Our research concerned the development of an autonomous robotic navigation system for orchard harvesting with a dual master-slave mode, the autonomous navigation tractor orchard transport robot being the master followed by a navigation orchard picking robot as the slave. This addresses the problem that in single master-slave navigation mode, agricultural combined harvesting equipment cannot stop repeatedly between rows of apple trees and drive continuously when turning. According to distances obtained from a global positioning system (GNSS), ground points were used to switch the navigation mode of the transport and picking robot. A cloth simulation filter (CSF) and random sample consensus (RANSAC) algorithm was used to obtain inter-row waypoints. The GNSS point was manually selected as the turn waypoint of the master and a kinematic model was used to compute the turn waypoints of the slave. Finally, we used a pure pursuit algorithm to track these waypoints sequentially to achieve master-slave navigation and ground head master-slave command navigation. The experimental results show that the data packet loss rate was less than 1.2% when the robot communicated in the orchard row within 50 m which meets the robot orchard communication requirements. The master-slave robot can achieve repeated stops in the row using follow navigation, which meets the demands of joint orchard harvesting. The maximum, minimum, mean and standard deviation of position deviation of the master robot were 5.3 cm, 0.8 cm, 2.4 cm, and 0.9 cm, respectively. The position deviations of the slave robot were larger than those of the master robot, with maximum, minimum, mean and standard deviation of 39.7 cm, 1.1 cm, 4.1 cm, and 5.6 cm, respectively. The maximum, minimum, mean and standard deviation of the following error between the master-slave robot were 4.4 cm, 0 cm, 1.3 cm, and 1 cm respectively. Concerning the ground head turn, the command navigation method allowed continuous turning, but the lateral deviation between robots was more than 0.3 m and less than 1 m, and the heading deviation was more than 10° and less than 90°.

In order to reduce the mechanical damage during the kiwifruit picking process, the fruit rate of the picked fruit should be improved. The mechanical properties of the epidermis and interior of the fruit during the harvesting process were studied, so as to analyze the damage principle of the fruit. Firstly, a three-dimensional model of kiwifruit was constructed by point cloud scanning, and the flesh and placenta were filled in order to become a complete kiwifruit model. The elastic modulus, failure stress, and density of the kiwifruit skin, flesh, and placenta were obtained experimentally, and the material properties of the kiwifruit model were endowed with properties. Secondly, the finite element method was used to analyze the epidermis and internal stress of the kiwifruit by simulating the two processes of grabbing kiwifruit and picking to fruit boxes. The results show that the relative error of the simulation and test of the simulated grasping of kiwifruit was 6.42%, and the simulation and test of picking to fruit box confirmed the existence of damage, and the reflectivity of the damaged point in the detection was 6.18% on average, and the hardness value decreased to 8.30 $\mathrm{kg}/{\mathrm{cm}}^2$ on average. The results from this study can provide a reference for control strategies and damage avoidance during grasping.