Deep Learning for Visual Navigation of Unmanned Ground Vehicles

被引：0

作者：

Mahony, Niall O' ^{[1
]}

Campbell, Sean ^{[1
]}

Krpalkova, Lenka ^{[1
]}

Riordan, Daniel ^{[1
]}

Walsh, Joseph ^{[1
]}

Murphy, Aidan ^{[2
]}

Ryan, Conor ^{[2
]}

机构：

[1] Inst Technol Tralee, IMaR Technol Gateway, Tralee, Ireland

[2] Univ Limerick, Biocomp & Dev Syst Res Grp, Limerick, Ireland

来源：

2018 29TH IRISH SIGNALS AND SYSTEMS CONFERENCE (ISSC) | 2018年

基金：

爱尔兰科学基金会;

关键词：

Visual Navigation; Autonomous vehicles; Deep Learning;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The capabilities that Artificial Intelligence and Computer Vision can provide to intelligent robotic systems is well recognized and as a result it is the subject of topical research in recent years. This paper will provide a broad review of the progress which has been made in applying deep learning and vision sensor data for the autonomous navigation of unmanned ground vehicles (UGVs). The current state-of-the-art techniques are compared in terms of their performance, implementation and deployment and performance. An outline of some of the most popular types of computer vision techniques is provided, as well as insights into how the recent availability of 3D vision systems can be exploited in the domain.

引用

页数：6

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