A Human-Robot Collaboration Framework for Improving Ergonomics During Dexterous Operation of Power Tools

Journal article (2021)

Authors

Wansoo Kim Istituto Italiano di Tecnologia
L. Peternel Human-Robot Interaction - Mechanical, Maritime and Materials Engineering
Marta Lorenzini Istituto Italiano di Tecnologia, Politecnico di Milano
Jan Babič Jozef Stefan Institute
Arash Ajoudani Istituto Italiano di Tecnologia
Research Group
Human-Robot Interaction (Mechanical, Maritime and Materials Engineering) (TU Delft)
Ergonomics Human-Robot Interaction Human performance modelling Industrial/organizational/workplace safety
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Published Date

2021

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Human-Robot Interaction

Abstract

In this work, we present a novel control approach to human-robot collaboration that takes into account ergonomic aspects of the human co-worker during power tool operations. The method is primarily based on estimating and reducing the overloading torques in the human joints that are induced by the manipulated external load. The human overloading joint torques are estimated and monitored using a whole-body dynamic state model. The appropriate robot motion that brings the human into the suitable ergonomic working configuration is obtained by an optimisation method that minimises the overloading joint torques. The proposed optimisation process includes several constraints, such as the human arm muscular manipulability and safety of the collaborative task, to achieve a task-relevant optimised configuration. We validated the proposed method by a user study that involved a human-robot collaboration task, where the subjects operated a polishing machine on a part that was brought to them by the collaborative robot. A statistical analysis of ten subjects as an experimental evaluation of the proposed control framework is provided to demonstrate the potential of the proposed control framework in enabling ergonomic and task-optimised human-robot collaboration.