摘要
由于果蔬采摘环境的不确定性和复杂性,机械臂在复杂环境中完成采摘,其路径规划需考虑实时避障。为实现采摘机械臂在不确定环境下安全采摘,提出一种改进RRT的动态避障算法,以提升机械臂在不确定采摘环境的适应性。针对基本快速扩展随机树算法(Rapidly-exploring Random Trees,RRT)在动态环境下迭代时间长、路径长、适应性差等问题,在RRT算法的基础上,引入目标导向策略,把终点以一定概率作为随机采样点的采样方向,提高算法的迭代效率;引入动态检测机制,对已完成规划的初始路径进行实时检测,使算法适应动态变化的环境。通过仿真分析改进RRT算法,结果表明:改进RRT算法的路径减少16%,迭代时间缩短86.5%;同时,动态检测机制使算法适应动态环境。
Due to the uncertainty and complexity of the harvesting environment for fruits and vegetables,the manipulator needs to consider real-time obstacle avoidance in completing harvesting tasks in complex environments.In order to achieve safe harvesting of manipulator in uncertain environments,an improved dynamic obstacle avoidance algorithm based on the rapidly-exploring random trees(RRT)algorithm is proposed to enhance the adaptability of manipulator in uncertain harvesting environments.In order to address the issues of long iteration time,long path length,and poor adaptability in dynamic environments of the basic RRT algorithm,this study first introduces a target-oriented strategy to increase the iteration efficiency of the algorithm by randomly sampling points with a certain probability towards the endpoint.Secondly,a dynamic detection mechanism is introduced to dynamically detect the initial path that has been planned,making the algorithm adaptable to changes in the environment.Simulation analysis shows that the improved RRT algorithm reduces path length by 16%and shortens iteration time by 86.5%compared to the basic RRT algorithm.Furthermore,the dynamic detection mechanism allows the algorithm to adapt to dynamic environments.
作者
李晓娟
陈涛
韩睿春
刘建璇
Li Xiaojuan;Chen Tao;Han Ruichun;Liu Jianxuan(College of Mechanical Engineering,Xinjiang University,Urumqi,830000,China)
出处
《中国农机化学报》
北大核心
2024年第4期193-198,F0003,共7页
Journal of Chinese Agricultural Mechanization
基金
国家自然科学基金(52265003)
机械制造系统工程国家重点实验室开放课题基金项目(sklms2022023)
新疆维吾尔自治区创新团队机器人及智能装备技术科技创新团队(2022D14002)。
关键词
果蔬采摘
机械臂
快速扩展随机树
动态避障
目标导向
动态检测
路径规划
pick fruits and vegetables
robotic arm
rapidly-exploring random trees
dynamic obstacle avoidance
goal orientation
dynamic detection
path planning
