Real-Time Map Generation by VLP-16 LiDAR sensor in GPS denied environment
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| Autores principales: | , |
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| Formato: | Recurso digital |
| Lenguaje: | inglés |
| Publicado: |
Zenodo
2025
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| _version_ | 1866901856886718464 |
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| author | Kumar, Ajay Kim, See Jo |
| author_facet | Kumar, Ajay Kim, See Jo |
| contents | <p>Navigation and orientation are severely relatable by 3D mapping in GPS-denied situations, especially for real-time applications. The usefulness of a 3D LiDAR, VLP 16 sensor for producing precise, high-resolution maps in an environment is confirmed by this paper investigation. To guarantee adaptability in dynamic and unstructured environments, the recommended strategy incorporates modern SLAM techniques. To verify LiDAR-generated maps for alignment accurateness and real-time performance, they are compared to google image data. According to experimental results, the system can create accurate 3D maps when GPS is unavailable, highlighting its potential for autonomous navigation, search and rescue missions, and urban exploration. The methodology improves the development of dependable autonomous systems in difficult environments by offering a framework for evaluating LiDAR-based mapping systems using defined references. The paper focuses on modifying and utilizing a real-time 3D mapping technique i.e. hdl graph slam that was created using python and C++. The setup of the algorithm and its application to SLAM assessment are described in this paper. The arrangement was implemented utilizing a 16 Channel LiDAR sensor on a mobile robot i.e. the Henes T780. When compared to google image, it is demonstrated that the HDL (high definition LiDAR) graph slam software methods and hardware combination produce accurate and good mapping results. </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16945768 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Real-Time Map Generation by VLP-16 LiDAR sensor in GPS denied environment Kumar, Ajay Kim, See Jo SLAM 3D LiDAR GPS-denied environment ROS Henes T780 robot <p>Navigation and orientation are severely relatable by 3D mapping in GPS-denied situations, especially for real-time applications. The usefulness of a 3D LiDAR, VLP 16 sensor for producing precise, high-resolution maps in an environment is confirmed by this paper investigation. To guarantee adaptability in dynamic and unstructured environments, the recommended strategy incorporates modern SLAM techniques. To verify LiDAR-generated maps for alignment accurateness and real-time performance, they are compared to google image data. According to experimental results, the system can create accurate 3D maps when GPS is unavailable, highlighting its potential for autonomous navigation, search and rescue missions, and urban exploration. The methodology improves the development of dependable autonomous systems in difficult environments by offering a framework for evaluating LiDAR-based mapping systems using defined references. The paper focuses on modifying and utilizing a real-time 3D mapping technique i.e. hdl graph slam that was created using python and C++. The setup of the algorithm and its application to SLAM assessment are described in this paper. The arrangement was implemented utilizing a 16 Channel LiDAR sensor on a mobile robot i.e. the Henes T780. When compared to google image, it is demonstrated that the HDL (high definition LiDAR) graph slam software methods and hardware combination produce accurate and good mapping results. </p> |
| title | Real-Time Map Generation by VLP-16 LiDAR sensor in GPS denied environment |
| topic | SLAM 3D LiDAR GPS-denied environment ROS Henes T780 robot |
| url | https://doi.org/10.5281/zenodo.16945768 |