A context-aware approach in realization of socially intelligent industrial robots |
| |
| Affiliation: | 1. Rabin Medical Center, Petach Tikva, Israel;2. Faculty of Medicine, Tel Aviv University, Israel;3. Princess Margaret Cancer Centre, Toronto, Canada;4. Department of Medicine, University of Toronto, Toronto, Canada;5. Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Canada;1. Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA;2. Center for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA;3. Center for Infection and Inflammation Imaging Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA;4. Department of Pharmacy, Johns Hopkins University School of Medicine, Baltimore, MD, USA;5. Russell H Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA;6. Department of Hospital Epidemiology and Infection Control, Johns Hopkins University School of Medicine, Baltimore, MD, USA;7. Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA;8. Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA;9. Howard County Health Department, Columbia, MD, USA;10. Maryland Department of Health and Mental Hygiene, Laboratories Administration, Baltimore, MD, USA;11. National Jewish Health Mycobacteriology Laboratory, Denver, CO, USA;12. Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA;1. School of Science, Wuhan University of Technology, Wuhan 430070, China;2. School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China |
| |
| Abstract: | Contemporary industrial environments are usually constrained or limited in order to fit a fast, cheap and non-error prone production. Human-like system capabilities are not generally desirable there. But, recent trends in industrial robotics demand robust, flexible and efficient robots with a certain level of autonomy. Therefore, new and different approaches and perspectives in designing of industrial facilities are required.This paper reveals how a context-based reasoning can be used to achieve an intelligent robot group behavior. In order to achieve adaptivity, self-recovery or scalability of the system, a COgnitive MOdel for the Robot group control (COMOR) is developed. COMOR can be understood as an interpreter used to transform high-level context to low-level data, allowing machines to make context-based decisions.COMOR has three main parts and relies on a simulated Social Capital phenomenon as a feature of people. The first part is used to collect significant information from the environment. The second part is used to provide a set of possible solutions respecting the semantic domain description. The last part of COMOR is used to provide a behavioral component ensuring an optimal solution to given environmental conditions. |
| |
| Keywords: | Cognitive robotics Context-awareness Probabilistic graphical models Ontology Ubiquitous computing |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
