SAPIR: Supervised and Adaptive Programming of Industrial Robots

Abstract

Cast parts have inconsistent geometry and grinding and deburring operations is to be carried out based on individual observation of every single workpiece. Normally, these operations are carried out manually by humans. However, due to the health risk associated with the grinding process, there is a strong incentive to explore new automated solutions. The industrial robot is viewed as a strong component for this job. Programming industrial robots is traditionally done by teach or offline programming methodologies. Both methods encounter problems in grinding/deburring operations. In traditional offline programming the robot path is generated from a CAD model of the workpiece. This CAD model holds no information on the irregularities (burrs) and then the necessary path cannot be created. This paper presents a new approach for supervised robot programming, which allows new field of application of industrial robots. In the near future, automatization of manufacturing processes with industrial robots in small and medium sized enterprise would be common. Instead of a costly, but fully automated solution, which works only from CAD model of workpiece and does not provide 100% satisfying result, an operator is involved in robot programming. The result is a 90% automated solution with the expertise of the worker. This interactive vision-based robot programming adds the required information into the offline programming environment. Thus, location and shape of any irregularities can be identified and the necessary deburring path created.