It is shown that the following approaches can be used for group management of mobile robotic platforms (MRP): centralized (concentrated), decentralized (distributed) and hybrid. It was determined that an urgent task is the development of a neurofuzzy management system for the MRP group, which must perform the distribution of tasks between the MRPs, the determination of MRP movement routes, joint planning of works and their synchronization. The requirements for the system of neurofuzzy management of the MRP group are formulated, the main of which are the provision of: effective management of the MRP group; minimization of time for tasks; flexibility and adaptability to changing working conditions; reliable and stable operation when implementing various scenarios; expansion of functions and scaling relative to the number of MRPs; accuracy and reliability of traffic management of each MRP; response to changes in working conditions; uninterrupted work of the MRP group; effective use of MRP resources; reduction of dimensions, weight and energy consumption; management in real time; collecting data on the environment and the state of the MRP; wireless communication between MRP; development of software tools taking into account the distributed architecture; implementation of a programming interface with the possibility of developing additional software and integration with other systems; saving data on the status of all MRPs for further analysis and improving the management of the MRP group. The following main stages of the development of the neurofuzzy control system by the MRP group were identified: problem formulation; analysis of system requirements; hardware design; development of a neurofuzzy control algorithm; software development; testing and tuning; implementation and operation. It is suggested that the development of the system of neurofuzzy control of the MRP group be carried out on the basis of an integrated approach, which includes: methods of neurofuzzy control of the MRP group, artificial neural networks and fuzzy logic; navigation methods, methods of pre-processing and image recognition; methods of intellectual processing and evaluation of data from sensors in conditions of interference and incomplete information; modern methods and algorithms of intelligent traffic control of MRP; modern element base (microcontrollers, systems-on-chip, FPGA, etc.); methods and means of automated design of hardware and software of MRP. It is proposed to implement the neurofuzzy control system by the MRP group on the basis of a problem-oriented approach, which involves a combination of universal software and specialized hardware, which ensures high efficiency of equipment use. The method of time allocation of resources of the storage medium of multiport memory has been improved, which, due to the consideration of the speed of the storage medium and external devices, ensures an increase in the number of devices with conflict-free access to the storage medium.
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