2,785 research outputs found
Block-Matching Optical Flow for Dynamic Vision Sensor- Algorithm and FPGA Implementation
Rapid and low power computation of optical flow (OF) is potentially useful in
robotics. The dynamic vision sensor (DVS) event camera produces quick and
sparse output, and has high dynamic range, but conventional OF algorithms are
frame-based and cannot be directly used with event-based cameras. Previous DVS
OF methods do not work well with dense textured input and are designed for
implementation in logic circuits. This paper proposes a new block-matching
based DVS OF algorithm which is inspired by motion estimation methods used for
MPEG video compression. The algorithm was implemented both in software and on
FPGA. For each event, it computes the motion direction as one of 9 directions.
The speed of the motion is set by the sample interval. Results show that the
Average Angular Error can be improved by 30\% compared with previous methods.
The OF can be calculated on FPGA with 50\,MHz clock in 0.2\,us per event (11
clock cycles), 20 times faster than a Java software implementation running on a
desktop PC. Sample data is shown that the method works on scenes dominated by
edges, sparse features, and dense texture.Comment: Published in ISCAS 201
Finding the Gap:Neuromorphic Motion Vision in Cluttered Environments
Many animals meander in environments and avoid collisions. How the underlying
neuronal machinery can yield robust behaviour in a variety of environments
remains unclear. In the fly brain, motion-sensitive neurons indicate the
presence of nearby objects and directional cues are integrated within an area
known as the central complex. Such neuronal machinery, in contrast with the
traditional stream-based approach to signal processing, uses an event-based
approach, with events occurring when changes are sensed by the animal. Contrary
to von Neumann computing architectures, event-based neuromorphic hardware is
designed to process information in an asynchronous and distributed manner.
Inspired by the fly brain, we model, for the first time, a neuromorphic
closed-loop system mimicking essential behaviours observed in flying insects,
such as meandering in clutter and gap crossing, which are highly relevant for
autonomous vehicles. We implemented our system both in software and on
neuromorphic hardware. While moving through an environment, our agent perceives
changes in its surroundings and uses this information for collision avoidance.
The agent's manoeuvres result from a closed action-perception loop implementing
probabilistic decision-making processes. This loop-closure is thought to have
driven the development of neural circuitry in biological agents since the
Cambrian explosion. In the fundamental quest to understand neural computation
in artificial agents, we come closer to understanding and modelling biological
intelligence by closing the loop also in neuromorphic systems. As a closed-loop
system, our system deepens our understanding of processing in neural networks
and computations in biological and artificial systems. With these
investigations, we aim to set the foundations for neuromorphic intelligence in
the future, moving towards leveraging the full potential of neuromorphic
systems.Comment: 7 main pages with two figures, including appendix 26 pages with 14
figure
A Mobile Platform for Movement Tracking Based on a Fast-Execution-Time Optical-Flow Algorithm
A multi-purpose mechanical platform to track moving objects in three-dimensional space has been developed. It is composed of one main microcontroller board that processes all system data, two cameras, three motors, and one secondary microcontroller board to position a platform with three degrees of freedom. The system computes the optical flow and moves the cameras accordingly, tracking motion within the visual scene. The platform operates autonomously. To the best of our knowledge, there are no similar systems reported with low-resolution image sensors and low-cost microcontrollers. Existing solutions rely on personal computers and advanced FPGAs to process image data. This article concludes that the optical flow operation is efficient even using an image sensor with very low resolution. Thus, the system complexity and image data processing are alleviated significantly. The platform can be easily adapted to different application scenarios by adding new peripherals, sensors, or image processing algorithms. A detailed description of the system design and experimental results are provided.Junta de Andalucía US-1264940, CEI- 07Ministerio de Economía y Competitividad RTI2018-097088-B-C31Office of Naval Research (ONR) N00014-19-1-215
NASA SBIR abstracts of 1991 phase 1 projects
The objectives of 301 projects placed under contract by the Small Business Innovation Research (SBIR) program of the National Aeronautics and Space Administration (NASA) are described. These projects were selected competitively from among proposals submitted to NASA in response to the 1991 SBIR Program Solicitation. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 301, in order of its appearance in the body of the report. Appendixes to provide additional information about the SBIR program and permit cross-reference of the 1991 Phase 1 projects by company name, location by state, principal investigator, NASA Field Center responsible for management of each project, and NASA contract number are included
NASA SBIR abstracts of 1990 phase 1 projects
The research objectives of the 280 projects placed under contract in the National Aeronautics and Space Administration (NASA) 1990 Small Business Innovation Research (SBIR) Phase 1 program are described. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses in response to NASA's 1990 SBIR Phase 1 Program Solicitation. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 280, in order of its appearance in the body of the report. The document also includes Appendixes to provide additional information about the SBIR program and permit cross-reference in the 1990 Phase 1 projects by company name, location by state, principal investigator, NASA field center responsible for management of each project, and NASA contract number
Small business innovation research. Abstracts of completed 1987 phase 1 projects
Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered
Flight Avionics Hardware Roadmap
As part of NASA's Avionics Steering Committee's stated goal to advance the avionics discipline ahead of program and project needs, the committee initiated a multi-Center technology roadmapping activity to create a comprehensive avionics roadmap. The roadmap is intended to strategically guide avionics technology development to effectively meet future NASA missions needs. The scope of the roadmap aligns with the twelve avionics elements defined in the ASC charter, but is subdivided into the following five areas: Foundational Technology (including devices and components), Command and Data Handling, Spaceflight Instrumentation, Communication and Tracking, and Human Interfaces
NASA Tech Briefs, July 2002
Topics include: a technology focus sensors, software, electronic components and systems, materials, mechanics, machinery/automation, manufacturing, bio-medical, physical sciences, information sciences, book and reports, and a special section of Photonics Tech Briefs
A sub-mW IoT-endnode for always-on visual monitoring and smart triggering
This work presents a fully-programmable Internet of Things (IoT) visual
sensing node that targets sub-mW power consumption in always-on monitoring
scenarios. The system features a spatial-contrast binary
pixel imager with focal-plane processing. The sensor, when working at its
lowest power mode ( at 10 fps), provides as output the number of
changed pixels. Based on this information, a dedicated camera interface,
implemented on a low-power FPGA, wakes up an ultra-low-power parallel
processing unit to extract context-aware visual information. We evaluate the
smart sensor on three always-on visual triggering application scenarios.
Triggering accuracy comparable to RGB image sensors is achieved at nominal
lighting conditions, while consuming an average power between and
, depending on context activity. The digital sub-system is extremely
flexible, thanks to a fully-programmable digital signal processing engine, but
still achieves 19x lower power consumption compared to MCU-based cameras with
significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa
Aerial Vehicles
This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space
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