G-ROBOT: An Intelligent Greenhouse Seedling Height Inspection Robot - Baoqi Wang; Yang Ding; Chunyan Wang; Deyu Li; Hongchang Wang; Zhilong Bie; Yuan Huang; Shengyong Xu (Journal of Robotics)
An intelligent and modular greenhouse seedling height inspection robot was designed to meet the demand for high-throughput, low-cost, and nondestructive inspection during the growth of greenhouse seedlings. The robot structure mainly consists of a multiterrain replacement chassis, an electronic control lift image acquisition support, and a quick disassembly mechanism. SolidWorks was used to design the robot and Adams was used for motion simulations. Based on STM32 and Raspberry Pi as the core, the robot is equipped with various sensors to build a reliable control system for intelligent navigation for inspection tasks as well as acquisition of high-quality images and environmental information data of seedling crops. The developed growth point detection algorithm based on the EfficientNet deep learning network can efficiently measure the heights of seedlings and the application of the host software and cloud server makes it easy to monitor and control the robot and store and manage various data. The results of the greenhouse experiment showed that the robot has an average battery life of 5.2 h after being fully charged, with satisfactory motion stability and environmental adaptability; the environmental information data collected were valid, and errors were within the acceptable range; the captured seedling crop images were of high quality, and the seedling height data obtained through algorithm analysis were valid and reliable. The robot is expected to be an intelligent assistant for seedling research and production.