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On 'A Kalman Filter-Based Algorithm for IMU-Camera Calibration: Observability Analysis and Performance Evaluation'

2013/11/18 by Yuanxin Wu, Wu, Yuanxin · 4 citations
Computer Science · Engineering · #Advanced Vision and Imaging #FOS: Computer and information sciences #FOS: Electrical engineering #Robotics (cs.RO) #Robotics and Sensor-Based Localization #Systems and Control (eess.SY) #Target Tracking and Data Fusion in Sensor Networks #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.1311.4769

openalex publication_date 2013/11/18 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28

Abstract

The above-mentioned work [1] in IEEE-TR'08 presented an extended Kalman filter for calibrating the misalignment between a camera and an IMU. As one of the main contributions, the locally weakly observable analysis was carried out using Lie derivatives. The seminal paper [1] is undoubtedly the cornerstone of current observability work in SLAM and a number of real SLAM systems have been developed on the observability result of this paper, such as [2, 3]. However, the main observability result of this paper [1] is founded on an incorrect proof and actually cannot be acquired using the local observability technique therein, a fact that is apparently not noticed by the SLAM community over a number of years.

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