Improving industrial robot positioning accuracy to the microscale using machine learning method

V Bucinskas, A Dzedzickis, M Sumanas, E Sutinys… - Machines, 2022 - mdpi.com
Positioning accuracy in robotics is a key issue for the manufacturing process. One of the
possible ways to achieve high accuracy is the implementation of machine learning (ML) …

[HTML][HTML] A two-step machining and active learning approach for right-first-time robotic countersinking through in-process error compensation and prediction of depth of …

M Leco, T McLeay, V Kadirkamanathan - Robotics and Computer …, 2022 - Elsevier
Robotic machining processes are characterised by errors arising from the limitations of the
industrial robots. These robot-related errors can compromise the overall manufacturing …

A study on new machining method applied to a collaborative robot for drilling

Y Miyake, Y Kondo - Robotics and Computer-Integrated Manufacturing, 2022 - Elsevier
In the assembly of aircraft fuselages, manual hole drilling is conducted in some cases
instead of applying robotic drilling due to the issues of burr formation and vibration. In …

An approach for using iterative learning for controlling the jet penetration depth in abrasive waterjet milling

A Rabani, J Madariaga, C Bouvier, D Axinte - Journal of Manufacturing …, 2016 - Elsevier
This paper presents a new methodology for controlling the jet penetration in abrasive
waterjet milling. The generation of milled parts by means of abrasive waterjet is traditionally …

Estimation-based quadratic iterative learning control for trajectory tracking of robotic manipulator with uncertain parameters

M Zhu, L Ye, X Ma - IEEE Access, 2020 - ieeexplore.ieee.org
In this paper, we consider iterative learning control for trajectory tracking of robotic
manipulator with uncertainty. An improved quadratic-criterion-based iterative learning …

On distributed knowledge bases for robotized small-batch assembly

M Stenmark, J Malec, K Nilsson… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
The flexibility demands in manufacturing are severe, eg, for rapid-change-over to new
product variants, while robots are flexible machines that potentially can be adapted to a …

A study on robot arm machining: Advance and future challenges.

R Pérez, SC Gutiérrez… - Annals of DAAAM & …, 2018 - search.ebscohost.com
Nowadays, it is not uncommon to find news and research about robotic machining
applications, as milling and drilling. The flexibility, programmability and low price of robots …

Unbalance Compensation of a Full Scale Test Rig Designed for HTR‐10GT: A Frequency‐Domain Approach Based on Iterative Learning Control

Y He, L Shi, Z Shi, Z Sun - Science and Technology of Nuclear …, 2017 - Wiley Online Library
Unbalance vibrations are crucial problems in heavy rotational machinery, especially for the
systems with high operation speed, like turbine machinery. For the program of 10 MW High …

Topics in machining with industrial robot manipulators and optimal motion control

B Olofsson - 2015 - portal.research.lu.se
Two main topics are considered in this thesis: Machining with industrial robot manipulators
and optimal motion control of robots and vehicles. The motivation for research on the first …

Force adaptation with recursive regression iterative learning controller

B Nemec, T Petrič, A Ude - 2015 IEEE/RSJ International …, 2015 - ieeexplore.ieee.org
In this paper we exploit Iterative Learning Controllers (ILC) schemes in force adaptation
tasks. We propose to encode the control signal with Radial Basis Functions (RBF), which …