Cognitive Robot Referencing System for High Accuracy Manufacturing Task

Abstract

Industrial robots can be considered very repeatable machines, but they usually lack of absolute accuracy. However, high accuracy during the execution of the task is becoming a more and more critical factor in industrial manufacturing domains. For that reason, in order to fully automatize manufacturing processes, high-precision tasks usually need the integration of additional sensors to improve robot accuracy. This paper proposes an embedded, cognitive and self-learning stereo-vision system that can be used to reference the robot position with respect to the work-piece, increasing robot accuracy locally. An industrial use-case is also proposed and experimental results are presented.