Research On Intelligent Navigation System Of BCI Based Bio-robot

Brain-Computer Interface (BCI), studies at how to enable the communication between brain and outside environment in unnatural way. It offers brain and the environment a two-way channel of information transmission, biosensor input outside information to the brain nervous system. Neural Signals can also be used to control external electronic mechanical devices. The technology could be used in restoring, improving or expanding the existing nervous system function, which gives a new interactive information model.Bio-robot means that we can use animals to complete expertise that are not convenient for people to do or people are afraid to do by using animal carcasses motor function, power supply system and movement of animals from the introduction of feelings or innervations. The use of biological control technology and the development of biological robot started in the 1990s. It is the product of the high integration of the electronic information technology, micro-fabrication technology and biological science. It is currently one of the most active technology development areas in the science.Qiushi Academy for Advanced Studies of Zhejiang University developed a bio-robot navigation system in 2006. Based on this system, we are going to develop an intelligent computer-controlled BCI based biological robot navigation system. This paper mainly covers the following aspects:First, the BCI and biological robot are reviewed. We talk about the BCI background and the objective of the development of bio-robot research. Then the (?)ent of this paper, an intelligent BCI based biological robot navigation system is described.Then, the existing experimental basis-the formed developed biological robot navigation systems, is briefly described. The work done between the start of the project and present results are introduced.Next, the overall philosophy of the intelligent navigation system is described. We introduce some key technologies related to the intelligent navigation system of this paper: digital image processing and analysis techniques, and motion-based analysis techniques.Then, the overall structure of the intelligent navigation system is introduced. The application of the digital image processing and analysis technology in the system is concretely described. The experimental environment modeling and path choosing and their actual application are concretely described.Finally, the system is integrated on the basis of the modules discussed above. Using the intelligent navigation system, some tests are shown. Some criteria on how to measure intelligent navigation systems efficiency are given.