Force reference extraction via human interaction for a robotic polishing task: Force-induced motion

Name: Force reference extraction via human interaction for a robotic polishing task: Force-induced motion
Author: Hamdan, Sara, Öztop, Erhan, Uğurlu, Regaip Barkan

İsim	Force reference extraction via human interaction for a robotic polishing task: Force-induced motion
Yazar	Hamdan, Sara, Öztop, Erhan, Uğurlu, Regaip Barkan
Basım Tarihi:	2019-10
Basım Yeri	- IEEE
Konu	Admittance control, Physical human-robot interaction, Intelligent robot control
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-1-7281-4569-3
Kayıt Numarası	770f4883-601a-4235-97f0-c91a5e3a7e3b
Lokasyon	Computer Science, Mechanical Engineering
Tarih	2019-10
Notlar	European Union (EU) ; H2020 project CoMRAde
Örnek Metin	In this paper, a method to control a manipulator using force-induced trajectory is proposed. The trajectory is learned from an operator doing the polishing task using a tool attached to the robot's end-effector. The learning process is performed by a deep neural network which is designed and trained to generate a force profile according to the states (joints' positions and velocities). The admittance control technique is utilized to make the manipulator compliant to the operator movements in the teaching mode. Spring-Damper system along with Inertia-Damper system has been studied to impose the relationship between the operator's applied force and the reaction of the manipulator. The universal robot (UR5) aside with a force sensor (OptoForce) are used to run the experiment. Robot Operation System (ROS) is used to accomplish the task in real-time. The polishing task is learned and achieved by the robot itself, and the force trajectories are better followed using the Inertia-Damper system as the admittance controlling scheme.
DOI	10.1109/SMC.2019.8914009

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Force reference extraction via human interaction for a robotic polishing task: Force-induced motion

Yazar Hamdan, Sara, Öztop, Erhan, Uğurlu, Regaip Barkan

Basım Tarihi 2019-10

Basım Yeri - IEEE

Konu Admittance control, Physical human-robot interaction, Intelligent robot control

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-1-7281-4569-3

Kayıt Numarası 770f4883-601a-4235-97f0-c91a5e3a7e3b

Lokasyon Computer Science, Mechanical Engineering

Tarih 2019-10

Notlar European Union (EU) ; H2020 project CoMRAde

Örnek Metin In this paper, a method to control a manipulator using force-induced trajectory is proposed. The trajectory is learned from an operator doing the polishing task using a tool attached to the robot's end-effector. The learning process is performed by a deep neural network which is designed and trained to generate a force profile according to the states (joints' positions and velocities). The admittance control technique is utilized to make the manipulator compliant to the operator movements in the teaching mode. Spring-Damper system along with Inertia-Damper system has been studied to impose the relationship between the operator's applied force and the reaction of the manipulator. The universal robot (UR5) aside with a force sensor (OptoForce) are used to run the experiment. Robot Operation System (ROS) is used to accomplish the task in real-time. The polishing task is learned and achieved by the robot itself, and the force trajectories are better followed using the Inertia-Damper system as the admittance controlling scheme.

DOI 10.1109/SMC.2019.8914009