Agriculture Mechanization – An Overview

emerging today (Figure 3a) for achieving high-precision accuracy through various reference-signal
configurations (e.g., RTK-GPS, multiple satellite systems, sensor fusion with complementary sensors, and
multiple sources of corrections).
Operator-guidance aids that provide feedback to the operator about required steering corrections
through audio and visual cues were the first systems on the market for precision guidance. This feature
allowed a vehicle system to follow paths parallel to prior operations across a field. These types of
systems worked well at decimeter accuracy and required no major control-system integration into the
vehicle.
The major benefits of these systems were to reduce overlap/underlap in field operations with extremely
wide implements, typically for spraying chemicals and fertilizers. The decrease in overlap meant the
parsimonious use of resources. The decrease in underlap meant that chemicals and fertilizers were
applied to every part of the field.
On the next level of evolution, automatic guidance systems appeared that managed steering for an
operator through automatic control. Automatic guidance systems enabled precision operations
depending on the type of GNSS signal and how it was integrated into the requirements of the
agricultural operations.
GNSS technology enabled the management of inputs such as seed, pesticides, and fertilizers with
precision across the field. For example, the chemical application to buffer zones and grassy waterways
was reduced based on sensing of the field location of these features. John Deere’s software product,
SwathControl Pro (Figure 3b), enabled farmers to manage the definition and execution of this capability.
GNSS technology provided the reference signal that enabled accurate vehicle location at the GNSS
sensor, but precision control of the machine required several additions to the system (e.g., attitude
correction, inertial sensors, implement control). With these features, a mobile CPS could correct the
attitude of the vehicle on uneven terrain and manage the vehicle system path for precision in the
execution of complex functions.
The ultimate in un-manned automation is the capability of driving complete field patterns under
autonomous management of the tractor-implement functions without frequent operator intervention.
Figure 3c shows one commercial example of the execution of this concept. The figure shows a very
rudimentary form of path planning, integrated with automatic guidance, that can increase productivity
by managing the paths a vehicle must follow. Path management can be programmed to reduce time loss
caused by navigation (e.g., turning around) and implement management.
Like precision agriculture, precision guidance creates data from its precision operations that could be
used in crop management. Examples of these data include information on the “as-applied” state of
operations, vehicle paths, and operational state variables. The data can then be used to meet the needs
of other ICT in systems automation and optimization.
System Automation and Control