日本フィジカルAI新聞

世界のフィジカルAIを、日本語で。

慣性ナビゲーションarXiv:2102.12220

三叉四元数フレームワークによる慣性ナビゲーション 第II部:誤差モデルと初期アライメントへの応用

A Trident Quaternion Framework for Inertial-based Navigation Part II: Error Models and Application to Initial Alignment

シェア:XThreadsFacebookLINEはてブBluesky

三叉四元数の左右誤差モデルを導出し、それに基づく拡張カルマンフィルタを設計して、車両のオドメータ支援による静止・走行中の姿勢アライメント性能を評価した論文。

著者: Wei Ouyang, Yuanxin Wu

分類: cs.RO, cs.SY, eess.SY

原文アブストラクト

This work deals with error models for trident quaternion framework proposed in the companion paper (Part I) and further uses them to investigate the odometer-aided static/in-motion inertial navigation attitude alignment for land vehicles. By linearizing the trident quaternion kinematic equation, the left and right trident quaternion error models are obtained, which are found to be equivalent to those derived from profound group affine. The two error models are used to design their corresponding extended Kalman filters (EKF), namely, the left-quaternion EKF (LQEKF) and the right-quaternion EKF (RQEKF). Simulations and field tests are conducted to evaluate their actual performances. Owing to the high estimation consistency, the L/RQEKF converge much faster in the static alignment than the traditional error model-based EKF, even under arbitrary large heading initialization. For the in-motion alignment, the L/RQEKF possess much larger convergence region than the traditional EKF does, although they still require the aid of attitude initialization so as to avoid large initial attitude errors.

関連論文

  1. 1Boston Dynamics、車輪付きAtlasの研究試作機を紹介研究・技術
  2. 2GXOとApptronik、Apolloの物流現場試験を拡大 最大1,000台の展開を構想量産・展開
  3. 3newmoとKDDIが資本業務提携 2028年に堺市で自動運転タクシー商用化目指す提携・買収
  4. 4NVIDIA、CoRLでGR00T 2とIsaac Lab 3.0を発表新製品・発表
  5. 5UC BerkeleyとNVIDIAの研究者、AIエージェントでロボット制御コードを仮想環境で改善研究・技術

PR・アフィリエイト広告

FRONTIER(GPU搭載BTOパソコン)

FRONTIER(GPU搭載BTOパソコン)の公式広告バナーFRONTIERでGPU搭載PCを見る ↗
PR本紙発行元 EmplifAI