ADAPTIVE REGULATION OF THE MANIPULATOR'S MOVEMENT SPEED DEPENDING ON THE DISTANCE TO THE PERSON AND THE LEVEL OF LOAD ON THE ACTUATOR

The article presents an approach to adaptive control of the manipulator speed based on fuzzy logic, which allows taking into account the distance to the person and the level of load on the executive body. The proposed model forms control actions in accordance with the logic of safe human-robot interaction, providing a dynamic change in speed to increase efficiency and safety. The system uses a set of linguistic rules and triangular membership functions to process fuzzy input data. The simulation results demonstrate the stable behavior of the system and confirm the feasibility of using fuzzy approaches in controlling the movement of manipulators in variable conditions. The developed approach has high potential for implementation in robotic systems that operate in close proximity to a person. Development prospects include integration with machine learning and real-time use on embedded platforms.