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

Topological path planning in GPS trajectory data

Corcoran, Padraig ORCID: https://orcid.org/0000-0001-9731-3385 2016. Topological path planning in GPS trajectory data. Sensors 16 (12) , 2203. 10.3390/s16122203

[thumbnail of sensors-16-02203 (1).pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution.

Download (5MB) | Preview

Abstract

This paper proposes a novel solution to the problem of computing a set of topologically inequivalent paths between two points in a space given a set of samples drawn from that space. Specifically, these paths are homotopy inequivalent where homotopy is a topological equivalence relation. This is achieved by computing a basis for the group of homology inequivalent loops in the space. An additional distinct element is then computed where this element corresponds to a loop which passes through the points in question. The set of paths is subsequently obtained by taking the orbit of this element acted on by the group of homology inequivalent loops. Using a number of spaces, including a street network where the samples are GPS trajectories, the proposed method is demonstrated to accurately compute a set of homotopy inequivalent paths. The applications of this method include path and coverage planning.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Additional Information: This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Publisher: MDPI
ISSN: 1424-8220
Date of First Compliant Deposit: 23 December 2016
Date of Acceptance: 16 December 2016
Last Modified: 05 May 2023 03:31
URI: https://orca.cardiff.ac.uk/id/eprint/97036

Citation Data

Cited 2 times 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