Personalized Robot-assisted Dressing using User Modeling in Latent Spaces

File Description SizeFormat 
2017-iros.pdfAccepted version2.55 MBAdobe PDFDownload
Title: Personalized Robot-assisted Dressing using User Modeling in Latent Spaces
Author(s): Zhang, F
Cully, A
Demiris, YIANNIS
Item Type: Conference Paper
Abstract: Robots have the potential to provide tremendous support to disabled and elderly people in their everyday tasks, such as dressing. Many recent studies on robotic dressing assistance usually view dressing as a trajectory planning problem. However, the user movements during the dressing process are rarely taken into account, which often leads to the failures of the planned trajectory and may put the user at risk. The main difficulty of taking user movements into account is caused by severe occlusions created by the robot, the user, and the clothes during the dressing process, which prevent vision sensors from accurately detecting the postures of the user in real time. In this paper, we address this problem by introducing an approach that allows the robot to automatically adapt its motion according to the force applied on the robot's gripper caused by user movements. There are two main contributions introduced in this paper: 1) the use of a hierarchical multi-task control strategy to automatically adapt the robot motion and minimize the force applied between the user and the robot caused by user movements; 2) the online update of the dressing trajectory based on the user movement limitations modeled with the Gaussian Process Latent Variable Model in a latent space, and the density information extracted from such latent space. The combination of these two contributions leads to a personalized dressing assistance that can cope with unpredicted user movements during the dressing while constantly minimizing the force that the robot may apply on the user. The experimental results demonstrate that the proposed method allows the Baxter humanoid robot to provide personalized dressing assistance for human users with simulated upper-body impairments.
Publication Date: 14-Dec-2017
Date of Acceptance: 14-Jun-2017
URI: http://hdl.handle.net/10044/1/56559
DOI: https://dx.doi.org/10.1109/IROS.2017.8206206
ISSN: 2153-0866
Publisher: IEEE
Journal / Book Title: Proceedings of 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Copyright Statement: © 2017 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.
Conference Name: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Publication Status: Published
Start Date: 2017-09-24
Finish Date: 2017-09-28
Conference Place: Vancouver, Canada
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering



Items in Spiral are protected by copyright, with all rights reserved, unless otherwise indicated.

Creative Commons