Crop image autonomous acquisition system based on ROS system

The research on monitoring methods of potato water stress status plays an important role in improving potato growth quality and yield. Based on thermal infrared and visible RGB images, the Crop Water Stress Index (CWSI) can be calculated and used to determine the status of crop water stress. To achieve automated, high-throughput, and non-destructive continuous collection of visible RGB, thermal infrared images, and raw temperature data, this study integrated and developed a crop inspection image acquisition system with binocular cameras and thermal infrared cameras. According to different functional requirements, the hardware parts were designed as different modules, including the main control module, motion control module, image acquisition module, and real-time monitoring module. The main control module implements photo taking control of the image acquisition module, transmission and storage of image and temperature data, and data interaction with the motion control module. Based on the robot operating system (ROS) architecture, multiple nodes were designed to communicate between each module node in publish/subscribe mode, including motion control node, thermal infrared camera node and binocular camera node. Through the one-day system feasibility test in the laboratory, it was concluded that the control accuracy of the motion module meets the needs of image acquisition. Each module and node control program can cooperate to complete image acquisition and local storage. Through the 18-day system stability test and application in the greenhouse, a total of 648 inspections were carried out, each inspection took 3 minutes, and 11664 visible light images, 5832 thermal infrared images and 5832 original temperature data were obtained. It was proved that the system was running stably, the image and temperature data were collected normally, and the function of automatic, high-throughput and non-destructive acquisition of the required data have been realized. The system provides an effective technical and equipment support for crop phenotypic information acquisition.