**4. Payload Hold-Release Mission Planning**

In this study, a path planning and tracking algorithm is proposed on three different maps. In order to guarantee that the algorithms run do not memorize the path, three maps with different starting and ending points, containing obstacles at different locations, are generated. On the first map, there are obstacles of equal size with a radius of 2 m. On the second map, there are obstacles of two different sizes with radii of 1 m and 2 m. On the third map, there are obstacles in three different sizes with radii of 1 m, 1.5 m, and 2 m. The environmental difficulty level of Map 1, Map 2, and Map 3 range from weak to strong, respectively, in performing the payload hold-and-release mission by coping with obstacles. Seven separate spherical obstacles are placed on each of the maps. The locations of these spherical barriers on three different maps are given in Table 1. As stated in the Table 1, the location of each obstacle in 3D space is expressed as the *X*, *Y*, *Z* positions and radius R. These spherical barriers are positioned in 3D space, as shown in Figure 5. Here, the point where the quadcopter starts its mission, holds and releases the payload is shown as star, square and circle, respectively. In addition, the numbers on the figure are used to label the obstacles. The numbers on the figure are used to name the obstacles. Considering the safe and shortest path conditions of the quadrotor on these generated maps, waypoints are determined by metaheuristic optimization algorithms such as PSO, GWO, and hybrid HHO–GWO. By following this determined path, the payload hold–release performance of the quadrotor has been analyzed.

**Figure 5.** Maps created for testing the performance of quadcopter path planning and tracking (**a**) for Scenario 1, (**b**) for Scenario 2, (**c**) for Scenario 3.


**Table 1.** Positions of obstacles with 3 different scenarios.
