• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1297-1300
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• 1993

Machine learning in an uncertain or unknown environment is of vital interest to those working with intelligent systems. The ability to garner new information, process it, and increase the understanding/ capability of the machine is crucial to the performance of autonomous systems. The field of artificial intelligence provides two major approaches to the problem of knowledge engineering-expert systems and neural networks. Harnessing the power of these two techniques in a hybrid, cooperating system holds great promise.

• 제어로봇시스템학회논문지
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• 제19권11호
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• pp.1036-1042
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• 2013

In this paper, an elderly assistance system is developed based on Xenomai, a real-time development framework cooperating with the Linux kernel. A Kinect sensor is used to recognize the behavior of the elderly and A-star search algorithm is implemented to find the shortest path to the person. The mobile robot also generates a trajectory using a digital convolution operator which is based on a Bezier curve for smooth driving. In order to follow the generated trajectory within the control period, we developed real-time tasks and compared the performance of the tracking trajectory with that of non real-time tasks. The real-time task has a better result on following the trajectory within the physical constraints which means that it is more appropriate to apply to an elderly assistant system.