LiDAR-based Robot Transplanter

In Japan, labor shortage of agriculture is becoming increasingly severe due to the lack of farmers and aging. Therefore, the development of automation of vegetable production such as transplanting, harvesting and transporting is required. In this paper, a self-localization method by using LiDAR and a robust control method of a transplanter are proposed for accurate transplanting. In this system, the path of transplanter is generated by using 3D point cloud data, and the transplanting part follows it and plant seedlings of cabbage accurately. Path generation is performed considering vehicle tilt in the roll direction depending on the environment of grooves. An accurate calculation of lateral and angular position of the transplanting part is also proposed. For path following control, sliding-mode control and inverse optimal control are applied to transplanter. The experimental results demonstrated the effectiveness of these proposed methods and problems we have to tackle on. Basically, it was possible to perform automated transplanting accurately, but there was an occasional problem of offset error from 0. It was confirmed that inverse optimal control is superior to sliding-mode control and is more robust to environmental changes.