Выдержка

The task of this paper is to find lost or frozen people in the wood. That takes accurate exploration of a large space with a minimum time duration. This work is dedicated to the architecture part of the assigned task. We give an architecture for robot-finder capable to find a human being in the wood or in the snow area. For us, the robot is blending of two elements, which we can develop independently. That are a wheeled platform and an operating module. In this task, we look at the second one. During that way we assume that the first one is developed, therefore the robot is driving upon the airbag or wheeled platform. Our solution to this task is architecture and algorithm. These two are made for and directed to learn robot follow the map and detect human being alongside. We use computer vision, neural network and GPS technologies. In the end, we have a theoretical basis for developing robot-finder.

Язык оригиналаанглийский
Название основной публикацииComputational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings
РедакторыBeniamino Murgante, Osvaldo Gervasi, Elena Stankova, Vladimir Korkhov, Sanjay Misra, Carmelo Torre, Eufemia Tarantino, David Taniar, Ana Maria A.C. Rocha, Bernady O. Apduhan
ИздательSpringer
Страницы761-771
Число страниц11
ISBN (печатное издание)9783030243043
DOI
СостояниеОпубликовано - 29 июн 2019
Событие19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Российская Федерация
Продолжительность: 1 июл 20194 июл 2019

Серия публикаций

НазваниеLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Том11622 LNCS
ISSN (печатное издание)0302-9743
ISSN (электронное издание)1611-3349

Конференция

Конференция19th International Conference on Computational Science and Its Applications, ICCSA 2019
СтранаРоссийская Федерация
ГородSaint Petersburg
Период1/07/194/07/19

Отпечаток

Simultaneous Localization and Mapping
Robot
Robots
Neural Networks
Neural networks
Wood
Snow
Computer Vision
Computer vision
Global positioning system
Architecture
Module

Предметные области Scopus

  • Теоретические компьютерные науки
  • Компьютерные науки (все)

Цитировать

Oleg, I., Sevostyanov, R., Degtyarev, A., Krasilnikov, E., Mingazova, M., Rusakov, A., ... Bobryshev, A. (2019). The Architecture of the Robot-Finder Based on SLAM and Neural Network. В B. Murgante, O. Gervasi, E. Stankova, V. Korkhov, S. Misra, C. Torre, E. Tarantino, D. Taniar, A. M. A. C. Rocha, ... B. O. Apduhan (Ред.), Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings (стр. 761-771). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11622 LNCS). Springer. https://doi.org/10.1007/978-3-030-24305-0_57
Oleg, Iakushkin ; Sevostyanov, Ruslan ; Degtyarev, Alexander ; Krasilnikov, Egor ; Mingazova, Maria ; Rusakov, Alexey ; Kondratieva, Olesya ; Bobryshev, Andrey. / The Architecture of the Robot-Finder Based on SLAM and Neural Network. Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. редактор / Beniamino Murgante ; Osvaldo Gervasi ; Elena Stankova ; Vladimir Korkhov ; Sanjay Misra ; Carmelo Torre ; Eufemia Tarantino ; David Taniar ; Ana Maria A.C. Rocha ; Bernady O. Apduhan. Springer, 2019. стр. 761-771 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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title = "The Architecture of the Robot-Finder Based on SLAM and Neural Network",
abstract = "The task of this paper is to find lost or frozen people in the wood. That takes accurate exploration of a large space with a minimum time duration. This work is dedicated to the architecture part of the assigned task. We give an architecture for robot-finder capable to find a human being in the wood or in the snow area. For us, the robot is blending of two elements, which we can develop independently. That are a wheeled platform and an operating module. In this task, we look at the second one. During that way we assume that the first one is developed, therefore the robot is driving upon the airbag or wheeled platform. Our solution to this task is architecture and algorithm. These two are made for and directed to learn robot follow the map and detect human being alongside. We use computer vision, neural network and GPS technologies. In the end, we have a theoretical basis for developing robot-finder.",
author = "Iakushkin Oleg and Ruslan Sevostyanov and Alexander Degtyarev and Egor Krasilnikov and Maria Mingazova and Alexey Rusakov and Olesya Kondratieva and Andrey Bobryshev",
year = "2019",
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isbn = "9783030243043",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
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editor = "Beniamino Murgante and Osvaldo Gervasi and Elena Stankova and Vladimir Korkhov and Sanjay Misra and Carmelo Torre and Eufemia Tarantino and David Taniar and Rocha, {Ana Maria A.C.} and Apduhan, {Bernady O.}",
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Oleg, I, Sevostyanov, R, Degtyarev, A, Krasilnikov, E, Mingazova, M, Rusakov, A, Kondratieva, O & Bobryshev, A 2019, The Architecture of the Robot-Finder Based on SLAM and Neural Network. в B Murgante, O Gervasi, E Stankova, V Korkhov, S Misra, C Torre, E Tarantino, D Taniar, AMAC Rocha & BO Apduhan (ред.), Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), том. 11622 LNCS, Springer, стр. 761-771, Saint Petersburg, Российская Федерация, 1/07/19. https://doi.org/10.1007/978-3-030-24305-0_57

The Architecture of the Robot-Finder Based on SLAM and Neural Network. / Oleg, Iakushkin; Sevostyanov, Ruslan; Degtyarev, Alexander; Krasilnikov, Egor; Mingazova, Maria; Rusakov, Alexey; Kondratieva, Olesya; Bobryshev, Andrey.

Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. ред. / Beniamino Murgante; Osvaldo Gervasi; Elena Stankova; Vladimir Korkhov; Sanjay Misra; Carmelo Torre; Eufemia Tarantino; David Taniar; Ana Maria A.C. Rocha; Bernady O. Apduhan. Springer, 2019. стр. 761-771 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 11622 LNCS).

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

TY - GEN

T1 - The Architecture of the Robot-Finder Based on SLAM and Neural Network

AU - Oleg, Iakushkin

AU - Sevostyanov, Ruslan

AU - Degtyarev, Alexander

AU - Krasilnikov, Egor

AU - Mingazova, Maria

AU - Rusakov, Alexey

AU - Kondratieva, Olesya

AU - Bobryshev, Andrey

PY - 2019/6/29

Y1 - 2019/6/29

N2 - The task of this paper is to find lost or frozen people in the wood. That takes accurate exploration of a large space with a minimum time duration. This work is dedicated to the architecture part of the assigned task. We give an architecture for robot-finder capable to find a human being in the wood or in the snow area. For us, the robot is blending of two elements, which we can develop independently. That are a wheeled platform and an operating module. In this task, we look at the second one. During that way we assume that the first one is developed, therefore the robot is driving upon the airbag or wheeled platform. Our solution to this task is architecture and algorithm. These two are made for and directed to learn robot follow the map and detect human being alongside. We use computer vision, neural network and GPS technologies. In the end, we have a theoretical basis for developing robot-finder.

AB - The task of this paper is to find lost or frozen people in the wood. That takes accurate exploration of a large space with a minimum time duration. This work is dedicated to the architecture part of the assigned task. We give an architecture for robot-finder capable to find a human being in the wood or in the snow area. For us, the robot is blending of two elements, which we can develop independently. That are a wheeled platform and an operating module. In this task, we look at the second one. During that way we assume that the first one is developed, therefore the robot is driving upon the airbag or wheeled platform. Our solution to this task is architecture and algorithm. These two are made for and directed to learn robot follow the map and detect human being alongside. We use computer vision, neural network and GPS technologies. In the end, we have a theoretical basis for developing robot-finder.

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U2 - 10.1007/978-3-030-24305-0_57

DO - 10.1007/978-3-030-24305-0_57

M3 - Conference contribution

AN - SCOPUS:85068607999

SN - 9783030243043

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 761

EP - 771

BT - Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings

A2 - Murgante, Beniamino

A2 - Gervasi, Osvaldo

A2 - Stankova, Elena

A2 - Korkhov, Vladimir

A2 - Misra, Sanjay

A2 - Torre, Carmelo

A2 - Tarantino, Eufemia

A2 - Taniar, David

A2 - Rocha, Ana Maria A.C.

A2 - Apduhan, Bernady O.

PB - Springer

ER -

Oleg I, Sevostyanov R, Degtyarev A, Krasilnikov E, Mingazova M, Rusakov A и соавт. The Architecture of the Robot-Finder Based on SLAM and Neural Network. В Murgante B, Gervasi O, Stankova E, Korkhov V, Misra S, Torre C, Tarantino E, Taniar D, Rocha AMAC, Apduhan BO, редакторы, Computational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings. Springer. 2019. стр. 761-771. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-24305-0_57