Occupancy Map Creation Using Aerial Image for Robot Navigation in Oil Palm Plantation

In the rapidly advancing field of robotics and precision agriculture, the autonomous Unmanned Ground Vehicles (UGVs) robot in oil palm agriculture environment presents both challenges and opportunities. A map of the oil palm plantation area is required for deployment and autonomous navigation of robots. Creating an occupancy map for this type of area using conventional surveying methods or using range equipment with simultaneous localization and mapping (SLAM) can be time consuming due to the very large area. This paper introduces an approach for semi-automatically creating occupancy grid maps for navigation by leveraging high-resolution aerial image. A comprehensive system is developed comprising tree crown detection, resolution estimation, and map creation modules. The proposed approach can produce reliable occupancy map of two types which are crop map and fenced map, catering to different navigation needs. This approach marks a significant step forward in utilizing remote-sensing data for the application of robotics in precision agriculture.