Abstract: Embodiments of this specification provide a multi-input model-compensated spraying control system and control method for agricultural robots, the method including: S1. building a flow and pressure control model; S2. controlling a liquid pump and an electric ball valve; S3. controlling the nozzle flow and pressure stabilization with PWM; and S4. based on a model-compensated multi-layer adaptive feedback control method, using the required flow of a system of the prescription map-based decision system and the vision-based decision system for precision spot spraying as control references, controlling a rotational speed of the liquid pump, an opening degree of the electric ball valve, and the duty ratio of the PWM proportional electromagnetic valve, adjusting the flow and the pressure by closed-loop feedback, to achieve pressure stabilization and flow control of each nozzle, and adjusting the flow and the pressure by closed-loop feedback, to ensure uniform and efficient spraying.

Abstract: A weeding robot and a method and apparatus for planning a weeding path for the weeding robot and a medium are provided. The method for planning a weeding path for the weeding robot includes the following steps: acquiring an image segmentation model based on neural network model training, where the image segmentation model is configured to identify and segment a weed target feature, a soil target feature and a crop target feature; and based on the weed target feature, acquiring the weed target feature by intra-camera tracking, and acquiring the weed target feature by inter-camera tracking, and planning a weeding path for a weeding robotic arm of the weeding robot, to enable the weeding robotic arm to weed according to the weeding path.

Abstract: A weeding robot and a method and apparatus for planning a weeding path for the weeding robot and a medium are provided. The method for planning a weeding path for the weeding robot includes the following steps: acquiring an image segmentation model based on neural network model training, where the image segmentation model is configured to identify and segment a weed target feature, a soil target feature and a crop target feature; and based on the weed target feature, acquiring the weed target feature by intra-camera tracking, and acquiring the weed target feature by inter-camera tracking, and planning a weeding path for a weeding robotic arm of the weeding robot, to enable the weeding robotic arm to weed according to the weeding path.