Diyar Khalis Bilal

Salahaddin University - Erbil | SUH · College of Engineering

In this work, an eye to hand camera based pose estimation system is developed for robotic machining and the accuracy of the estimated pose is improved using two different approaches, namely Long Short Term Memory (LSTM) neural networks and sparse regression. To improve the accuracy obtained from the Levenberg–Marquardt (LM) based pose estimation al...

In this work a feedforward control approach based on SINDYc (Sparse Identification of Nonlinear Dynamics with Control) is proposed for increasing the trajectory tracking accuracy of industrial robots. Initially, the dynamic relationship between the desired and the actual trajectory is sparsely identified using polynomial basis functions. Then a new...

In this work a monocular machine vision based pose estimation system is developed for industrial robots and the accuracy of the estimated pose is improved via sparse regression. The proposed sparse regression based method is used improve the accuracy obtained from the Levenberg-Marquardt (LM) based pose estimation algorithm during the trajectory tr...

This paper deals with the development of a realtime structural health monitoring system for airframe structures to localize and estimate the magnitude of the loads causing deflections to the critical components, such as wings. To this end, a framework that is based on artificial neural networks is developed where features that are extracted from a...