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An assistive decision-and-control architecture for force-sensitive hand–arm systems driven by human–machine interfaces

Vogel, Jörn and Haddadin, Sami and Jarosiewicz, Beata and Simeral, John D. and Bacher, Daniel and Hochberg, Leigh R. and Donoghue, John P. and Smagt van der, Patrick (2015) An assistive decision-and-control architecture for force-sensitive hand–arm systems driven by human–machine interfaces. The International Journal of Robotics Research, 34 (6). SAGE Publications. doi: 10.1177/0278364914561535. ISSN 0278-3649.

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Official URL: http://ijr.sagepub.com/content/34/6/763.full


Fully autonomous applications of modern robotic systems are still constrained by limitations in sensory data processing, scene interpretation, and automated reasoning. However, their use as assistive devices for people with upper-limb disabilities has become possible with recent advances in “soft robotics”, that is, interaction control, physical human–robot interaction, and reflex planning. In this context, impedance and reflex-based control has generally been understood to be a promising approach to safe interaction robotics. To create semi-autonomous assistive devices, we propose a decision-and-control architecture for hand–arm systems with “soft robotics” capabilities, which can then be used via human–machine interfaces (HMIs). We validated the functionality of our approach within the BrainGate2 clinical trial, in which an individual with tetraplegia used our architecture to control a robotic hand–arm system under neural control via a multi-electrode array implanted in the motor cortex. The neuroscience results of this research have previously been published by Hochberg et al. In this paper we present our assistive decision-and-control architecture and demonstrate how the semi-autonomous assistive behavior can help the user. In our framework the robot is controlled through a multi-priority Cartesian impedance controller and its behavior is extended with collision detection and reflex reaction. Furthermore, virtual workspaces are added to ensure safety. On top of this we employ a decision-and-control architecture that uses sensory information available from the robotic system to evaluate the current state of task execution. Based on a set of available assistive skills, our architecture provides support in object interaction and manipulation and thereby enhances the usability of the robotic system for use with HMIs. The goal of our development is to provide an easy-to-use robotic system for people with physical disabilities and thereby enable them to perform simple tasks of daily living. In an exemplary real-world task, the participant was able to serve herself a beverage autonomously for the first time since her brainstem stroke, which she suffered approximately 14 years prior to this research.

Item URL in elib:https://elib.dlr.de/100631/
Document Type:Article
Title:An assistive decision-and-control architecture for force-sensitive hand–arm systems driven by human–machine interfaces
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Vogel, JörnUNSPECIFIEDhttps://orcid.org/0000-0002-1987-0028UNSPECIFIED
Jarosiewicz, BeataBrown UniversityUNSPECIFIEDUNSPECIFIED
Simeral, John D.Brown UniversityUNSPECIFIEDUNSPECIFIED
Bacher, DanielBrown UniversityUNSPECIFIEDUNSPECIFIED
Hochberg, Leigh R.Brown UniversityUNSPECIFIEDUNSPECIFIED
Donoghue, John P.Brown UniversityUNSPECIFIEDUNSPECIFIED
Smagt van der, PatrickTechnische Universität MünchenUNSPECIFIEDUNSPECIFIED
Date:May 2015
Journal or Publication Title:The International Journal of Robotics Research
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
Publisher:SAGE Publications
Keywords:assistive robotics, medical robotics, brain machine interfaces
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Terrestrial Assistance Robotics (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Robotics and Mechatronics (since 2013)
Deposited By: Vogel, Jörn
Deposited On:08 Dec 2015 13:26
Last Modified:06 Nov 2023 09:33

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