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.

Original languageEnglish
Title of host publicationComputational Science and Its Applications- ICCSA 2019 - 19th International Conference, Proceedings
EditorsBeniamino Murgante, Osvaldo Gervasi, Elena Stankova, Vladimir Korkhov, Sanjay Misra, Carmelo Torre, Eufemia Tarantino, David Taniar, Ana Maria A.C. Rocha, Bernady O. Apduhan
PublisherSpringer Nature
Pages761-771
Number of pages11
ISBN (Print)9783030243043
DOIs
StatePublished - 29 Jun 2019
Event19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation
Duration: 1 Jul 20194 Jul 2019
Conference number: 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11622 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Computational Science and Its Applications, ICCSA 2019
Abbreviated titleICCSA 2019
Country/TerritoryRussian Federation
CitySaint Petersburg
Period1/07/194/07/19

    Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

ID: 43696086