DEVELOPMENT OF FUZZY BLOCKS INTENDED FOR AGENTS CONSTITUTING INTELLIGENT SYSTEM OF MOBILE ROBOT MOVEMENT PLANNING
Keywords:unknown environment, static obstacles, multi-agent system, planned track, mobile robot, fuzzy logic
With the advancement of technologies, there are attempts to automate the majority of processes for various reasons, for instance, to improve and optimize production or to perform actions that may cause risk to people’s health, etc. Therefore, the use of mobile autonomous robots is becoming increasingly important as the limits of the potential of the use of autonomous mobile robots in the industry have not yet been reached. The attempts have been made to achieve this by developing optimum trajectory calculation algorithms which enable the robot to move freely in both static and dynamic environments and use an optimum trajectory. Therefore, the subject of study in this article was movement of a mobile robot in an unknown environment using a multi-agent device system and fuzzy logics, and the goal of the study was to prepare the methods for development of intelligent systems for planning mobile robot movement in an unknown environment using multi-agent device and fuzzy logics ensuring the robot will accomplish the planned and adjusted on the go safe trajectory in the environment with unknown obstacles. Based on this, the robot arm model has been developed after calculating in the article the missing parameters of the experimental mobile robot in order to analyze the peculiarities of using the multi-agent device as well as the specifics and challenges of using fuzzy logics. 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 mobile robot movement in an unknown static environment using a multi-agent system, which was characterized by the use of fuzzy blocks corresponding each agent, and localization of each solution to the task of planning robot movement in each specific situation, which enables to improve the accuracy and efficiency of movement planning.