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作 者:管翔宇 周勇[1] 胡楷雄 GUAN Xiangyu;ZHOU Yong;HU Kaixiong(School of Transportation and Logistics Engineering,Wuhan University of Technology,Wuhan 430063,China)
机构地区:[1]武汉理工大学交通与物流工程学院
出 处:《组合机床与自动化加工技术》2025年第2期81-86,共6页Modular Machine Tool & Automatic Manufacturing Technique
基 金:国家自然科学基金项目(51975444)。
摘 要:针对实现机械臂在运动学限制条件下提升作业效率与稳定性目标,提出了一种基于改进JAYA算法的机械臂时间最优轨迹规划方法。选取UR5e机器人为研究对象,构建针对时间最优化的数学模型,并采纳3-5-3混合多项式插值方法,进行轨迹规划的设计与分析。针对所建立的数学模型对标准的JAYA算法进行改进,通过Tent混沌映射进行种群初始化,并引入局部吸引点和历史种群来分别优化局部搜索和全局搜索,从而提高算法性能。利用改进的JAYA算法进行了机械臂时间最优轨迹规划实验,结果表明,相比标准粒子群算法(PSO)和标准JAYA算法具有更高的寻优精度和更强的跳出局部最优解能力,优化后的各关节位移、速度和加速度曲线平滑,运行时间减少了39.7%。In order to improve the working efficiency and stability of the manipulator under kinematic constraints,a time-optimal trajectory planning method of the manipulator based on the improved JAYA algorithm is proposed.Selecting robot UR5e as the research object,the mathematical model of time optimization target is established and the 3-5-3 hybrid polynomial interpolation method is adopted for trajectory planning design and analysis.According to the established mathematical model,the standard JAYA algorithm is improved by using Tent chaotic mapping for population initialization,and introducing local attraction points and historical populations to optimize local search and global search respectively,thus improving the performance of the algorithm.An experiment was conducted on the time optimal trajectory planning of a robotic arm using the improved JAYA algorithm.The results indicate that in contrast to the conventional particle swarm optimization(PSO) algorithm and the standard JAYA algorithm,the improved JAYA algorithm demonstrates superior optimization precision and greater capacity to escape local optimal solutions.It yields smooth displacement,velocity,and acceleration curves for each joint,resulting in a notable 39.7% reduction in runtime.
分 类 号:TH112[机械工程—机械设计及理论] TG659[金属学及工艺—金属切削加工及机床]
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