Abstract: An image acquisition device and image processing method for an agricultural harvesting operation machine. The agricultural harvesting operation machine comprises a body and an image acquisition device; the image acquisition device comprises an image capturing component and a communication machine; the image acquisition device is mounted on the body; the communication machine is communicatably connected to the image capturing component so as to obtain acquired image information from the image capturing component, thereby assisting in adjusting the working position and operation speed of the body. Also provided is an image processing method. Information required by harvesting operation is taken into full consideration, images of the position of an agricultural harvesting operation machine are acquired, and multiple acquired images are efficiently processed.

Abstract: An intelligent system and a method for coordinating harvester and logistics vehicle are illustrated. The intelligent system comprises a harvester terminal and a logistics vehicle terminal. The harvester terminal comprises a repository monitoring module and a control module, wherein the repository monitoring module monitors storage information of a storage bin of the harvester. The control module receives the storage information from the repository monitoring module, and determines whether the storage location of the storage bin of the harvester reaches a preset location. The harvester terminal and the logistics vehicle terminal are communicatively connected. When the storage location of the storage bin of the harvester reaches the preset location, the control module sends a transport instruction to the logistics vehicle terminal to control the logistics vehicle to transport grain, thereby achieving intelligent coordination between the harvester and the logistics vehicle.

Abstract: A system and method for automatic row alignment driving by a harvester when harvesting above-ground crops includes an elastic row sensing module, a processing module, a controlling module, and a steering module. The elastic row sensing module is disposed on a front grain thresher/grain isolator of the harvester, collecting data as to physical contact with the crop. The elastic row sensing module includes a deformable elastomer in contact with the high stem crop, the sensor detects and reports deformation of the elastomer. The processing module determines current alignment state of the harvester and the controlling module determines any corrective steering signal for the harvester. The steering module controls steering direction.

Abstract: Disclosed are a material pushing apparatus and a charging method thereof, and a material pushing machine and a material pushing method thereof. The material pushing apparatus comprises a charger (200) and a material pushing machine (100), and when the material pushing machine moves to the position where the charger is located, the charger can automatically supplement electric energy to the material pushing machine, such that the automation level of the material pushing apparatus is improved.

Abstract: A method for constructing a convolutional neural network model based on farmland images is applied in an electronic device. The method includes following steps: obtaining a number of farmland images of at least one farmland; obtaining a plurality of standard segmentation farmland images corresponding to each of the farmland images; dividing the farmland images and the standard segmentation farmland images into a training image set and a test image set; taking the farmland images and the standard segmentation farmland images in the training image set as input of a convolutional neural network, and constructing a convolutional neural network model based on the farmland images; and verifying the convolutional neural network model by using the farmland images in the test image set and the standard segmentation farmland images, and optimizing a plurality of parameters of the convolutional neural network model based on the farmland images.