Modular Fuzzy-Neuro Controller Driven by Spoken Language Commands

Pulasinghe, Koliya; Watanabe, Keigo; Izumi, Kiyotaka; Kiguchi, Kazuo

doi:10.1109/tsmcb.2003.811511

Cited by 48 publications

(32 citation statements)

References 11 publications

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“…Modularity, that is the purposeful separation into subsystems, has been found an attractive solution for this problem for robot controllers (Kaya & Alhajj, 2005) or speech recognition controller (Pulansinghe, Watanabe, Izumi, & Kiguchi, 2004).…”

Section: Timementioning

confidence: 99%

Modularity and Commonality Research: Past Developments and Future Opportunities

Fixson

2007

Concurrent Engineering

144

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Research on modularity and commonality has grown substantially over the past 15 years.Searching 36 journals over more than the past 35 years, I identify over 160 references in the engineering and management literature that focus on modularity or commonality in the product and process development context. Each of the references is analyzed along the dimensions subject, effect, and research method. The subjects of these studies have been products, processes, organizations, and even innovations, although the set of references shows a strong preference towards products. Similarly, a broad range of effects has been studied, albeit with the topic cost dominating all other effects. A variety of research methods has been applied to the study of modularity and commonality but the distribution of research methods differs substantially for modularity and commonality research. Despite the wealth of existing research, there are still significant opportunities for future research. In particular, studies that incorporate modularity and commonality's multiple effects on various players along the supply chain, that combine multiple research methods, and that follow systems over time appear very promising.

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Section: Timementioning

confidence: 99%

Modularity and Commonality Research: Past Developments and Future Opportunities

Fixson

2007

Concurrent Engineering

144

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“…However, sub-cluster 2 is focused on applications, challenges and user views, while Sub-cluster 8 covers technologies that make these robots possible. Voice recognition systems [85] and especially designed actuators [86] are found here.…”

Section: Appendix a Bibliometric Analysis Of Human-robot Interactionmentioning

confidence: 93%

Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase

Mejía

Kajikawa

2017

Applied Sciences

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Abstract:As robotics becomes ubiquitous, there is increasing interest in understanding how to develop robots that better respond to social needs, as well as how robotics impacts society. This is evidenced by the growing rate of publications on social robotics. In this article, we analyze the citation network of academic articles on social robotics to understand its structure, reveal research trends and expose its knowledgebase. We found eight major clusters, namely robots as social partners, human factors and ergonomics on human robot interaction, robotics for children's development, swarm robotics, emotion detection, assessment of robotic surgery, robots for the elderly and telepresence and human robot interaction in rescue robots. In addition, despite its social focus, social science literature as a source of knowledge is barely present. Research trends point to studies on applications, rather than to specific technologies or morphologies, and in particular, towards robots as partners, for child development and assistance for the elderly.

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“…However, the quantitative meanings of uncertain terms are fixed. Methods based on fuzzy inference systems for quantifying predetermined values for the uncertain terms in verbal instruction based on the current state of the robot have been proposed [12,13]. The method proposed in [14] adapts the meaning of uncertain information based on the immediate previous state of the robot.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Interpretation of Ambiguous Voice Instructions based on the Environment and the User’s Intention for Improved Human-Friendly Robot Navigation

2017

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Human-friendly interactive features are preferred for domestic service robots. Humans prefer to use verbal communication in order to convey instructions to peers. Those voice instructions often include uncertain terms such as "little" and "far". Therefore, the ability to quantify such information is mandatory for human-friendly service robots. The meaning of such voice instructions depends on the environment and the intention of the user. Therefore, this paper proposes a method in order to interpret the ambiguities in user instructions based on the environment and the intention of the user. The actual intention of the user is identified by analyzing the pointing gestures accompanied with the voice instructions since pointing gestures can be used in order to express the intention of the user. A module called the motion intention switcher (MIS) has been introduced in order to switch the intention of the robot based on the arrangement of the environment and the point referred by the gesture. Experiments have been carried out in an artificially-created domestic environment. According to the experimental results, the behavior of the MIS is effective in identifying the actual intention of the user and switching the intention of the robot. Moreover, the proposed concept is capable of enhancing the uncertain information evaluation ability of robots.

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Modular Fuzzy-Neuro Controller Driven by Spoken Language Commands

Cited by 48 publications

References 11 publications

Modularity and Commonality Research: Past Developments and Future Opportunities

Modularity and Commonality Research: Past Developments and Future Opportunities

Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase

Enhancing Interpretation of Ambiguous Voice Instructions based on the Environment and the User’s Intention for Improved Human-Friendly Robot Navigation

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