Artificial intelligence in robot control systems; IOP Conference Series: Materials Science and Engineering; Vol. 363 : Cognitive Robotics

מידע ביבליוגרפי
Parent link:IOP Conference Series: Materials Science and Engineering
Vol. 363 : Cognitive Robotics.— 2018.— [012013, 6 p.]
מחבר ראשי: Korikov A. M. Anatoly Mikhailovich
מחבר תאגידי: Национальный исследовательский Томский политехнический университет (ТПУ)
סיכום:Title screen
This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.
שפה:אנגלית
יצא לאור: 2018
נושאים:
גישה מקוונת:https://doi.org/10.1088/1757-899X/363/1/012013
http://earchive.tpu.ru/handle/11683/51794
פורמט: אלקטרוני Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=658779
תיאור
סיכום:Title screen
This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.
DOI:10.1088/1757-899X/363/1/012013