A review of various calibration techniques of MEMS inertial sensors is presented in this
paper. MEMS inertial sensors are subject to various sources of error, so it is essential to …

Inertial measurement unit (IMU) comprising of the accelerometer and gyroscope is prone to
various deterministic errors like bias, scale factor, and nonorthogonality, which need to be …

In order to increase accuracy and robustness in state estimation for robotics, a growing
number of applications rely on data from multiple complementary sensors. For the best …

This paper proposes an approach to calibrate off-the-shelf cameras and inertial sensors to
have a useful integrated system to be used in static and dynamic situations. When both …

In this paper, we present a probabilistic framework to recover the extrinsic calibration
parameters of a lidar-IMU sensing system. Unlike global-shutter cameras, lidars do not take …

This paper explores the combination of inertial sensor data with vision. Visual and inertial
sensing are two sensory modalities that can be explored to give robust solutions on image …

This paper presents a tracking system for ego-motion estimation which fuses vision and
inertial measurements using EKF and UKF (Extended and Unscented Kalman Filters) …

With growing demands for accuracy in sensor fusion, increasing attention is being paid to
temporal offsets as a source of deterministic error when processing data from multiple …

Camera pose estimation is the cornerstone of Augmented Reality applications. Pose
tracking based on camera images exclusively has been shown to be sensitive to motion …

External effects such as shocks and temperature variations affect the calibration of visual-
inertial sensor systems and thus they cannot fully rely on factory calibrations. Re-calibrations …