IMU-Camera Calibration: Observability Analysis
نویسندگان
چکیده
منابع مشابه
On the Observability and Self-Calibration of Visual-Inertial Navigation Systems
We examine the observability properties of visual-inertial navigation systems, with an emphasis on self-calibration of the six degrees-of-freedom rigid body transform between a camera and an inertial measurement unit (IMU). Our analysis depends on a differential geometric formulation of the calibration problem, and on an algebraic test for the ‘observability rank condition’, originally defined ...
متن کاملVisual-Inertial Sensor Fusion: Localization, Mapping and Sensor-to-Sensor Self-calibration
Visual and inertial sensors, in combination, are able to provide accurate motion estimates and are well-suited for use in many robot navigation tasks. However, correct data fusion, and hence overall performance, depends on careful calibration of the rigid body transform between the sensors. Obtaining this calibration information is typically difficult and time-consuming, and normally requires a...
متن کاملOn 'A Kalman Filter-Based Algorithm for IMU-Camera Calibration: Observability Analysis and Performance Evaluation'
The above-mentioned work [1] 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 obse...
متن کاملFast Relative Pose Calibration for Visual and Inertial Sensors
Accurate vision-aided inertial navigation depends on proper calibration of the relative pose of the camera and the inertial measurement unit (IMU). Calibration errors introduce bias in the overall motion estimate, degrading navigation performance sometimes dramatically. However, existing camera-IMU calibration techniques are difficult, time-consuming and often require additional complex apparat...
متن کاملOnline temporal calibration for camera-IMU systems: Theory and algorithms
When fusing visual and inertial measurements for motion estimation, each measurement’s sampling time must be precisely known. This requires knowledge of the time offset that inevitably exists between the two sensors’ data streams. The first contribution of this work is an online approach for estimating this time offset, by treating it as an additional state variable to be estimated along with a...
متن کامل