基于层次分解的在线三维RRT^(*)协同航路规划

Online three-dimensional RRT^(*)cooperative route planning based on hierarchical decomposition

针对多机时间协同航路规划问题提出一种基于层次分解的在线三维规划方法。首先,将高维强耦合协同规划问题按3层分解为低维的简单优化问题。其次,提出基于反双曲正切函数的协同指标参数的优化方法,以解决各无人机时间间隔过大导致绕飞消耗的问题。然后,提出基于滚动时域的三维快速搜索随机树^(*)(three dimensional rapidly-exploring random tree^(*)based on receding horizon,TRH-RRT^(*))在线航路规划算法,用有偏随机样本增加采样点利用率,用人工势场法引导RRT^(*)节点生长并基于滚动时域的节点去除法减少非必要的扫描过程。最后,针对多机会聚攻击任务进行了仿真验证,结果表明所提方法在航路规划时间及规划结果方面具备一定优越性。

Aiming at the time cooperative route planning problem of multiple unmanned aerial vehicles(UAVs),an online three-dimensional planning method based on hierarchical decomposition is proposed.Firstly,the high dimensional strong coupling cooperative planning problem is decomposed into a low dimensional simple optimization problem according to 3 layers.Secondly,an optimization method of cooperative index parameters based on the inverse hyperbolic tangent function is presented in order to solve the diversion consumption problem caused by excessive time intervals between UAVs.Then,an online route planning algorithm of three-dimensional rapidly-exploring random tree^(*)based on receding horizon(TRH-RRT^(*))is proposed.The biased random samples are employed to increase the utilization of sampling points,the artificial potential field is exploited to guide the growth of RRT^(*)nodes and the node removal method based on receding horizon is applied to reducing the unnecessary scanning process.Finally,the simulation results for attack mission of UAVs convergence show that the proposed method possesses advantages in planning time and planning results.