Research On Contact Force Optimization And Compliant Grasping Of End-effector Of Apple Harvesting Robot

China is a large agricultural country and its apple output ranks first in the world.Due to the rapid economic development,domestic agricultural labor resources are becoming increasingly tense.At the same time,apple picking has the characteristics of obvious seasonality and heavy workload.Therefore,in order to reduce the labor cost of apple picking and improve the picking efficiency,it is urgent to carry out research on agricultural robot picking technology.The end effector of an apple picking robot is an important device for direct contact with apples when performing picking tasks.Due to the fragile biological characteristics of apples,during the picking process,the apple is often damaged due to excessive grasping force or the apple falls due to insufficient grasping force.Therefore,how to improve the robustness and flexibility of the end effector control system and reduce the damage rate are the problems that must be solved for the commercialization of agricultural picking robots.This article aims to realize the soft picking of apples and reduce the rate of apple picking damage.The researches are carried out on theanalysis of the optimal grasping mode of the end effector,the optimization of the apple grasping force and the adaptive impedance control algorithm.The main content of the article as follows:(1)The apple plastic deformation model was established,and the optimal grasping mode of the end effector was determined.First,based on the Burgers model to characterize the creep characteristics of the apple,the viscoelastic parameters of the apple were obtained through the apple compression test.Then,according to the different changing trends of the closing speed of the end effector,the closing mode of the end effector was subdivided into three different grasping modes: uniform deceleration,first uniform speed and then deceleration,and variable deceleration.using MATLAB to calculate and analyze the relationship of grasping force between the end effector and the apple.Finally,took the plastic deformation of apple as the damage standard,the grasping speed changed from 1mm/s to 20mm/s,the grasping time changed from 1s to 3s,the grasping process in three different grasping modes was simulated to calculate the plastic deformation of the apple,and the optimal grasping mode for the apple was determined.(2)The stability of the end effector grasping apples was analyzed,the mathematical description of the contact force distribution optimization problem of the end effector was constructed,and the improved Newton method was used to find the optimal solution to the contact force distribution model.First,the grasping stability of the end effector was analyzed based on the force closure theory,and the torque constraints was introduced under the premise of comprehensively considering the force closure constraints and the nonlinear friction cone constraints;then,the constraint conditions were processed through the obstacle function,and the penalty factor was introduced to construct the model of the contact force distribution optimization of the end effector;Then,the improved Newton method was used to solve the contact force distribution model,the optimal contact force for grasping the target apple was determined by the method of numerical example analysis under the premise of selecting the penalty factor,and the efficiency of the solution was verified.Finally,the influence of the penalty factor on the contact force optimization results was analyzed,and the feasibility of the contact force distribution optimization algorithm was verified.(3)An improved adaptive impedance control algorithm was designed to realize the stable and smooth grasping for the end effector.First,the mathematical model of the end effector was established based on the apple picking robot experiment system.Then,the principle of positionbased impedance control was introduced,and the influence of impedance parameters on the control performance of the system was analyzed to select appropriate impedance parameters.due to that the traditional impedance controller could not satisfy the grasping force control under the condition of uncertain environmental information,the adaptive controller was designed to improve traditional impedance controller.Finally,combined with the optimal contact force,the designed adaptive impedance algorithm was simulated by MATLAB,compared with the traditional impedance control algorithm under the conditions of certain environmental information and uncertain environmental information,it was verified that the improved adaptive impedance controller had better anti-interference ability and suppleness.(4)The apple picking robot experimental platform was used to verify the optimal grasping mode,the feasibility of contact force distribution optimization Algorithm and flexibility of the adaptive impedance control algorithm.First,the end effector was controlled to move in the selected optimal grasping mode.By comparing the theoretical data of the grasping force and the actual data measured by the force sensor,the accuracy of the apple plastic deformation theory was verified.Then,the optimal contact force under different penalty factors was calculated multiple times by using Monte Carlo simulation probability analysis,the end effector was controlled by software to grasp,and the reliability of optimization models was verified by the grasping success rate.Finally,the traditional impedance control algorithm and the adaptive impedance control algorithm were used to conduct multiple comparison experiments.According to the actual grasping force data measured by the force sensor,the adaptive impedance control algorithm was found superior to the traditional position-based impedance control algorithm in terms of overshoot and system robustness.