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

Vision-aided inertial navigation systems (V-INSs) can provide precise state estimates for the 3-D motion of a vehicle when no external references (e.g., GPS) are available. This is achieved by combining inertial measurements from an inertial measurement unit (IMU) with visual observations from a cam...

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Veröffentlicht in:	IEEE transactions on robotics 2008-10, Vol.24 (5), p.1143-1156
Hauptverfasser:	Mirzaei, F.M., Roumeliotis, S.I.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy Algorithm design and analysis Algorithms Applied sciences Artificial intelligence Calibration Cameras Computer science control theory systems Control system analysis Control theory. Systems Estimating techniques Exact sciences and technology Extended Kalman filter Fundamental areas of phenomenology (including applications) Global Positioning System Inertial inertial measurement unit (IMU)-camera calibration Inertial navigation Kalman filters Lie derivatives Measurement Modelling and identification Motion estimation Navigation systems Observability observability of nonlinear systems Pattern recognition. Digital image processing. Computational geometry Performance analysis Performance evaluation Physics Satellite navigation systems Sensors Solid dynamics (ballistics, collision, multibody system, stabilization...) Solid mechanics State estimation Transformations Vehicles vision-aided inertial navigation
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