Inertial-sensor-based attitude estimation is a crucial technology in various applications, from human motion tracking to autonomous aerial and ground vehicles. Application scenarios differ characteristics of the performed motion, presence disturbances, environmental conditions. Since state-of-the-art estimators do not generalize well over these characteristics, their parameters must be tuned fo...

A filter for estimating spacecraft attitude quaternion and gyro drift from vector measurements in the presence of white noises in the gyro error, in the drift dynamics, and in the line-of-sight measurement error is developed. The variance parameters of the white noises are unknown, and are modeled as non-anticipative second order stochastic processes. The approach taken in this work consists in...

This research develops and evaluates a robotic rotational motion platform to test lunarlanding-like attitude, sensing and control. The platform is equipped with thrusters, sensors, and computer control and is restricted to orientation maneuvers. The platform is mass balanced and suspended on a bearing that accommodates 60 degrees of excursion in roll, pitch and yaw. The platform operates in a c...

Attitude determination using the smartphone’s inertial sensors poses a major challenge due to sensor low-performance grade and variate nature of walking pedestrian. In this paper, data-driven techniques are employed address that challenge. To end, hybrid deep learning model based solution for attitude estimation is proposed. Here, classical equations applied form an adaptive complementary filte...