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Article

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Title

Optimizing Appearance-Based Localization with Catadioptric Cameras: Small-Footprint Models for Real-Time Inference on Edge Devices

Authors

[ 1 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ D ] phd student | [ P ] employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics, electrical engineering and space technology

Year of publication

2023

Published in

Sensors

Journal year: 2023 | Journal volume: vol. 23 | Journal number: iss. 14

Article type

scientific article

Publication language

english

Keywords
EN
  • omnidirectional vision
  • mobile robot
  • localization
  • deep learning
  • edge computing
Abstract

EN This paper considers the task of appearance-based localization: visual place recognition from omnidirectional images obtained from catadioptric cameras. The focus is on designing an efficient neural network architecture that accurately and reliably recognizes indoor scenes on distorted images from a catadioptric camera, even in self-similar environments with few discernible features. As the target application is the global localization of a low-cost service mobile robot, the proposed solutions are optimized toward being small-footprint models that provide real-time inference on edge devices, such as Nvidia Jetson. We compare several design choices for the neural network-based architecture of the localization system and then demonstrate that the best results are achieved with embeddings (global descriptors) yielded by exploiting transfer learning and fine tuning on a limited number of catadioptric images. We test our solutions on two small-scale datasets collected using different catadioptric cameras in the same office building. Next, we compare the performance of our system to state-of-the-art visual place recognition systems on the publicly available COLD Freiburg and Saarbrücken datasets that contain images collected under different lighting conditions. Our system compares favourably to the competitors both in terms of the accuracy of place recognition and the inference time, providing a cost- and energy-efficient means of appearance-based localization for an indoor service robot.

Date of online publication

18.07.2023

Pages (from - to)

6485-1 - 6485-25

DOI

10.3390/s23146485

URL

https://www.mdpi.com/1424-8220/23/14/6485

Comments

Article number: 6485

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Release date

18.07.2023

Date of Open Access to the publication

at the time of publication

Full text of article

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Access level to full text

public

Ministry points / journal

100

Impact Factor

3,9 [List 2022]

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