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作 者:李克玉 陆永耕[1] 鲍世通 徐培真 LI Ke-yu;LU Yong-gen;BO Shi-tong;XU Pei—zhen(Electrical College,Shanghai Institute of Electrical Engineering,Shanghai 200240,China)
出 处:《计算机仿真》2021年第8期59-63,96,共6页Computer Simulation
摘 要:RRT算法由于其在复杂环境中有强大的随机搜索能力,在无人机避障规划中被广泛运用。为了提高无人机避障规划的效率,提出了一种基于预规划路径优化RRT算法的无人机三维避障规划算法。算法首先在障碍物膨胀规则和相交规则下生成预规划路径,然后将预规划路径看做成连续的质点组成,按一定的扩展树步长的比例从连续质点取点来确定搜索树的随机状态点,最后RRT算法在这些随机状态点的引导下进行搜索,生成避障规划路径。仿真结果表明,改进的RRT算法生成的预规划路径降低了障碍物搜索的时间和增强了搜索树扩展的方向性;预先确定的随机状态点使搜索树在扩展中具有方向性,可减少新生节点的个数和路径长度,进而提高了无人机避障路径规划的效率,使得最终生成避障路径的时间更优。RRT algorithm is widely used in UAV obstacle avoidance planning because of its strong random search ability in complex environment.In order to improve the efficiency of UAV obstacle avoidance planning,this paper proposes a three-dimensional obstacle avoidance planning algorithm for UAV based on pre-planning path optimization RRT algorithm.The algorithm first generates the pre-planned path under the rules of obstacle expansion and intersection,then regards the pre-planned path as a continuous particle composition,and determines the random state points of the search tree from the continuous particle according to a certain proportion of the step size of the extended tree.Finally,the RRT algorithm searches under the guidance of these random state points to generate obstacle avoidance planning path.The simulation results show that the pre-planned path generated by the improved RRT algorithm reduces the time of obstacle search and enhances the direction of the search tree expansion;the pre-determined random state points make the search tree directional in the expansion,which can reduce the number of new nodes and the path length,thus improving the efficiency of UAV obstacle avoidance path planning,and achieving better time for final generation of obstacle avoidance path.
关 键 词:快速扩展随机树算法 预规划路径 三维避障规划 算法改进 无人机
分 类 号:TP301.6[自动化与计算机技术—计算机系统结构]
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