Look around you: sequence-based radar place recognition with learned rotational invariance

This paper details an application which yields significant improvements to the adeptness of place recognition with Frequency-Modulated Continuous-Wave scanning, 360-degrees field of view radar - a commercially promising sensor poised for exploitation in mobile autonomy. We show how a rotationally-in...

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Váldodahkkit: Gadd, M, De Martini, D, Newman, P
Materiálatiipa: Conference item
Giella:English
Almmustuhtton: IEEE 2020
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author Gadd, M
De Martini, D
Newman, P
author_facet Gadd, M
De Martini, D
Newman, P
author_sort Gadd, M
collection OXFORD
description This paper details an application which yields significant improvements to the adeptness of place recognition with Frequency-Modulated Continuous-Wave scanning, 360-degrees field of view radar - a commercially promising sensor poised for exploitation in mobile autonomy. We show how a rotationally-invariant metric embedding for radar scans can be integrated into sequence-based trajectory matching systems typically applied to videos taken by visual sensors. Due to the complete horizontal field of view inherent to the radar scan formation process, we show how this off-the-shelf sequence-based trajectory matching system can be manipulated to detect place matches when the vehicle is travelling down a previously visited stretch of road in the opposite direction. We demonstrate the efficacy of the approach on 26 km of challenging urban driving taken from the largest radar-focused urban autonomy dataset released to date - showing a boost of 30 % in recall at high levels of precision over a nearest neighbour approach.
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spelling oxford-uuid:ad72a11f-6fc1-4b51-9245-8f73cd28dd2b2022-03-27T03:35:42ZLook around you: sequence-based radar place recognition with learned rotational invarianceConference itemhttp://purl.org/coar/resource_type/c_5794uuid:ad72a11f-6fc1-4b51-9245-8f73cd28dd2bEnglishSymplectic ElementsIEEE2020Gadd, MDe Martini, DNewman, PThis paper details an application which yields significant improvements to the adeptness of place recognition with Frequency-Modulated Continuous-Wave scanning, 360-degrees field of view radar - a commercially promising sensor poised for exploitation in mobile autonomy. We show how a rotationally-invariant metric embedding for radar scans can be integrated into sequence-based trajectory matching systems typically applied to videos taken by visual sensors. Due to the complete horizontal field of view inherent to the radar scan formation process, we show how this off-the-shelf sequence-based trajectory matching system can be manipulated to detect place matches when the vehicle is travelling down a previously visited stretch of road in the opposite direction. We demonstrate the efficacy of the approach on 26 km of challenging urban driving taken from the largest radar-focused urban autonomy dataset released to date - showing a boost of 30 % in recall at high levels of precision over a nearest neighbour approach.
spellingShingle Gadd, M
De Martini, D
Newman, P
Look around you: sequence-based radar place recognition with learned rotational invariance
title Look around you: sequence-based radar place recognition with learned rotational invariance
title_full Look around you: sequence-based radar place recognition with learned rotational invariance
title_fullStr Look around you: sequence-based radar place recognition with learned rotational invariance
title_full_unstemmed Look around you: sequence-based radar place recognition with learned rotational invariance
title_short Look around you: sequence-based radar place recognition with learned rotational invariance
title_sort look around you sequence based radar place recognition with learned rotational invariance
work_keys_str_mv AT gaddm lookaroundyousequencebasedradarplacerecognitionwithlearnedrotationalinvariance
AT demartinid lookaroundyousequencebasedradarplacerecognitionwithlearnedrotationalinvariance
AT newmanp lookaroundyousequencebasedradarplacerecognitionwithlearnedrotationalinvariance