Ever since people had to assemble things, developing ways to manage, move and manufacture products has been an ongoing evolutionary pressure. From the first water-driven grain mill to steam-powered belt-driven machinist stations, automating work to maximize productivity has been a key aspect of engineering.
While production engineering is still a space for specialists, the expansion of advanced solutions in sensors and controls provides almost any engineer with the tools needed to create a product or system that is competitive with the output from most production houses.
The Industry 4.0 revolution (Figure 1) is enabling a new generation of Automated Guided Vehicles (AGVs) for use in the first wave of smart manufacturing and distribution facilities. This revolution also requires new ways of thinking across all aspects of materials handling, especially when it comes to functional safety and reducing accidents in the workplace, and in turn, presenting a new challenge for sensor and control manufacturers.
A Market on the Move
The adoption of AGVs into the materials handling ecosystem has been far from spectacular, but all that is changing with the fourth technology revolution and the rise of the interconnected workplace. AGVs currently represent about 10 percent of the global market for automated materials handling equipment. This presents an opportunity to those willing to make the effort to integrate the latest technologies into their solutions, jumping into the marketplace at the front of the wave instead of responding to the splash.
The future of AGVs will undoubtedly be autonomous – systems that are adaptive and feature intelligence-based capabilities that allow them to respond within boundary domains to situations that were not pre-programmed in the design. Autonomous vehicles for use in factories, industrial facilities, retail outlets, and warehouses (Figure 2) can be categorized into four distinct types: forklift trucks (moving goods horizontally and vertically); pallet lift trucks (horizontal only); tow vehicles; and unit load carriers (to convey heavy goods from conveyor to assembly line).
Today, most AGVs are deployed to automate materials handling and packaging logistics, with man and machine working together. A few companies are taking automation to the next level by adding a robot arm to pick up the desired object, taking man completely out of the equation. While this is where the industry is heading, object recognition and grasping are two of the biggest challenges to be fully resolved.
So why are manufacturing and logistics facilities increasingly moving towards AGV-based solutions? One of the reasons is that in the long term, AGVs have been shown to be more efficient and cost-effective than human controlled materials handling equipment. In addition, AGVs are intrinsically safer, since they remove the issue of operator error.
Although there are arguments against this, such as the high level of initial capital investment required, and the cost and effort of a factory floor re-configuration to implement, these issues are minor compared to the larger obstacle of technology awareness. This can extend to developing standards and require creating a functional ecosystem for the next generation of solutions.
Safe Automation with Sensors
Modern AGVs require a wide range of sensors that provide critical feedback to the control system about the AGV’s surroundings and operation. The sensors used to navigate, like LiDAR and cameras, and those used to control ground speed and direction, like encoders, are critical to ensure precise and safe operation.
Lidar for Accurate AGV Navigation
One of the most recent innovations in AGV design is the use and application of lidar technology. Similar to radar, lidar instead uses laser beams of light bouncing off the environment to accurately measure object range and 3D shape, while also providing intensity data that helps detect things like lane markings. Whereas camera-based solutions, for example, can sometimes struggle in environments that are prone to sudden vibration, low light or dust. Compared to other navigation approaches, lidar does not require external targets such as reflectors, RFID, or markers for navigation. As such, they are suited not only for localization and mapping, but also to help prevent collisions and ensure loads are properly and safely engaged and placed.
Traditionally, lidar sensors have been costly and based on a mechanical scanning design. lidar technology is moving forward and now, entirely solid-state solutions (i.e. they have no moving parts) require less power and deliver higher resolution at a longer range. Not only is this new generation of lidar sensors more reliable than mechanical models, it is also more affordable. By mounting several small solid-state lidar sensors in an array, a live 3D surround view is created that can detect and track stationary and moving objects as required.
The latest lidar solutions offer high resolution and system flexibility, which fits well with applications that rely on natural navigation, and technology that includes both vision and laser-guided components. Areas of interest and scan patterns can be configured as needed and the compact, modular design allows for the integration of third-party performance processing hardware and software.
Encoders Monitor Speed and Direction
In order to control ground speed and direction in response to the data coming from the navigation technology in a broad range of AGVs, highly precise and safety-rated encoders are often used.
To minimize or eliminate risk to machinery and systems in industrial applications, components such as encoders can be certified to industry standards of performance and safety levels. For AGV applications, components that are rated up to Safety Integrity Level 3 (SIL3), are ideal, as this allows for the highest safety level in the system. SIL3-rated encoders (Figure 3) can often be more expensive than those that have a lower safety rating, but they greatly reduce the risk of failure to the system, which in the case of an AGV navigating a warehouse, could prevent costly damage or injury.
Using encoders of a lower rating, like SIL2 or less, often means that additional encoders may be required for redundancy in order to achieve an acceptable level of risk in a given application. The need for extra components adds complexity and cost to the system, and can be a serious issue in the space-restricted design of automated/autonomous vehicles.
Draw-Wire Sensors Ensure Proper Mast Height
The aforementioned sensors and functions are used broadly across the entire range of AGV applications. If we focus on fork lift truck and pallet lift truck AGVs, specifically, then several other sensors also need to be considered.
In these applications, additional encoders and position sensors are required to ensure safe and controlled operation. The mast height (or fork height) control could be considered for driven lift trucks but it is essential in lift truck AGVs.
Controlling the mast or fork height in a lift truck is crucial for proper load positioning as goods must be safely removed or stored at varying heights and it can prevent collisions with overhead items. Also known in the industry as cable transducers, string potentiometers, linear position string pots, and string encoders, draw wire sensors are used to provide precise linear position feedback of the mast.
These components utilize a flexible cable, a spring-loaded spool, and a sensor (an optical encoder with incremental, absolute, analog or potentiometric output or, in some cases, a Hall effect sensor). These are ideal for wet, dirty or outdoor environments. This type of position sensor can also be used in AGVs to monitor lateral fork movements for automatic pre-setting in various pallet sizes.
Rotary Hall effectt Sensors Help Prevent Load Spills
Rotary Hall effect sensors are used in AGVs for different functions such as the fork tilt control in lift truck AGVs (and lift trucks in general). Positioned at the bottom of the mast, this sensor provides the functionality to calibrate and control the inclination of the fork and prevent the load from being spilled. In addition, electric-driven scissor lift tables can be integrated into the AGVs in order to raise and lower a static fixture onto the vehicle for transport, or to position the product for human interface. In these cases, a rotary Hall effect sensor is used to measure the inclination of the lateral scissors and then regulate the fixture to the desired height.
There are also other sensors used in AGVs. Pressure sensors can be used to control the load weight in forklifts, and load cells can be used for the same function in unit load carriers. In magnetic navigation systems, specific sensors for track guidance along magnetic tape are used. The magnetic sensor measures how far from the center of the tape it is and provides the information to the motor controller, which then adjusts the steering so the vehicle remains on the center of the track.
AGVs, guided by inertial navigation, use transponders to verify that the vehicle is on course and a gyroscope to detect the slightest change in the direction of the vehicle. In lift truck applications, in order to prevent the AGVs from colliding and to safely load and unload pallet materials, compact photoelectric sensors are integrated into the narrow, fork cone ends as well as the metal chassis.
The materials handling sector is one of the most important elements to designers, manufacturers and engineers working with sensing and control technologies. The rise of Automated Guided Vehicles is accelerating the development of new and even more sophisticated sensing solutions.
