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Adaptive control of multiped robot. / Demin, Alexander; Vityaev, Evgeniy.

In: Procedia Computer Science, Vol. 145, 2018, p. 629-634.

Research output: Contribution to journal › Conference article › peer-review

Harvard

Demin, A & Vityaev, E 2018, 'Adaptive control of multiped robot', Procedia Computer Science, vol. 145, pp. 629-634. https://doi.org/10.1016/j.procs.2018.11.071

APA

Demin, A., & Vityaev, E. (2018). Adaptive control of multiped robot. Procedia Computer Science, 145, 629-634. https://doi.org/10.1016/j.procs.2018.11.071

Vancouver

Demin A, Vityaev E. Adaptive control of multiped robot. Procedia Computer Science. 2018;145:629-634. doi: 10.1016/j.procs.2018.11.071

Author

Demin, Alexander ; Vityaev, Evgeniy. / Adaptive control of multiped robot. In: Procedia Computer Science. 2018 ; Vol. 145. pp. 629-634.

BibTeX

@article{51da329dcd394cccafe268814429f7e0,
title = "Adaptive control of multiped robot",
abstract = "In the paper, a logical-probabilistic method of adaptive control of modular systems is presented. It base on the functional similarity of modules, the logical-probabilistic algorithm of directed search of rules and joint training of control modules. Starting with the search for common rules for all modules of the control system then it upload them with a more specific ones in accordance with the ideas of semantical-probabilistic inference. With the use of an interactive 3D-simulator, successful experiments were conducted with virtual multiped robot mode. Experimental studies have shown that the proposed approach is quite effective and can be used to manage modular systems with a large number of degrees of freedom.",
keywords = "control system, knowledge discovery, learning control system rules, modular robots, LOCOMOTION",
author = "Alexander Demin and Evgeniy Vityaev",
note = "This work is financially supported by the Russian Science Foundation grant #17-11-01176.; 9th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2018 ; Conference date: 22-08-2018 Through 24-08-2018",
year = "2018",
doi = "10.1016/j.procs.2018.11.071",
language = "English",
volume = "145",
pages = "629--634",
journal = "Procedia Computer Science",
issn = "1877-0509",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Adaptive control of multiped robot

AU - Demin, Alexander

AU - Vityaev, Evgeniy

N1 - This work is financially supported by the Russian Science Foundation grant #17-11-01176.

PY - 2018

Y1 - 2018

N2 - In the paper, a logical-probabilistic method of adaptive control of modular systems is presented. It base on the functional similarity of modules, the logical-probabilistic algorithm of directed search of rules and joint training of control modules. Starting with the search for common rules for all modules of the control system then it upload them with a more specific ones in accordance with the ideas of semantical-probabilistic inference. With the use of an interactive 3D-simulator, successful experiments were conducted with virtual multiped robot mode. Experimental studies have shown that the proposed approach is quite effective and can be used to manage modular systems with a large number of degrees of freedom.

AB - In the paper, a logical-probabilistic method of adaptive control of modular systems is presented. It base on the functional similarity of modules, the logical-probabilistic algorithm of directed search of rules and joint training of control modules. Starting with the search for common rules for all modules of the control system then it upload them with a more specific ones in accordance with the ideas of semantical-probabilistic inference. With the use of an interactive 3D-simulator, successful experiments were conducted with virtual multiped robot mode. Experimental studies have shown that the proposed approach is quite effective and can be used to manage modular systems with a large number of degrees of freedom.

KW - control system

KW - knowledge discovery

KW - learning control system rules

KW - modular robots

KW - LOCOMOTION

UR - http://www.scopus.com/inward/record.url?scp=85059455947&partnerID=8YFLogxK

U2 - 10.1016/j.procs.2018.11.071

DO - 10.1016/j.procs.2018.11.071

M3 - Conference article

AN - SCOPUS:85059455947

VL - 145

SP - 629

EP - 634

JO - Procedia Computer Science

JF - Procedia Computer Science

SN - 1877-0509

T2 - 9th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2018

Y2 - 22 August 2018 through 24 August 2018

ER -

ID: 25327453