1,137 research outputs found
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 âReal Timeâ 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 NTSBâs âMost Wantedâ 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 RechenkapazitÀt und eingeschrÀnkten Hardwareressourcen zu kÀmpfen. Viele
Echtzeitalgorithmen fĂŒr die Fusion von multimodalen Sensordaten können, bedingt durch den hohen
Bedarf an RechenkapazitĂ€t und Energie, auf solchen Systemen ĂŒberhaupt nicht ausgefĂŒhrt werden,
oder zu mindesten nicht in Echtzeit. Der hohe Bedarf an Energie und RechenkapazitÀt hat seine
Ursache darin, dass die Architektur der ausfĂŒhrenden Hardware und der ausgefĂŒhrte Algorithmus
nicht aufeinander abgestimmt sind. Dies betrifft auch Algorithmen zu Spurverfolgung. Mit Hilfe von
alternativen Hardwarearchitekturen fĂŒr die generische AusfĂŒhrung solcher Algorithmen könnten sich
einige der typischerweise vorliegenden EinschrĂ€nkungen ĂŒberwinden 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 AusfĂŒhrung auf traditionellen
Architekturen haben Teilchenfilter gegenĂŒber anderen Algorithmen einen signifikanten Nachteil,
allerdings ist hier ein groĂer Leistungszuwachs durch die nebenlĂ€ufige AusfĂŒhrung vieler
Rechenschritte möglich. Eine generische Hardwarearchitektur fĂŒr Teilchenfilter könnte deshalb die
oben genannten Systeme stark entlasten.
Das allgemeine Thema dieses Forschungsvorhabens sind Hardware-Software-Architekturen fĂŒr die
multimodale Sensordatenfusion auf eingebetteten Systemen - speziell fĂŒr Aufgaben der
Spurverfolgung, mit dem Ziel eine leistungsfĂ€hige Architektur fĂŒr die Berechnung entsprechender
Algorithmen auf eingebetteten Systemen zu entwickeln, die fĂŒr Anwendungen in der Robotik und
VerkehrsĂŒberwachung auf FlughĂ€fen geeignet ist. Das Augenmerk des Forschungsvorhabens liegt
dabei auf der Integration von vom Einsatzgebiet abhÀngigen Konzepten in die Architektur von
Systemen zur Spurverfolgung mit Bayeschen Filtern, sowie auf verteilten Hardware-Software
Spurverfolgungssystemen zur Ăberwachung und FĂŒhrung des Rollverkehrs auf FlughĂ€fen.
Eine âRunway Incursionâ (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 dafĂŒr gesorgt, das RIs seit ĂŒber
einem Jahrzehnt auf der âMost Wantedâ-Liste des NTSB fĂŒr Verbesserungen der Sicherheit stehen.
JĂŒngere VorfĂ€lle zeigen, dass das Problem noch nicht behoben ist. Technologische MaĂnahmen die in
nennenswerter Zahl eingesetzt wurden sind das ASDE-X und das A-SMGCS. Obwohl diese MaĂnahmen
eine deutliche Verbesserung darstellen und die Zahl der RIs deutlich reduzieren, gibt es einige RISituationen
die von diesen Systemen nicht optimal abgedeckt werden. AuĂerdem detektieren sie RIs
ist nicht so schnell wie erwĂŒnscht und sind - auĂer fĂŒr die gröĂten FlughĂ€fen - zu teuer. Lokale Sensoren
mit kurzer Reichweite könnten eine Lösung sein um die fĂŒr die zuverlĂ€ssige Erkennung von RIs
notwendige PrĂ€zision bei der Ăberwachung 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 fĂŒr ein
solches System entwickeln. 3) Einen Prototypen des Systems realisieren, das die oben gennannte
Hardware zur Spurverfolgung einsetzt
A reference control architecture for service robots implemented on a climbing vehicle
Teleoperated robots are used to perform hazardous tasks
that human operators cannot carry out. The purpose of this paper is
to present a new architecture (ACROSET) for the development of these
systems that takes into account the current advances in robotic architectures
while adopting the component-oriented approach. The architecture
is currently being used, tested and improved in the development of an
heterogeneous family of robots in the context of the EFTCoR project. It
is also presented the Adaâ95 implementation of ACROSET for a climbing
robot.This work has been partially supported by European Union (GROWTH G3RD-CT-
00794) and the Spanish Government programs CICYT (TIC2003-07804-C05-02) and
Seneca (PB/5/FS/02)
A Survey of Spiking Neural Network Accelerator on FPGA
Due to the ability to implement customized topology, FPGA is increasingly
used to deploy SNNs in both embedded and high-performance applications. In this
paper, we survey state-of-the-art SNN implementations and their applications on
FPGA. We collect the recent widely-used spiking neuron models, network
structures, and signal encoding formats, followed by the enumeration of related
hardware design schemes for FPGA-based SNN implementations. Compared with the
previous surveys, this manuscript enumerates the application instances that
applied the above-mentioned technical schemes in recent research. Based on
that, we discuss the actual acceleration potential of implementing SNN on FPGA.
According to our above discussion, the upcoming trends are discussed in this
paper and give a guideline for further advancement in related subjects
Embedding runtime verification post-deployment for real-time health management of safety-critical systems
As cyber-physical systems increase in both complexity and criticality, formal methods have gained traction for design-time verification of safety properties.
A lightweight formal method, runtime verification (RV), embeds checks necessary for safety-critical system health management; however, these techniques have been slow to appear in practice despite repeated calls by both industry and academia to leverage them.
Additionally, the state-of-the-art in RV lacks a best practice approach when a deployed system requires increased flexibility due to a change in mission, or in response to an emergent condition not accounted for at design time.
Human-robot interaction necessitates stringent safety guarantees to protect humans sharing the workspace, particularly in hazardous environments.
For example, Robonaut2 (R2) developed an emergent fault while deployed to the International Space Station.
Possibly-inaccurate actuator readings trigger the R2 safety system, preventing further motion of a joint until a ground-control operator determines the root-cause and initiates proper corrective action.
Operator time is scarce and expensive; when waiting, R2 is an obstacle instead of an asset.
We adapt the Realizable, Responsive, Unobtrusive Unit (R2U2) RV framework for resource-constrained environments.
We retrofit the R2 motor controller, embedding R2U2 within the remaining resources of the Field-Programmable Gate Array (FPGA) controlling the joint actuator.
We add online, stream-based, real-time system health monitoring in a provably unobtrusive way that does not interfere with the control of the joint.
We design and embed formal temporal logic specifications that disambiguate the emergent faults and enable automated corrective actions.
We overview the challenges and techniques for formally specifying behaviors of an existing command and data bus.
We present our specification debugging, validation, and refinement steps.
We demonstrate success in the Robonaut2 case study, then detail effective techniques and lessons learned from adding RV with real-time fault disambiguation under the constraints of a deployed system
On microelectronic self-learning cognitive chip systems
After a brief review of machine learning techniques and applications, this Ph.D. thesis examines several approaches for implementing machine learning architectures and algorithms into hardware within our laboratory.
From this interdisciplinary background support, we have motivations for novel approaches that we intend to follow as an objective of innovative hardware implementations of dynamically self-reconfigurable logic for enhanced self-adaptive, self-(re)organizing and eventually self-assembling machine learning systems, while developing this new particular area of research.
And after reviewing some relevant background of robotic control methods followed by most recent advanced cognitive controllers, this Ph.D. thesis suggests that amongst many well-known ways of designing operational technologies, the design methodologies of those leading-edge high-tech devices such as cognitive chips that may well lead to intelligent machines exhibiting
conscious phenomena should crucially be restricted to extremely well defined constraints.
Roboticists also need those as specifications to help decide upfront on otherwise infinitely free hardware/software design details.
In addition and most importantly, we propose these specifications as methodological guidelines tightly related to ethics and the nowadays well-identified workings of the human body and of its psyche
- âŠ