Numerical and Experimental Validation of an Autonomous Navigation and Mapping Framework for Mobile Robotics

Autonomous navigation in agricultural environments remains a key challenge for the deployment of mobile robots in precision viticulture. In this paper, we present the numerical and experimental validation of a LiDAR–inertial navigation and mapping framework for mobile robots operating in vineyard-like scenarios. A realistic vineyard simulation environment reproducing the geometric structure of vine rows is first developed to evaluate the performance of the proposed framework, considering multiple metrics including mapping time, speed stability, path tracking error, and point cloud reconstruction density. Then, the proposed approach is tested in a real vineyard using a Scout 2.0 mobile robot. Numerical and experimental results demonstrate the feasibility of the navigation and mapping strategy and its robustness during extensive repeated tests in the field.