BWIBots: A platform for bridging the gap between AI and human–robot interaction research
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- Piyush Khandelwal
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Shiqi Zhang
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Jivko Sinapov
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Matteo Leonetti
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Jesse Thomason
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Fangkai Yang
- Schlumberger Software Technology, TX, USA
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- Ilaria Gori
- Electrical and Computer Engineering, University of Texas at Austin, TX, USA
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- Maxwell Svetlik
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Priyanka Khante
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Vladimir Lifschitz
- Department of Computer Science, University of Texas at Austin, TX, USA
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- J. K. Aggarwal
- Electrical and Computer Engineering, University of Texas at Austin, TX, USA
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- Raymond Mooney
- Department of Computer Science, University of Texas at Austin, TX, USA
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- Peter Stone
- Department of Computer Science, University of Texas at Austin, TX, USA
説明
<jats:p> Recent progress in both AI and robotics have enabled the development of general purpose robot platforms that are capable of executing a wide variety of complex, temporally extended service tasks in open environments. This article introduces a novel, custom-designed multi-robot platform for research on AI, robotics, and especially human–robot interaction for service robots. Called BWIBots, the robots were designed as a part of the Building-Wide Intelligence (BWI) project at the University of Texas at Austin. The article begins with a description of, and justification for, the hardware and software design decisions underlying the BWIBots, with the aim of informing the design of such platforms in the future. It then proceeds to present an overview of various research contributions that have enabled the BWIBots to better (a) execute action sequences to complete user requests, (b) efficiently ask questions to resolve user requests, (c) understand human commands given in natural language, and (d) understand human intention from afar. The article concludes with a look forward towards future research opportunities and applications enabled by the BWIBot platform. </jats:p>
収録刊行物
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- The International Journal of Robotics Research
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The International Journal of Robotics Research 36 (5-7), 635-659, 2017-02-08
SAGE Publications