日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

週刊ニュースレター購読
キャリブレーションarXiv:2608.25135v1

連続時間フレームワークにおける傾斜面への地上制約LiDAR-IMUキャリブレーションの拡張

Extending Ground-Constraint LiDAR-IMU Calibration to Tilted Surfaces in a Continuous-Time Framework

シェア:XThreadsFacebookLINEはてブBluesky

本論文は、地上車両のLiDAR-IMUキャリブレーションを非平坦環境に拡張し、傾斜面上の平面運動でも適用可能な新しい地上平面残差を提案する。実験では、傾斜面と平坦面の両方で再現性が向上することを示した。

著者: Vassili Korotkine, Pierre Chamoun, Mohammed Ayman Shalaby, James Richard Forbes

分類: cs.RO

原文アブストラクト

This paper presents a novel method that extends targetless LiDAR-IMU calibration for ground vehicles to non- flat environments. Calibration typically necessitates full exci- tation of the sensor rig, a requirement that is not fulfilled by ground vehicles in normal operation. To address the degenerate planar motion, state-of-the-art methods propose residuals that assume the colinearity of the gravity and physical surface normal vectors, restricting usage to cases where the ground is assumed flat. This paper proposes ground-plane residuals that do not require this assumption, and are applicable for planar motion on a tilted surface. Results are demonstrated on a dataset collected from a Husky ground vehicle, on the M2DGR dataset, as well as on an offroad vehicle dataset. Repeatability is shown to be improved both in tilted and flat-ground scenarios, with strong improvement demonstrated for the tilted case. The implementation and experiments are open-sourced at https://github.com/vkorotkine/licalib_tilted_ground.

関連論文