Different fields of industry and in-service support widely use robots, mechatronic and robotic technology systems in their activities. This is related to growing functionalities that result from using more advanced control systems the development of which is based on available achievements in the technical measures of computing. Therefore, the subject of study in this article was movement of a robot manipulator in using a fuzzy logics and neural network, and the goal of the study was to develop methods for designing combined intelligent planning and control systems for robot-manipulator movement in static dynamic environments based on the combined use of fuzzy logic apparatus and artificial neural networks to reduce the possibility of robot-manipulator’s joints colliding into unknown obstacles located in its operating area. Based on this, the robot arm model has been developed after calculating in the article the missing parameters of the experimental robot manipulator in order to analyze the peculiarities of using the fuzzy logics device as well as the specifics and challenges of using neural network. As a result of the study performed in the article, significant data were obtained based on which a method was offered for an intelligent system for planning robot manipulator movement in static environment using a fuzzy blocks, which was characterized by the use of neural network corresponding each block, and localization of each solution to the task of planning robot manipulator movement in each specific situation, which enables to improve the accuracy and efficiency of movement planning.
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