Three-dimensional flight path planning by artificial immune algorithm

Abstract

Artificial immune algorithm (AIA) is used for offline as well as online path planning in this paper. Firstly, AIA is divided into three cases: 1. antibody is randomly selected to inoculate; 2. all antibodies are inoculated; 3. every antibody is inoculated, but inoculated location is selected at random. At the same time, we have simulated two kinds of threat uncertainties and one special occasion (no-fly-zone): changing the size of a certain kind of threat or increasing the number of unexpected threat. Based on above flight path planned, we adjust level path to meet maximum turning angle restriction, and vertical track to normal acceleration and curvature constraint by slope restriction algorithm and curvature smoothing algorithm making practical steering possible. And we also reduced the redundant path points (or frequent turning) to easy pilot manipulate and decrease the unsafe factors of flight. In addition, 3 orders B-spline curve is utilized for representing 3D path. At last, the simulated three-dimensional flight path by improved electric potential method and artificial immune algorithm are compared and the result is: artificial immune algorithm is not only feasible for searching three dimensional path applications, but there is a great reduction of the computational time.