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Real-time robot topological localization and mapping with limited visual sampling in simulated buried pipe networks

Authors :
Xiangyu S. Li
T. L. Nguyen
Anthony G. Cohn
Mehmet Dogar
Netta Cohen
Source :
Frontiers in Robotics and AI, Vol 10 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

Introduction: Our work introduces a real-time robotic localization and mapping system for buried pipe networks.Methods: The system integrates non-vision-based exploration and navigation with an active-vision-based localization and topological mapping algorithm. This algorithm is selectively activated at topologically key locations, such as junctions. Non-vision-based sensors are employed to detect junctions, minimizing the use of visual data and limiting the number of images taken within junctions.Results: The primary aim is to provide an accurate and efficient mapping of the pipe network while ensuring real-time performance and reduced computational requirements.Discussion: Simulation results featuring robots with fully autonomous control in a virtual pipe network environment are presented. These simulations effectively demonstrate the feasibility of our approach in principle, offering a practical solution for mapping and localization in buried pipes.

Details

Language :
English
ISSN :
22969144
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Robotics and AI
Publication Type :
Academic Journal
Accession number :
edsdoj.bfd3f5c4a2f84a5882893a23c79b5804
Document Type :
article
Full Text :
https://doi.org/10.3389/frobt.2023.1202568