Harvesting efficiencies: How GNSS guidance improves precision agriculture and construction

Centimeter-level positioning and high-accuracy orientation of machinery enable automation of many construction, mining and farming tasks, and take them one step closer to being performed by autonomous machines. Machine control increases jobsite safety, operational efficiency and productivity.

Using data from GNSS satellites, total stations and 3D models, machine-control hardware and software solutions determine a machine’s current position on the Earth and compare it with the desired design surface, mining task or cultivation technique. They also monitor and sometimes control the position and orientation of implements — such as blades, buckets and seeders — with respect to the machine. By talking directly to the machine’s hydraulics, machine automation shifts responsibility for accuracy and speed from the operator to the technology.

On construction sites, automation guides motor graders, excavators, dozers and other heavy machines, making operations easier to manage. This makes contractors more productive and experienced operators more efficient. With this technology, less experienced operators are able to take on more complex tasks, and all operators become more accurate. Machine automation also increases the capabilities of the machines themselves, so that excavators and compact machines are now doing finish grade work once reserved for larger and more expensive dozers.

Operators in the cab and engineers and supervisors at their desks can control and monitor progress in real time, with views of the whole layout as well as specific slopes, roads, ditches and other elements, including those under water.

Using GNSS guidance to aid application of fertilizer, pesticides and herbicides saves time and money. (Photo: Septentrio)

About half of all motor graders and a third of all dozers use positioning sensors and a display to provide operators with the position of the blade with reference to the target grade. A typical machine control set-up consists of a GNSS receiver and a display (jointly referred to as a “cab kit”) and inertial measurement units (IMUs) on the blades and other implements.

From the display, the operator loads a project design, which tells the system the cut, fill and other design information it needs. The operator then chooses a lane and may choose a vertical offset, which temporarily adjusts the design grade, making it possible to accomplish the work in steps, from rough to finish grading. Operators can also record points and scan a pavement in real time as they repair it.

While used by the construction industry on earthworks equipment since the late 1990s, machine control has recently benefited from:

• The increase in the number of GNSS signals available, particularly on the new L5 frequency
• IMUs, which measure blade movements with respect to the machine 100 times per second, one order of magnitude more than non-IMU grade-control systems
• The growing availability of continuously operating reference stations (CORS) and other GPS networks, which eliminate the need to set up a base
• New mastless systems, which integrate a receiver into the top of the cab and connect it wirelessly with IMUs to orient the blade, obviating the need to install a long mast pole on the blade and connect it by cable to the receiver and improving safety, visibility and equipment durability
• New interfaces designed to be as easy to use as a cell phone, shortening the operators’ learning curve.

While these developments are hastening the advent of autonomous construction, mining and farming machines, remaining barriers to this vision include hardware and software issues as well as questions of data exchange, legal liability and operator training — issues analogous to those facing the development of autonomous cars and trucks.

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Photo: Septentrio

Septentrio-guided dino roams the fields

The DINO is a one-ton farming robot made by NAIO Technologies that operates autonomously using GNSS positioning and maps for navigation. Of the 170 NAIO farming robots currently in operation, about 30% are DINOs, which are typically used on large farms.

In 2016, NAIO and Septentrio, a manufacturer of industrial high-end GNSS technologies, began to research the integration of full GNSS solutions into NAIO’s robots.

Today, the DINO carries a Septentrio NR3, consisting of a GNSS receiver and antenna in a single housing, which provides it with RTK centimeter-level positioning accuracy. Farmers can use the NR3 to map their fields, then attach it to the DINO to guide it.

The DINO automates weeding within complex and quickly changing environments. NAIO plans to soon add seeding and fertilization to its robot’s capabilities.

To operate reliably in the narrow lanes between crops, the DINO requires an accurate GNSS receiver with strong resistance to multipath and jamming.

The safety of field hands and the protection of the crops also require the receiver to have good integrity, which is a measure of the trust that can be placed in the correctness of the information it supplies. Accuracy, robustness, and integrity are all strong suits of Septentrio’s NR3.

While the DINO mostly operates continuously, it sometimes stops to avoid animals or humans, or for other safety reasons. A major advantage of the NR3 and other sensors that NAIO is using, is that they enable the robot to perform cold-starts very rapidly and with a stable heading.

Machine control, guidance and automation defined

Using GNSS guidance to aid application of fertilizer, pesticides and herbicides saves time and money. (Photo: fotokostic/iStock/Getty Images Plus/Getty Images)

The terms machine control, machine guidance and machine automation are not interchangeable.

Machine control is a generic term that refers to the integration of positioning tools into a construction, mining or farming machine to determine its position on the Earth and relative to a desired design surface, mining task or cultivation technique.

Within machine control, machine guidance systems display these data in the cab — assisting the machine’s operator in steering the machine and in maneuvering its implements to shape the ground, mine minerals, plant seeds or perform other related tasks — while machine automation systems directly steer the machine, achieving greater levels of precision than human operators could. The term automated machine guidance (AMG) is sometimes also used.