Automatic Loading and Unloading Control System of Cable Materials Based on Artificial Immune Algorithm Remote Sensing Image Recognition Technology

Loading, unloading, transportation and transfer of materials is the key link connecting transportation, storage and distribution. It constantly appears and is repeated, including loading, unloading, transfer, classification, warehousing and warehousing. At present, the loading, unloading and transportation of many materials are still in the operation state of combining manpower, cart and forklift. The development of automatic control system for loading, unloading and transferring of cable materials can effectively improve the efficiency of loading, unloading and transferring of materials, reduce labor intensity and reduce costs. In this paper, the control strategy of automatic loading and unloading of materials based on artificial immune algorithm (AIA) remote sensing image recognition technology is proposed, which provides technical support for the construction of automatic loading and unloading control system of cable materials. The results show that, compared with the support vector machine (SVM) algorithm, the accuracy of AIA is improved by more than 20%. On this basis, the machine vision-based image recognition technology and binocular stereo vision recognition and positioning technology can be used to realize the identification and positioning of freight yard containers, and the bar code positioning technology and motor absolute encoder can be used to realize the motion positioning of each operating mechanism of container cranes.