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.
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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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