机械手不同抓取控制方式对番茄机械损伤的影响分析

为了分析机械手不同抓取控制方式对番茄造成的机械损伤。通过Burgers粘弹性模型描述番茄的变形特征,利用蠕变实验获得番茄样本的粘弹性参数。选择匀减速、先匀速后减速以及变减速作为3种典型的抓取控制方式,并利用一次函数、巴特沃斯幅度平方函数和指数函数3种函数曲线描述末端执行器实际抓取过程中不同抓取控制方式的速度变化。在此基础上,对番茄塑性变形进行求解,分析在抓取时间一定时,不同抓取控制方式下番茄的塑性变形规律,并以最小塑性变形为依据,确定最优的抓取策略。结果表明:抓取控制方式3为最优抓取控制方式,当抓取速度v0=1 mm/s,抓取时间t0=1 s时,产生的最小塑性变形最小,红熟前期和红熟中期番茄的最小塑性变形分别为0.002 6 mm和0.009 8 mm。以抓取控制方式3进行抓取控制实验,实验数据和理论数据的吻合度较高,决定系数R2为0.99,验证了抓取控制方式3作为最优抓取控制方式的合理性和可行性,为优化机械手抓取过程提供了参考。

Impact of Robot Grasping Control Modes on Mechanical Damage of Tomato

In order to analyze the impact of robot grasping control modes on mechanical damage of tomato, the Burgers model was used to express the deformation characteristics of tomato, and the viscoelastic parameters of tomato were obtained by the creep experiment. Three kinds of variations of speed, i.e., motion with uniform deceleration, deceleration after uniform motion and motion with variable deceleration were selected to indicate different grasping control modes. The linear function, Butterworth amplitude square function and exponential function were used to represent different grasping control modes during the robot grasping process. On this basis, the model of plastic deformation of tomato was solved, and the rules of tomato plastic deformations in different grasping control modes were analyzed when the grasping time was constant. Then, the optimal grasping strategy was selected based on the minimum plastic deformation. Experimental results indicated that the third grasping control mode was selected as the best grasping strategy, when the grasping speed was 1mm/s, the grasping time was 1s, the plastic deformation of tomato was the smallest, the early maturity and middle maturity of plastic deformations were 0.0026mm and 0.0098mm, respectively. Using the third grasping control mode to carry out the grasping control experiment, the simulation results were highly identical with measured results, the determination coefficient R2 was 0.99, which proved the rationality and feasibility of the third mode as the optimal grasping control mode. This research can offer a reference for robots grasping process optimization.