Next Article in Journal
Geospatial Cyberinfrastructure and Geoprocessing Web—A Review of Commonalities and Differences of E-Science Approaches
Next Article in Special Issue
An Improved Neural Network Training Algorithm for Wi-Fi Fingerprinting Positioning
Previous Article in Journal
Towards an Authoritative OpenStreetMap: Conflating OSM and OS OpenData National Maps’ Road Network
Previous Article in Special Issue
Indoor Positioning for Smartphones Using Asynchronous Ultrasound Trilateration
ISPRS Int. J. Geo-Inf. 2013, 2(3), 729-748; doi:10.3390/ijgi2030729
Article

HCTNav: A Path Planning Algorithm for Low-Cost Autonomous Robot Navigation in Indoor Environments

,
, * ,
,
 and
Human Computer Technology Laboratory, EPS, Universidad Autónoma de Madrid. Francisco Tomás y Valiente 11, E-28049 Madrid, Spain
* Author to whom correspondence should be addressed.
Received: 25 June 2013 / Revised: 29 July 2013 / Accepted: 31 July 2013 / Published: 9 August 2013
(This article belongs to the Special Issue Indoor Positioning and Indoor Navigation)
View Full-Text   |   Download PDF [1705 KB, 13 August 2013; original version 9 August 2013]   |   Browse Figures

Abstract

Low-cost robots are characterized by low computational resources and limited energy supply. Path planning algorithms aim to find the optimal path between two points so the robot consumes as little energy as possible. However, these algorithms were not developed considering computational limitations (i.e., processing and memory capacity). This paper presents the HCTNav path-planning algorithm (HCTLab research group’s navigation algorithm). This algorithm was designed to be run in low-cost robots for indoor navigation. The results of the comparison between HCTNav and the Dijkstra’s algorithms show that HCTNav’s memory peak is nine times lower than Dijkstra’s in maps with more than 150,000 cells.
Keywords: low-cost indoor navigation; path planning algorithm; autonomous robot low-cost indoor navigation; path planning algorithm; autonomous robot
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Share & Cite This Article

Export to BibTeX |
EndNote


MDPI and ACS Style

Pala, M.; Eraghi, N.O.; López-Colino, F.; Sanchez, A.; de Castro, A.; Garrido, J. HCTNav: A Path Planning Algorithm for Low-Cost Autonomous Robot Navigation in Indoor Environments. ISPRS Int. J. Geo-Inf. 2013, 2, 729-748.

View more citation formats

Supplement

Article Metrics

Comments

Citing Articles

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert