Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.3
3.9
Journals
Sensors
Special Issues
Neuromorphic Computing for Event-Based Sensors and Actuators
sensors-logo
Submit to Sensors Review for Sensors Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Neuromorphic Computing for Event-Based Sensors and Actuators

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 10808

Special Issue Editors

Prof. Dr. Alejandro Linares-Barranco

E-Mail Website
Guest Editor
Robotic and Technology of Computers Lab, University of Seville, 41004 Sevilla, Spain
Interests: neuromorphic engineering; embedded systems; FPGA; VLSI; robotics
Special Issues, Collections and Topics in MDPI journals
Dr. Chiara Bartolozzi

E-Mail Website
Guest Editor
Fondazione Istituto Italiano di Tecnologia, 16163 Genova, Italy
Interests: neuromorphic engineering; event-driven (ED) sensors; robotic sensors
Prof. Dr. Jörg Conradt

E-Mail Website
Guest Editor
KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
Interests: neuro engineering; robotics; cognitive systems; neuromorphic engineering

Special Issue Information

Dear Colleagues,

Neuromorphic computation proposes a paradigm shift from Von Neumann architectures that requires the support of unconventional (neuromorphic) hardware devices. Big companies and university spin-offs are investing in the development of such platforms, with notable examples of Loihi (INTEL), TrueNorth (IBM), SpiNNaker (U. Manchester), Dynap (INI-UZH-ETHZ, AiCTX) and Neurogrid (Stanford U.). On the other hand, Field-Programmable Gate Arrays (FPGA) are easily configurable devices that proved to be useful to develop, test and demonstrate neuromorphic algorithms, especially useful in embedded applications.

All these platforms can deploy algorithms that process the information in a neuro-inspired way, using spikes all the way from sensory encoding (from neuromorphic sensors) up to control of actuators.

This special issue focusses on neuromorphic sensing, processing and control algorithms implemented on neuromorphic platforms and FPGAs, especially dealing with event-by-event information processing that best exploits the advantage of neuromorphic sensing.

We look forward to your participation in this Special Issue.

Prof. Dr. Alejandro Linares-Barranco
Dr. Chiara Bartolozzi
Prof. Dr. Jörg Conradt
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sensory event-based post-processing
  • sensory fusion
  • deep-learing neuromorphic computing
  • optic flow
  • stereo vision
  • actuators and control
  • robotics

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

16 pages, 9559 KiB  
Article
Event-Based Gesture Recognition through a Hierarchy of Time-Surfaces for FPGA
by Ricardo Tapiador-Morales, Jean-Matthieu Maro, Angel Jimenez-Fernandez, Gabriel Jimenez-Moreno, Ryad Benosman and Alejandro Linares-Barranco
Sensors 2020, 20(12), 3404; https://doi.org/10.3390/s20123404 - 16 Jun 2020
Cited by 12 | Viewed by 3470
Abstract
Neuromorphic vision sensors detect changes in luminosity taking inspiration from mammalian retina and providing a stream of events with high temporal resolution, also known as Dynamic Vision Sensors (DVS). This continuous stream of events can be used to extract spatio-temporal patterns from a [...] Read more.
Neuromorphic vision sensors detect changes in luminosity taking inspiration from mammalian retina and providing a stream of events with high temporal resolution, also known as Dynamic Vision Sensors (DVS). This continuous stream of events can be used to extract spatio-temporal patterns from a scene. A time-surface represents a spatio-temporal context for a given spatial radius around an incoming event from a sensor at a specific time history. Time-surfaces can be organized in a hierarchical way to extract features from input events using the Hierarchy Of Time-Surfaces algorithm, hereinafter HOTS. HOTS can be organized in consecutive layers to extract combination of features in a similar way as some deep-learning algorithms do. This work introduces a novel FPGA architecture for accelerating HOTS network. This architecture is mainly based on block-RAM memory and the non-restoring square root algorithm, requiring basic components and enabling it for low-power low-latency embedded applications. The presented architecture has been tested on a Zynq 7100 platform at 100 MHz. The results show that the latencies are in the range of 1 μ s to 6.7 μ s, requiring a maximum dynamic power consumption of 77 mW. This system was tested with a gesture recognition dataset, obtaining an accuracy loss for 16-bit precision of only 1.2% with respect to the original software HOTS. Full article
(This article belongs to the Special Issue Neuromorphic Computing for Event-Based Sensors and Actuators)
►▼ Show Figures

Figure 1

33 pages, 1218 KiB  
Article
Design and Realization of an Efficient Large-Area Event-Driven E-Skin
by Florian Bergner, Emmanuel Dean-Leon and Gordon Cheng
Sensors 2020, 20(7), 1965; https://doi.org/10.3390/s20071965 - 31 Mar 2020
Cited by 14 | Viewed by 6660
Abstract
The sense of touch enables us to safely interact and control our contacts with our surroundings. Many technical systems and applications could profit from a similar type of sense. Yet, despite the emergence of e-skin systems covering more extensive areas, large-area realizations of [...] Read more.
The sense of touch enables us to safely interact and control our contacts with our surroundings. Many technical systems and applications could profit from a similar type of sense. Yet, despite the emergence of e-skin systems covering more extensive areas, large-area realizations of e-skin effectively boosting applications are still rare. Recent advancements have improved the deployability and robustness of e-skin systems laying the basis for their scalability. However, the upscaling of e-skin systems introduces yet another challenge—the challenge of handling a large amount of heterogeneous tactile information with complex spatial relations between sensing points. We targeted this challenge and proposed an event-driven approach for large-area skin systems. While our previous works focused on the implementation and the experimental validation of the approach, this work now provides the consolidated foundations for realizing, designing, and understanding large-area event-driven e-skin systems for effective applications. This work homogenizes the different perspectives on event-driven systems and assesses the applicability of existing event-driven implementations in large-area skin systems. Additionally, we provide novel guidelines for tuning the novelty-threshold of event generators. Overall, this work develops a systematic approach towards realizing a flexible event-driven information handling system on standard computer systems for large-scale e-skin with detailed descriptions on the effective design of event generators and decoders. All designs and guidelines are validated by outlining their impacts on our implementations, and by consolidating various experimental results. The resulting system design for e-skin systems is scalable, efficient, flexible, and capable of handling large amounts of information without customized hardware. The system provides the feasibility of complex large-area tactile applications, for instance in robotics. Full article
(This article belongs to the Special Issue Neuromorphic Computing for Event-Based Sensors and Actuators)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop