October 28, 2016
material handling update | Automated Guided Vehicles

AGVs pioneer new paths in the warehouse

AGVs pioneer new paths in the warehouse

Advances in navigation technology could allow automated guided vehicles to boldly go where no AGV has gone before.

By Toby Gooley

In the early days of automated guided vehicles (AGVs), there typically was just one way the computer-controlled autonomous load carriers could find their way around the manufacturing plants where they initially were used: by following wires embedded in the floor. While revolutionary back then—load carriers could for the first time trundle around a facility without a human operator—that method was simply the first stage of a technological evolution that is not only changing the equipment itself but is also stretching the boundaries of where AGVs can go and how they're used.

In recent years, the number of navigation methods used by AGVs as they pick up, carry, and drop off their loads in factories, warehouses, and distribution centers has multiplied. But AGV manufacturers aren't done yet; they continue to tinker with existing guidance technologies and develop new ones. What follows is a brief overview of some of the navigation technologies in use today, along with a preview of what AGV users can expect in the future.


Wires (also known as inductive guidance) and another early guidance method, magnetic tape, remain popular options, particularly for small and medium-sized operations, in part because they are relatively inexpensive and can offer a quick payback. With wire guidance, a continuous wire path is embedded in the floor. Antennas on the vehicle detect a radio signal from the wire, and encoders on the wheels calculate the distance traveled.

Magnetic tape, which also requires a continuous path, is attached to the floor with an adhesive and may require a protective coating. A sensor on the underside of the vehicle detects the magnetic field, leading the vehicle to follow the tape.

A variation on this theme is a magnetic grid, which uses magnets affixed to or embedded in the floor in a grid pattern. An onboard sensor detects the magnets, and the reference points are stored in the AGV's memory as X and Y coordinates. A gyroscope on the vehicle measures and maintains direction, and a wheel encoder calculates the distance traveled. In a magnetic grid, the guide paths can easily be changed.

Still another option is inertial navigation, where transponders are embedded in the floor. An onboard gyroscope detects slight directional changes and corrects the vehicle's travel path to keep it on course. Providers such as Daifuku's Jervis B. Webb division note that inertial guidance vehicles can operate in almost any environment, including tight aisles and extreme temperatures.


More recently developed guidance technologies rely on various ways of measuring distances, mapping, storing data, and decision making for navigation. All provide a degree of flexibility that earlier technologies couldn't offer—probably the biggest reason for the inroads AGVs are now making in warehouses and DCs. They all make it easy and fast to reprogram routes, require no (or, in the case of laser guidance, minimal) additional infrastructure, and can navigate on their own around obstacles.

Laser-guided vehicles map and store the facility layout in the vehicle's computer. A laser transmitter/receiver mounted on the vehicle detects reflective strips located at fixed reference points and measures both its distance and angle relative to the reflectors. By triangulating two reference points, the AGV can determine and update its location. AGV maker JBT Corp., for example, says its patented laser-guidance technology uses an eye-safe laser scanner that "strobes" the operating area and updates its position several times per second, resulting in highly accurate positioning. Transbotics, another AGV developer, touts laser guidance for its accuracy, reliability, security, dynamic traffic management, and short installation times.

Natural-feature guidance is a relative newcomer to the AGV scene. AGVs equipped with this type of technology record and store reference images as a map of the operating area. They then navigate by calculating their position relative to existing features—walls, racks, I-beams, doorways, stacks of pallets, and so forth—following the most efficient path, just as a human being would when walking through the facility. A major advantage of this technology is that it requires no markers, transponders, or reflectors. In addition, guide paths can easily be changed by retraining the AGV or by drawing a new route on the map. Sweden's Kollmorgen was one of the first to develop this capability, and others have followed. AutoGuide, for example, is about to introduce a low-profile AGV that measures the locations of natural features to use as reference points as it moves along its route, says Sarah Carlson, vice president of marketing and business development.

In somewhat similar fashion, the Otto Motors division of Clearpath Robotics uses simultaneous localization and mapping (SLAM) technology for its self-driving material handling vehicles—the same underlying technology used in self-driving highway vehicles, says Simon Drexler, director of industrial solutions. Otto uses laser-based "lidar" (from "light" and "radar") scanning to gather data and construct a highly detailed map of the facility floor. Once it has the reference map, it can navigate any route without a defined path or line. The vehicle is intelligent enough to plan and follow its own route, Drexler says. Once the reference map is in place, users can drag and drop location pins on the map to instruct the vehicle where to stop for pickups and dropoffs.

Vehicles that use vision-based navigation come closest to processing visual information the way a human being does. AGVs built by Seegrid, which pioneered this technology, use five pairs of stereo cameras to record the surrounding environment as an operator "trains" them by walking them through their route. The cameras take two images simultaneously, achieving binocular vision with depth perception that's similar to a human being's. This information is used to create a three-dimensional map of the surroundings every few centimeters; the images are then tied together to create a route, explains Jeff Christensen, Seegrid's vice president of products. The AGVs replay the route from their memory and follow it precisely. Changing the route is a simple matter of taking them on another "walk" with an operator.

While each navigation method has its advantages, each has some drawbacks, too. For wire guidance, the principal drawback is that paths are fixed and cannot be easily changed, since they require cutting into the floor. Magnetic tape paths are also fixed but can be changed with comparatively little time and expense. And magnetic grids can be expanded without making major alterations to the facility, though extensive layouts can get complicated.

The more technologically complex navigation systems also have some constraints. Vision-guided AGVs, for instance, need a certain level of ambient light, and their cameras and lenses aren't suited for cold environments. As with human vision, the farther away an object is, the harder it is to judge that distance. Laser and lidar users praise their accuracy, but if lasers from two vehicles point at each other, they can in effect blind each other's sensors, a phenomenon known as dazzling interference, Christensen says. Similarly, bright sunlight has been known to interrupt the images and compromise data gathering in natural-feature and vision guidance systems, Carlson says. Plus, natural-feature technology would be ineffective in environments where there are frequent changes or few permanent features or structures to navigate off of, she adds.


Can AGVs get any more sophisticated than they already are? The vendors we spoke with for this story believe that more advances in navigation technology are just over the horizon. For example, innovations in image-sensing technology for consumer applications will benefit AGV design, says Seegrid's Christensen. The availability of more-sensitive image sensors that provide exceptionally high-quality images in less-than-ideal conditions continues to grow. His company's vehicles, for instance, will soon be able to take high-resolution pictures in lower light because of such advances.

New developments in navigation are one reason AGVs are moving more deeply into warehousing, distribution, and supply chain applications, AutoGuide's Carlson says. She also predicts that navigation systems that allow users to control a small fleet of AGVs through an app on a tablet, mobile phone, or laptop without a large-scale traffic management software installation will make these vehicles affordable and feasible for smaller companies.

The new navigation technologies will help customers participate in and take advantage of Industry 4.0, the "fourth industrial revolution," characterized by the acquisition, analysis, and consumption of real-time operational data, says Drexler of Clearpath Robotics. "That's where I see the industry going—moving more away from the focus on hard goods and more toward the utilization of real-time data."

Advances in autonomous cars and trucks are likely to influence material handling AGVs in the future, all agree. "AGVs have been around a lot longer, but autonomous cars are a really big story in a much bigger sphere than warehousing, so there will continue to be a lot more discoveries and development in that area," Christensen says. "[Automakers] can learn something from autonomous industrial vehicles, and we can learn some things from what they're doing."

Drexler, for one, believes AGVs will have an edge over autonomous highway vehicles. "We believe the adoption rate for self-driving vehicles will accelerate faster indoors than outdoors," he says. Otto Motors, he adds, is currently on track to surpass Google's self-driving car in the number of autonomous miles driven by the end of next year.

Related story: Starting over. Read about how Calsonic Kansei North America eliminated local drayage, built a brand-new DC, and installed custom-designed automatic guided carts. The award-winning project achieved ROI well ahead of schedule.

About the Author

Toby Gooley
Contributing Editor
Contributing Editor Toby Gooley is a freelance writer and editor specializing in supply chain, logistics, material handling, and international trade. She previously was Senior Editor at DC VELOCITY and Editor of DCV's sister publication, CSCMP's Supply Chain Quarterly. Prior to joining AGiLE Business Media in 2007, she spent 20 years at Logistics Management magazine as Managing Editor and Senior Editor covering international trade and transportation. Prior to that she was an export traffic manager for 10 years. She holds a B.A. in Asian Studies from Cornell University.

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