Visual shape and position sensing algorithm for a continuum robot; IOP Conference Series: Materials Science and Engineering; Vol. 1019 : 14th International Forum on Strategic Technology (IFOST 2019)

Visual shape and position sensing algorithm for a continuum robot; IOP Conference Series: Materials Science and Engineering; Vol. 1019 : 14th International Forum on Strategic Technology (IFOST 2019)

Bibliographic Details
Parent link:IOP Conference Series: Materials Science and Engineering
Vol. 1019 : 14th International Forum on Strategic Technology (IFOST 2019).— 2021.— [012066, 6 p.]
Corporate Authors: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Научно-образовательная лаборатория обработки и анализа больших данных, Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение информационных технологий
Other Authors: Manakov R. A., Kolpashchikov D. Yu. Dmitry Yurjevich, Danilov V. V. Vyacheslav Vladimirovich, Laptev N. V. Nikita Vitalievich, Skirnevsky I. P. Igor Petrovich, Gerget O. M. Olga Mikhailovna
Summary:Title screen
Continuum robots represent an actively developing and fast-growing technology in robotics. To successfully implement control and path planning of continuum robots it is important to develop an accurate three-dimensional shape and position sensing algorithm. In this paper, we propose an algorithm for the three-dimensional reconstruction of the continuum robot shape. The algorithm is performed during several steps. Initially, images from two cameras are processed by applying pre-processing and segmentation techniques. Then, the gradient descent method is applied to compare two-dimensional skeleton points of both masks. Having compared these points, it finds a skeleton of the robot in a threedimensional form. Additionally, the proposed algorithm is able to define key points using the distance from the robot base along the center line. The latter allows controlling the position of points of interest defined by a user. As a result, the developed algorithm achieved a relatively high level of accuracy and speed.
Language:English
Published: 2021
Subjects:
электронный ресурс
труды учёных ТПУ
робототехника
управление
роботы
алгоритмы
сегментация
Online Access:http://earchive.tpu.ru/handle/11683/64567
https://doi.org/10.1088/1757-899X/1019/1/012066
Format: Electronic Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=663574

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