Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions

Conventional control of robotic manipulators requires prior knowledge of their kinematic structure. Model-learning controllers have the advantage of being able to control robots without requiring a complete kinematic model and work well in less structured environments. Our recently proposed Encoderl...

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Bibliographic Details
Main Authors: Ahmad AlAttar, Petar Kormushev
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Robotics
Subjects:
Online Access:https://www.mdpi.com/2218-6581/9/4/76
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spelling doaj-a4ee3850bcd3464fb9a9a62ea0a277122020-11-25T03:13:17ZengMDPI AGRobotics2218-65812020-09-019767610.3390/robotics9040076Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual QuaternionsAhmad AlAttar0Petar Kormushev1Robot Intelligence Lab, Dyson School of Design Engineering, Imperial College London, London SW7 2DB, UKRobot Intelligence Lab, Dyson School of Design Engineering, Imperial College London, London SW7 2DB, UKConventional control of robotic manipulators requires prior knowledge of their kinematic structure. Model-learning controllers have the advantage of being able to control robots without requiring a complete kinematic model and work well in less structured environments. Our recently proposed Encoderless controller has shown promising ability to control a manipulator without requiring any prior kinematic model whatsoever. However, this controller is only limited to position control, leaving orientation control unsolved. The research presented in this paper extends the state-of-the-art kinematic-model-free controller to handle orientation control to manipulate a robotic arm without requiring any prior model of the robot or any joint angle information during control. This paper presents a novel method to simultaneously control the position and orientation of a robot’s end effector using locally weighted dual quaternions. The proposed novel controller is also scaled up to control three-degrees-of-freedom robots.https://www.mdpi.com/2218-6581/9/4/76orientation controlmodel learningadaptive controlkinematic-model-free controllocally weighted dual quaternions
collection DOAJ
language English
format Article
sources DOAJ
author Ahmad AlAttar
Petar Kormushev
spellingShingle Ahmad AlAttar
Petar Kormushev
Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions
Robotics
orientation control
model learning
adaptive control
kinematic-model-free control
locally weighted dual quaternions
author_facet Ahmad AlAttar
Petar Kormushev
author_sort Ahmad AlAttar
title Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions
title_short Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions
title_full Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions
title_fullStr Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions
title_full_unstemmed Kinematic-Model-Free Orientation Control for Robot Manipulation Using Locally Weighted Dual Quaternions
title_sort kinematic-model-free orientation control for robot manipulation using locally weighted dual quaternions
publisher MDPI AG
series Robotics
issn 2218-6581
publishDate 2020-09-01
description Conventional control of robotic manipulators requires prior knowledge of their kinematic structure. Model-learning controllers have the advantage of being able to control robots without requiring a complete kinematic model and work well in less structured environments. Our recently proposed Encoderless controller has shown promising ability to control a manipulator without requiring any prior kinematic model whatsoever. However, this controller is only limited to position control, leaving orientation control unsolved. The research presented in this paper extends the state-of-the-art kinematic-model-free controller to handle orientation control to manipulate a robotic arm without requiring any prior model of the robot or any joint angle information during control. This paper presents a novel method to simultaneously control the position and orientation of a robot’s end effector using locally weighted dual quaternions. The proposed novel controller is also scaled up to control three-degrees-of-freedom robots.
topic orientation control
model learning
adaptive control
kinematic-model-free control
locally weighted dual quaternions
url https://www.mdpi.com/2218-6581/9/4/76
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AT petarkormushev kinematicmodelfreeorientationcontrolforrobotmanipulationusinglocallyweighteddualquaternions
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