Timothy Havens Publishes on Fuzzy Adaptive Extended Kalman Filter

International Journal of Intelligent Unmanned Systems coverHanieh Deilamsalehy (ECE) and Timothy Havens (ECE/CS) published a paper entitled, “Fuzzy adaptive extended Kalman filter for robust 3D pose estimation,” in the International Journal of Intelligent Unmanned Systems, vol. 6, no. 2, pp. 50-68.

doi.org/10.1108/IJIUS-12-2017-0014

Timothy Havens is the William and Gloria Jackson Associate Professor of Computer Systems in the Department of Electrical and Computer Engineering and the director of the Center for Data Sciences (DataS). DataS is part of ICC, the Institute of Computing & Cybersystems at Michigan Tech.

Hanieh Deilamsalehy, who graduated in 2017 with a PhD in Electrical Engineering from Michigan Tech, is working at Microsoft.

Purpose

Estimating the pose – position and orientation – of a moving object such as a robot is a necessary task for many applications, e.g., robot navigation control, environment mapping, and medical applications such as robotic surgery. The purpose of this paper is to introduce a novel method to fuse the information from several available sensors in order to improve the estimated pose from any individual sensor and calculate a more accurate pose for the moving platform.