工业机器人时间-能量最优轨迹规划  

Time-Energy Optimum Trajectory Planning for Industrial Robot

作　　者：浦玉学[1] 舒鹏飞 蒋祺[2] 陈卫中 PU Yuxue;SHU Pengfei;JIANG Qi;CHEN Weizhong(College of Civil Engineering,Hefei University of Technology,Hefei 230009,China;College of Aerospace Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,China;Kunshan Huaheng Welding Equipment Corporation,Suzhou,Jiangsu 215300,China)

机构地区：[1]合肥工业大学土木与水利工程学院,合肥230009 [2]南京航空航天大学航空宇航学院,南京210016 [3]昆山华恒焊接股份有限公司,江苏苏州215300

出　　处：《计算机工程与应用》2019年第22期86-90,151,共6页Computer Engineering and Applications

基　　金：国家自然科学基金（No.51605127）

摘　　要：针对工业机器人时间最优、能耗最优的多目标轨迹优化问题,提出了一种基于改进引力搜索算法的最优轨迹规划方法。将引力搜索算法的种群按照惯性质量的大小均分为两组。首先引领组的粒子进行小范围的邻域搜索。然后引领组通过施加引力来引导跟随组的粒子进行位置更新。同时引入人工蜂群算法的贪婪选择策略,每次更新保留较优解。以自主研发的150 kg重载机器人为实验对象,将所提算法与标准人工蜂群算法和引力搜索算法进行比较,结果表明所提算法具有更优性能。Aiming at the multi-objective trajectory optimization problem with optimal travelling time and energy consumption, an optimal trajectory planning method for industrial robots based on Improved Gravitational Search Algorithm(IGSA)is proposed. The agents of the gravitational search algorithm are divided into two groups according to the size of the inertial mass. Firstly, the particles of the leading group perform a small-range neighborhood search. Then, the leading group guides the onlookers group to update positions by applying gravity. And the greedy selection strategy of Artificial Bee Colony algorithm(ABC)is adopted to remain better solutions. Taking the self-developed 150 kg heavy-duty robot as experimental object, IGSA is compared with ABC and GSA, the result shows that the performance of IGSA is better than the other two.

关 键 词：工业机器人 轨迹规划 引力搜索算法 人工蜂群算法 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]