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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.22331 |
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| _version_ | 1866911621311365120 |
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| author | Relia, Lomash Singla, Jai G Amitabh Dube, Nitant |
| author_facet | Relia, Lomash Singla, Jai G Amitabh Dube, Nitant |
| contents | This study analyses simulated and real-world implementations of depth-aware rover navigation, highlighting the transition from stereo vision to monocular depth estimation using edge AI. A Unity-based lunar terrain simulator with stereo cameras and OpenCV's StereoSGBM was used to generate disparity maps. A physical rover built on Raspberry Pi 4 employed UniDepthV2 for monocular metric depth estimation and YOLO12n for real-time object detection. While stereo vision yielded higher accuracy in simulation, the monocular approach proved more robust and cost-effective in real-world deployment, achieving 0.1 FPS for depth and 10 FPS for detection. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_22331 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Depth-Aware Rover: A Study of Edge AI and Monocular Vision for Real-World Implementation Relia, Lomash Singla, Jai G Amitabh Dube, Nitant Computer Vision and Pattern Recognition This study analyses simulated and real-world implementations of depth-aware rover navigation, highlighting the transition from stereo vision to monocular depth estimation using edge AI. A Unity-based lunar terrain simulator with stereo cameras and OpenCV's StereoSGBM was used to generate disparity maps. A physical rover built on Raspberry Pi 4 employed UniDepthV2 for monocular metric depth estimation and YOLO12n for real-time object detection. While stereo vision yielded higher accuracy in simulation, the monocular approach proved more robust and cost-effective in real-world deployment, achieving 0.1 FPS for depth and 10 FPS for detection. |
| title | Depth-Aware Rover: A Study of Edge AI and Monocular Vision for Real-World Implementation |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2604.22331 |