基于遗传算法的新型混联搬运机器人的轨迹优化设计  

Optimal Planning of New Hybrid Palletizing Robot Based on Genetic Algorithm

作　　者：李伟[1] 常光明[1] 王权[1] 管健[1] 

机构地区：[1]郑州轻工业学院机电工程学院,郑州450002

出　　处：《煤矿机械》2015年第11期50-53,共4页Coal Mine Machinery

摘　　要：传统路径规划方式多采用多项式样条曲线,次数高,轨迹计算量大,考虑工作效率及运动平稳性的要求,提出了基于速度约束的4-3-4关节空间的轨迹规划,并采用基于外点惩罚函数法的遗传算法优化多项式插值时间,通过Matlab进行各关节的位置、速度、加速度仿真验证表明,所设计的方案能保证机器人运动时间最短,且关节曲线连续平稳。Traditional polynomial path planning approach has a high frequency, large amount of calculation of trajectory. Considering efficiency and smooth movement requirements, then a method of4-3-4 track joint space planning based on kinematic constraints is presented. using the penalty function method based on genetic algorithm to optimize the outer point polynomial interpolation time position of each joint,with Matlab simulation, velocity, acceleration simulation results show that the design of the program to ensure that the time of robot motion shortest and joint continuous smooth curve.

关 键 词：搬运机器人 遗传算法 轨迹优化 MATLAB仿真 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]