In recent years, with the rapid development of science and technology, agricultural robots
have gradually begun to replace humans, to complete various agricultural operations …

Due to the increasing demand for food, the global shortage of agricultural labor and the
reduction in the utilization of agricultural resources, the demand for agricultural autonomous …

Crop row detection is one of the foundational and pivotal technologies of agricultural robots
and autonomous vehicles for navigation, guidance, path planning, and automated farming in …

Crop-row line detection is key to realizing the accurate spraying of crops; however, it is
challenging because of uneven lighting, weeds, and missing plants within rows. In this …

Vision based autonomous navigation is widely used for agricultural robots. However, factors
such as large area of weed, discontinuous crop rows, and differences in ambient lighting …

In various complex field environments, machine learning-based crop row detection faces
challenges like rigidity and low adaptability. To address this issue, we integrated deep …

Due to the undulating topography, the world contains numerous irregularly shaped small
fields. Autonomous navigation along the curved edges of these fields is crucial for achieving …

This study focuses on real-time detection of maize crop rows using deep learning
technology to meet the needs of autonomous navigation for weed removal during the maize …

3D lane detection plays a crucial role in autonomous driving by extracting structural and
traffic information from the road in 3D space to assist the self-driving car in rational, safe, and …

This paper presents a general procedure for enabling autonomous row following in crops
during early-stage growth, without relying on absolute localization systems. A model based …