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Competitive high variance, low volume manufacturing with robot manipulators

Abstract

Competitive robotized manufacturing of high specter variance, low volume product lines represents market opportunities for manufacturing companies, but cost-efficient production is challenging. In this paper, we present two main industry use cases which represent key challenges to be solved for cost-efficient low-volume, high-variance production. The use cases are found in collaboration with three manufacturing companies. We identify and describe these challenges which include perception and manipulation with shiny/high-reflectivity parts, human-machine interfaces for robot reconfiguration and calibration between simulated and real-world environments. In this paper, we present new methods for meeting these challenges: machine vision for handling sensor data with low quality in robot manipulation, automated robot programming based on CAD-models and automated calibration. Moreover, we implement and demonstrate the methods on the two identified industry use cases for robotized assembly.

Category

Academic chapter/article/Conference paper

Client

  • Research Council of Norway (RCN) / 269747

Language

English

Author(s)

Affiliation

  • SINTEF Digital / Mathematics and Cybernetics
  • SINTEF Digital / Smart Sensor Systems
  • SINTEF Manufacturing

Year

2020

Publisher

IEEE conference proceedings

Book

Proceeding of 3rd International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS2020)

ISBN

978-1-7281-6419-9

Page(s)

1 - 7

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