触觉传感阵列信号的信息融合处理

在智能机器人服装中,压力传感器阵列输出性能易受环境温度、电压扰动等非目标参量因素的影响,其间存在的交叉干扰常导致测量精度显著降低。针对上述问题,提出了一种新的用于测量分布压力的压电传感阵列及其信号处理的方法。设计了传感信号的处理流程;析取并有效地处理了置信距离矩阵和关系矩阵融合中的有用数据;提出了用概率最大值法和极大似然法对多传感器信息作有效融合处理的方法。实验结果表明,该方法可消除温度对压力传感器的影响,减小了单个传感器不确定性的误差影响,提高了压力分布测量数据的稳定性和测量精度,可显著改进压力图像重构精度。

Information fusion for tactile sensor array signals

In the intelligent robot suit, the output performance of piezoelectric sensor array is easy to be influenced by non target factors, such as environment temperature, voltage fluctuation and so on, resulting in obvious measurement precision decrease due to the intercross interference among the sensors. Aiming at the above problem, a new tactile sensor array as well as signal processing method for distributed pressure measurement is presented. The processing flow of sensor signal is designed to extract and effectively process the useful data in the confidence distance matrix and relation matrix by means of mathematical statistics based approach. The fusion processing technique with maximum probability method and maximum likelihood method for multi sensor information is presented. The experimental result shows that the proposed method can eliminate the temperature impact on pressure sensor to reduce the error influence from uncertainty of single sensor and enhance the stability and measure precision for distributed pressure measurement data, which outstandingly improves the reconstruction precision of pressure image.