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.
UR - http://www.scopus.com/inward/record.url?scp=85068607999&partnerID=8YFLogxK
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 Nature
T2 - 19th International Conference on Computational Science and Its Applications, ICCSA 2019
Y2 - 1 July 2019 through 4 July 2019
ER -