NDLI: Unsupervised learning of object affordances for planning in a mobile manipulation platform

Content Provider	IEEE Xplore Digital Library
Author	Ugur, E. Sahin, E. Oztop, E.
Copyright Year	2011
Description	Author affiliation: Cognitive Mechanisms Labs., Advanced Telecommunications Institute International, Kyoto, Japan (Oztop, E.) \|\| Biological ICT, National Institute of Information and Communication Technology, Kyoto, Japan (Ugur, E.) \|\| KOVAN Research Lab., Department of Computer Engineering, Middle East Technical University, Ankara, Turkey (Sahin, E.)
Abstract	In this paper, we use the notion of affordances, proposed in cognitive science, as a framework to propose a developmental method that would enable a robot to ground symbolic planning mechanisms in the continuous sensory-motor experiences of a robot. We propose a method that allows a robot to learn the symbolic relations that pertain to its interactions with the world and show that they can be used in planning. Specifically, the robot interacts with the objects in its environment using a pre-coded repertoire of behaviors and records its interactions in a triple that consist of the initial percept of the object, the behavior applied and its effect, defined as the difference between the initial and the final percept. The method allows the robot to learn object affordance relations which can be used to predict the change in the percept of the object when a certain behavior is applied. These relations can then be used to develop plans using forward chaining. The method is implemented and evaluated on a mobile robot system with limited object manipulation capabilities. We have shown that the robot is able to learn the physical affordances of objects from range images and use them to build symbols and relations that can be used in making multi-step predictions about the affordances of objects and achieve complex goals.
Starting Page	4312
Ending Page	4317
File Size	559514
Page Count	6
File Format	PDF
ISBN	9781612843865
ISSN	10504729
e-ISBN	9781612843858
DOI	10.1109/ICRA.2011.5979677
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-09
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robot sensing systems Accuracy Planning Training Support vector machines Three dimensional displays
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Monitoring of manipulation activities for a service robot using supervised learning

Transparent object detection and reconstruction on a mobile platform

Navigation in three-dimensional cluttered environments for mobile manipulation

Using Object Affordances to Improve Object Recognition

Improving point-cloud accuracy from a moving platform in field operations

Going beyond the perception of affordances: Learning how to actualize them through behavioral parameters

Multilevel part-based model for object manipulation

Joint detection and tracking of boundaries using cooperative mobile sensor networks

Creating household environment map for environment manipulation using color range sensors on environment and robot

Unsupervised learning of object affordances for planning in a mobile manipulation platform

Similar Documents

Monitoring of manipulation activities for a service robot using supervised learning

Transparent object detection and reconstruction on a mobile platform

Navigation in three-dimensional cluttered environments for mobile manipulation

Using Object Affordances to Improve Object Recognition

Improving point-cloud accuracy from a moving platform in field operations

Going beyond the perception of affordances: Learning how to actualize them through behavioral parameters

Multilevel part-based model for object manipulation

Joint detection and tracking of boundaries using cooperative mobile sensor networks

Creating household environment map for environment manipulation using color range sensors on environment and robot

Unsupervised learning of object affordances for planning in a mobile manipulation platform