苹果采摘机械手的逆运动学求解研究

为了提高苹果采摘机械手的采摘成品率，保证采摘后苹果质量，提出一种引入采摘综合因素的苹果采摘机械手的逆运动学求解方法。首先，采用Denavit Hartenberg模型对苹果采摘机械手进行建模，并将逆运动学求解问题转化为规划问题，其中，目标函数为所求得逆运动学参数对应的机械手末端中心坐标与待求坐标欧式距离。然后，在遗传算法选择、交叉、变异算子进行全局搜索的基础上，结合非线性规划对目标函数进行局部搜索。最后，借助随机森林算法将逆运动学求解结果分为3个姿势等级。试验表明，非线性遗传算法在苹果采摘机械手的逆运动学求解上相比遗传算法精度提高了8～25 mm，随机森林算法可以很好地对其求逆结果进行优化，从而提高苹果采摘成品率。

Research on inverse kinematics solution of apple picking manipulator

In order to improve the stability and yield of apple picking robot， the method of inverse kinematics of picking manipulator was proposed. First， the D H model was used to establish the model of the apple picking robot. Kinematics problem of apple picking robot was thus translated into programming problem. The objective function was the Euclidean distance between the apple picking robot coordinate and unknown coordinate. In order to obtain the inverse kinematic parameters， the genetic algorithm was then used for global search， which included selection， crossover and mutation operators， and non linear programming was used for local search based on the result of genetic algorithm. Finally， the kinematic parameters were divided into 3 grades by random forest algorithm. Experiment showed that compared with the genetic algorithm， the algorithm proposed in the present study improved the accuracy by 8-25 mm in solution of inverse kinematics. In conclusion， the proposed method was valid for kinematics problem， and thus would help improve the yield of apple picking robot.