Coder Social home page Coder Social logo

event-driven's Introduction

| Read the Documentation | Download the Code |

event-driven

YARP integration for event-cameras and other neuromorphic sensors

rvtfmc.mp4

Libraries that handle neuromorphic sensors, such as the dynamic vision sensor, installed on the iCub can be found here, along with algorithms to process the event-based data. Examples include, optical flow, corner detection and ball detection. Demo applications for the iCub robot, and tutorials for running them, include saccading and attention, gaze following a ball, and vergence control.

@article{Glover2017b,
author = {Glover, Arren and Vasco, Valentina and Iacono, Massimiliano and Bartolozzi, Chiara},
doi = {10.3389/frobt.2017.00073},
journal = {Frontiers in Robotics and AI},
pages = {73},
title = {{The event-driven Software Library for YARP โ€” With Algorithms and iCub Applications}},
volume = {4},
year = {2018}
}

Libraries

Event-driven libraries provide basic functionality for handling events in a YARP environment. The library has definitions for:

  • core
    • codecs to encode/decode events to be compatable with address event representation (AER) formats.
    • Sending packets of events in ev::packet that is compatible with yarpdatadumper and yarpdataplayer.
    • asynchronous reading and writing ports that ensure data is never lost and giving access to latency information.
    • helper functions to handle event timestamp wrapping and to convert between timestamps and seconds.
  • vision
    • filters for removing salt and pepper noise.
    • sparse event warping using camera intrinsic parameters and extrinsic parameters for a stereo-pair
    • methods to draw events onto the screen in a variety of methods
  • algorithms
    • event surfaces such as the Surface of Active Events (SAE), Polarity Integrated Images (PIM), and Exponentially Reduced Ordinal Surface (EROS)
    • corner detection
    • optical flow

TOOLS

  • vFramer - visualisation of events streamed over a YARP port. Various methods for visualisation are available.
  • calibration - estimating the camera intrinsic parameters
  • vPreProcess - splitting different event-types into separate event-streams, performing filtering, and simple augmentations (flipping etc.)
  • atis-bridge - bridge between the Prophesee ATIS cameras and YARP
  • zynqGrabber - bridge between zynq-based FPGA sensor interface and YARP

Applications

Applications that implement the algorithms available in event-driven are found in our companion repository

event-driven-demos

How to Install:

Comprehensive instructions available for installation.

References

Glover, A., and Bartolozzi C. (2016) Event-driven ball detection and gaze fixation in clutter. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2016, Daejeon, Korea. Finalist for RoboCup Best Paper Award

Vasco V., Glover A., and Bartolozzi C. (2016) Fast event-based harris corner detection exploiting the advantages of event-driven cameras. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2016, Daejeon, Korea.

V. Vasco, A. Glover, Y. Tirupachuri, F. Solari, M. Chessa, and Bartolozzi C. Vergence control with a neuromorphic iCub. In IEEE-RAS International Conference on Humanoid Robots (Humanoids), November 2016, Mexico.

event-driven's People

Contributors

reafrancesco avatar arrenglover avatar chiarabartolozzi avatar randaz81 avatar iaxama avatar ale-git avatar pattacini avatar simbamford avatar lsrosa avatar ghoshsuman avatar aikolina avatar marco-monforte avatar giuliadangelo avatar drdanz avatar lunagava avatar traversaro avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.