| Autor: |
Xiangyu S. Li, T. L. Nguyen, Anthony G. Cohn, Mehmet Dogar, Netta Cohen |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Frontiers in Robotics and AI, Vol 10 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2296-9144 |
| DOI: |
10.3389/frobt.2023.1202568 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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