Simulation-based two stage sequencing of robotic assembly operations with deformable objects

Shir Ben-David; Ran Shneor; Shahar Zuler; Zachi Mann; Alex Greenberg; Sigal Berman

doi:10.1016/j.ifacol.2021.08.020

Simulation-based two stage sequencing of robotic assembly operations with deformable objects

Shir Ben-David, Ran Shneor, Shahar Zuler, Zachi Mann, Alex Greenberg, Sigal Berman

Department of Industrial Engineering and Management

Research output: Contribution to journal › Conference article › peer-review

Abstract

Automatic generation of assembly sequences for products containing deformable objects, is an important step required for fully automated production. Robotic manipulation with deformable objects involves handling uncertainty related to object deformation which should be accounted for during assembly sequence planning (ASP). This work describes a two-stage sequencing planning of robotic assembly operations with deformable objects. ASP is an NP-hard problem and many heuristics have been developed for solving it. We suggest a method that improves a purely heuristic ASP by using a heuristic stage based on genetic algorithm (GA) and an additional robotic simulation stage. The method was demonstrated with products with deformable objects and promising results were achieved.

Original language	English
Pages (from-to)	175-180
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	54
Issue number	1
DOIs	https://doi.org/10.1016/j.ifacol.2021.08.020
State	Published - 1 Jan 2021
Event	17th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2021 - Budapest, Hungary Duration: 7 Jun 2021 → 9 Jun 2021

Keywords

Deformable objects
Genetic algorithm
Robotic assembly
Robotic simulation
Sequencing

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.1016/j.ifacol.2021.08.020

Cite this

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title = "Simulation-based two stage sequencing of robotic assembly operations with deformable objects",

abstract = "Automatic generation of assembly sequences for products containing deformable objects, is an important step required for fully automated production. Robotic manipulation with deformable objects involves handling uncertainty related to object deformation which should be accounted for during assembly sequence planning (ASP). This work describes a two-stage sequencing planning of robotic assembly operations with deformable objects. ASP is an NP-hard problem and many heuristics have been developed for solving it. We suggest a method that improves a purely heuristic ASP by using a heuristic stage based on genetic algorithm (GA) and an additional robotic simulation stage. The method was demonstrated with products with deformable objects and promising results were achieved.",

keywords = "Deformable objects, Genetic algorithm, Robotic assembly, Robotic simulation, Sequencing",

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AU - Ben-David, Shir

AU - Shneor, Ran

AU - Zuler, Shahar

AU - Mann, Zachi

AU - Greenberg, Alex

AU - Berman, Sigal

PY - 2021/1/1

Y1 - 2021/1/1

N2 - Automatic generation of assembly sequences for products containing deformable objects, is an important step required for fully automated production. Robotic manipulation with deformable objects involves handling uncertainty related to object deformation which should be accounted for during assembly sequence planning (ASP). This work describes a two-stage sequencing planning of robotic assembly operations with deformable objects. ASP is an NP-hard problem and many heuristics have been developed for solving it. We suggest a method that improves a purely heuristic ASP by using a heuristic stage based on genetic algorithm (GA) and an additional robotic simulation stage. The method was demonstrated with products with deformable objects and promising results were achieved.

AB - Automatic generation of assembly sequences for products containing deformable objects, is an important step required for fully automated production. Robotic manipulation with deformable objects involves handling uncertainty related to object deformation which should be accounted for during assembly sequence planning (ASP). This work describes a two-stage sequencing planning of robotic assembly operations with deformable objects. ASP is an NP-hard problem and many heuristics have been developed for solving it. We suggest a method that improves a purely heuristic ASP by using a heuristic stage based on genetic algorithm (GA) and an additional robotic simulation stage. The method was demonstrated with products with deformable objects and promising results were achieved.

KW - Deformable objects

KW - Genetic algorithm

KW - Robotic assembly

KW - Robotic simulation

KW - Sequencing

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DO - 10.1016/j.ifacol.2021.08.020

M3 - Conference article

AN - SCOPUS:85120693539

SN - 2405-8963

VL - 54

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T2 - 17th IFAC Symposium on Information Control Problems in Manufacturing INCOM 2021

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Simulation-based two stage sequencing of robotic assembly operations with deformable objects

Abstract

Keywords

ASJC Scopus subject areas

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