ANALYSIS OF ALGORITHMS BASED ON CLASSICAL AND QUANTUM COMPUTING ELEMENTS FOR INTELLIGENT ROBOT CONTROL
Annotatsiya
The paper reviews classical and quantum computing algorithms for the intelligent control of industrial robots. Classical methods, including artificial neural networks, fuzzy logic, adaptive control and numerical optimization, remain the main practical tools because they are well understood and can run in real time. Quantum methods are discussed for search, optimization, inverse kinematics and decision-making in large solution spaces, with particular attention to Grover's search algorithm, quantum annealing and hybrid classical–quantum schemes. The two groups of methods are compared by computational basis, practical readiness, typical tasks, advantages and limitations. Noise, decoherence and the small number of available qubits still prevent direct industrial use of quantum methods. For the near future, the most realistic option is a hybrid architecture in which classical controllers handle real-time control and quantum modules solve selected optimization subproblems.