A Graphical Model for unifying tracking and classification within a multimodal Human-Robot Interaction scenario

Rehrl, Tobias; Gast, Jürgen; Theißing, Nikolaus; Bannat, Alexander; Arsic, D.; Wallhoff, Frank; Rigoll, Gerhard; Mayer, Christoph; Radig, Bernd

doi:10.1109/cvprw.2010.5543751

Cited by 1 publication

(1 citation statement)

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“…For the most reliable communication between robot and human, multimodal interfaces are used these days. In those interfaces for the interaction the principles of multiple senses, most often hearing and sight, are used [2,3]. In general, unimodal interaction, mainly based on recognition of acoustic signals has lower requirements for technical equipment and computational complexity.…”

Section: Introductionmentioning

confidence: 99%

Voice Command Recognition in Multirobot Systems: Information Fusion

Micek

Hyben

Fratrik

et al. 2012

International Journal of Advanced Robotic Systems

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Recent Multirobot systems (MRS) are moving from theoretical considerations and from development and research centres to the area of practical applications. The solutions to real practical problems bring new challenges which are derived from actual requirements, while they are also interesting from theoretical point of view. One of the interesting areas of investigation is the problem of distributed data processing by limited computing and communicationperformance of individual components in MRS. In this article, the authors try to demonstrate, using a simple example, the possibilities of distributed solution of classification tasks. Such questions as: - To what extent it is appropriate to distribute the tasks among individual elements of the system and to what extent to minimalize the requests on the communication subsystem? - Is it more appropriate, in the design concept of distributed data processing, to use a data fusion system, features fusion or decision fusion? are not universally solvable. Therefore, we refrain from the analytical analysis and the choice of appropriate level of information fusion, but in four different scenarios we focus on solving ‘voice command recognition‘ ‐ we would like to show the advantages and disadvantages of individual approaches. The experiments described and the results achieved are based on simulation experiments and verified by experimental and demonstrative MRS

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Section: Introductionmentioning

confidence: 99%