  Organic weed control is a vital to improve crop yield with a sustainable
approach. In this work, a directed energy weed control robot prototype
specifically designed for organic farms is proposed. The robot uses a novel
distributed array robot (DAR) unit for weed treatment. Soybean and corn
databases are built to train deep learning neural nets to perform weed
recognition. The initial deep learning neural nets show a high performance in
classifying crops. The robot uses a patented directed energy plant eradication
recipe that is completely organic and UV-C free, with no chemical damage or
physical disturbance to the soil. The deep learning can classify 8 common weed
species in a soybean field under natural environment with up to 98% accuracy.
