多约束条件下无人艇和无人机集群协同航迹规划

Cooperative path planning of USV and UAV swarms under multiple constraints

    摘要
  • 摘要:
      目的  为实现海上无人集群在执行任务过程中的安全航行和通信保持，开展无人艇（USV）和无人机（UAV）集群协同航迹规划问题的研究。
      方法  采用禁入和禁出地理围栏进行场景建模，将规避威胁和障碍问题转化为地理围栏约束。针对平台之间的碰撞冲突和通信连接问题，提出基于时序检测的碰撞冲突和通信保持约束判断准则。以集群平均航行时间为航迹优化函数，将多约束条件转化为惩罚函数，采用自适应差分进化算法进行优化求解。
      结果  仿真结果表明，所提方法能够在威胁和障碍环境中保持无人艇和无人机集群的安全航行和通信连接，并在满足多约束的条件下实现集群平均航行时间最短。
      结论  该方法可用于海上无人集群面对威胁和障碍环境时的离线航迹规划，具有一定的应用价值。

     

    Abstract:
      Objectives  For achieving navigational safety and continuous communication link between swarms of unmanned marine vehicle (UMV) during mission execution, the cooperative path planning of unmanned surface vehicle (USV) and unmanned aerial vehicle (UAV) swarms is studied.
      Methods  Keep-in and keep-out geo-fences are used to carry out scene modelling, and the problems of threat and obstacle avoidance are transformed into geo-fence constraints. Aiming at collision avoidance and continuous communication link between vehicles, a judgment criterion for the constraints of collision avoidance and communication link via time sequence detection is proposed. The average travel time (ATT) of the swarm is taken as the path optimization function, and the multiple constraints are transformed into penalty functions. A self-adaptive differential evolution algorithm is adopted to solve the optimization problem.
      Results  The proposed method can ensure safe navigation and communication link between USV and UAV swarms in hostile and obstacle-filled environment, and achieve the shortest ATT under multiple constraints.
      Conclusions  This method has practical value for the off-line path planning of UMV swarms in the hostile and obstacle-filled environment.

     

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