The Industry 4.0 revolution is enabling a new generation of Automated Guided Vehicles (AGVs) for use in the first wave of smart manufacturing and distribution facilities. But AGVs are in turn presenting a new challenge to sensing and control manufacturers, especially when it comes to navigation. By Alessandro Bosio, Sensata Technologies
A market on the move
The future of AVGs will undoubtedly be autonomous – systems that are adaptive and feature intelligence-based capabilities that allow them to respond within boundaried domains to situations that were not pre-programmed in the design.
Autonomous vehicles for use in factories, industrial facilities, retail outlets, warehouses, etc., can be categorised 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 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 yet 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. AGVs are also intrinsically safer, for they remove the issue of operator error.
Arguments against, however, include the high level of initial capital investment but perhaps the biggest barrier to the wider adoption of AGVs is that there is not yet a single navigation technology against which a consistent standard can be set, compared, and measured.
Navigation and steering control
AGV manufacturers most commonly consider the four following technologies for new equipment/ installation: magnetic navigation; laser-guided navigation; vision-guided navigation; and natural navigation.
Magnetic navigation. Various light-duty AGVs use magnetic tape for the guide path. One major advantage of tape over wired guidance is that it can be easily removed and relocated if the course needs to change. It also removes the expense involved in restructuring the floor of the factory or warehouse. A limitation of this method is that the routes have to be fixed and well defined by the tape. If any obstacle is detected in front of the AGV, it stops and waits for the problem to be solved (for example, the obstacle to be removed) before it restarts.
Laser-guided navigation is similar to an electronic eye, which, by means of reflectors positioned on the surrounding walls, uses triangulation to determine the exact position of the vehicle to allow it to carry out the required tasks in the operating area. The advantage of laser-guided technology is that it requires no floor work as in the case of magnetic guidance systems. Additionally, route changes can be made easily via software updates.
Vision-guided vehicles (VGVs) use optic sensors (cameras), in addition to other sensors such as speed or laser sensors, to navigate, and software within the vehicle effectively builds a 3D map of its operating environment. This technology allows the vehicles to operate in automatic or manual mode for maximum flexibility.
AGVs based on natural navigation technology do not require reflectors or markers so they require less installation time and are easily integrated into existing systems, minimizing the impact on current operations. In this type of navigation, Light Detection and Ranging (LiDAR), is the main technology used.
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 can sometimes struggle in environments that are prone to sudden vibration, low light or dust, LiDAR systems prove to be more reliable. They do not require external targets such as reflectors, RFID, or markers for navigation. As such, they are ideally suited not only for localisation and mapping, but also to help prevent collisions and ensure loads are properly and safely engaged and placed.
Traditionally, LiDAR sensors have been costly; new, entirely solid-state solutions, however, are more affordable and require less power and deliver higher resolution at a longer range. 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.
A perfect fit for applications relying on natural navigation (and a technology that includes both vision and laser-guided components), the latest LiDAR solutions offer the highest resolution with the maximum amount of system flexibility. 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.