This study proposes a novel application of neural computing based on deep learning for the
real-time prediction of motion parameters for underwater maneuvering object. The intelligent …

This work presents a dataset of human-operated robot motion to be used within the context
of assistive robotics and assorted fields, such as learning from demonstrations, machine …

This paper proposes a kinesthetic–tactile fusion feedback system based on virtual
interaction. Combining the results of human fingertip deformation characteristics analysis …

Estimating the state of a system by fusing sensor data is a major prerequisite in many
applications. When the state is time-variant, derivatives of the Kalman filter are a popular …

This paper proposes a target model for radar state estimation based on the Bishop or
Parallel Transport frame, extending upon previous work using the Frenet-Serret frame to …

Accurate and robust autonomous underwater navigation (AUV) requires the fundamental
task of position estimation in a variety of conditions. Additionally, the US Navy would prefer …

This paper presents an extension to the original Frenet-Serret and Bishop frame target
models used in the invariant extended Kalman filter (IEKF) to account for tangential …

Tracking a manoeuvrable target requires kinematic models that are representative of target
trajectories. The Frenet-Serret and Bishop formulae in equations (1) and (2) provide a …