Increasing object flexibility of vacuum gripper systems through a common grasp search

Gripper systems play a crucial role in robot-based automation. Frequent refitting hinders automation in companies with high product variance, but flexible gripper systems are costly. Therefore, this paper presents a software-based methodology to increase the object flexibility of standardized gripper systems during their design phase. The first step is to use clustering algorithms based on the physical properties of the workpieces to find similarities. Afterward, an optimization is used to identify common grasp points across workpieces. The approach is validated using vacuum gripper systems as a low-cost automation tool and printed circuit board assemblies (PCBAs) as exemplary workpieces.