Title:
Task-Learning Policies for Collaborative Task Solving in Human-Robot Interaction
Task-Learning Policies for Collaborative Task Solving in Human-Robot Interaction
dc.contributor.author | Park, Hae Won | |
dc.contributor.corporatename | Georgia Institute of Technology. Institute for Robotics and Intelligent Machines | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. Human-Automation Systems Lab | en_US |
dc.contributor.corporatename | Georgia Institute of Technology. School of Electrical and Computer Engineering | en_US |
dc.date.accessioned | 2016-04-20T15:17:14Z | |
dc.date.available | 2016-04-20T15:17:14Z | |
dc.date.issued | 2012 | |
dc.description | Copyright ©2012 ACM | en_US |
dc.description | DOI: 10.1145/2388676.2388752 | |
dc.description.abstract | The objective of this doctoral research is to design multimodal task-learning policies for a robotic system that targets the exchange of task rules between humans and robots. This objective is achieved through a collaborative task application during human-robot interaction where the two partners learn a task from each other and accomplish a shared goal. As a first step, a method to model human-action primitives using a pattern-recognition technique is presented. Next, algorithms are developed to generate turn-taking strategies in response to human task behaviors. The contribution of this work is in engaging robots with humans in collaborative play task by modeling statistical patterns of play behaviors and reusing previously learned knowledge to reduce the decision process. Here, results of previous work are presented, and remaining works including deploying a physically embodied agent and developing an evaluation platform are outlined. | en_US |
dc.embargo.terms | null | en_US |
dc.identifier.citation | Park, H. W. (2012). Task-Learning Policies for Collaborative Task Solving in Human-Robot Interaction. Proceedings of the 14th ACM international Conference on Multimodal Interaction (ICMI '12), pp. 341-344. | en_US |
dc.identifier.doi | 10.1145/2388676.2388752 | |
dc.identifier.isbn | 978-1-4503-1467-1 | |
dc.identifier.uri | http://hdl.handle.net/1853/54748 | |
dc.language.iso | en_US | en_US |
dc.publisher | Georgia Institute of Technology | en_US |
dc.publisher.original | Association for Computing Machinery | |
dc.subject | Collaborative task learning and solving | en_US |
dc.subject | Human-robot interaction | en_US |
dc.title | Task-Learning Policies for Collaborative Task Solving in Human-Robot Interaction | en_US |
dc.type | Text | |
dc.type.genre | Proceedings | |
dspace.entity.type | Publication | |
local.contributor.corporatename | School of Civil and Environmental Engineering | |
local.contributor.corporatename | Institute for Robotics and Intelligent Machines (IRIM) | |
relation.isOrgUnitOfPublication | 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c | |
relation.isOrgUnitOfPublication | 66259949-abfd-45c2-9dcc-5a6f2c013bcf |
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