Abstract
The path planning of the Unmanned Aerial Vehicle (UAV) refers to searching a feasible path from the start to the end under the restriction of combat mission, geography, dynamic constrains of the UAV, etc. The real-time planning can improve the survival probability of UAV in modern complicated battlefield. In this paper, we improve the traditional Ant Colony Optimization (ACO) algorithm to four-Dimensional (4D), which can perform real-time path planning in a dynamic environment. In addition, we add the velocity planning to the path planning, making the path more accurate. Further, Considering the performance constraints and safety of the UAV, we use the cost of Residual Sum of Squares (RSS) as an evaluation index to the velocity optimization. The simulation results show that the velocity of UAV can be dynamically changed with the time advancing and environment changing, and the speed is changing more smoothly to satisfy the actual flight requirements with our velocity optimization algorithm.
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