マルチステート制約カルマンフィルタの即時更新戦略
An Immediate Update Strategy of Multi-State Constraint Kalman Filter
MSCKFにおいて、遅延更新ではなく再構成した3D特徴点と観測制約に基づく即時更新を導入し、推定精度を向上させる手法を提案・検証した。
著者: Qingchao Zhang, Wei Ouyang, Jiale Han, Qi Cai, Maoran Zhu, Yuanxin Wu
分類: cs.RO
原文アブストラクト
The lightweight Multi-state Constraint Kalman Filter (MSCKF) has been well-known for its high efficiency, in which the delayed update has been usually adopted since its proposal. This work investigates the immediate update strategy of MSCKF based on timely reconstructed 3D feature points and measurement constraints. The differences between the delayed update and the immediate update are theoretically analyzed in detail. It is found that the immediate update helps construct more observation constraints and employ more filtering updates than the delayed update, which improves the linearization point of the measurement model and therefore enhances the estimation accuracy. Numerical simulations and experiments show that the immediate update strategy significantly enhances MSCKF even with a small amount of feature observations.
