Visual simultaneous localisation and map-building supported by structured landmarks

Author:

Bączyk Robert,Kasiński Andrzej

Abstract

Visual simultaneous localisation and map-building supported by structured landmarksVisual simultaneous localisation and map-building systems which take advantage of some landmarks other than point-wise environment features are not frequently reported. In the following paper the method of using the operational map of robot surrounding, which is complemented with visible structured passive landmarks, is described. These landmarks are used to improve self-localisation accuracy of the robot camera and to reduce the size of the Kalman-filter state-vector with respect to the vector size involving point-wise environment features only. Structured landmarks reduce the drift of the camera pose estimate and improve the reliability of the map which is built on-line. Results of simulation experiments are described, proving advantages of such an approach.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Reference19 articles.

1. Simultaneous localization and mapping (SLAM): Part II;T. Bailey;IEEE Robotics & Automation Magazine,2006

2. Vision-based mobile robot localization with simple artificial landmarks;R. Bączyk,2003

3. Towards simultaneous recognition, localization and mapping for hand-held and wearable cameras;R. Castle,2007a

4. Video-rate recognition and localization for wearable cameras;R. Castle,2007b

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Cyberphysical System Based Mass-Customization Approach with Integration of Industry 4.0 and Smart City;Wireless Communications and Mobile Computing;2017

2. Mobile Robot Applied to QR Landmark Localization Based on the Keystone Effect;Mechatronics and Robotics Engineering for Advanced and Intelligent Manufacturing;2016-08-23

3. Efficient RGB–D data processing for feature–based self–localization of mobile robots;International Journal of Applied Mathematics and Computer Science;2016-03-01

4. A Hybrid Field of View Vision System for Efficient Robot Self-localization with QR Codes;Advances in Intelligent Systems and Computing;2016

5. Incorporating Static Environment Elements into the EKF-Based Visual SLAM;Advances in Intelligent Systems and Computing;2015-09-09

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3