Learning symbolic representations of actions from human demonstrations

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Title: Learning symbolic representations of actions from human demonstrations
Authors: Ahmadzadeh, SR
Paikan, A
Mastrogiovanni, F
Natale, L
Kormushev, P
Caldwell, DG
Item Type: Conference Paper
Abstract: In this paper, a robot learning approach is pro- posed which integrates Visuospatial Skill Learning, Imitation Learning, and conventional planning methods. In our approach, the sensorimotor skills (i.e., actions) are learned through a learning from demonstration strategy. The sequence of per- formed actions is learned through demonstrations using Visu- ospatial Skill Learning. A standard action-level planner is used to represent a symbolic description of the skill, which allows the system to represent the skill in a discrete, symbolic form. The Visuospatial Skill Learning module identifies the underlying constraints of the task and extracts symbolic predicates (i.e., action preconditions and effects), thereby updating the planner representation while the skills are being learned. Therefore the planner maintains a generalized representation of each skill as a reusable action, which can be planned and performed inde- pendently during the learning phase. Preliminary experimental results on the iCub robot are presented.
Issue Date: 31-May-2015
Date of Acceptance: 30-Jan-2015
URI: http://hdl.handle.net/10044/1/26178
DOI: http://dx.doi.org/10.1109/ICRA.2015.7139728
Publisher: IEEE
Start Page: 3801
End Page: 3808
Journal / Book Title: Proc. IEEE Intl Conf. on Robotics and Automation (ICRA 2015)
Copyright Statement: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Conference Name: ICRA 2015
Start Date: 2015-05-26
Finish Date: 2015-05-30
Conference Place: Seattle, Washington
Appears in Collections:Dyson School of Design Engineering

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