Precision Agriculture, 1, 95᎐113 1999
ᮊ 1999 Kluwer Academic Publishers. Manufactured in The Netherlands.
Robotic Weed Control System for Tomatoes
W. S. LEE, D. C. SLAUGHTER, AND D. K. GILES firstname.lastname@example.org
Biological and Agricultural Engineering, Uni
ersity of California, Da
is, CA 95616
Abstract. A real-time intelligent robotic weed control system was developed for selective herbicide
application to in-row weeds using machine vision and precision chemical application. The robotic vision
system took 0.34s to process one image, representing a 11.43 cm by 10.16 cm region of seedline
containing 10 plant objects, allowing the prototype robotic weed control system to travel at a continuous
rate of 1.20 kmrh. The overall performance of the robotic system in a commercial processing tomato
field and in simulated trials is discussed.
Keywords: robotics, machine vision, weed control, tomatoes
Tomatoes are one of the leading vegetable crops produced in California. In 1996,
over 9 billion kg of processing tomatoes were produced in California, accounting
for 93% of all processing tomatoes produced in the U.S. USDA and NASS, 1997 .
A total of 5.9 million kg of agricultural chemicals herbicides, insecticides, fungi-
cides, and other chemicals were used to produce processing tomatoes in California
alone in 1994 USDA, NASS and ERS, 1995 . This heavy reliance on chemicals
raises many environmental and economic concerns, causing many farmers to seek
alternatives for weed control in order to reduce chemical use in farming.
Conventional mechanical cultivation cannot selectively remove weeds located in
the seedline and there are no selective herbicides for some croprweed situations.
Since hand labor is costly, an automated weed control system may be economically
feasible. A precision robotic weed control system could also reduce or eliminate
the need for chemicals. Although there have been many efforts to control in-row
weeds, no system is currently available for real-time field use.
The goal of this project was to build a real-time machine vision based robotic weed
control system that can detect crop and weed locations, kill weeds and thin crop
plants. The system was required to recognize tomato plants and weeds outdoors in
commercial tomato fields using image processing techniques while moving forward
at a constant speed.