Adaptive and Self-learning Slaughter Robots

The project is concerned with research in adaptive learning algorithms. The algorithms will enable robots to react to variations in input, perform ongoing corrections during operations and make adjustments to subsequent operations based on evaluation of the output.
In processes such as the slaughtering of animals and processing of meat, the carcasses and cuts vary in size and composition. The traditional control systems for automatic processes in slaughterhouses rely on strict standardization of these products. When this cannot be guaranteed, automation is either abandoned or large margins of error are introduced, resulting in high cost and suboptimal utilization of the resources. Moreover, customers require that the end-product is customized according to their individual preferences, something traditional automated systems have difficulties handling. With large variations in both input and output, an adaptive robot platform is preferable to more dedicated production machinery.