リー群に適応した統合確率データ関連フィルタ
The Integrated Probabilistic Data Association Filter Adapted to Lie Groups
目標追跡アルゴリズムIPDAFを、連結単模リー群上で運動する等速目標モデルとリー群上の観測に対応できるよう拡張し、SE(2)上の地上車両追跡に適用した論文。
著者: Mark E. Petersen, Randal W. Beard
分類: cs.RO
原文アブストラクト
The Integrated Probabilistic Data Association Filter (IPDAF) is a target tracking algorithm based on the Probabilistic Data Association Filter that calculates a statistical measure that indicates if an estimated representation of the target properly represents the target or is generated from non-target-originated measurements. The main contribution of this paper is to adapt the IPDAF to constant velocity target models that evolve on connected, unimodular Lie groups, and where the measurements are also defined on a Lie group. We present an example where the methods developed in the paper are applied to the problem of tracking a ground vehicle on the special Euclidean group SE(2).