چكيده به لاتين
Path planning is the important and complicated part of naviGAtion system in quadrotors Which has a significant effect on increasing the robot's autonomy. From the past to the now, several methods have been used to route robots in different operating and environmental conditions. Given that the collective movement of quadrotors has many benefits, such as cost reduction, reduced operation time, reduced sensitivity to external conditions, etc., the issue of tracking the collective movement of quadrotors is considered here. It should be noted that the movement of robots is also predetermined and the obstacles in this environment are completely static. By analyzing various routing algorithms, including classical algorithms and computational intelligence, and using the strengths of each, and according to environmental and operational conditions, we first used the high-speed RRT sampling-based algorithm in order to Determining the initial and possible distribution. Then, the results of this algorithm entered the combined GA-PSO algorithm and by combining with the other primary population and the desired cost function, more optimal answers were provided. The routes of this algorithm were more efficient than the RRT algorithm and also satisfied the non-collision of quadrotors with each other. Then, the Bezier curve was used to smooth and fix the fractures of the path and to consider the time of movement and cinematic constraints. The control points and time intervals required to create this curve were optimized by the PSO algorithm. The results included smooth paths that provided short path constraints, minimal movement time, non-collision with obstacles and other quadrotors, and speed limits. Quadrotor dynamic modeling was further developed using Euler-Newton method. The equations of motion were determined by the assumptions, and implemented in the Simulink environment. Simulink's auto-tuning section was also used to design the PID controller coefficients
