The rapid, stable, and undamaged picking of small-sized spherical fruits are one of the key technologies to improve the level of intelligent picking robots and reduce grading operations. Cherry tomatoes were selected as the research object in this work. Picking strategies of two-stage “Holding-Rotating” and finger-end grasping were determined. The end-effector was designed to separate the fruit from the stalk based on the linear motion of the constraint part and the rotating gripper. This work first studied the human hand-grasping of cherry tomatoes and designed the fingers with sinusoidal characteristics. The mathematical model of a single finger of the gripper was established. The structural parameters of the gripper were determined to meet the requirements of the grabbing range from 0 to 61.6 mm. Based on the simulation model, the constraint part was set to 6 speeds, and the fruit sizes were set to 20 mm, 30 mm, and 40 mm, respectively. When the speed was 0.08m/s, the results showed that the grabbing time was 0.5381 s, 0.387 s, and 0.2761 s, respectively, and the maximum grabbing force was 0.9717 N, 3.5077 N, and 4.0003 N now of clamping, respectively. It met the picking requirements of high speed and low loss. The criterions of two-index stability and undamaged were proposed, including the grasping index of the fixed value and the slip detection of variance to mean ratio. Therefore, the control strategy and algorithm based on two-stage and two-index for rapid, stable, and non-destructive harvesting of small fruit were proposed. The results of the picking experiment for seventy-two cherry tomatoes showed that the picking success rate was 95.82%, the average picking time was 4.86 s, the picking damage rate was 2.90%, the browning rate was 2.90% in 72 h, and the wrinkling rate was 1.49% in 72 h, which can meet the actual small spherical fruit picking requirements. The research will provide an idea for the flexible end-effectors with humanoid grasp function and provides a theoretical reference for small spherical fruit picking.

To solve the technical problem that wheeled vehicles are prone to skidding on complex ground, due to poor adhesion performance, a tire-tread-structure design method based on the bionic principle is proposed in this paper. The 3D model of a goat’s foot was obtained using reverse engineering technology, and the curve equation was fitted by extracting the contour data of its outer-hoof flap edge, which was applied to the tire-tread-structure design. The bionic and herringbone-pattern rubber samples were manufactured, and a soil-tank test was carried out using an electronic universal tensile-testing machine, in order to verify the simulation results. The results showed that the overall adhesion of the bionic tread-pattern was greater than that of the normal tread-pattern with the same load applied and the same height and angle of the tread-pattern structure, and the maximum adhesion was increased by 14.23%. This research will provide a reference for optimizing the pattern structure and thus improving the passing performance of wheeled vehicles.

In order to improve the slope movement stability and flexibility of quadruped robot, a theoretical design method of a flexible spine of a robot that was based on bionics was proposed. The kinematic characteristics of the spine were analyzed under different slopes with a Saanen goat as the research object. A Qualisys track manager (QTM) gait analysis system was used to obtain the trunk movement of goats under multiple slopes, and linear time normalization (LTN) was used to calibrate and match typical gait cycles to characterize the goat locomotion gait under slopes. Firstly, the spatial angle changes of cervical thoracic vertebrae, thoracolumbar vertebrae, and lumbar vertebrae were compared and analyzed under 0°, 5°, 10°, and 15° slopes, and it was found that the rigid and flexible coupling structure between the thoraco–lumbar vertebrae played an obvious role when moving on the slope. Moreover, with the increase in slope, the movement of the spine changed to the coupling movement of thoraco–lumbar coordination movement and a flexible swing of lumbar vertebrae. Then, the Gaussian mixture model (GMM) clustering algorithm was used to analyze the changes of the thoraco–lumbar vertebrae and lumbar vertebrae in different directions. Combined with anatomical knowledge, it was found that the motion of the thoraco–lumbar vertebrae and lumbar vertebrae in the goat was mainly manifested as a left–right swing in the coronal plane. Finally, on the basis of the analysis of the maximin and variation range of the thoraco–lumbar vertebrae and lumbar vertebrae in the coronal plane, it was found that the coupling motion of the thoraco–lumbar cooperative motion and flexible swing of the lumbar vertebrae at the slope of 10° had the most significant effect on the motion stability. SSE, R², adjusted-R², and RMSE were used as evaluation indexes, and the general equations of the spatial fitting curve of the goat spine were obtained by curve fitting of Matlab software. Finally, Origin software was used to obtain the optimal fitting spatial equations under eight movements of the goat spine with SSE and adjusted-R² as indexes. The research will provide an idea for the bionic spine design with variable stiffness and multi-direction flexible bending, as well as a theoretical reference for the torso design of a bionic quadruped robot.

In view of the low accuracy and slow speed of goat-face recognition in real breeding environments, dairy goats were taken as the research objects, and video frames were used as the data sources. An improved YOLOv4 goat-face-recognition model was proposed to improve the detection accuracy; the original backbone network was replaced by a lightweight GhostNet feature extraction network. The pyramid network of the model was improved to a channel management mechanism with a spatial pyramid structure. The path aggregation network of the model was improved into a fusion network with residual structure in the form of double parameters, in order to improve the model’s ability to detect fine-grained features and distinguish differences between similar faces. The transfer learning pre-training weight loading method was adopted, and the detection speed, the model weight, and the mean average precision (mAP) were used as the main evaluation indicators of the network model. A total of 2522 images from 30 dairy goats were augmented, and the training set, validation set, and test set were divided according to 7:1:2. The test results of the improved YOLOv4 model showed that the mAP reached 96.7%, and the average frame rate reached 28 frames/s in the frontal face detection. Compared with the traditional YOLOv4, the mAP improved by 2.1%, and the average frame rate improved by 2 frames/s. The new model can effectively extract the facial features of dairy goats, which improves the detection accuracy and speed. In terms of profile face detection, the average detection accuracy of the improved YOLOv4 goat-face-recognition network can reach 78%. Compared with the traditional YOLOv4 model, the mAP increased by 7%, which effectively demonstrated the improved profile recognition accuracy of the model. In addition, the improved model is conducive to improving the recognition accuracy of the facial poses of goats from different angles, and provides a technical basis and reference for establishing a goat-face-recognition model in complex situations.

In order to improve the adhesive and passing performance of agricultural tracked vehicles under a non-structural environment, a theoretical design method of the structure of a bionic track pattern is proposed in this article. The Saanen goat is taken as the experimental subject, and the hoof tips and hoof spheres are taken as the characteristic functional parts, whose pressure is measured by thin film pressure sensors. The Qualisys Track Manager (QTM) gait analysis system was used to obtain the gait sequence of goats under multi-slope. The changes in vertical ground reaction force (GRF) and vertical impulse (VI) of the hoof tips and spheres and adhesion coefficient under multi-slope were analyzed. The results show that with the increase in slope, the GRF is transferred from the left hind hoof to the right front hoof, and the right front hoof has the most significant effect. Under the 10-degree slope, the peak vertical GRF and VI of the inner tip of the right front hoof are the largest; peak vertical GRF is 146.20 N, and VI is 127.67 N·s. The adhesion coefficient is the largest; the right front and left hind hoof are in the diagonal two-phase supported state, and μ is 0.3455. Therefore, the inner tip of the right front hoof is used as a bionic prototype to design the track pattern architecture. It provides a theoretical basis for the design and optimization of bionic patterns applied to agricultural tracked vehicles.

Goats can walk freely and flexibly in complex environments such as concave and convex or soft ground. And their flexible spine has functions such as adjusting balance and providing auxiliary power during movement, while the limbs only have support functions. The spine has an adjustable and decisive role in the pressure on the sole of the hoof of the goat. Therefore, the goat spine was taken as the bionic prototype, the three-dimensional force distribution of the goat body space was analyzed, and the optimal spinal space curve was explored, combined with the goat gait cycle. Based on the study of spinal curve arrangement and placement, the spinal curve was stretched along the grouser length direction. The soil contact surface structure of the track monomer was constructed based on functional simulation. And the bionic structure of the track monomer with superior adhesion performance was explored. The results of simulation analysis and soil tank test both showed that the attachment performance of bionic structure was better than that of an ordinary structure. It showed that adding bionic curves to the contact surface of the track monomer could significantly improve the adhesion performance, and the bionic structure with a single bionic curve arranged on the complete contact surface of the track monomer had the best adhesion performance. Moreover, the adhesion of the optimal track monomer bionic structure was increased by 19.22 N compared with an ordinary structure in the soil tank test, which verified the superiority of the track monomer bionic structure design. It provides a new method and a new idea for improving the adhesion performance of tracked vehicle in hilly areas.