From Table 2, we can see that the average optimal value which is got by IAFSA is better than the standard AFSA.
The table shows that, compared with standard AFSA, the search ability of IAFSA is enhanced.
As shown in Figure 4, the search ability of IAFSA is stronger than of AFSA, and the convergence speed is faster.
The performance of path planning with the IAFSA application in robot navigation is shown in Figure 8(a).
In Table 4, the route obtained by IAFSA is the shortest.
However, the proposed IAFSA in this paper makes the step smaller, the trajectory smoother, and the total route shorter.
In Table 5, we can find out that the path got by IAFSA is the shortest, followed by [A.
The IAFSA is applied to the path planning problem of mobile robot which is equipped with ROS.