Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Appearance-based SLAM in a network space

Corcoran, Padraig ORCID: https://orcid.org/0000-0001-9731-3385, Steiner, Ted, Bertolotto, Michela and Leonard, John 2015. Appearance-based SLAM in a network space. Presented at: IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 26-30 May 2015. 2015 IEEE International Conference on Robotics and Automation (ICRA). IEEE, pp. 5791-5798. 10.1109/ICRA.2015.7140010

[thumbnail of Corcoran_ICRA_2015.pdf]
Preview
PDF - Accepted Post-Print Version
Download (872kB) | Preview

Abstract

The task of Simultaneous Localization and Mapping (SLAM) is regularly performed in network spaces consisting of a set of corridors connecting locations in the space. Empirical research has demonstrated that such spaces generally exhibit common structural properties relating to aspects such as corridor length. Consequently there exists potential to improve performance through the placement of priors over these properties. In this work we propose an appearance-based SLAM method which explicitly models the space as a network and in turn uses this model as a platform to place priors over its structure. Relative to existing works, which implicitly assume a network space and place priors over its structure, this approach allows a more formal placement of priors. In order to achieve robustness, the proposed method is implemented within a multi-hypothesis tracking framework. Results achieved on two publicly available datasets demonstrate the proposed method outperforms a current state-of-the-art appearance-based SLAM method.

Item Type: Conference or Workshop Item (Paper)
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics
Publisher: IEEE
ISSN: 1050-4729
Date of First Compliant Deposit: 25 April 2016
Last Modified: 01 Nov 2022 09:53
URI: https://orca.cardiff.ac.uk/id/eprint/89574

Citation Data

Cited 1 time in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics