Autonomous Mobile Robots (AMR): Definition, Applications, Alternatives
An autonomous mobile robot (AMR) or Automated Guided Vehicle (AGV) – when looking to automate intralogistic transport processes, one seems to face a choice between two different technologies. But are the differences between AMR and AGV really that significant?
What is an Autonomous Mobile Robot (AMR)?
The term autonomous mobile robots (AMR) refers to transport robots that have a high degree of autonomy. They adjust their travel routes based on current spatial conditions and autonomously avoid obstacles. The term is often used to distinguish autonomous mobile robots (AMR) from the established Automated Guided Vehicles (AGV). An AGV is a transport robot that only follows predefined routes and does not deviate from them. Examples include magnetic tracks, optical guides, or even virtual tracks via laser navigation. The terms AGV and FTS (Automated Transport System) are often incorrectly used synonymously. However, an FTS is not a single vehicle, but rather a complete system made up of multiple AGVs (or FTFs in German). Automated Guided Vehicles (AGVs) are considered to have less flexibility compared to autonomous robotics.
SAFELOG S3 in coordinated operation at Dresselhaus (Image: © SAFELOG).
However, this distinction doesn’t make sense.
There are hardly any technological differences between AMR and AGV/FTF. The hardware of the robots is nearly identical in terms of drive, battery, control, or safety technology. And the often mentioned superior sensors, such as 3D cameras for environmental detection, can be used when needed in nearly all types of mobile robots. Even in terms of navigation, the similarities are significant. Many modern AGV systems have the ability for free navigation – which is why they should be called both AGVs and AMRs.
Therefore, it is no longer up-to-date to differentiate between AMR and AGV.
Both are mobile transport robots that take on specific transport tasks and, depending on the application, must fulfill certain autonomous capabilities, such as avoiding obstacles or detouring.
SAFELOG mobile robots with Periphery Setup at SportOkay (Image: © SAFELOG).
How much autonomy is sensible?
Since AMRs navigate autonomously, their driving behavior is often less precisely predictable. Especially in production environments, where high temporal precision is required due to just-in-time scheduling, autonomously navigating robots can jeopardize process safety with their unpredictable driving behavior. In automation with mobile robots on the traditional assembly line, in the linking of sources and sinks in production logistics, or in line supply from the warehouses, too much autonomy jeopardizes the achievement of the required goals. This is because a detour causes a time delay or creates an obstruction for other process participants.
If there are additional (manual) vehicles on the shop floor or complex traffic rules need to be followed, it is difficult to ensure a predictable workflow with autonomous systems. The autonomous robots may even overtake each other when they encounter obstacles. This disrupts the delivery sequence based on the pearl chain principle.
In contrast, when a robot navigates with little autonomy on a defined route, it performs its tasks efficiently, safely, and reliably. This is a key advantage when many transport robots need to interact with each other, as well as with other vehicles or peripheral systems. The situation is different in applications in intralogistics, where the delivery time and sequence play a secondary or no role at all.
Autonomy can be advantageous in a picking warehouse. There are often no mandatory route guidelines, a freely navigable area, and the transport tasks are not tightly scheduled. Instead, the focus is on goals such as quickly locating goods.
What really matters in automation with transport robots
Autonomous navigation is not a cure-all for faulty processes. If pallets, bicycles, or other items are randomly placed and disrupt intralogistics workflows, these are structural problems that cannot be solved through automation with transport robots.
Example of a poorly-organized factory hall (Image: © Adobe Stock).
Ultimately, the success of a project depends not on the level of autonomy, but on cost efficiency and stable, high technical availability. The in-house staff must be able to get the system up and running again in case of disruptions. The fewer technologies and sensors are integrated into a robot, the fewer potential sources of error and technological dependencies there are. This makes the system very robust. It is also crucial to choose a flexible robotics solution. This is because a control station is usually required to manage the robots. It is expensive to purchase, program, and maintain, and is particularly uneconomical for smaller automation projects with few robots. Additionally, if the control station experiences a malfunction, the entire fleet can fail.
Example of a well-organized factory hall (Image: © Adobe Stock).
Modern mobile transport robots therefore have agent-based control. The robots communicate decentrally with each other in a swarm, sharing their position, destination, and route, and exchanging information about disruptions on the routes. In the event of a malfunction, only the affected vehicle stops, while the swarm continues with its tasks. This eliminates the costly downtime of entire fleets. The technical availability of the solution can reach over 99%. Route planning and authorizations for route sections also occur based on the internal communication within the swarm. The agent-based control enables efficient operation of robot fleets ranging from a few to several hundred vehicles. There is only a relatively higher effort required for the initial setup due to the fleet size. This allows for a cost-effective automation solution for small businesses, even with a low number of robots. Additionally, quick ROIs can be achieved, especially in connection with leasing and financing models. With decentralized control, both efficiency and process reliability increase.
Summary
The distinction between autonomous mobile robots (AMR) and driverless transport vehicles (FTF/AGV) is irrelevant. Both terms describe mobile transport robots with varying levels of autonomy.
Whether autonomous navigation makes sense depends on the specific application. The success of automation with transport robots is determined by the stability of the system, cost efficiency, and fleet availability.