Abstract. Robot engineering and related technologies have been rapidly developing during the last decades providing more and more opportunities for using robots in various fields of human activity. In the first place, this is due to continuous improvement of the characteristics of robot engines, energy resources, on-board system calculation tools, and, most importantly, development of sensory tools. This not only improves the management of the robot movement, but also allows for developing custom control systems of advanced levels. At the beginning of this century, the most rapid development in the field of mobile robots was observed in autonomous mobile robots that function in an unknown environment, which constitute the research object of this article. Therefore, the purpose of this article is to prepare the intelligent systems development methods for mobile robot motion planning, which ensure that the robot performs a planned and adjusted during the movement safe trajectory in an environment with unfamiliar obstacles. In order to achieve this purpose, a theoretical research of the mechatronic mobile robot's movement in an unknown environment was carried out, based on which the corresponding results of the research have been obtained, i.e. the theoretical operative control systems for mobile robot's movement in an unknown environment have been tested in real practical situation by designing a theoretical scheme for this research that consists of a laboratory model of a bi-cycle mobile robot and a special algorithm for its operative control. The results of the research evaluate the effectiveness of such mobile robot operation, also they show the progress and resutls of the theoretical experiment in unknown environment with certain obstacles set out in random places on the mobile robot path, as well as they identify the main factors how to improve the experimental research base.
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.
Abstract. The application of mobile robots is becoming more and more common in order to perform various tasks under conditions where the presence of the human in their site is impossible on safety grounds or unacceptable due to the reduction of the productivity of the technological equipment served by them. The objective of robot movement planning is to guarantee the desirable robot movement path as it moves across the planned path on the basis of controlling impacts, i.e. sensors. Numerous investigations were carried out under unknown environment conditions, which were intended for addressing the problem of robot movement without colliding with obstacles in its path by employing various navigation methods. The purpose of this paper is to analyse navigation methods employed for addressing the problem of robot movement without colliding with obstacles in its path under unknown environment conditions. The paper analyses the multi-agent system framework, generalized agent control system framework, local path planning algorithm for robots in an unknown two-dimensional space and other related questions in order to reach the above-mentioned purpose.Keywords: geometric path planning method, multi-agent system, artificial potential method, global planning, local planning. IntroductionThe development of mobile robotics is determined by the desire to replace men at hard and routine, dangerous and responsible work, i.e. in warehouses for efficiently moving materials from stocking shelves to order fulfilment zones, in hospitals for moving materials, in military for clearing mines, in household for vacuuming or gardening etc. The most important characteristics of such robot are mobility and autonomy. In this case, autonomy is necessary in order to guarantee the movement in an unknown environment so that the mobile robot (MR) is able to independently move in an unknown environment performing the task set.The mobile robot movement planning is the most important issue of the autonomous robototechnical system control and one of the fields of modern science and practice most actively investigated. The solution to the task of robot movement planning colliding encompasses questions related with scientific fields such as artificial intelligence, computational geometry, computer simulation and the theory of automatic control. The automation of the movement planning process by also minimising the time costs for preparation and completion operations as well as by accelerating the process of switching the robot from one production task to another constitute the basis for flexible production organisation.Various achievements of scientists in this field enabled to determine the priority trends of mobile robot development. The main design tasks of mobile robot movement in unknown environment conditions are provided in Figure 1 [1; 2].It is easy to understand that the solution to the tasks listed above (Figure 1) requires the solution to a variety of main autonomous mobile robot tasks. First, the robot shall plan a fast and passable route i...
The significance of automated control systems to contemporary society is profound, as large-scale industrial robots are used in industrial plants, autonomous vacuum cleaners are applied at home, and autonomous cars are driven in the streets. Regardless of the nature of the robot, one of its main tasks is to do no harm to the person and the environment, and that is the greatest problem of robotics-orientation. Therefore, the problem of orientation of autonomous robots is being solved by a robot exploring the environment, remembering the space and time-varying environmental changes. On that ground, the task of this article is to develop such scientific researches, which define the mobile robot motion in an unknown environment, based on fuzzy logic and the analysis of neural networks, setting an aim to work out methods for developing intellectual systems for planning a mobile robot motion fuzzy logic and neural networks to ensure that the robot performs the planned and adjusted on the way safe trajectory in an environment with unknown obstacles. Therefore, the entire study in the article is aimed at the analysis of fuzzy logic that is analysed as the entirety of the mathematical description methods of fuzzy sets with the formalization of logical conclusions from the fuzzy assumptions, as in this case the decision-making mechanism always allows the generation of the robot's responsive motions caused by the appearance of obstacles in its trajectory; as well as the analysis of neural networks, which links between neurons determine the complexity and flexibility of the operation of the entire neural network, by addressing the problem of planning a mobile robot motion in an unknown environment and which basically depends upon the level of specific network training. As a result of the study, the method of a mobile robot motion in an unknown dynamic environment was created by using a multi-agent system, involving a combination of neural networks and fuzzy blocks.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.