Algorithm 2 CASSA for 3d UAV route planning

/*Initialization*/ 1. Set the parameters of CASSA same as Algorithm 1; 2. Set the start point $(x_S,y_S)$, target point $(x_T,y_T)$, the boundaries of the map space, and     the number of control points $n$; 3. Set the position$(x_{threat},y_{threat})$ and the range of threats; /*Iterative search*/ 4. while ($t<T_{\max }$) 5. Each sparrow represents a route; sort the population of sparrows from best to worst by     order of cost function Equation (10) for each sparrow 6. $G=rand(1)$; 7. for $i=1:F_d$ 8.   Update the finder’s position using Equation (7); 9. end for 10. for $i=(F_d+1):n$ 11.   Update the entrant’s position using Equation (3); 12. end for 13. for $i=1:S_d$ 14.   Update the threatened sparrow’s position using Equation (4); 15. end for 16. Evaluate the cost for each route by Equation (13), then select the top S elite sparrows with the     best fitness value and implement adaptive mutation for them by Equation (9); 17. Get the current new route; 18. If the new route is better than before, update it; 19. Generate the B-Spline curve with the $n$ waypoints. 20. $t=t+1$; 21. end while 22. Output the best route and its cost value. 23. Post-process results and visualization