  Cultivation and weeding are two of the primary tasks performed by farmers
today. A recent challenge for weeding is the desire to reduce herbicide and
pesticide treatments while maintaining crop quality and quantity. In this paper
we introduce BonnBot-I a precise weed management platform which can also
performs field monitoring. Driven by crop monitoring approaches which can
accurately locate and classify plants (weed and crop) we further improve their
performance by fusing the platform available GNSS and wheel odometry. This
improves tracking accuracy of our crop monitoring approach from a normalized
average error of 8.3% to 3.5%, evaluated on a new publicly available corn
dataset. We also present a novel arrangement of weeding tools mounted on linear
actuators evaluated in simulated environments. We replicate weed distributions
from a real field, using the results from our monitoring approach, and show the
validity of our work-space division techniques which require significantly less
movement (a 50% reduction) to achieve similar results. Overall, BonnBot-I is a
significant step forward in precise weed management with a novel method of
selectively spraying and controlling weeds in an arable field
