The paper presents the concept of an intelligent superstructure designed to combine automated vertical storage systems, mobile robots and standard control systems for both warehouse and production processes into a single complex. The proposed mathematical model describes the key aspects of product placement, robot routing, and accounting for equipment throughput. Optimization algorithms allow you to create and quickly adjust storage and relocation plans based on dynamic changes (spikes in demand, disruptions, priority orders). The simulation results confirm that the implemented system helps to reduce time and resource costs, increases throughput and ensures higher adaptability of logistics operations.

Keywords: logistics, warehouse optimization, automated vertical storage systems, mobile robots, collaborative robots, warehouse management system, production process management system, mathematical model, optimization algorithms, intelligent system

The article develops calibration methods to improve accuracy and reduce operating costs of robotic systems in warehouse logistics. Special attention is given to the use of laser sensors and offset parameters, enabling the robot's position to adapt to changing conditions. The methodology includes the stages of initialization, orientation, and final verification, which help minimize deviations and reduce the need for manual adjustments. This approach ensures consistent operational accuracy and lowers operating costs through automated and adaptive robot calibration settings.

Keywords: robot calibration, warehouse automation, laser sensor, offset, positioning accuracy, robotic system, adaptive calibration, automatic calibration, collaborative robot, cobot

The article discusses automatic selection of coefficients for PID controllers of quadcopter motors based on a 3D model. This selection became possible thanks to the method discussed in the article for exporting a 3D model of a quadcopter, created in the Solidworks CAD system, into the Matlab/Simulink environment, as well as with the further use of the SimMechanics library. To select the coefficients, a quadcopter control system is also implemented to the Simulink project, the signals from one sent to the motors in accordance with their physical location. The result of the article is a flight visualization of a 3D model of a quadcopter with a control system implemented in Simulink.

Keywords: solidworks, matlab, simulink, quadcopter, uav, pid, simmechanics