Simulation Model for Robotic Pick-Point Evaluation for 2-F Robotic Gripper

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...

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Bibliographic Details
Published inApplied sciences Vol. 13; no. 4; p. 2599
Main Authors Bencak, Primož, Hercog, Darko, Lerher, Tone
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.02.2023
Subjects
ADAMS
Algorithms
Analysis
Cloud computing
Collaboration
Complexity
Computer simulation
Computer-generated environments
Grippers
Industrial robots
Internet of Things
intralogistics
Logistics
Machine vision
Matlab
MATLAB/Simulink
Physics
pick-point determination
Picking
robotic bin-picking
Robotics
Robots
Simulation
simulation model
Simulation models
Software
Trends
Vision systems
Warehouses
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Summary: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.
ISSN:2076-3417
2076-3417
DOI:10.3390/app13042599