HCTNav: A path planning algorithm for low-cost autonomous robot navigation in indoor environments
Entity
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesPublisher
MDPIDate
2013-08-09Citation
10.3390/ijgi2030729
ISPRS International Journal of Geo-Information 2.3 (2013): 729-748
ISSN
2220-9964DOI
10.3390/ijgi2030729Funded by
This work has been partially supported by the Spanish “Ministerio de Ciencia e Innovación”, under project TEC2009-09871.Editor's Version
http://dx.doi.org/10.3390/ijgi2030729Subjects
Low-cost indoor navigation; Path planning algorithm; Autonomous robot; TelecomunicacionesNote
© 2013 by MDPI (http://www.mdpi.org). Reproduction is permitted for noncommercial purposes.Rights
© 2013 MDPIAbstract
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.
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Google Scholar:Pala, Marco
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Osati Eraghi, Nafiseh
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López Colino, Fernando Jesús
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Sánchez González, Alberto
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Castro, Ángel de
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Garrido Salas, Javier
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