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Abstract
Event-driven (ED) cameras are an emerging technology that sample the visual signal based on changes in the signal magnitude, rather than at a fixed-rate over time. The change in paradigm results in a camera with a lower latency, that uses less power, has reduced bandwidth, and higher dynamic range. Such cameras offer many potential advantages for on-line, autonomous, robots; however the sensor data does not directly integrate with current image-based frameworks and software libraries. The iCub robot uses Yet Another Robot Platform (YARP) as middleware to provide modular processing and connectivity to sensors and actuators. This paper introduces a library that incorporates an event-based framework into the YARP architecture, allowing event cameras to be used with the iCub (and other YARP-based) robots. We describe the philosophy and methods for structuring events to facilitate processing, while maintaining low-latency and real-time operation. We also describe several processing modules made available open-source, and three example demonstrations that can be run on the neuromorphic iCub.
Highlights
Conventional vision sensors used in robotics rely on the acquisition of sequences of static images at fixed temporal intervals
This paper introduces the event-driven software libraries and infrastructure that is built upon Yet Another Robot Platform (YARP) and integrates with the iCub robot
On the iCub robot, a Linux driver reads the events from the camera FPGA interface and the zynqGrabber module exposes the data on a YARP port
Summary
Conventional vision sensors used in robotics rely on the acquisition of sequences of static images at fixed temporal intervals Such a sensor provides the most information when the temporal dynamics of the scene match the sample-rate. Modules include pre-processing utilities, visualization, low-level event-driven vision processing algorithms (e.g., corner detection), and robot behavior applications. These modules can be run and used by anyone for purely vision-based tasks, without the need for an iCub robot by using: pre-recorded datasets, a “stand-alone” camera with a compatible FPGA, a “stand-alone” camera with the compatible USB connection, or by contributing a custom camera interface to the open-source library. We begin with a brief description of the current state-ofthe-art in ED vision for robotics
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