基于行为协同和虚拟目标相结合的无人机实时航路规划

针对实时航路规划问题,综合考虑航路最优、平滑性、全局收敛性以及从威胁域的逃逸能力等限制时,还没有有效的规划算法.为此提出了一种基于行为协同和虚拟目标相结合的无人机实时航路规划方法.该方法将无人机的航路规划行为分为局部和全局行为:局部行为采用基于模糊控制的方法,用来实现威胁体规避;全局行为使用全局算法,通过全局目标和虚拟目标的切换实现了全局目标收敛和威胁域边界跟踪,然后通过模糊控制器对两种行为进行协同.最后通过分析、证明以及几种不同情形下的仿真表明该方法具有航路短、平滑和全局收敛的特点.

Real-time path planning for unmanned aerial vehicles using behavior coordination and virtual goal

There is no effective real-time path planning algorithm for unmanned aerial vehicles to meet the simultaneous requirements in flight path optimization, smoothness, global convergence, and evasion. We propose a real-time path planning approach based on the coordination of the global and local behaviors. This approach realizes the path planning by controlling the local behavior and the global behavior. A fuzzy logic controller(FLC) for controlling the local behavior is designed to achieve the threat-avoidance. The global turning angle algorithm for controlling the global behavior realizes the global goal convergence and boundary following of threatening region through switching between the global goal and virtual goals. The coordination mechanism based on fuzzy logic is used to fuse the control commands of two behavior controllers for UAVs. Through different analysis, proofs, and simulations, we verify that the propose approach provides characteristics of shorter path, smoothness and global convergence.