To ensure the attack mission success rate, a trajectory with high survivability and accepted path length and multiple paths with different attack angles must be planned. This paper proposes a novel path planning algorithm based on orthogonal particle swarm optimization, which divides population individual and speed vector into independent orthogonal parts, velocity and individual part update independently, this improvement advances optimization effect of traditional particle swarm optimization in the field of path planning, multiple paths are produced by setting different attacking angles, this method is simulated on electronic chart, the simulation result shows the effect of this method.
A new path planning method for UAV in static workspace is presented. The method can find a nearly optimal path in
short time which satisfies the UAV kinematic constraints. The method makes use of the skeletons to construct the graph
of the planning space considering the configuration of the obstacles and utilizes the graph to find a shortest collision-free
path, and a novel technique is utilized to convert the free path into a feasible path. The method can be applied to different
applications and easy to be implemented. Experimental results showed that the path planning can be done in a fraction of
second on a contemporary workstation (2-3 seconds) under the condition of satisfying the kinematic constraints.