An incidence angle detection system for automatic assembly tools using the RHI neural network model

One problem arising from the industrial application of automatic assembly of tools controlled by artificial vision systems is the angle the tool must turn given the position of the object to be assembled. Not only are current solutions to this problem computationally expensive but also the algorithms upon which they are based are elaborate and complex. In this paper a system that works directly on digitized images to obtain the necessary pixels so that the different object oriented instances can be discerned is discussed. Such an inference will be used to compute the angle between the object and the reference position