Traversability estimation system for mobile robot in heterogeneous environment with different underlying surface characteristics; Computer Sciences and Information Technologies (CSIT)
| Parent link: | Computer Sciences and Information Technologies (CSIT).— 2017.— [P. 549-554] |
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| المؤلف الرئيسي: | |
| مؤلف مشترك: | |
| مؤلفون آخرون: | |
| الملخص: | Title screen One of the key tasks of Outdoor-type mobile robotics is traversability estimation of underlying surfaces in a in a priori of an unknown heterogeneous environment. The paper presents practical realization of traversability estimation system based on group method of data handling (GMDH). This method is classical technique of data mining and one of the first techniques of Deep Learning. The results of color, geometry and texture features extraction by developed computer vision unit are presented step by step. Also the results of model training (Twice-Multilayered Modified Polynomial Neural Network with active neurons is used as one of the GMDH algorithms) for different input features subsets combinations and for two variants of traversability estimation (the robot leaves the area being traversed, but remains within a specified radius and traversing an area within a given time) are considered. The obtained results testify the efficiency of the developed traversability estimation system. Режим доступа: по договору с организацией-держателем ресурса |
| اللغة: | الإنجليزية |
| منشور في: |
2017
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://doi.org/10.1109/STC-CSIT.2017.8098847 |
| التنسيق: | الكتروني فصل الكتاب |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=664817 |
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| 200 | 1 | |a Traversability estimation system for mobile robot in heterogeneous environment with different underlying surface characteristics |f A. A. Andrakhanov, A. V. Stuchkov | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 19 tit.] | ||
| 330 | |a One of the key tasks of Outdoor-type mobile robotics is traversability estimation of underlying surfaces in a in a priori of an unknown heterogeneous environment. The paper presents practical realization of traversability estimation system based on group method of data handling (GMDH). This method is classical technique of data mining and one of the first techniques of Deep Learning. The results of color, geometry and texture features extraction by developed computer vision unit are presented step by step. Also the results of model training (Twice-Multilayered Modified Polynomial Neural Network with active neurons is used as one of the GMDH algorithms) for different input features subsets combinations and for two variants of traversability estimation (the robot leaves the area being traversed, but remains within a specified radius and traversing an area within a given time) are considered. The obtained results testify the efficiency of the developed traversability estimation system. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 463 | |t Computer Sciences and Information Technologies (CSIT) |o 12th International Scientific and Technical Conference, Lviv, Ukraine, 5-8 September, 2017 |v [P. 549-554] |d 2017 | ||
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a mobile robot | |
| 610 | 1 | |a heterogeneous environment | |
| 610 | 1 | |a underlying surface | |
| 610 | 1 | |a raversability | |
| 610 | 1 | |a computer vision | |
| 610 | 1 | |a contour extraction | |
| 610 | 1 | |a testing ground | |
| 610 | 1 | |a group method of data handling (GMDH) | |
| 610 | 1 | |a twice-multilayered modified polynomial neural network with active neurons | |
| 610 | 1 | |a machine learning | |
| 610 | 1 | |a festo robotino | |
| 610 | 1 | |a мобильные роботы | |
| 610 | 1 | |a проходимость | |
| 610 | 1 | |a поверхности | |
| 610 | 1 | |a компьютерное зрение | |
| 610 | 1 | |a обработка данных | |
| 700 | 1 | |a Andrakhanov |b A. A. |c Specialist in the field of electrical engineering |c Assistant of the Department of Tomsk Polytechnic University |f 1982- |g Anatoliy Aleksandrovich |3 (RuTPU)RU\TPU\pers\38561 |9 20819 | |
| 701 | 1 | |a Stuchkov |b A. V. |g Anton Vitaljevich | |
| 712 | 0 | 2 | |a Национальный исследовательский Томский политехнический университет |b Инженерная школа информационных технологий и робототехники |c 2017- |x TPU |7 ca |8 rus |9 28330 |
| 801 | 2 | |a RU |b 63413507 |c 20210520 |g RCR | |
| 856 | 4 | |u https://doi.org/10.1109/STC-CSIT.2017.8098847 | |
| 942 | |c CF | ||