Agriculture Reference
In-Depth Information
tractors are one potential solution (Noguchi
et al., 1997). Sensors are an essential
part of intelligent agricultural machinery. Machine vision, in particular, can supply
information about current crop status, including maturity (Ahmad
et al., 1999) and
weed infestations (Tian
et al., 1999). The information gathered through machine
vision and other sensors such as global positioning system (GPS) can be used to
create field management schedules for chemical application, cultivation, and har-
vest. This chapter will discuss the application of robot vehicles in agriculture using
new technologies. Research institutions around the globe are conducting research on
autonomous vehicles for agricultural use, and usually they rely on a real-time kine-
matic GPS (RTK-GPS), geographical information system (GIS), image sensors, and
virtual reference station, etc. (Kondo
et al., 2011). The most advanced technologies
relating to intelligent robot vehicles will be addressed here.
2.2 OVERVIEW OF A ROBOT FARMING SYSTEM
The robot farming system will fully automate farming, from planting to harvesting
to the stage where the products reach the end user (Noguchi and Barawid, 2011). A
robot tractor and a planting robot will be used to plant and seed the crops using navi-
gation sensors. A full overview of the robot farming system is shown in Figure 2.1.
It includes a robot management system, a real-time monitoring system, a navigation
system, and a safety system. In the robot farming system, the robot vehicles receive
Information
exchange
Retailers
LAN
Producers'
cooperation
Robot
management
system
Drying facility
Farmers
Acquisition of
working
condition
- Wireless LAN
- Packet communication
Robot tractor
Robot combine
harvester
Rice-planting
robot
On-site
worker
FIGURE 2.1
Overview of robot farming system.
