{"ID":2826352,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.19567","arxiv_id":"2512.19567","title":"LIMOncello: Iterated Error-State Kalman Filter on the SGal(3) Manifold for Fast LiDAR-Inertial Odometry","abstract":"This work introduces LIMOncello, a tightly coupled LiDAR-Inertial Odometry system that models 6-DoF motion on the $\\mathrm{SGal}(3)$ manifold within an iterated error-state Kalman filter backend. Compared to state representations defined on $\\mathrm{SO}(3)\\times\\mathbb{R}^6$, the use of $\\mathrm{SGal}(3)$ provides a coherent and numerically stable discrete-time propagation model that helps limit drift in low-observability conditions. LIMOncello also includes a lightweight incremental i-Octree mapping backend that enables faster updates and substantially lower memory usage than incremental kd-tree style map structures, without relying on locality-restricted search heuristics. Experiments on multiple real-world datasets show that LIMOncello achieves competitive accuracy while improving robustness in geometrically sparse environments. The system maintains real-time performance with stable memory growth and is released as an extensible open-source implementation at https://github.com/CPerezRuiz335/LIMOncello.","short_abstract":"This work introduces LIMOncello, a tightly coupled LiDAR-Inertial Odometry system that models 6-DoF motion on the $\\mathrm{SGal}(3)$ manifold within an iterated error-state Kalman filter backend. Compared to state representations defined on $\\mathrm{SO}(3)\\times\\mathbb{R}^6$, the use of $\\mathrm{SGal}(3)$ provides a co...","url_abs":"https://arxiv.org/abs/2512.19567","url_pdf":"https://arxiv.org/pdf/2512.19567v2","authors":"[\"Carlos Pérez-Ruiz\",\"Joan Solà\"]","published":"2025-12-22T16:50:10Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false,"code_links":[{"ID":605738,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2826352,"paper_url":"https://arxiv.org/abs/2512.19567","paper_title":"LIMOncello: Iterated Error-State Kalman Filter on the SGal(3) Manifold for Fast LiDAR-Inertial Odometry","repo_url":"https://github.com/CPerezRuiz335/LIMOncello","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}