Problem of Robotic Precision Cutting of the Geometrically Complex Shape from an Irregular Honeycomb Grid | Научно-инновационный портал СФУ

Problem of Robotic Precision Cutting of the Geometrically Complex Shape from an Irregular Honeycomb Grid

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: International Conference on Intelligent Robotics and Applications, ICIRA 2020

Год издания: 2020

Идентификатор DOI: 10.1007/978-3-030-66645-3_10

Ключевые слова: honeycomb blocks, mobile robots, modeling, robotics technology

Аннотация: The article considers solving the problem of precision cutting of honeycomb blocks. The urgency of using arbitrary shapes application cutting from honeycomb blocks made of modern composite materials is substantiated. The problem is to obtain a cut of the given shape from honeycomb blocks. The complexity of this problem is in the irregular pattern of honeycomb blocks and the presence of double edges, which forces an operator to scan each block before cutting. It is necessary to take into account such restrictions as the place and angle of the cut and size of the knife, its angle when cutting and the geometry of cells. For this problem solving, a robotic complex has been developed. It includes a device for scanning the geometry of a honeycomb block, software for cutting automation and a cutting device itself. The software takes into account all restrictions on the choice of the location and angle of the operating mechanism. It helps to obtain the highest quality cut and a cut shape with the best strength characteristics. An actuating device has been developed and implemented for both scanning and cutting of honeycomb blocks directly. The necessary tests were carried out on real aluminum honeycomb blocks. Some technical solutions are used in the cutting device to improve the quality of cutting honeycomb blocks. The tests have shown the effectiveness of the proposed complex. Robotic planar cutting made it possible to obtain precise cutting with a high degree of repeatability. © 2020, Springer Nature Switzerland AG.

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Издание

Журнал: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Выпуск журнала: Vol. 12595 LNAI

Номера страниц: 112-120

ISSN журнала: 03029743

Издатель: Springer Science and Business Media Deutschland GmbH

Персоны

  • Kubrikov M.V. (Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy Av. 31, Krasnoyarsk, 660037, Russian Federation)
  • Saramud M.V. (Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy Av. 31, Krasnoyarsk, 660037, Russian Federation, Siberian Federal University, 79 Svobodny Avenue, Krasnoyarsk, 660041, Russian Federation)
  • Karaseva M.V. (Reshetnev Siberian State University of Science and Technology, Krasnoyarsky Rabochy Av. 31, Krasnoyarsk, 660037, Russian Federation, Siberian Federal University, 79 Svobodny Avenue, Krasnoyarsk, 660041, Russian Federation)

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