English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/97434
Share/Impact:
Statistics
logo share SHARE   Add this article to your Mendeley library MendeleyBASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Title

Planning surface cleaning tasks by learning uncertain drag actions outcomes

AuthorsMartínez, David ; Alenyà, Guillem ; Torras, Carme
Issue Date2013
CitationProceedings of the 1st Workshop on Planning and Robotics: 106-111 (2013)
AbstractA method to perform cleaning tasks is presented where a robot manipulator autonomously grasps a textile and uses different dragging actions to clean a surface. Actions are imprecise, and probabilistic planning is used to select the best sequence of actions. The characterization of such actions is complex because the initial autonomous grasp of the textile introduces differences in the initial conditions that change the efficacy of the robot cleaning actions. We demonstrate that the action outcome probabilities can be learned very fast while the task is being executed, so as to progressively improve robot performance. The learner adds only a little overhead to the system compared to the improvements obtained. Experiments with a real robot show that the most effective plan varies depending on the initial grasp, and that plans become better after only a few learning iterations.
DescriptionPresentado al 23rd ICAPS (Workshop on PlanRob) 2013 celebrado en Roma del 10 al 14 de junio.
Publisher version (URL)http://icaps13.icaps-conference.org/
URIhttp://hdl.handle.net/10261/97434
Appears in Collections:(IRII) Comunicaciones congresos
Files in This Item:
File Description SizeFormat 
Planning surface.pdf170,65 kBUnknownView/Open
Show full item record
Review this work
 


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.