电子设计工程
電子設計工程
전자설계공정
ELECTRONIC DESIGN ENGINEERING
2014年
12期
5-8
,共4页
多传感器%神经网络%数据融合%测距系统
多傳感器%神經網絡%數據融閤%測距繫統
다전감기%신경망락%수거융합%측거계통
multi-sensor%neural networks%data fusion%ranging system
针对单超声波的测距缺陷，采用多个超声波结合红外开关共同测距，提高整体测量精度；针对BP神经网络训练收敛速度慢，容易陷入局部极小值等缺点，加入动量-自适应因子来改进BP神经网络；将改进的BP应用于移动机器人传感器旅行家II号数据融合中，实践证明，经改进后的BP神经网络收敛精度高误差小，融合后的信息比未经融合的信息更精确。
針對單超聲波的測距缺陷，採用多箇超聲波結閤紅外開關共同測距，提高整體測量精度；針對BP神經網絡訓練收斂速度慢，容易陷入跼部極小值等缺點，加入動量-自適應因子來改進BP神經網絡；將改進的BP應用于移動機器人傳感器旅行傢II號數據融閤中，實踐證明，經改進後的BP神經網絡收斂精度高誤差小，融閤後的信息比未經融閤的信息更精確。
침대단초성파적측거결함，채용다개초성파결합홍외개관공동측거，제고정체측량정도；침대BP신경망락훈련수렴속도만，용역함입국부겁소치등결점，가입동량-자괄응인자래개진BP신경망락；장개진적BP응용우이동궤기인전감기여행가II호수거융합중，실천증명，경개진후적BP신경망락수렴정도고오차소，융합후적신식비미경융합적신식경정학。
To solve the problem of the drawbacks of single ultrasonic distance measurement, a common ranging method of the multiple ultrasonic combined with the infrared switch was presented, and the accuracy of measurement was improved by using this method; Regarding the shortcomings of BP neural network (BPNN) training convergence speed and easily falling into local minima, the momentum adaptive factor was used to improve the BPNN, and then the improved BPNN was applied to the UP-VoyagerⅡmobile robot in data fusion . Practical application shows that,the fused data is more accurate than the unfused data.
