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...
Main Authors: | , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-09-01
|
Series: | Robotics |
Subjects: | |
Online Access: | https://www.mdpi.com/2218-6581/9/4/76 |
id |
doaj-a4ee3850bcd3464fb9a9a62ea0a27712 |
---|---|
record_format |
Article |
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 |
work_keys_str_mv |
AT ahmadalattar kinematicmodelfreeorientationcontrolforrobotmanipulationusinglocallyweighteddualquaternions AT petarkormushev kinematicmodelfreeorientationcontrolforrobotmanipulationusinglocallyweighteddualquaternions |
_version_ |
1724647636850442240 |