Predicting and Optimizing Ergonomics in Physical Human-Robot Cooperation Tasks

Linda van der Spaa, Michael Gienger, Tamas Bates, Jens Kober

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
9 Downloads (Pure)

Abstract

This paper presents a method to incorporate ergonomics into the optimization of action sequences for bi-manual human-robot cooperation tasks with continuous physical interaction. Our first contribution is a novel computational model of the human that allows prediction of an ergonomics assessment corresponding to each step in a task. The model is learned from human motion capture data in order to predict the human pose as realistically as possible. The second contribution is a combination of this prediction model with an informed graph search algorithm, which allows computation of human-robot cooperative plans with improved ergonomics according to the incorporated method for ergonomic assessment. The concepts have been evaluated in simulation and in a small user study in which the subjects manipulate a large object with a 32 DoF bimanual mobile robot as partner. For all subjects, the ergonomic-enhanced planner shows their reduced ergonomic cost compared to a baseline planner.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Robotics and Automation, ICRA 2020
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages1799-1805
ISBN (Electronic)978-1-7281-7395-5
DOIs
Publication statusPublished - 2020
Event2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France
Duration: 31 May 202031 Aug 2020

Conference

Conference2020 IEEE International Conference on Robotics and Automation, ICRA 2020
CountryFrance
CityParis
Period31/05/2031/08/20

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