Research On Intelligent Vehicle's Avoiding Obstacle System Based On Multisensor Information Fusion

Intelligent vehicle is a kind of wheeled mobile robots,and is widly used in life course and industry,what's more,how the vehicle avoids obstacles is a very important problem.For the surroundings'unpridicted,single sensor can not meet the need, but the birth of multisensor information fusion technology successfully solved the problem. It is a new practical technology.It makes judgement about the surroundings,which the single sensor can't compare with,by synthesising the sensors'datas.The paper makes the research on the intelligent vehicle's avoiding obstacles adopting the metheods of fuzzy neural network based on BP model.The paper uses 5 ultrasonic sensors to measure the obstcles'distance in the vehicle's left, left front, front, right front and right, moreover uses the infrared sensors to judge the obstacles'existing in the distance of ultrasonic sensors'blind zones, then fuses the datas from ultrasonic sensors and infrared sensors to get the obstacles'stations, next input the fused datas to the fuzzy neural network to get vehicle's moving commands.The article first introduces the theory of multisensor information fusion technology and the vehicle's structure and function, second elaborates on the designs in hardware and soft hardware, including the choices of sensors, ultrasonic sensors'applied circuit, program flow,fuzzy neural network's structure and algorithm's realization,finally draws a conclusion about the work,and points out the lacks, and prospects the future works.