Dynamic Analysis and Modeling of DNN-based Visual Servoing Systems

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Abstract

The integration of deep learning and control techniques has created robotic systems capable of implementing visual servoing and navigating autonomously in unknown environments. However, analyzing the effect that timing interactions between controllers and deep neural networks have, has received little attention in the literature. In this paper we describe a novel model that includes the effects that detection loss and inference latency have on the controller of a visual servoing system. To test our model we created a target tracking system consisting of a video camera mounted on a moving platform that tracks objects using deep neural networks.

OriginalsprogEngelsk
TitelIntelligent Computing - Proceedings of the 2022 Computing Conference
RedaktørerKohei Arai
Antal sider13
ForlagSpringer
Publikationsdato11 jul. 2022
Sider855-867
ISBN (Trykt)978-3-031-10463-3
ISBN (Elektronisk)978-3-031-10464-0
DOI
StatusUdgivet - 11 jul. 2022
BegivenhedSAI 2022 -
Varighed: 14 jul. 202215 jul. 2022

Konference

KonferenceSAI 2022
Periode14/07/202215/07/2022
NavnLecture Notes in Networks and Systems
Nummer2
Vol/bind507
ISSN2367-3370

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