Using Quantum Computings During Collaborative Mobile Robot Trajectory Constructing

Abstract

The article considers a method for constructing a trajectory of a collaborative mobile robot using quantum computing in combination with classical optimization algorithms. The purpose of the study is to develop a mathematical model and numerical simulation of a quantum-oriented approach to constructing a trajectory of a collaborative robot, which allows minimizing energy costs in motion planning and ensuring obstacle avoidance in a dynamic environment. The scientific novelty of the work lies in the application of quantum optimization methods for multivariate planning, which allows avoiding local minima and guaranteeing the search for globally optimal solutions even in the case of complex configuration spaces. During the numerical simulation, it was demonstrated that the formed trajectories ensure successful obstacle avoidance and reaching the target point without deviations from the grid. Conclusions: analysis of the results showed stabilization of the energy function at the level of −350…−420, which confirms the effectiveness of optimization and convergence to the best solutions after 100–150 iterations. The constructed graphs confirmed that the robot’s movement is consistent with the calculated quantum plans, and the deviation between the predicted and executed trajectories is minimized. The use of the energy efficiency criterion allowed us to evaluate different route construction scenarios, where the best plans stabilized with a margin of optimality relative to the worst options by 15–20%. Qualitative analysis of the constructed trajectories confirmed the consistency between the predicted and executed paths, and quantitative results proved a reduction in the number of steps when reaching the target point. The results obtained prove that the proposed method is promising for constructing reliable and energy-optimal trajectories in collaborative robotic systems Industry 5.0.