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Real-Time Three-Dimensional Smooth Path Planning for Unmanned Aerial Vehicles in Completely Unknown Cluttered Environments

机译:无人空中车辆在完全未知杂乱环境中的实时三维平滑路径规划

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This paper presents a real-time three-dimensional path planning algorithm for improving autonomous navigation of Unmanned Aerial Vehicles (UAVs) operating in completely unknown cluttered environments. The algorithm generates smooth paths consisting of continuous piecewise Bézier curves in real time. Specifically, a RRT*-based waypoint generation algorithm is firstly proposed for the exploration of collision-free waypoints successively during flight. Besides, a novel real-time path smoothing technique is developed to generate continuous collision-free paths that satisfy the motion constraints of UAVs. This is achieved by fitting Bézier curves between consecutive waypoints based on the particle swarm optimization (PSO) algorithm. Lastly, a path selection strategy is also introduced to seek for an optimum path when multiple solutions are available. The simulation results demonstrate the superiority of the proposed real-time three-dimensional smooth path planning algorithm.
机译:本文提出了一种实时三维路径规划算法,用于改善在完全未知的杂乱环境中运行的无人航空车辆(无人机)的自主导航。该算法生成平滑路径,实时由连续分段Bézier曲线组成。具体地,首先提出了一种RRT *基于航点生成算法,以在飞行期间连续地探索无碰撞的航点。此外,开发了一种新颖的实时路径平滑技术,以产生满足无人机的运动约束的连续碰撞路径。这是通过基于粒子群优化(PSO)算法的连续航点之间的Bézier曲线来实现。最后,还引入了路径选择策略以在多种解决方案可用时寻求最佳路径。仿真结果证明了所提出的实时三维平滑路径规划算法的优越性。

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