| China is the world’s largest apple producer,and until now,the selective harvesting of apples has been done by human hands.As the labor force shrinks and the apple industry upgrades,the harvesting of apples will be replaced by robots.In this paper,apple as the picking object,according to the physical characteristics of apple,focus on the design of a simple structure and control,strong load,flexible grasp,good envelope apple picking end-effector and the identification of the mature apple.The thesis mainly completes the following work:(1)The research status of end-effector at home and abroad and the traditional manual picking action mode were analyzed.On this basis,the deficiencies in the structural design of the existing end-effector were proposed.Taking Fuji Apple as the research object,the physical and mechanical properties of Fuji Apple were analyzed,providing data support for the design of the end-effector.According to the physical characteristics,the range of apple capture is determined to be 70 ～100 mm.According to the mechanical properties of apple,the trigger value of the pressure sensor is set as 50 N.(2)based on bionics principle and principle of underactuated mechanical structure design of the end executor,combined with the physical properties of apple,from the Angle of practical end executor has carried on the concrete structure design,in order to improve the adaptive ability of the fingers,fingers using arc structure,with flexible material,the design of curved fingers arc mouth diameter of 100 mm,The central Angle of the near finger is 60°,the central Angle of the far finger is 33.4°,and the finger width is 15 mm.By adding a pressure sensor to the finger,the end-effector can improve its active sensing ability and control the strength of the apple during the picking process.(3)The 3D model of end-effector was established based on Solidworks software,and virtual prototype was established in ADAMS to simulate the actual grasping effect of apples of different sizes.Through simulation analysis,the contact force changes between apples and fingers at different knuckles and finger displacement and speed changes during grasping were evaluated.The grasping adaptive ability and stability of underactuated arc mechanical finger are verified.ANSYS was used to carry out finite element simulation analysis on the transmission mechanism and finger,and the maximum stress of the end-effector was 54.8 MPa and the maximum deformation was 0.0086 mm,which met the design requirements.The endeffector prototype was fabricated by 3D printing technology,and its rationality and grasping performance were tested.The verification shows that the end-effector has good practical effect and achieves the design goal.(4)In this paper,apple images in the natural environment were collected to establish a data set,and the apple data set was expanded by rotation,changing brightness and sharpness,adding noise and other methods.The YOLOv5 s network was used for apple recognition,and the CBAM attention module was added to improve the recognition accuracy.Co MPared with the benchmark model,the accuracy of the trained model increased by 3.4 percentage points,the recall rate increased by 5 percentage points,and the average value could reach 95.1%,showing good accuracy.By using the Real Sense D435 camera,the improved YOLOv5 s target detection based on Pyto CH is realized,and the position information under the camera coordinates of the detected target is returned. |
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