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A General Framework for Incremental Processing of Multimodal Inputs
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-9437-6599
Mälardalen University, School of Innovation, Design and Engineering.
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0002-5224-8302
Mälardalen University, School of Innovation, Design and Engineering.ORCID iD: 0000-0001-5141-7242
2011 (English)In: Proceedings of the 13th international conference on multimodal interfaces, New York: ACM Press, 2011, 225-228 p.Conference paper, Published paper (Refereed)
Abstract [en]

Humans employ different information channels (modalities) such as speech, pictures and gestures in their commu- nication. It is believed that some of these modalities are more error-prone to some specific type of data and therefore multimodality can help to reduce ambiguities in the interaction. There have been numerous efforts in implementing multimodal interfaces for computers and robots. Yet, there is no general standard framework for developing them. In this paper we propose a general framework for implementing multimodal interfaces. It is designed to perform natural language understanding, multi- modal integration and semantic analysis with an incremental pipeline and includes a multimodal grammar language, which is used for multimodal presentation and semantic meaning generation.

Place, publisher, year, edition, pages
New York: ACM Press, 2011. 225-228 p.
Identifiers
URN: urn:nbn:se:mdh:diva-13586DOI: 10.1145/2070481.2070521Scopus ID: 2-s2.0-83455176699ISBN: 978-1-4503-0641-6 (print)OAI: oai:DiVA.org:mdh-13586DiVA: diva2:466129
Conference
International Conference on Multimodal Interaction - ICMI 2011
Available from: 2011-12-15 Created: 2011-12-15 Last updated: 2015-06-26Bibliographically approved
In thesis
1. Human Robot Interaction Solutions for Intuitive Industrial Robot Programming
Open this publication in new window or tab >>Human Robot Interaction Solutions for Intuitive Industrial Robot Programming
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Over the past few decades the use of industrial robots has increased the efficiency as well as competitiveness of many companies. Despite this fact, in many cases, robot automation investments are considered to be technically challenging. In addition, for most small and medium sized enterprises (SME) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods for industrial robots are too complex for an inexperienced robot programmer, thus assistance from a robot programming expert is often needed.  We hypothesize that in order to make industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis we propose a high-level natural language framework for interacting with industrial robots through an instructional programming environment for the user.  The ultimate goal of this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.In this thesis we mainly address two issues. The first issue is to make interaction with a robot easier and more natural through a multimodal framework. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than programming issues of the robot. This approach shifts the focus of industrial robot programming from the coordinate based programming paradigm, which currently dominates the field, to an object based programming scheme.The second issue addressed is a general framework for implementing multimodal interfaces. There have been numerous efforts to implement multimodal interfaces for computers and robots, but there is no general standard framework for developing them. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline and includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2012. 94 p.
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 149
Keyword
huamn robot interaction, industrial robots, intuitive programming
National Category
Robotics
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-14315 (URN)978-91-7485-060-4 (ISBN)
Presentation
2012-03-28, Lambda, Högskoleplan 1, Rosenhil, Västerås, 13:15 (English)
Opponent
Supervisors
Projects
robot colleague project
Available from: 2012-03-07 Created: 2012-03-07 Last updated: 2015-01-14Bibliographically approved
2. Planning and Sequencing Through Multimodal Interaction for Robot Programming
Open this publication in new window or tab >>Planning and Sequencing Through Multimodal Interaction for Robot Programming
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Over the past few decades the use of industrial robots has increased the efficiency as well as the competitiveness of several sectors. Despite this fact, in many cases robot automation investments are considered to be technically challenging. In addition, for most small and medium-sized enterprises (SMEs) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods of industrial robots are too complex for most technicians or manufacturing engineers, and thus assistance from a robot programming expert is often needed. The hypothesis is that in order to make the use of industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis, a novel system for task-level programming is proposed. The user interacts with an industrial robot by giving instructions in a structured natural language and by selecting objects through an augmented reality interface. The proposed system consists of two parts: (i) a multimodal framework that provides a natural language interface for the user to interact in which the framework performs modality fusion and semantic analysis, (ii) a symbolic planner, POPStar, to create a time-efficient plan based on the user's instructions. The ultimate goal of this work in this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.This thesis mainly addresses two issues. The first issue is a general framework for designing and developing multimodal interfaces. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline. The framework also includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation. Such a framework helps us to make interaction with a robot easier and more natural. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high-level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than the programming issues of the robot. The second issue addressed is due to inherent characteristics of communication with the use of natural language; instructions given by a user are often vague and may require other actions to be taken before the conditions for applying the user's instructions are met. In order to solve this problem a symbolic planner, POPStar, based on a partial order planner (POP) is proposed. The system takes landmarks extracted from user instructions as input, and creates a sequence of actions to operate the robotic cell with minimal makespan. The proposed planner takes advantage of the partial order capabilities of POP to execute actions in parallel and employs a best-first search algorithm to seek the series of actions that lead to a minimal makespan. The proposed planner can also handle robots with multiple grippers, parallel machines as well as scheduling for multiple product types.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2014. 164 p.
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 166
Keyword
human robot interaction, industrial robots, planning, multimodal interaction
National Category
Engineering and Technology Computer Science Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-26474 (URN)978-91-7485-175-5 (ISBN)
Public defence
2014-12-08, Gamma, Mälardalens högskola, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2014-11-06 Created: 2014-11-06 Last updated: 2014-11-27Bibliographically approved

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