Abstract:According to different planting modes, strawberries can be divided into two types:ridge planting and elevated planting. Compared with elevated planting, ridge planting had lower costs and occupied a larger proportion in China. To adapt to the agricultural practices of planting strawberries in the field, strawberry picking in the field was achieved, and problems such as labor shortage and rising costs, a dual-arm strawberry picking robot suitabT for the field planting mode. This robot can travel between strawberry ridges and automatically recognize mature strawberries to complete picking and collection. The design used the Arduino Nano V3.0 development board as the main controller which was developed based on Ubuntu 20.04. With the NVIDIA edge computing platform Jetson Xavier NX as the core, the mobile platform of the robot usesd a four-wheel steering chassis with high clearance, the real sense L515 as the recognition device for mature strawberries, the target detection frame and key point information of strawberry fruits through YOLO v8-Pose network was obtained, and the acquisition of strawberry handle posture and the positioning of picking points in combination with key points and point cloud processing. Two sets of robotic arms were installed with integrated end effectors for cutting and clamping strawberry stalks. The entire picking system was driven by the Arduino Nano V3.0 development board, and both sides of the robotic arm were equipped with L515 cameras. Through the recognition and capture of the cameras, the coordinate data of the strawberry fruit was transmitted to Jetson Xavier NX through a serial bus to drive the end of the robotic arm and achieve strawberry picking. Finally, a picking experiment was conducted in a strawberry orchard on site. The experimental results showed that the success rate of picking without obstruction at the stem was 85.4%, and the success rate with partial obstruction was 75.5%. The average time for picking a strawberry was12.5 s, and the damage rate was18.5%.