| Issue |
MATEC Web Conf.
Volume 388, 2023
2023 RAPDASA-RobMech-PRASA-AMI Conference Advanced Manufacturing Beyond Borders - The 24th Annual International RAPDASA Conference joined by RobMech, PRASA and AMI, hosted by CSIR and CUT
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|---|---|---|
| Article Number | 04009 | |
| Number of page(s) | 18 | |
| Section | Robotics and Mechatronics | |
| DOI | https://doi.org/10.1051/matecconf/202338804009 | |
| Published online | 15 December 2023 | |
A comparison of visual place recognition methods using a mobile robot in an indoor environment
1 Centre for Robotics and Future Production, Manufacturing Cluster, Council for Scientific and Industrial Research, South Africa
2 School of Computer Science and Applied Mathematics, University of the Witwatersrand, South Africa
* Corresponding author: bveden@csir.co.za
Spatial awareness is an important competence for a mobile robotic system. A robot needs to localise and perform context interpretation to provide any meaningful service. With the deep learning tools and readily available sensors, visual place recognition is a first step towards identifying the environment to bring a robot closer to spatial awareness. In this paper, we implement place recognition on a mobile robot considering a deep learning approach. For simple place classification, where the task involves classifying images into a limited number of categories, all three architectures; VGG16, Inception-v3 and ResNet50, perform well. However, considering the pros and cons, the choice may depend on available computational resources and deployment constraints.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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