Abstract
Robotic bin-picking performance has been gaining attention in recent years with the development of increasingly advanced camera and machine vision systems, collaborative and industrial robots, and sophisticated robotic grippers. In the random bin-picking process, the wide variety of objects in terms of shape, weight, and surface require complex solutions for the objects to be reliably picked. The challenging part of robotic bin-picking is to determine object pick-points correctly. This paper presents a simulation model based on ADAMS/MATLAB cosimulation for robotic pick-point evaluation for a 2-F robotic gripper. It consists of a mechanical model constructed in ADAMS/View, MATLAB/Simulink force controller, several support functions, and the graphical user interface developed in MATLAB/App Designer. Its functionality can serve three different applications, such as: (1) determining the optimal pick-points of the object due to object complexity, (2) selecting the most appropriate robotic gripper, and (3) improving the existing configuration of the robotic gripper (finger width, depth, shape, stroke width, etc.). Additionally, based on this analysis, new variants of robotic grippers can be proposed. The simulation model has been verified on a selected object on a sample 2-F parallel robotic gripper, showing promising results, where up to 75% of pick-points were correctly determined in the initial testing phase.
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