An overview of autonomous crop row navigation strategies for unmanned ground vehicles

Abstract

Unmanned ground vehicles (UGVs) are becoming popular for use in agricultural environments. These unmanned systems are implemented in order to address human labor shortages throughout the agricultural industry, and improve food safety throughout the production cycle of produce crop. Common uses of UGVs in agriculture include: detection of animal fecal matter, surveys of crop growth, detection of crop damage from storms or floods, and detection of unwanted pests or molds. Navigation of crop rows is typically accomplished using vision-based cameras and global positioning system (GPS) units. Machine vision strategies are implemented to detect crop row contours and edges to ensure proper navigation of rows without damaging crops. A number of other control and navigation strategies exist for autonomous movements of UGVs. This paper provides a survey and overview of autonomous navigation strategies for UGVs with applications to agricultural environments.