Neuromorphic Stereo Vision: A Survey of Bio-Inspired Sensors and Algorithms

Autor(en)
Lea Steffen, Daniel Reichard, Jakob Weinland, Jacques Kaiser, Arne Roennau, Rüdiger Dillmann
Zeitschrift
Frontiers in Neurorobotics
Jahr
2019
Ausgabe
13
Monat
Mai
Abstract
Any visual sensor, whether artificial or biological, maps the 3D-world on a 2D-representation. The missing dimension is depth and most species use stereo vision to recover it. Stereo vision implies multiple perspectives and matching, hence it obtains depth from a pair of images. Algorithms for stereo vision are also used prosperously in robotics. Although, biological systems seem to compute disparities effortless, artificial methods suffer from high energy demands and latency. The crucial part is the correspondence problem; finding the matching points of two images. The development of event-based cameras, inspired by the retina, enables the exploitation of an additional physical constraint – time. Due to their asynchronous course of operation, considering the precise occurrence of spikes, Spiking Neural Networks take advantage of this constraint. In this work, we investigate sensors and algorithms for event-based stereo vision leading to more biologically plausible robots. Hereby, we focus mainly on binocular stereovision.
Link
https://www.frontiersin.org/article/10.3389/fnbot.2019.00028
DOI
10.3389/fnbot.2019.00028
Forschungsfelder
Service-Robotik und mobile Manipulation
Projekt
Human Brain Project, NeuroReact - Echtzeitfähige neuronale Planung für reaktive Industrieroboter
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Eingetragen von
Lea Steffen