Abstract
In orchards, there are many tasks that have not yet been automated, such as harvesting, transportation, weeding, and monitoring. In this study, we attempted 3D mapping and automatic driving in a chestnut orchard using simultaneous localization and mapping (SLAM) with 3D-LiDAR and an IMU. As a result, parameters suitable for normal distribution transform (NDT) matching in a chestnut orchard were identified. In automatic driving, the lateral error of the path was less than 10 cm, which was sufficient for an agricultural robot to travel in an orchard. The effect of the abundance of foliage on the accuracy of self-position estimation was small, indicating the reusability of the created 3D map.
