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Publicação
Survey of SLAM Algorithms with ROS Support
| Nome: | Descrição: | Tamanho: | Formato: | |
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| 3.15 MB | Adobe PDF |
Orientador(es)
Resumo(s)
Simultaneous Localization and Mapping (SLAM) algorithms are a key component in enabling autonomous navigation for robotic systems. This study presents a comprehensive assessment of state-of-the-art SLAM algorithms, focusing exclusively on those with Robot Operating System (ROS) support. The study aims to provide insights into the computational performance of these algorithms by leveraging the benchmark results reported in their respective studies. Each algorithm's performance metrics, as reported in their benchmark studies, are analyzed and compared. This compara-ive analysis not only highlights the strengths and weaknesses of individual algorithms but also provides a broader understanding of their applicability across diverse robotic platforms and environments. Overall, this study contributes to the advancement of SLAM research by offering a comparative evaluation tailored to ROS-supported algorithms. The findings serve as a valuable resource to make informed decisions regarding the selection and implementation of SLAM solutions in real-world applications.
Descrição
keywords recuperadas da ieee.
Palavras-chave
Surveys Measurement Simultaneous localization and mapping Operating systems Focusing Benchmark testing Autonomous robots SLAM Survey ROS
Contexto Educativo
Citação
A. Teixeira, H. Costelha, L. C. Bento and C. Neves, "Survey of SLAM Algorithms with ROS Support," 2024 7th Iberian Robotics Conference (ROBOT), Madrid, Spain, 2024, pp. 1-7, doi: 10.1109/ROBOT61475.2024.10796865.
Editora
ieee
Licença CC
Sem licença CC