In recent years, Japan has seen a decline in the working-age population, which plays a central role in economic activity, due to the combined effects of a low birthrate and an aging population. This trend has raised concerns about the contraction of economic activity and the intensification of related social issues. Furthermore, in the agricultural sector, the aging of workers has progressed significantly, making labor force reinforcement an urgent issue. To address these problems, efforts using IoT, AI, and robotics have been undertaken. However, many of the developed robots are primarily designed to grasp only a single specific type of crop. In response to this limitation, we are working on the development of a system that focuses on grasping multiple types of crops. In this presentation, we describe the development of a system using sensor data from a pneumatic gripper and machine learning, as well as the results of validation experiments conducted to confirm the system’s effectiveness..
KAJIE et al. (Wed,) studied this question.