  Modern herbicide application in agricultural settings typically relies on
either large scale sprayers that dispense herbicide over crops and weeds alike
or portable sprayers that require labor intensive manual operation. The former
method results in overuse of herbicide and reduction in crop yield while the
latter is often untenable in large scale operations. This paper presents the
first fully autonomous robot for weed management for row crops capable of
computer vision based navigation, weed detection, complete field coverage, and
automatic recharge for under \$400. The target application is autonomous
inter-row weed control in crop fields, e.g. flax and canola, where the spacing
between croplines is as small as one foot. The proposed robot is small enough
to pass between croplines at all stages of plant growth while detecting weeds
and spraying herbicide. A recharging system incorporates newly designed robotic
hardware, a ramp, a robotic charging arm, and a mobile charging station. An
integrated vision algorithm is employed to assist with charger alignment
effectively. Combined, they enable the robot to work continuously in the field
without access to electricity. In addition, a color-based contour algorithm
combined with preprocessing techniques is applied for robust navigation relying
on the input from the onboard monocular camera. Incorporating such compact
robots into farms could help automate weed control, even during late stages of
growth, and reduce herbicide use by targeting weeds with precision. The robotic
platform is field-tested in the flaxseed fields of North Dakota.

Robotics