智能化无人机测绘路径规划与动态避障算法研究

Research on Intelligent UAV Mapping Path Planning and Dynamic Obstacle Avoidance Algorithm

在常规无人机路径规划和动态避障算法中,研究人员通常采用随机选择的方式为无人机生成避障路线,往往会导致无人机的安全避障率不足。因此,提出智能化无人机测绘路径规划与动态避障算法。首先,划分无人机的测绘环境空间,通过栅格法选择最优路线,设置无人机的限制和环境约束。其次,预测无人机的碰撞路线,根据是否碰撞设定速度的加减,无法有效避障时通过强化学习法重新规划无人机的行进路线,再转回已有的最优路径规划中。最后,进行实验分析。实验结果表明,所设计的动态避障算法具有一定的优势,能够有效避开障碍物,优于对照组。

In conventional drone path planning and dynamic obstacle avoidance algorithms,researchers usually use a random selection method to generate obstacle avoidance routes for drones,which often leads to insufficient safety obstacle avoidance rate.Therefore,intelligent drone mapping path planning and dynamic obstacle avoidance algorithm are proposed.Firstly,divide the surveying environment space of the drone,select the optimal route through the grid method,and set the limitations and environmental constraints of the drone.Secondly,predict the collision route of the drone,and based on whether the collision occurs,adjust the speed accordingly.If obstacle avoidance cannot be effectively achieved,use reinforcement learning methods to re plan the drone's travel route,and then revert back to the existing optimal path planning.Finally,conduct experimental analysis.The experimental results show that the designed dynamic obstacle avoidance algorithm has certain advantages,can effectively avoid obstacles,and is superior to the control group.