Based on Artificial Immune Algorithm of Robot Multi-Sensor Signal Variation Characteristics of the Detection Method

Abstract

With the continuous improvement of robot intelligent, constantly expanding range of applications, as well as multi-sensor information fusion technology, the traditional single sensor signal transmission problem has become multi-sensor transmission problems or multiple source signal transmission problems. This brought a large amount of signal variation and signals multiple variation problems. The traditional detection algorithm has been unable to meet the requirements; therefore, this paper puts forward a kind of robot multisensory signal variation test method based on artificial immune algorithm. First, establish the dynamic changes of the signal variability of equations to get the cross point of the distribution of the signal variability of variability, then update signal variation characteristic database, in the database selection signal variation characteristics. The method overcomes the drawbacks of traditional algorithms; the experiments show that this algorithm can avoid the defect signal variability of mutation, to improve the accuracy of signal variation detection.  DOI: http://dx.doi.org/10.11591/telkomnika.v11i12.3682