Development of an adaptive intermodal container handling control subsystem based on automatic recognition algorithms

Abstract

One of most important research area of our paper is development of adaptive container loading system w ith computer vision algorithms for smooth container lan ding on the platform (truck, trailer or well car of the train), whereas excessive vibration is caused at th at moment, this vibration and shocks can cause cont ainer and/or cargo damage. This paper presents container crane grabber adaptive positioning subsystem that uses computer vision algorithms. Designed subsystem consists of two separate parts: an automatic image recognition system and the adaptive control system, which is based on neural network with fuzzy interf ace. This network is using learning algorithms so it can easily control container crane motors and adapt to changing conditions (container weight, platform hei ght). Functional computer vision algorithms is prop osed and based on them computer programs was developed. Electric circuits is also created and described, th at allows testing and validation of this subsystem.