden, oder zu mindesten nicht in Echtzeit. Der hohe Bedarf an Energie und Rechenkapazität hat seine Ursache darin, dass die Architektur der ausführenden Hardware und der ausgeführte Algorithmus nicht aufeinander abgestimmt sind. Dies betrifft auch Algorithmen zu Spurverfolgung. Mit Hilfe von alternativen Hardwarearchitekturen für die generische Ausführung solcher Algorithmen könnten sich einige der typischerweise vorliegenden Einschränkungen überwinden lassen. Eine Reihe von Aufgaben, die sich mit anderen Spurverfolgungsalgorithmen nicht lösen lassen, lassen sich mit dem Teilchenfilter, einem Algorithmus aus der Familie der Bayesschen Filter lösen. Bei der Ausführung auf traditionellen Architekturen haben Teilchenfilter gegenüber anderen Algorithmen einen signifikanten Nachteil, allerdings ist hier ein großer Leistungszuwachs durch die nebenläufige Ausführung vieler Rechenschritte möglich. Eine generische Hardwarearchitektur für Teilchenfilter könnte deshalb die oben genannten Systeme stark entlasten. Das allgemeine Thema dieses Forschungsvorhabens sind Hardware-Software-Architekturen für die multimodale Sensordatenfusion auf eingebetteten Systemen - speziell für Aufgaben der Spurverfolgung, mit dem Ziel eine leistungsfähige Architektur für die Berechnung entsprechender Algorithmen auf eingebetteten Systemen zu entwickeln, die für Anwendungen in der Robotik und Verkehrsüberwachung auf Flughäfen geeignet ist. Das Augenmerk des Forschungsvorhabens liegt dabei auf der Integration von vom Einsatzgebiet abhängigen Konzepten in die Architektur von Systemen zur Spurverfolgung mit Bayeschen Filtern, sowie auf verteilten Hardware-Software Spurverfolgungssystemen zur Überwachung und Führung des Rollverkehrs auf Flughäfen. Eine „Runway Incursion“ (RI) ist ein Vorfall auf einem Flugplatz, bei dem ein Fahrzeug oder eine Person sich unerlaubt in einem Abschnitt der Start- bzw. Landebahn befindet, der einem Verkehrsteilnehmer zur Benutzung zugewiesen wurde. Der wachsende Flugverkehr hat dafür gesorgt, das RIs seit über einem Jahrzehnt auf der „Most Wanted“-Liste des NTSB für Verbesserungen der Sicherheit stehen. Jüngere Vorfälle zeigen, dass das Problem noch nicht behoben ist. Technologische Maßnahmen die in nennenswerter Zahl eingesetzt wurden sind das ASDE-X und das A-SMGCS. Obwohl diese Maßnahmen eine deutliche Verbesserung darstellen und die Zahl der RIs deutlich reduzieren, gibt es einige RISituationen die von diesen Systemen nicht optimal abgedeckt werden. Außerdem detektieren sie RIs ist nicht so schnell wie erwünscht und sind - außer für die größten Flughäfen - zu teuer. Lokale Sensoren mit kurzer Reichweite könnten eine Lösung sein um die für die zuverlässige Erkennung von RIs notwendige Präzision bei der Überwachung des Rollverkehrs zu erreichen. Vor diesem Hintergrund sollen die folgenden Ziele erreicht werden. 1) Die Machbarkeit eines Runway Incursion Vermeidungssystems, das auf lokalen Sensoren basiert, zeigen. 2) Einen umsetzbaren Entwurf für ein solches System entwickeln. 3) Einen Prototypen des Systems realisieren, das die oben gennannte Hardware zur Spurverfolgung einsetzt

Oceanic and atmospheric forcing of Larsen C Ice-Shelf thinning

The catastrophic collapses of Larsen A and B ice shelves on the eastern Antarctic Peninsula have caused their tributary glaciers to accelerate, contributing to sea-level rise and freshening the Antarctic Bottom Water formed nearby. The surface of Larsen C Ice Shelf (LCIS), the largest ice shelf on the peninsula, is lowering. This could be caused by unbalanced ocean melting (ice loss) or enhanced firn melting and compaction (englacial air loss). Using a novel method to analyse eight radar surveys, this study derives separate estimates of ice and air thickness changes during a 15-year period. The uncertainties are considerable, but the primary estimate is that the surveyed lowering (0.066 ± 0.017 m yr−1) is caused by both ice loss (0.28 ± 0.18 m yr−1) and firn-air loss (0.037 ± 0.026 m yr−1). The ice loss is much larger than the air loss, but both contribute approximately equally to the lowering because the ice is floating. The ice loss could be explained by high basal melting and/or ice divergence, and the air loss by low surface accumulation or high surface melting and/or compaction. The primary estimate therefore requires that at least two forcings caused the surveyed lowering. Mechanisms are discussed by which LCIS stability could be compromised in the future. The most rapid pathways to collapse are offered by the ungrounding of LCIS from Bawden Ice Rise or ice-front retreat past a "compressive arch" in strain rates. Recent evidence suggests that either mechanism could pose an imminent risk

Strategies for efficient foraging in a deep-diving bird; the imperial shag (Phalacrocorax atriceps).

Predators are frequently involved in an arms race with their prey, with improved abilities on one side demanding compensatory improvements on the other. Those that breathe air but forage underwater are faced with the additional challenge of capturing prey in a medium where their own capacity to remain is limited. This thesis examines some of the strategies used by my model organism, the imperial shag (Phalacrocorax atriceps) to enhance its foraging efficiency. I did this by using recent developments in animal-attached technology to measure the patterns and costs of bird behaviour during foraging at a fine-scale. Time appeared to be of the essence for these birds, as their movements were consistent with a strategy to maximise the rate of energy gain. Male and female shags were found to forage at depths where their foraging efficiency was maximised, which manifested itself in the horizontal segregation of male and female foraging areas. Analysis of the mechanical power used underwater suggested that these birds may be limited in the burst speeds they can produce at shallow depths; as the greater the power required to counteract their buoyancy the less is available for prey pursuit. Finally, analysis of the fine-scale tortuosity in the foraging movements of imperial shags revealed that the distribution of their prey was not aggregated at the scales over which they forage. Nevertheless, tortuosity was a good indicator of prey ingestion rates and revealed that shags adjusted their movements to recent prey encounter within both prey-searching and resting phases. This work indicates that imperial shags have an extensive armoury of strategies by which they may increase their efficiency as underwater predators, and methods used and refined in this thesis mean that users are now well-equipped to investigate them

Proceedings of the 3rd International Conference on Models and Technologies for Intelligent Transportation Systems 2013

Challenges arising from an increasing traffic demand, limited resource availability and growing quality expectations of the customers can only be met successfully, if each transport mode is regarded as an intelligent transportation system itself, but also as part of one intelligent transportation system with “intelligent” intramodal and intermodal interfaces. This topic is well reflected in the Third International Conference on “Models and Technologies for Intelligent Transportation Systems” which took place in Dresden 2013 (previous editions: Rome 2009, Leuven 2011). With its variety of traffic management problems that can be solved using similar methods and technologies, but with application specific models, objective functions and constraints the conference stands for an intensive exchange between theory and practice and the presentation of case studies for all transport modes and gives a discussion forum for control engineers, computer scientists, mathematicians and other researchers and practitioners. The present book comprises fifty short papers accepted for presentation at the Third Edition of the conference. All submissions have undergone intensive reviews by the organisers of the special sessions, the members of the scientific and technical advisory committees and further external experts in the field. Like the conference itself the proceedings are structured in twelve streams: the more model-oriented streams of Road-Bound Public Transport Management, Modelling and Control of Urban Traffic Flow, Railway Traffic Management in four different sessions, Air Traffic Management, Water Traffic and Traffic and Transit Assignment, as well as the technology-oriented streams of Floating Car Data, Localisation Technologies for Intelligent Transportation Systems and Image Processing in Transportation. With this broad range of topics this book will be of interest to a number of groups: ITS experts in research and industry, students of transport and control engineering, operations research and computer science. The case studies will also be of interest for transport operators and members of traffic administration

Applications of Internet of Things

This book introduces the Special Issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITSs), (II) location-based services (LBSs), and (III) sensing techniques and applications. Three papers on ITSs are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBSs are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by Gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al

Intelligent Transportation Related Complex Systems and Sensors

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data

Enhancing the mechanical efficiency of skilled rowing through shortened feedback cycles

In elite level rowing competition, the average velocities of medallists differ by less than 1 % over 2000 m. Nations place sporting excellence in high regard and this magnifies the importance of success. As a result, sports science and technology is increasingly used to achieve marginal performance gains. This research considers how to advance biomechanical analysis and skills training provision with a particular focus on the technical and practical delivery of real-time feedback to coaches and athletes, thereby shortening the amount of time between feedback cycles. Underpinning any biomechanical feedback intervention, validated determinants of performance are required. Previous research revealed that, while gross biomechanical measures such as athlete power, stroke rate and stroke length have previously been used as key determinants of performance, elite athletes are nowadays performing within expected ranges and therefore it is no longer possible to easily differentiate crews using these measures alone. This thesis describes workshops held with elite coaches to investigate biomechanical efficiency where the outcomes led to a focus on how a boat accelerates and decelerates during a stroke and hence how the boat's velocity fluctuates. Novel metrics are proposed to quantify aspects of a stroke cycle and used to analyse an elite data set, collected using a standardised protocol. It is shown that individual elite rowers can be successfully differentiated and benchmark values of performance are presented. Consideration of previous research suggests that there is currently no suitably functional and flexible biomechanical real-time feedback system to deliver complex skills training in rowing. Therefore, this thesis describes the research that has led to the development and evaluation of new technology to deliver visual and audible interfaces that support the delivery of concurrent and terminal feedback in water and land-based environments. Coaches and athletes were involved throughout the design process to optimise system suitability and encourage adoption. The technology empowers a coach to intricately manipulate feedback provision, thereby promoting motor control and learning theory best practice. Novel insights relevant to designing interactive systems for use within an elite sporting population are also discussed. This research presents an end-to-end strategy for the applied delivery of real-time feedback to skilled rowers bringing together engineering and social science disciplines. A land-based case series reveals that while statistically significant skill learning was not achieved, participants acquired sport specific technical awareness and heightened motivation as a result of the skills training intervention. Existing motor learning literature was tested as part of the study with a key finding being the lack of support for audible display of stroke acceleration through frequency modulation. Study limitations were identified that explain the lack of an effect of skills training on rower efficiency. The study also acted as a validation of the use of a land-based simulator to monitor and manipulate stroke velocity and a validation of the candidate feedback interfaces that had been implemented. As of result of this work, rowing coaches are able to evaluate their athletes in a novel way, achieving a deeper appreciation of their biomechanical efficiency. Upon identifying athletes with a need for technical development, coaches can intervene with the proposed methodology of skill development making use of the new technologies developed to deliver performance gains. This methodology would achieve enhanced validity through a deeper understanding of the reliability of the new metrics and their relationship to boat speed. Future attempts to test for skill learning should build upon the findings made in this work and, in due course, technology and theory should combine to deliver terminal feedback training during water-based rowing

Arrayed LiDAR signal analysis for automotive applications

Light detection and ranging (LiDAR) is one of the enabling technologies for advanced driver assistance and autonomy. Advances in solid-state photon detector arrays offer the potential of high-performance LiDAR systems but require novel signal processing approaches to fully exploit the dramatic increase in data volume an arrayed detector can provide. This thesis presents two approaches applicable to arrayed solid-state LiDAR. First, a novel block independent sparse depth reconstruction framework is developed, which utilises a random and very sparse illumination scheme to reduce illumination density while improving sampling times, which further remain constant for any array size. Compressive sensing (CS) principles are used to reconstruct depth information from small measurement subsets. The smaller problem size of blocks reduces the reconstruction complexity, improves compressive depth reconstruction performance and enables fast concurrent processing. A feasibility study of a system proposal for this approach demonstrates that the required logic could be practically implemented within detector size constraints. Second, a novel deep learning architecture called LiDARNet is presented to localise surface returns from LiDAR waveforms with high throughput. This single data driven processing approach can unify a wide range of scenarios, making use of a training-by-simulation methodology. This augments real datasets with challenging simulated conditions such as multiple returns and high noise variance, while enabling rapid prototyping of fast data driven processing approaches for arrayed LiDAR systems. Both approaches are fast and practical processing methodologies for arrayed LiDAR systems. These retrieve depth information with excellent depth resolution for wide operating ranges, and are demonstrated on real and simulated data. LiDARNet is a rapid approach to determine surface locations from LiDAR waveforms for efficient point cloud generation, while block sparse depth reconstruction is an efficient method to facilitate high-resolution depth maps at high frame rates with reduced power and memory requirements.Engineering and Physical Sciences Research Council (EPSRC

LIPIcs, Volume 277, GIScience 2023, Complete Volume

LIPIcs, Volume 277, GIScience 2023, Complete Volum

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments