Most modern consumer-grade cameras are often equipped with a rolling shutter
mechanism, which is becoming increasingly important in computer vision, robotics and …

Multi-modal data fusion has gained popularity due to its diverse applications, leading to an
increased demand for external sensor calibration. Despite several proven calibration …

In this paper, we study state estimation of multi-visual-inertial systems (MVIS) and develop
sensor fusion algorithms to optimally fuse an arbitrary number of asynchronous inertial …

In this letter, we propose a probabilistic continuous-time visual-inertial odometry (VIO) for
rolling shutter cameras. The continuous-time trajectory formulation naturally facilitates the …

Accurate intersensor spatiotemporal transformation is the fundamental prerequisite for
multisensor fusion. However, traditional discrete-time calibration methods have natural …

In this paper, we study in-depth the problem of online self-calibration for robust and accurate
visual-inertial state estimation. In particular, we first perform a complete observability …

The emerging applications of the Internet of Things (IoT), such as driverless cars, have an
increasing need for precise vehicle positioning. Inertial navigation systems (INSs) became a …

Accurate, efficient, and robust state estimation is more important than ever in robotics as the
variety of platforms and complexity of tasks continue to grow. Historically, discrete-time filters …

In many camera-based applications, it is necessary to find the geometric relationship
between incoming rays and image pixels, ie, the projection model, through the geometric …

The integrated inertial system, typically integrating an IMU and an exteroceptive sensor such
as radar, LiDAR, and camera, has been widely accepted and applied in modern robotic …