92 research outputs found

    On-Manifold Recursive Bayesian Estimation for Directional Domains

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    Towards High-Performance Solid-State-LiDAR-Inertial Odometry and Mapping

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    We present a novel tightly-coupled LiDAR-inertial odometry and mapping scheme for both solid-state and mechanical LiDARs. As frontend, a feature-based lightweight LiDAR odometry provides fast motion estimates for adaptive keyframe selection. As backend, a hierarchical keyframe-based sliding window optimization is performed through marginalization for directly fusing IMU and LiDAR measurements. For the Livox Horizon, a newly released solid-state LiDAR, a novel feature extraction method is proposed to handle its irregular scan pattern during preprocessing. LiLi-OM (Livox LiDAR-inertial odometry and mapping) is real-time capable and achieves superior accuracy over state-of-the-art systems for both LiDAR types on public data sets of mechanical LiDARs and in experiments using the Livox Horizon. Source code and recorded experimental data sets are available on Github.Comment: 15 page

    Towards High-Performance Solid-State-LiDAR-Inertial Odometry and Mapping

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    Hyperspherical Deterministic Sampling Based on Riemannian Geometry for Improved Nonlinear Bingham Filtering

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    Highly Parallelizable Plane Extraction for Organized Point Clouds Using Spherical Convex Hulls

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    Fourier Filters, Grid Filters, and the Fourier-Interpreted Grid Filter

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