Robust Visual Localization in Compute-Constrained Environments by Salient Edge Rendering and Weighted Hamming Similarity

• URL: http://arxiv.org/abs/2509.25520v1
• Date: Mon, 29 Sep 2025 21:22:35 GMT
• Title: Robust Visual Localization in Compute-Constrained Environments by Salient Edge Rendering and Weighted Hamming Similarity
• Abstract summary: We consider the problem of vision-based 6-DoF object pose estimation in the context of the notional Mars Sample Return campaign.<n>We propose a novel localization algorithm leveraging a custom metric together with a new template matching to the edge domain.<n>Our method consistently beats the state of the art in compute and memory-constrained localization, both in terms of robustness and accuracy, in turn enabling new possibilities for cheap and reliable localization on general-purpose hardware.
• Score: 1.2621048930928775
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We consider the problem of vision-based 6-DoF object pose estimation in the context of the notional Mars Sample Return campaign, in which a robotic arm would need to localize multiple objects of interest for low-clearance pickup and insertion, under severely constrained hardware. We propose a novel localization algorithm leveraging a custom renderer together with a new template matching metric tailored to the edge domain to achieve robust pose estimation using only low-fidelity, textureless 3D models as inputs. Extensive evaluations on synthetic datasets as well as from physical testbeds on Earth and in situ Mars imagery shows that our method consistently beats the state of the art in compute and memory-constrained localization, both in terms of robustness and accuracy, in turn enabling new possibilities for cheap and reliable localization on general-purpose hardware.

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