Simulation of Trajectory Optimization and Load Balancing of Micro-UAV Carrying Platforms Based on Genetic Algorithms
Shaohong Li, Haifeng Zhang, Meihui Sun · 2025
With the widespread application of micro-VAV in aerial photography and scientific research, parallel mechanism carrying platforms have become critical equipment for evaluating their control algorithms and sensor performance. A six-degree-of-freedom (6-DOF) parallel platform trajectory optimization method is presented. It aims to reduce the actuator energy consumption and balance the load. Firstly, a dynamic model of the Stewart platform is constructed, taking into account the kinematic and dynamic features of both the platform and its limbs. Secondly, genetic algorithms are employed to optimize trajectory parameters, a fitness function is designed to minimize actuator forces, while introducing workspace constraints to ensure trajectory feasibility. Finally, force distribution and trajectory diagrams are plotted for performance analysis. The experimental results indicate that the optimized energy consumption is reduced by an average of approximately 41%, and the maximum driving force required for the branches is reduced by an average of around 24.8%. It meets the requirements of high precision and stability for UAV dynamic simulation and testing.