NDLI: Low-latency heading feedback control with neuromorphic vision sensors using efficient approximated incremental inference

Content Provider	IEEE Xplore Digital Library
Author	Mueller, Erich Censi, Andrea Frazzoli, Emilio
Copyright Year	2015
Description	Author affiliation: Massachusetts Inst. of Tech, United States (Mueller, Erich; Frazzoli, Emilio) \|\| MIT, United States (Censi, Andrea)
Abstract	Asynchronous neuromorphic vision sensors have unique properties that make them ideal for high speed control applications. We consider a one dimensional simplification of a more general six dimensional trajectory tracking problem for mobile platforms, and present a computationally efficient method for feedback control that takes advantage of the asynchronous, event-based nature of these sensors to provide very high bandwidth and low latency feedback. This is an important step toward application of these incredible sensors to mobile robotic systems and useful in its own right. Through experimental tests we compare sensors and show that neuromorphic vision sensors can provide good closed loop performance in terms of computation, data rate, frequency and latency, and tracking error.
Starting Page	992
Ending Page	999
File Size	966167
Page Count	8
File Format	PDF
e-ISBN	9781479978861
DOI	10.1109/CDC.2015.7402002
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-15
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Brightness Neuromorphics Heuristic algorithms Cameras Optical sensors Vehicle dynamics
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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