Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs)
The use of AGV (Automated Guided Vehicles) in warehousing and factories as an alternative to forklift trucks has been available for some time now. As technologies for sensing, mapping and navigation have improved over the last decade, Autonomous Mobile Robots (or Industrial Mobile Robots) are now available. With the two terms being used interchangeably, what is the difference, and which is better suited to different applications?
Note that in this article we refer only to ground based vehicles and make no distinction between wheels, tracks. It is also assumed that the robots are working in an indoor environment.
AGV or AMR?
The key aspect of an AGV is that it is a guided vehicle with guidance being provided by marked lines or wires on the floor, radio beacons, camera systems or lasers. These ensure that the vehicle is guided along a set path and cannot stray from that path. Initially used in warehousing and logistics, their use has spread to factory environments to replace forklift trucks. Quite often, AGVs work in an environment separated from humans to maintain safety.
Autonomous Mobile Robots (or Industrial Mobile Robots) differ in that they can navigate through the workspace freely. This means that AMRs map and autonomously plan their own routes to maximise efficiency. The key benefit to this is that if there is an obstruction on a planned route, the robot can re-plan to avoid it while an AGV could not without human intervention.
AGVs are generally considered to be more predictable than AMRs with known arrival times and routes. AMRs offer a high level of flexibility, but if the vehicle decides to avoid an obstruction may create a delay in workflow.
Original designs of AGVs and AMRs were based on adapted forklift truck platforms and today many keep those traditional design characteristics. As interest in the AGV/AMR market has grown, three main types have become common:
- Tow truck – which pulls a cart or trolley behind it.
- Forked – almost identical to a traditional pallet/reach/forklift truck but unmanned.
- Flat top (also known as mouse) - moves underneath a pallet, shelf or trolley to lift it and then move or carries an industrial manipulator.
Over the last decade the flat top variant has become the predominant form factor used for AMRs as they have been generally developed ‘ground up’ allowing the integration of navigation technologies and different payloads (such as conveyors or industrial robot arms) to be implemented.
Most AMRs are produced by new entrants to the market, however existing tow and fork truck manufacturers offer ‘autonomy’ ready vehicles that can be fitted with autonomous navigation and drive technologies either in production or afterwards.
Types of AMR
An American National Standard describing Industrial Mobile Robots (ANSI/RIA 15.08 Part 1) was published in December 2020. The standard focuses on the AMR type of robot and whilst currently not harmonised internationally, it provides useful definitions for the types of AMRs in use:
|Type A||Autonomous Mobile Robot (platform only)||
Type A plus a passive or active attachment
that is not a manipulator.
A mobile manipulator, where the manipulator
is what would be considered an industrial
robot, mounted to a mobile platform that
could be either an IMR Type A or an AGV
Navigation and Mapping
Navigation technologies for AGVs consist of either an electro-magnetic tape or wire (embedded in the facilities floor) or a beacon system (utilising radio, vision or lasers). Some AGVs will have a map downloaded into their control systems with pre-planned routes plotted in. In these systems navigation is provided by beacons or scannable images (e.g., 3D barcodes) along the vehicles route.
For AMRs, navigation choice largely depends on the environment being operated in. Static based mapping systems use laser guidance with the assumption that the environment rarely changes. For more dynamic environments, SLAM (Simultaneous Localisation and Mapping) allows the robot to scan its surroundings and update its map as it changes. For best results, static and dynamic mapping can be combined.
Whilst traditional AGVs will tend to rely on magnetic or laser sensors for guidance, the use of bar code scanners (laser or vision based) is often used for finding a position in the workspace. An alternative approach here is the use of radio beacons and triangulation. However, this can become unreliable in facilities with a large amount of metal racking such as warehouses.
For dynamic mapping and guidance (SLAM based), laser sensors are used to create a 3D map of an environment and any obstacles within it. Known as LIDAR this technology is similar to that found in autonomous road vehicles. It can be backed up with machine vision to create a visual map of an environment. This allows the robot to use the LIDAR for long range sensing and planning and the cameras for shorter range obstacle sensing and visual representation. As computer vision software has advanced, Visual SLAM has become possible with maps being created dynamically from cameras alone without the need for expensive and fragile LIDAR systems.
Sensor choice is highly reliant on the operating environment with most AGVs and AMRs using systems designed to work in controlled indoor environments. For applications outside the factory walls, the technology converges on that used for autonomous vehicles.
As with most technologies, the pace of development moves faster that the development of safety standards and for many years there was no relevant standard for AGVs or AMRs.
In February 2020, ISO3691-4:2020 was published setting out the safety requirements of driverless trucks and their systems. However, this standard was not published in the European Commission’s official journal and therefore is not harmonised Type-C under the Machinery Directive or the UK’s Supply of Machinery (Safety) Regulations.
As a standard though, ISO3692-4 does have useful information on the design and safety requirements of an AGV/AMR and is useful standard for this growing market. It is expected to be harmonised in the future, until then it cannot be used alone to prove conformity and should be used in conjunction with other standards and thorough risk assessments.
It's also worth noting that if the mobile robot is carrying an industrial robot, then this would be considered a hybrid robot and so ISO10218 and others would have to be considered.
Uses in Industry
AGVs have been predominately used in the logistics industry to automate the transport of items around a warehouse. The use of AGVs in factories has tended to be in the automotive industry to date. Regardless of industry the products being carried have been typically of a pallet size and over 250kg. Some organisations have used AGV tow trucks to transport smaller kits of parts to lineside operations to support lean just in time manufacturing.
As the AMR market has developed, lower payload vehicles have come to the fore with an emphasis on moving smaller items. Typically used in warehousing to support goods to man picking (typically for e-commerce), alternative uses are being found in many manufacturing situations where the robots can transport smaller items from workstation to workstation or from storage to point of use.
AMRs that are fitted with industrial robot arms are finding uses both in warehousing and manufacturing. In warehouses there is growing but nascent market for AMRs that not only transport goods but also pick them from shelves as well. In manufacturing, such AMRs are finding uses in situations where a fixed robot installation would not be cost effective or flexible.
Benefits and Drawbacks
There are several key benefits to using AGVs or AMRs in either a warehouse or manufacturing facility:
- The removal of the human driver has been shown to decrease the number of collisions between vehicles, equipment, other vehicles and importantly people.
- Both AGVs and AMRs are less prone to mistakes which improves overall efficiency of a warehouse or manufacturing facility.
Investment cost is often cited as a drawback of both AGVs and AMRs. Costs are falling year on year and if a long-term approach is taken to ROI, AGV/AMRs should compare favourably against manual methods.
A lack of inherent flexibility in AGVs can be a drawback but also a benefit as they provide a predictable workflow. However, should a route become blocked, AGV based systems would not be able to pass it causing delays and bottlenecks. This can be answered using dynamic AMRs which can replan their routes which provides maximum flexibility. This though can cause unpredictable workflow schedules which should be borne in mind.
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