Abstract: Orientation is required in the navigation applications in the outdoorslike horticulture, forestry, agriculture, civil or social works, industrial works, geo-studies, space works and other applications of unloading or loading of vehicles.The main aim of the research is to develop algorithm for autonomous navigation of non-holonomic vehicles using interval type-2 fuzzy logic system and neural networks in simulated environment using MATLAB. It was noticed that network configuration and training of neural network indicates that good training results could be achieved. From the findings of the analysis, it was observed that by adopting the fuzzy control improved by neural network, it can able to identify the nearest way of vehicle efficiently.For future work it can be extended for autonomous navigation of non-holonomic vehicles using artificial intelligence techniques in simulated environment using LABVIEW platform which can be applied to environmental applications.

• Publication Date: 29-Aug-2015
• DOI: 10.15224/978-1-63248-073-6-19
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Abstract: The position determination method has been used widely in location based industry. Precise determination of a mobile position is one of the significant problems in geolocation. Among geolocation techniques, both time difference of arrival (TDOA) and angle of arrival (AOA) are the most widely used methods for estimation of mobile position. In this paper, TDOA/AOA hybrid position estimation formula is proposed to express a mobile position. This hybrid scheme improves the estimation performance by increasing reliable measurement data set. Also, we suggest Newton method based optimization algorithm to obtain a solution that minimizes determination error. Some simulations confirm that the proposed Newton method based optimization algorithm improves the accuracy for acquiring a mobile position estimate.

• Publication Date: 29-Aug-2015
• DOI: 10.15224/978-1-63248-073-6-20
• Views: 0
• Downloads: 0