RAGNAROK: Radar-Aided Gravity-Normalized Alignment for Robus
Overview
Source roundup from published reports. Claims below are attributed to their publishers, not independently verified. arXiv Robotics — research abstracts: RAGNAROK: Radar-Aided Gravity-Normalized Alignment for Robust Open Keyframe-based Radar-Visual-Kinematic-Inertial SLAM. This research presents RAGNAROK, the first radar-visual-kinematic-inertial SLAM system designed for robust operation in challenging environments. It integrates slip- and rolling-contact-aware leg velocity estimation, a k…
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“, adaptive weighting, and online extrinsic calibration. Extensive experiments on public and self-collected datasets demonstrate that RAGNAROK achieves robust performance under challenging conditions and outperforms state-of-the-art baselines. The source code and dataset are available at https://github.com/hanjun815/RAGNAROK.”
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Artifact availability · dataset: available
“, adaptive weighting, and online extrinsic calibration. Extensive experiments on public and self-collected datasets demonstrate that RAGNAROK achieves robust performance under challenging conditions and outperforms state-of-the-art baselines. The source code and dataset are available at https://github.com/hanjun815/RAGNAROK.”
Exact source · revision 1Source owner not reported
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- arXiv Robotics — research abstractsRAGNAROK: Radar-Aided Gravity-Normalized Alignment for Robust Open Keyframe-based Radar-Visual-Kinematic-Inertial SLAM
This research presents RAGNAROK, the first radar-visual-kinematic-inertial SLAM system designed for robust operation in challenging environments. It integrates slip- and rolling-contact-aware leg velocity estimation, a kinematics-aware radar factor, and degradation-aware image enhancement. The system also includes a B-spline-based radar-aided proprioceptive backbone and adaptive weighting, with extensive experiments showing improved performance over existing baselines.
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