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Smart motion sensing for autonomous robots


Mandloi, N K; Bartolozzi, C; Indiveri, G (2014). Smart motion sensing for autonomous robots. In: Biomedical Circuits and Systems Conference (BioCAS) 2014, Lausanne, 22 October 2014 - 24 October 2014, 520-523.

Abstract

Small autonomous robots require fast, compact, and low-power sensors for processing visual signals and safely navigating in their environment. We present a custom VLSI vision sensor with these characteristics that provides information on the scene contrast, local motion, and position of salient targets. The Tracker Motion Sensor (TMS) is a mixed signal vision system with focal-plane continuous time processing circuits that computes spatial and temporal derivatives for performing edge detection, and for measuring their velocity and direction. In addition, the TMS contains analog circuits that implement a model of selective attention that reports the position of visual targets in order of decreasing saliency. We describe the main circuit blocks and present measurements from the fabricated chip to show how it is an ideal sensor for robotic applications that must select and track moving targets.

Abstract

Small autonomous robots require fast, compact, and low-power sensors for processing visual signals and safely navigating in their environment. We present a custom VLSI vision sensor with these characteristics that provides information on the scene contrast, local motion, and position of salient targets. The Tracker Motion Sensor (TMS) is a mixed signal vision system with focal-plane continuous time processing circuits that computes spatial and temporal derivatives for performing edge detection, and for measuring their velocity and direction. In addition, the TMS contains analog circuits that implement a model of selective attention that reports the position of visual targets in order of decreasing saliency. We describe the main circuit blocks and present measurements from the fabricated chip to show how it is an ideal sensor for robotic applications that must select and track moving targets.

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Additional indexing

Item Type:Conference or Workshop Item (Speech), refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Event End Date:24 October 2014
Deposited On:25 Feb 2015 10:45
Last Modified:23 Aug 2017 17:10
Publisher:Institute of Electrical and Electronics Engineers
Series Name:Biomedical Circuits and Systems Conference (BioCAS)
Publisher DOI:https://doi.org/10.1109/BioCAS.2014.698177

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