Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/32305

Robotic Pick-and-Place Time Optimization: Application to Footwear Production

Title:
Robotic Pick-and-Place Time Optimization: Application to Footwear Production
Authors:
Borrell Méndez, Jorge  
PEREZ-VIDAL, CARLOS
Segura-Heras, José Vicente  
PÉREZ-HERNÁNDEZ, JUAN JOSÉ
Editor:
Institute of Electrical and Electronics Engineers
Department:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Issue Date:
2020-11-10
URI:
https://hdl.handle.net/11000/32305
Abstract:
This article considers the problem of optimizing the task sequences carried out by a dual-arm manipulator robot in a footwear production setting. The robot has to identify the pieces of a shoe put in a tray and pick-and-place them in a shoe mould for further processing. The shoe pieces arrive on a tray in random positions (patterns) and can be picked up in different order. In such a setting, a decision tree model is developed to recognize the pattern and predict the optimal sequence for picking the pieces up, thus, the picking and decision-making time is minimized. Two shoe models are considered for training and validating the solution proposed and the developed algorithm is applied in the real setting. There are not many studies which use the decision trees in sequencing and scheduling problems in robotics. The ndings of this article show that the decision tree method has advantages in task planning in a complex environment consisting of multiple trajectories and possible collisions between robot arms.
Keywords/Subjects:
Classification
decision tree algorithms
optimization
pick-and-place
dual arm robotics
Knowledge area:
CDU: Ciencias aplicadas
Type of document:
application/pdf
Access rights:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI:
https://doi.org/10.1109/ACCESS.2020.3037145
Appears in Collections:
Artículos Estadística, Matemáticas e Informática



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