Active visual object search using affordance-map in real world: A human-centric approach

Piyathilaka, L; Kodagoda, S

Active visual object search using affordance-map in real world: A human-centric approach

Piyathilaka, L

Kodagoda, S

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Publication Type:: Conference Proceeding
Citation:: 2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 1427 - 1432
Issue Date:: 2014-01-01

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Field	Value	Language
dc.contributor.author	Piyathilaka, L https://orcid.org/0000-0003-4676-9387	en_US
dc.contributor.author	Kodagoda, S https://orcid.org/0000-0001-5175-9138	en_US
dc.date.issued	2014-01-01	en_US
dc.identifier.citation	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014, 2014, pp. 1427 - 1432	en_US
dc.identifier.isbn	9781479951994	en_US
dc.identifier.uri	http://hdl.handle.net/10453/32236
dc.description.abstract	© 2014 IEEE. Human context is the most natural explanation why objects are placed and arranged in a particular order in an indoor environment. Usually, humans arrange objects in order to support their intended activities in a given environment. However, most of the common approaches for robotic object search involve modelling object-object relationships. In this paper, we hypothesize such relationships are centered around humans and bring human context to object search by modelling human-objects relationships through affordance-map. It identifies locations in a 3D map which support a particular affordance using virtual human models. Therefore, our approach does not require to observe real humans in the scene. The affordance-map and object-human-robot relationship are then used to infer the object search strategy. We tested our algorithm using a mobile robot that actively searched for the object 'computer monitors' in an office environment with promising results.	en_US
dc.relation.ispartof	2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014	en_US
dc.relation.isbasedon	10.1109/ICARCV.2014.7064525	en_US
dc.title	Active visual object search using affordance-map in real world: A human-centric approach	en_US
dc.type	Conference Proceeding
utslib.for	091303 Autonomous Vehicles	en_US
dc.location.activity	Singapore
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/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2014 IEEE. Human context is the most natural explanation why objects are placed and arranged in a particular order in an indoor environment. Usually, humans arrange objects in order to support their intended activities in a given environment. However, most of the common approaches for robotic object search involve modelling object-object relationships. In this paper, we hypothesize such relationships are centered around humans and bring human context to object search by modelling human-objects relationships through affordance-map. It identifies locations in a 3D map which support a particular affordance using virtual human models. Therefore, our approach does not require to observe real humans in the scene. The affordance-map and object-human-robot relationship are then used to infer the object search strategy. We tested our algorithm using a mobile robot that actively searched for the object 'computer monitors' in an office environment with promising results.

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http://hdl.handle.net/10453/32236