Development of a Guidance System for an Agricultural Wheeled Robotic Platform in Row Crop Fields - Hossein Behfar; Fahime Hashemi; Arezu Nobakht (Biomechanism and Bioenergy Research)
Smart and precision agriculture seeks to boost the efficiency of operations and crop yield by using modern technology. Modern tools such as sensors, imagery cameras, and deep learning enable farmers to identify and control weeds, pests, and diseases in real-time. A robotic platform can carry these modern types of equipment and achieve the mentioned objectives precisely. Automatic and accurate navigation of this autonomous robot in agricultural fields is essential for performing these precision tasks. An agricultural robotic platform was designed and developed for row crop fields. The robot navigation system comprises two main components: a vision-based row detection system for path tracking and a motion controller system. The vision-based guidance system processes acquired image data from a tilted camera in front of the robot to identify the crop row's position. The Hough transform method was used to determine the position of the crop rows. Using the resultant guidance line equations, the motion controller directs the robot to move automatically between rows without harming the crops. Differential speed steering allows both wheels on the robot to rotate at different speeds. The steering system improved the robot position error by controlling both powered wheel speeds. To move the robot among the crop rows, it generates the wheel speed difference command. The robotic platform effectively followed the rows of sugar beets at a velocity of 0.5 m/s, exhibiting an average lateral offset of 12 mm and a standard deviation of 22 mm.