Learning by demonstration for co-operative navigation with assistive mobility devices

Poon, J; Miro, JV

Learning by demonstration for co-operative navigation with assistive mobility devices

Poon, J Miro, JV

Permalink

Publication Type:: Conference Proceeding
Citation:: Australasian Conference on Robotics and Automation, ACRA, 2015
Issue Date:: 2015-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published versionAdobe PDF (853.32 kB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Poon, J	en_US
dc.contributor.author	Miro, JV https://orcid.org/0000-0002-0083-7797	en_US
dc.date.available	2015-10-19	en_US
dc.date.issued	2015-01-01	en_US
dc.identifier.citation	Australasian Conference on Robotics and Automation, ACRA, 2015	en_US
dc.identifier.issn	1448-2053	en_US
dc.identifier.uri	http://hdl.handle.net/10453/44214
dc.description.abstract	This work proposes a learning by demonstration framework for intuitive navigational adaptation of human-robot interactive mobile systems. Co-navigation algorithms for mobile robots tend to be highly parameterised with variables that may be difficult to manually con- figure to an individual user's desired behaviours by non-Technical personnel, e.g. carers and therapists overseing activities with would-be intelligent power mobility devices. The proposed framework automatically learns suitable joy- stick inputs for safe handling of the platform from a healthy user aware of a desired subset of behaviours (generic collision avoidance, wall- following and forward/reverse alignment manoeuvres) through performance of a small set of elementary training exercises, without the need and risk associated to trial-And-error vari\able tuning. The paper compares the semi-Autonomous capability of the proposed learning scheme with the popular Vector Field Histogram local planner in a corridor navigation task, showing its ability to safely generalise to different environments despite the simplicity of the training demonstrations.	en_US
dc.relation.ispartof	Australasian Conference on Robotics and Automation, ACRA	en_US
dc.title	Learning by demonstration for co-operative navigation with assistive mobility devices	en_US
dc.type	Conference Proceeding
utslib.for	091303 Autonomous Vehicles	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Students
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

This work proposes a learning by demonstration framework for intuitive navigational adaptation of human-robot interactive mobile systems. Co-navigation algorithms for mobile robots tend to be highly parameterised with variables that may be difficult to manually con- figure to an individual user's desired behaviours by non-Technical personnel, e.g. carers and therapists overseing activities with would-be intelligent power mobility devices. The proposed framework automatically learns suitable joy- stick inputs for safe handling of the platform from a healthy user aware of a desired subset of behaviours (generic collision avoidance, wall- following and forward/reverse alignment manoeuvres) through performance of a small set of elementary training exercises, without the need and risk associated to trial-And-error vari\able tuning. The paper compares the semi-Autonomous capability of the proposed learning scheme with the popular Vector Field Histogram local planner in a corridor navigation task, showing its ability to safely generalise to different environments despite the simplicity of the training demonstrations.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/44214