Abstract
Dead reckoning is a common navigation method in extraterrestrial rover missions. However, its effectiveness is often limited by the accumulated error from odometry, which can be mitigated through global localization techniques. We introduce a global localization method that utilizes horizon line matching with a digital elevation map (DEM) for a lunar rover equipped only with an RGB-D camera. The method consists of two main phases: generating a horizon line dataset by projecting the DEM onto a pose search network (PSN) and aligning horizon lines from individual poses with the actual horizon line captured by the rover's camera. Our approach employs feature-level matching instead of traditional pixel-level matching, significantly improving the stability and efficiency of the localization process. By adopting innovative segmentation and search strategies, we also reduce the computational complexity of curve matching. The effectiveness of our method is validated through high-fidelity lunar simulations, demonstrating superior localization accuracy compared to other DEM-based methods. Our approach presents a compelling solution for enhancing the navigation capabilities of lunar rovers with a limited sensor system.
Original language | English |
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Pages (from-to) | 8744-8756 |
Number of pages | 13 |
Journal | IEEE Transactions on Aerospace and Electronic Systems |
Volume | 60 |
Issue number | 6 |
DOIs | |
Publication status | Published - 2024 |
Keywords
- Curve matching
- digital elevation map (DEM)
- global localization
- lunar rover