Path Planning of Uninhabited Aerial Vehicle Added the Guiding Factor

Path planning is vital to the application of Uninhabited Aerial Vehicle (UAV). A good path planning can be obtained by searching out a path between the start location and end location in time, along which UAV is able to accomplish the flight mission and avoid the hostile threats well. Due to the big search space, the original ant algorithm system (ACS) can easily converge to the local optimization and calculates efficiency slowly. The guiding factor is added to modify ACS and to solve the problems mentioned above. It can reduce the blindness of local search and ensure ants to reach the destination node. Both operations of the simple obstacle and the mixture obstacle are using to prove the method mentioned above. From the results of simulation, we can conclude: (1) The guiding factor can help to avoid both the simple obstacle and the mixture obstacles accurately and to obtain the optimal flight path. (2) Compared with conventional ACS, the calculate efficiency is higher and the local optimization is inexistence under modified ACS.