Integrated Intelligence for Human-Robot Teams
| Autor: | Thomas M. Howard, Menglong Zhu, Luis E. Navarro-Serment, Arne Suppe, Anthony Stentz, Robert Dean, Terence Keegan, Kostas Daniilidis, Barry A. Bodt, Nicholas Roy, Jianbo Shi, Craig Lennon, Felix Duvallet, Christian Lebiere, Marshal Childers, Jerry Vinokurov, Sangdon Park, Martial Hebert, Jean Oh, Abdeslam Boularias, Daniel Barber, Oscar J. Romero, Matthew R. Walter |
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| Rok vydání: | 2017 |
| Předmět: |
Computer science
business.industry media_common.quotation_subject Context (language use) Robotics Mobile robot 02 engineering and technology 01 natural sciences Human–robot interaction 010309 optics Symbol grounding Human–computer interaction Perception 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing Artificial intelligence business Natural language media_common |
| Zdroj: | Springer Proceedings in Advanced Robotics ISBN: 9783319501147 ISER |
| Popis: | With recent advances in robotics technologies and autonomous systems, the idea of human-robot teams is gaining ever-increasing attention. In this context, our research focuses on developing an intelligent robot that can autonomously perform non-trivial, but specific tasks conveyed through natural language. Toward this goal, a consortium of researchers develop and integrate various types of intelligence into mobile robot platforms, including cognitive abilities to reason about high-level missions, perception to classify regions and detect relevant objects in an environment, and linguistic abilities to associate instructions with the robot’s world model and to communicate with human teammates in a natural way. This paper describes the resulting system with integrated intelligence and reports on the latest assessment. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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