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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2502.17581 |
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| _version_ | 1866929729946255360 |
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| author | Zhao, Peijie Arefin, Zunayed Meneguzzi, Felipe Pereira, Ramon Fraga |
| author_facet | Zhao, Peijie Arefin, Zunayed Meneguzzi, Felipe Pereira, Ramon Fraga |
| contents | In this demonstration, we develop IntentRec4Maps, a system to recognise users' intentions in interactive maps for real-world navigation. IntentRec4Maps uses the Google Maps Platform as the real-world interactive map, and a very effective approach for recognising users' intentions in real-time. We showcase the recognition process of IntentRec4Maps using two different Path-Planners and a Large Language Model (LLM).
GitHub: https://github.com/PeijieZ/IntentRec4Maps |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_17581 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Intention Recognition in Real-Time Interactive Navigation Maps Zhao, Peijie Arefin, Zunayed Meneguzzi, Felipe Pereira, Ramon Fraga Artificial Intelligence In this demonstration, we develop IntentRec4Maps, a system to recognise users' intentions in interactive maps for real-world navigation. IntentRec4Maps uses the Google Maps Platform as the real-world interactive map, and a very effective approach for recognising users' intentions in real-time. We showcase the recognition process of IntentRec4Maps using two different Path-Planners and a Large Language Model (LLM). GitHub: https://github.com/PeijieZ/IntentRec4Maps |
| title | Intention Recognition in Real-Time Interactive Navigation Maps |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2502.17581 |