改进鸽群和Morphin算法的混合路径规划算法研究  

Research on Hybrid Path Planning Algorithm Based on Improved Pigeon Flock and Morphin Algorithm

作　　者：支奕琛 谷玉海[2] 徐小力[1] 龙伊娜 ZHI Yi-chen;GU Yu-hai;XU Xiao-li;LONG Yi-na(Key Laboratory of Measurement and Control Technology,Ministry of Education,Beijing Information Science and Technology,Beijing 100192,China;Mechanical and Electrical Engineering,Beijing Information Science and Technology University,Beijing 100192,China)

机构地区：[1]北京信息科技大学现代测控技术教育部重点实验室,北京100192 [2]北京信息科技大学机电工程学院,北京100192

出　　处：《机械设计与制造》2024年第6期53-57,63,共6页Machinery Design & Manufacture

基　　金：促进高校内涵发展—学科建设专项资助项目(5112011015)。

摘　　要：针对目前无人车在复杂环境例如同时存在静态和动态障碍物的环境下路径规划能力较弱的情况,提出了一种引入自适应权重系数的鸽群算法和Morphine算法的混合路径规划算法。(1)在栅格地图中确定起点和终点同时建立环境模型;(2)在鸽群算中加入自适应权重系数进行改进从而规划出一条全局最优路径,无人车按照全局路径行驶,当无人车的传感器探测到未知的静态或动态障碍物情况下,将会立刻运用Morphine算法进行相应的路线设计,从而实现对障碍物的躲避,无人车躲避障碍物后回到原来的路径上继续行驶至目标点。通过仿真实验和在无人车上的实际应用验证了该混合路径规划算法的有效性和可行性。Aiming at the weak path planning ability of unmanned vehicles in complex environments such as static and dynamic obstacles at the same time,a hybrid path planning algorithm based on pigeon flock algorithm and Morphine algorithm with adaptive weight coefficients is proposed.The first step is to determine the starting point and the end point in the grid map while es-tablishing an environment model.The second step is to add adaptive weight coefficients to the pigeon calculation to make improve-ments to plan a global optimal path.The unmanned vehicle drives according to the global path.When the sensor of the unmanned vehicle detects an unknown static or dynamic obstacle,it immediately calls the Morphine algorithm for local path planning to avoid the obstacle.The unmanned vehicle returns to the original path after avoiding the obstacle and continues to drive to the tar-get point.The effectiveness and feasibility of the hybrid path planning algorithm are verified by simulation experiments and practi-cal applications on unmanned vehicles.

关 键 词：无人车 障碍物 改进鸽群算法 Morphine算法 

分 类 号：TH16[机械工程—机械制造及自动化] TP3[自动化与计算机技术—计算机科学与技术]