Many techniques for robot localization rely on the assumption that both process and
measurement noises are uncorrelated, white, and normally distributed. However, if this …

Attitude control is an essential flight capability. Whereas flying robots commonly rely on
accelerometers for estimating attitude, flying insects lack an unambiguous sense of gravity …

This paper proposes a state estimator for legged robots operating in slippery environments.
An Invariant Extended Kalman Filter (InEKF) is implemented to fuse inertial and velocity …

Although drone technology has advanced rapidly, replicating the dynamic control and wind-
sensing abilities of biological flight is still beyond reach. Biological studies reveal that insect …

This paper proposes a robust sensor fusion algorithm to accurately track the spatial location
and motion of a human under various dynamic activities, such as walking, running, and …

Existing homography and optical flow methods are erroneous in challenging scenes, such
as fog, rain, night, and snow because the basic assumptions such as brightness and …

The combination of visual and inertial sensors for state estimation has recently found wide
echo in the robotics community, especially in the aerial robotics field, due to the lightweight …

Existing optical flow methods are erroneous in challenging scenes, such as fog, rain, and
night because the basic optical flow assumptions such as brightness and gradient constancy …

We present RS-Diffusion, the first Diffusion Models-based method for single-frame Rolling
Shutter (RS) correction. RS artifacts compromise visual quality of frames due to the row wise …

This paper develops a simple and low-cost method for 3D, high-rate vehicle state estimation,
specially designed for free-flying Micro Aerial Vehicles (MAVs). We fuse observations from …