IROS 2015 Paper Abstract


Paper WeAT1.5

Gao, Yixing (Imperial College London), Chang, Hyung Jin (Imperial College London), Demiris, Yiannis (Imperial College London)

User Modelling for Personalised Dressing Assistance by Humanoid Robots

Scheduled for presentation during the Regular session "Human-Robot Interaction 2" (WeAT1), Wednesday, September 30, 2015, 09:30−09:45, Saal D

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, Sept 28 - Oct 03, 2015, Congress Center Hamburg, Hamburg, Germany

This information is tentative and subject to change. Compiled on July 5, 2020

Keywords Human-Robot Interaction, Humanoid Interaction, Medical Systems, Healthcare, and Assisted Living


Assistive robots can improve the well-being of disabled or frail human users by reducing the burden that activities of daily living impose on them. To enable personalised assistance, such robots benefit from building a user-specific model, so that the assistance is customised to the particular set of user abilities. In this paper, we present an end-to-end approach for home-environment assistive humanoid robots to provide personalised assistance through a dressing application for users who have upper-body movement limitations. We use randomised decision forests to estimate the upper-body pose of users captured by a top-view depth camera, and model the movement space of upper-body joints using Gaussian mixture models. The movement space of each upper-body joint consists of regions with different reaching capabilities. We propose a method which is based on real-time upper-body pose and user models to plan robot motions for assistive dressing. We validate each part of our approach and test the whole system, allowing a Baxter humanoid robot to assist human to wear a sleeveless jacket.



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