Paper Info
Title
Programming by demonstration of probabilistic decision making on a multi-modal service robot
Abstract
In this paper we propose a process which is able to generate abstract service robot mission representations, utilized during execution for autonomous, probabilistic decision making, by observing human demonstrations. The observation process is based on the same perceptive components as used by the robot during execution, recording dialog between humans, human motion as well as objects poses. This leads to a natural, practical learning process, avoiding extra demonstration centers or kinesthetic teaching. By generating mission models for probabilistic decision making as Partially observable Markov decision processes, the robot is able to deal with uncertain and dynamic environments, as encountered in real world settings during execution. Service robot missions in a cafeteria setting, including the modalities of mobility, natural human-robot interaction and object grasping, have been learned and executed by this system.
Year
DOI
Venue
2010
10.1109/IROS.2010.5652268
Intelligent Robots and Systems
Keywords
Field
DocType
Markov processes,decision making,dexterous manipulators,human-robot interaction,learning (artificial intelligence),multi-robot systems,probability,service robots,human demonstrations,human-robot interaction,kinesthetic teaching,learning process,multi-modal service robot,object grasping,partially observable Markov decision processes,probabilistic decision making
Programming by demonstration,Social robot,Computer vision,Computer science,Robot kinematics,Markov decision process,Artificial intelligence,Probabilistic logic,Robot,Human–robot interaction,Service robot
Conference
ISSN
ISBN
Citations 
2153-0858
978-1-4244-6674-0
3
PageRank 
References 
Authors
0.44
10
5
Name
Order
Citations
PageRank
Sven R. Schmidt-Rohr11038.80
Martin Lösch2826.35
Rainer Jäkel3635.99
Rüdiger Dillmann42201262.95
Schmidt-Rohr, S.R.581.92