Evaluation of Long-term LiDAR Place Recognition

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

Abstrakti

We compare a state-of-the-art deep image retrieval and a deep place recognition method for place recognition using LiDAR data. Place recognition aims to detect previously visited locations and thus provides an important tool for navigation, mapping, and localisation. Experimental comparisons are conducted using challenging outdoor and indoor datasets, Oxford Radar RobotCar and COLD, in the "long-term" setting where the test conditions differ substantially from the training and gallery data. Based on our results the image retrieval methods using LiDAR depth images can achieve accurate localization (the single best match recall 80%) within 5.00 m in urban outdoors. In office indoors the comparable accuracy is 50 cm but is more sensitive to changes in the environment.
AlkuperäiskieliEnglanti
Otsikko2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
KustantajaIEEE
Sivut4487-4492
Sivumäärä6
ISBN (elektroninen)978-1-6654-1714-3
DOI - pysyväislinkit
TilaJulkaistu - 2021
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE/RSJ International Conference on Intelligent Robots and Systems -
Kesto: 27 syysk. 20211 lokak. 2021

Julkaisusarja

NimiProceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems
ISSN (elektroninen)2153-0866

Conference

ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems
Ajanjakso27/09/211/10/21

Julkaisufoorumi-taso

  • Jufo-taso 1

Sormenjälki

Sukella tutkimusaiheisiin 'Evaluation of Long-term LiDAR Place Recognition'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

Siteeraa tätä