Table 1.
Agricultural sprayer robot specifications.
Fig 1.
System architecture of precision agricultural spraying robot.
Table 2.
Computer specifications.
Fig 2.
Architecture of YOLO-based object detection model.
Table 3.
Intrinsic and extrinsic parameters of camera.
Fig 3.
Object coordinates transformation from camera frame to world frame.
Fig 4.
Robot camera field of view with spraying zones formation.
Fig 5.
Pressure response with varying numbers of active SVs.
Fig 6.
Block diagram of cascaded controller for pressure control system.
Table 4.
Pressure-flow response for open solenoid-valves.
Fig 7.
Approximate actual sprayed positions (plus sign) of the desired position (circle sign).
Fig 8.
Average spray position error.
Fig 9.
Field testing for selective spraying application.
Table 5.
YOLO algorithms performance for tobacco crop detection.
Fig 10.
Detection of tobacco plant using YOLOv5n model.
Fig 11.
Constant spray angle achieved under different number of active solenoid valves at constant pressure.
Fig 12.
(a) Spray boom pressure response based on cascaded controller. (b) Cascaded vs cascaded assisted by disturbance attenuation function.
Fig 13.
Filtered pressure signal using low-pass filter.
Table 6.
Objective function for pressure control system.
Table 7.
Stability analysis of pressure system with ISE objective function.