Труды Института механики им. Р.Р. Мавлютова
Электронный научный журнал | Electronic Scientific Journal
Proceedings of the Mavlyutov Institute of Mechanics
In this paper, various variants of decomposition of tasks in a group of robots using cloud computing technologies are considered. The specifics of the field of application (teams of robots) and solved problems are taken into account. In the process of decomposition, the solution of one large problem is divided into a solution of a series of smaller, simpler problems. Three ways of decomposition based on linear distribution, swarm interaction and synthesis of solutions are proposed. The results of experimental verification of the developed decomposition algorithms are presented, the working capacity of methods for planning trajectories in the cloud is shown. The resulting solution is a component of the complex task of building effective teams of robots.
decomposition of tasks,
group of mobile robots,
distributed control system
Problem: The solution to one of the theoretical problems of distributed cloud management in a group of robots is the decomposition of tasks between robots of a group.
Methods: the methods of system analysis and multiagent approach in the development of cloud computing system architecture.
The various variants of the decomposition of tasks in a group of robots using cloud computing technologies proposed in the results of the research make it possible to use the system to control a group of robots when solving complex computing tasks that require a large number of local calculations and approvals. Three ways of decomposition are proposed: on the basis of linear distribution, swarm interaction and synthesis of solutions. Linear distribution involves dividing the problem into smaller ones in the form of a hierarchical tree, in which the selected subtasks of the lowest level of decomposition are solved in separate cloud applications. Roaming interaction assumes that the largest tasks are solved individually by individual robots from the group, and the selected tasks at each level of decomposition are solved in separate cloud applications. In the synthesis of solutions, individual subtasks are integrated into the overall solution, and the number of cloud applications in this case corresponds to a set of methods (approaches) by which a solution of the particular problem can be found. Depending on the general task assigned to the group of robots and the functionality of individual robots, one of the methods of decomposition is selected. At the next level of the management system, effective methods for allocating the resources of the computing system are proposed for their optimal use, taking into account the chosen decomposition model.