碩士 / 國立彰化師範大學 / 數位學習研究所 / 97 / In this study, an intelligent navigation system is developed by using fuzzy logic and Cell Assemblies (CAs) approaches and various kinds of sensors in accordance with human behavior are imported. Since disaster areas may be extremely dangerous and broad, it is important to make the robot’s movement be safer and more efficient; therefore, two models based on different purposes are designed. More specifically, ‘Robot navigation’ model implemented by fuzzy logic is applied to a narrow or dark place while ‘intelligent cognitive’ model is utilized in intelligent direction change in an open area by integrating vision camera.
In particular, the intelligent cognitive model that is implemented by CAs with fatiguing Leaky Integrate and Fire (fLIF) neurons absorb the ideals of working and long-term memory to imitate the cognitive processes of human. Additionally, there is no difficulty to combine and expand this model to be multi-functional, which makes it the same as human learning.
In this study, the clever combination of sensors significantly reduces the frequency of using vision and imaging processing. Furthermore, the combined system can avoid potential risk and efficiently shorten the motion time by importing the video camera. This system has been tested in several simulated schemes of environments and the experimental results have proved that it can not only produce right action commands regarding different schemes but also improve the motion path effectively to meet the requirements of disaster relieving.
| Identifer | oai:union.ndltd.org:TW/097NCUE5395005 |
| Date | January 2009 |
| Creators | Mingyao Huang, 黃明堯 |
| Contributors | Yufang Cheng, 程于芳 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 66 |
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