Real-Time Localization Framework for Autonomous Basketball Robots
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866917199728345088 |
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| author | Medarametla, Naren Mondal, Sreejon |
| author_facet | Medarametla, Naren Mondal, Sreejon |
| contents | Localization is a fundamental capability for autonomous robots, enabling them to operate effectively in dynamic environments. In Robocon 2025, accurate and reliable localization is crucial for improving shooting precision, avoiding collisions with other robots, and navigating the competition field efficiently. In this paper, we propose a hybrid localization algorithm that integrates classical techniques with learning based methods that rely solely on visual data from the court's floor to achieve self-localization on the basketball field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_08713 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Real-Time Localization Framework for Autonomous Basketball Robots Medarametla, Naren Mondal, Sreejon Robotics Artificial Intelligence Computer Vision and Pattern Recognition I.2.9; I.2.10 Localization is a fundamental capability for autonomous robots, enabling them to operate effectively in dynamic environments. In Robocon 2025, accurate and reliable localization is crucial for improving shooting precision, avoiding collisions with other robots, and navigating the competition field efficiently. In this paper, we propose a hybrid localization algorithm that integrates classical techniques with learning based methods that rely solely on visual data from the court's floor to achieve self-localization on the basketball field. |
| title | Real-Time Localization Framework for Autonomous Basketball Robots |
| topic | Robotics Artificial Intelligence Computer Vision and Pattern Recognition I.2.9; I.2.10 |
| url | https://arxiv.org/abs/2601.08713 |