Towards persistent visual navigation using SMART


Autoria(s): Pepperell, Edward; Corke, Peter; Milford, Michael
Data(s)

01/12/2013

Resumo

In this paper, we present SMART (Sequence Matching Across Route Traversals): a vision- based place recognition system that uses whole image matching techniques and odometry information to improve the precision-recall performance, latency and general applicability of the SeqSLAM algorithm. We evaluate the system’s performance on challenging day and night journeys over several kilometres at widely varying vehicle velocities from 0 to 60 km/h, compare performance to the current state-of- the-art SeqSLAM algorithm, and provide parameter studies that evaluate the effectiveness of each system component. Using 30-metre sequences, SMART achieves place recognition performance of 81% recall at 100% precision, outperforming SeqSLAM, and is robust to significant degradations in odometry.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/65528/

Publicador

ARAA

Relação

http://eprints.qut.edu.au/65528/3/65528.pdf

http://www.araa.asn.au/acra/acra2013/papers/pap131s1-file1.pdf

Pepperell, Edward, Corke, Peter, & Milford, Michael (2013) Towards persistent visual navigation using SMART. In Proceedings of Australasian Conference on Robotics and Automation, ARAA, University of New South Wales, Sydney, Australia.

http://purl.org/au-research/grants/ARC/DE120100995

Direitos

Copyright 2013 Please consult the authors

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080104 Computer Vision #Place Recognition #Localisation
Tipo

Conference Paper