冗余漂浮空间机器人多任务轨迹规划  

Multitask-based trajectory planning of redundant floating space robotics

作　　者：赵素平 陈超波[1] 阎坤 宋晓华 ZHAO Suping;CHEN Chaobo;YAN Kun;SONG Xiaohua(School of Electronic Information Engineering,Xi′an Technological University,Xi′an 710021,China)

机构地区：[1]西安工业大学电子信息工程学院,陕西西安710021

出　　处：《哈尔滨工程大学学报》2024年第9期1818-1825,共8页Journal of Harbin Engineering University

基　　金：国家自然科学基金项目(62103315);陕西省科技厅基金项目(2022GY-236,2022GY-306).

摘　　要：针对冗余漂浮空间机器人在单次行程中连续执行多项轨道任务的能耗最优轨迹规划问题,本文提出一种改进遗传算法,将同时优化3种类型基因引入,使得每条染色体包含3部分,即任务序列、与任务序列对应的关节构型序列和描述机器人关节轨迹的正弦多项式系数,对染色体的3部分进行独立编码,并在迭代寻优过程中对3个组成部分独立执行交叉和变异操作。仿真结果表明:与传统遗传算法相比,本文算法具有精度高、计算量少和CPU时间短的优点。For a redundant floating space robot performing multiple tasks in one travel,an improved genetic algo-rithm(IGA)is proposed to solve the corresponding trajectory planning problem.Three gene categories are simulta-neously optimized,and each chromosome consists of three parts.The three parts include a sequential order of task points,a sequential order of joint configurations corresponding to task points,and a sine polynomial coefficient em-ployed to depict joint trajectories.The three parts are separately encoded,and the crossover and mutation opera-tions are separately performed during iterations.Simulation results show that,compared with traditional genetic al-gorithms,IGA has higher efficiency,less calculation,and shorter CPU time.

关 键 词：空间机器人 自由度冗余 漂浮基座 多任务轨迹规划 关节构型 遗传算法 改进遗传算法 多刚体动力学 

分 类 号：V448[航空宇航科学与技术—飞行器设计]