Achieving success in agricultural activities heavily relies on precise navigation in row crop fields. Recently, segmentation-based navigation has emerged as a reliable technique when GPS-based localization is unavailable or higher accuracy is needed due to vegetation or unfavorable weather conditions. It also comes in handy when plants are growing rapidly and require an online adaptation of the navigation algorithm. This work applies a segmentation-based visual agnostic navigation algorithm to lavender fields, considering both simulation and real-world scenarios. The effectiveness of this approach is validated through a wide set of experimental tests, which show the capability of the proposed solution to generalize over different scenarios and provide highly-reliable results.

翻译：在农业生产活动中，精准导航是行播作物田间作业成功的关键。当基于GPS的定位不可用，或因植被遮挡、恶劣天气需要更高导航精度时，基于分割的导航技术已成为可靠方法。尤其是当作物快速生长需在线调整导航算法时，该技术更具实用性。本研究将基于分割的视觉无关导航算法应用于薰衣草田，综合考虑了仿真与真实场景。通过大量实验测试验证了该方法的有效性，结果表明所提方案能够泛化至不同场景并输出高可靠性结果。