Augmented reality-assisted reconfiguration and workspace visualization of malleable robots: workspace modification through holographic guidance
File(s)Augmented reality malleable robots (Final version).pdf (3.2 MB)
Accepted version
Author(s)
Ranne, Alex
Clark, Angus Benedict
Rojas, Nicolas
Type
Journal Article
Abstract
Malleable robots are a type of reconfigurable serial robot capable of adapting their topology, through the use of variable stiffness malleable links, to desired tasks and workspaces by varying the relative positioning between their revolute joints. However, their reconfiguration is nontrivial, lacking intuitive communication between the human and the robot, and a method of efficiently aligning the end effector to a desired position. In this article, we present the design of an interactive augmented reality (AR) alignment interface, which helps a malleable robot understand the user’s task requirements, visualizes to the user the requested robot’s configuration and its workspace, and guides the user in reconfiguring the robot to achieve that configuration. Through motion tracking of a physical two degree-of-freedom (2 DoF) malleable robot, which can achieve an infinite number of workspaces, we compute the accuracy of the system in terms of initial calibration and overall accuracy, and demonstrate its viability. The results demonstrated a good performance, with an average repositioning accuracy of 9.64 ± 2.06 mm and an average base alignment accuracy of 10.54 ± 4.32 mm in an environment the size of 2,000 mm × 2,000 mm × 1,200 mm.
Date Issued
2022-01-31
Date Acceptance
2021-12-09
Citation
IEEE Robotics & Automation Magazine, 2022, 29 (1), pp.2-13
ISSN
1070-9932
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Start Page
2
End Page
13
Journal / Book Title
IEEE Robotics & Automation Magazine
Volume
29
Issue
1
Copyright Statement
© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
UKRI Centre for Doctoral Training in AI for Healthcare
Identifier
https://ieeexplore.ieee.org/document/9696302
Grant Number
EP/S023283/1
Subjects
Science & Technology
Technology
Automation & Control Systems
Robotics
TELEOPERATION
NAVIGATION
0801 Artificial Intelligence and Image Processing
0906 Electrical and Electronic Engineering
0913 Mechanical Engineering
Industrial Engineering & Automation
Publication Status
Published online
Date Publish Online
2022-01-31