超声传感器补偿算法在机器人避障中的应用

分析了井下钻孔机器人避障中超声波传感器的局限性,并提出解决的方案。着重指出对超声波进行温度、湿度补偿,尝试用Elman反馈神经网络逼近函数。Elman网络隐含层采用"Tansig"激活函数,输出层用"Pureline"激活函数,保证了只要有足够多的隐含层神经元个数,网络就可以任意精度逼近任意函数。经实验验证:对超声测距进行温度、湿度补偿后,其测量精度提高了2个数量级。大大改善系统中避障模块的工作效率,提高了钻孔机器人躲避障碍物的能力。

Application of ultrasonic sensor compensating algorithms in robot obstacle avoidance

The limitation of the ultrasonic sensor in the underground drilling robot avoids obstacle is analyzed,and the scheme solved is put forward.To emphasize that,temperature and humidity compensation to ultrasonic wave sensor is carried on.Try to use Elman feedback neural network to approach function.Elman network latent layer adopts "Tansig" activate function,output layer activate function with"Pureline",this guarantees that once the network has enough layers,it can approach wanton function with wanton precision.Experiment proves that ultrasonic ranging's measurement precision can raise two orders of magnitude after carying on the temperature and humidity compensation.The working efficiency of obstacle avoidance in the system is improved greatly,the ability of drilling robot obstacle avoidance is improved.