Research On UAV Path Planning In Simulated Battlefield Environment

With the warfare’s gradual development of unmanned and intelligent,UAVs will be widely used in complex battlefield environments.Such an environment puts forward higher requirements on the path planning capabilities of military UAVs.Robot path planning refers to planning a collision-free path from the starting point to the target area that satisfies the constraints of the environment and the robot itself in a working environment with obstacles.However,the battlefield environment is different from the working space of an ordinary robot,it has complex constraints,such as facing various threat from the enemy’s air,ground and sea.The existing path planning algorithms are not effective in the battlefield environment.It is challenging to plan a high-quality path from the starting point to the target area in such an environment.Therefore,this article conducted a research on UAV path planning in a simulated battlefield environment.The main research contents include:（1）Aiming at the problem of global path planning in the battlefield environment,the idea of vector is introduced on the basis of the RRT* algorithm,and the VRRT* algorithm is proposed.In the node expansion process of algorithm,the repulsion vector,gravitation vector and threat vector are introduced to intervene the expansion point.The gravitation vector guides the expansion point toward the target area,the repulsion vector guides the expansion point to escape the enemy’s attack range,and the threat vector guides the expansion point away from enemy military units with high threat.The trade-off between security and efficiency of the global path is realized.（2）Aiming at the enemy’s mobile threat,a path re-planning algorithm suitable for the battlefield environment is proposed.The method based on Kalman Filter is used to predict the position of the enemy’s mobile threat,and the path is re-planned according to the predicted position,which improves the efficiency of the path re-planning algorithm.Faced with the failure of path re-planning due to the enemy’s tight defense,the Mean Shift clustering algorithm is used to identify the enemy’s military formations,and the idea of Attention Mechanism is introduced to evaluate the importance of each formation.Select key formations to launch an attack,and then re-plan the path after breaking through the enemy’s defensive barrier to ensure the success rate of path planning.（3）Aiming at the enemy’s hunting strategy,a local path planning algorithm in the battlefield environment is proposed based on the Artificial Potential Field algorithm.Create a gravitational field centered on the location of frigate,and create multiple repulsion fields centered on the location of enemy fighter.Calculate the gravitational and repulsive forces based on the position of the UAV in the gravitational field and the repulsion field.The two act together to guide UAV to avoid rounding up and further improves the safety of the path.The experimental results show that the path planned by the VRRT* algorithm proposed in this dissertation has high efficiency while ensuring safety;the path re-planning algorithm and local path planning algorithm in this dissertation have better performance in the face of mobile threats.It can further ensure the safety of drones.The synergy of various algorithms can make the UAV in the battlefield environment reach the target area smoothly to complete the task.