Design And Motion Planning Of Mobile Apple Picking Robot

With the continuous advancement of agricultural modernization,fruit harvest has become a very important part of agricultural engineering.As a fruit that is commonly needed in people's lives,the degree of automation of picking is particularly important,so a large number of robots have been used for apple picking.However,there is still room for improvement in the picking efficiency of apple picking robots,which is closely related to its structure and motion planning.To this end,in this paper,a four-degree-of-freedom picking manipulator structure was designed for the growth environment of apple,and the research on picking motion planning was carried out.First of all,the software and hardware design of the mobile picking robot platform is carried out.On the hardware platform,the mobile chassis and the mechanical arm are designed to select the corresponding hardware of the picking robot vision system and the main control system,and the wheels and joint motors and their corresponding drives are selected.On the software system,the Lab color model and the Hough gradient method are used to identify and locate the target.The PID algorithm is combined with the photoelectric encoder to realize the speed closure of the servo motor.The corresponding program is programmed and tested to verify the effectiveness of the above method.Secondly,in order to realize the picking of the manipulator,the picking manipulator structure is used in the paper,and the end joint separation method is used to establish the picking posture of the manipulator,and the cycloidal motion equation is selected as the manipulator joint trajectory planning curve.Combined with the picking posture and joint kinematics constraints,the mathematical model of the optimal motion planning of the manipulator with the shortest picking time is proposed.Then,in order to improve the performance of the above motion planning model,a small world optimization algorithm based on elite agglomeration effect is proposed.The algorithm adds a hierarchical individual attraction strategy to the long connection,and adaptively adjusts the number of searches and the size of the neighborhood in the short connection according to the node optimization effect.The convergence of the algorithm and numerical tests are carried out to verify the advancement of the algorithm.The simulation experiment is carried out to verify the optimization effect of the algorithm on the motion planning model.Finally,in order to test the effectiveness and stability of the whole picking robot system,the physical experiment of the picking robot platform prototype was carried out.The picking and motion planning experiments were carried out on the apples at the higher,middle and lower elevations,and the proposed algorithm was compared with the tabu genetic algorithm and simple small world algorithm.The experimental results show that the picking manipulator model,motion planning method and algorithm are reliable and stable.