‘무인 운반 차량(AGV) 대 자율 주행 로봇(AMR) : 올바른 로봇을 선택하는 것’이라는 주제로 마우저 일렉트로닉스(Mouser Electronics)의 포니마 압뜨(Poornima Apte)에게 들어봤다.
“‘AGV·AMR selection’ depends on facility·operation requirements·budget”
AGV provides ideal structured and predictable environments, while AMR provides dynamic spatial flexibility and adaptability.
Both types have many benefits, and the right match can increase employee productivity and return on investment.
At Dubai airport, I was hoping to catch an unmanned 'rapid passenger transport' to transfer from one terminal to another.
The system considers a series of tracks and follows a set path repeatedly without relying on humans for navigation.
These seamless Dubai operations have been used for airport transportation around the world.
In the process, I couldn’t help but think of the parallel use cases of robotics, automated guided vehicles (AGVs) and autonomous mobile robots (AMRs).
AGVs and AMRs transport materials and goods and have many practical applications in warehouses, retail, restaurants, hospitality, and even healthcare environments.
The robot can save on labor costs by acting as a 'fetch' in transporting goods.
AGV transports goods and moves them in fixed paths.It is a robot that moves along the Rona line.
Markings on the floor, such as magnetic strips or wires, serve as landmarks for the robot to follow.
AMR is a more advanced version of AGV. AMR is also a transport robot, but it uses various sensing methods and algorithms to navigate around a place.
This will help you understand the differences between the two robots and the design considerations currently in use to decide which robot you need.
■ Key differences between AGV and AMR As the name suggests, AGVs are automated, while AMRs are autonomous.
In that sense, AMR is more intelligent and requires less human intervention in its operation.
The biggest difference between the two robots is how they navigate space: AGVs require more hand-holding than autonomous ones.
Because they follow a predetermined path or track using magnetic tape, laser, or optical tape, the AGV's cameras or sensors can follow tape or lines painted on the floor.
AMR, on the other hand, does not require such a limited environment. It can move more autonomously without needing guidance.
LiDAR or computer vision technology can be used to map and learn the path.
Advanced algorithms such as simultaneous localization and mapping (SLAM) can help AMRs map and track themselves so they know where to go next.
SLAM technology has been used in friendly restaurant delivery robots that bring orders to your table.
■ Choosing the right robot for your operating environment These fundamental differences in the way these robots navigate are additional differences between AGVs and AMRs, and are important considerations when considering investments in these technologies.
■ Operating environment If the environment in which the robot will operate is dynamic and changing, an AGV may not be the best choice.
AGVs require much more prescribed paths and work best in highly structured environments where traffic is predictable and tasks are routine.
For example, if the robot is expected to carry items from shelf to shelf in a warehouse along the same path every time and the design is expected to remain in place for years, an AGV is a better choice. If the warehouse or other environment in which the robot operates is busier and more unpredictable, robot navigation becomes more complex.
The space in the lanes where the robot can move may be narrow. In these cases, AMR may be a better choice.
■ Cost and Flexibility AMRs are typically more expensive than AGVs because they have more advanced sensors and algorithms.
However, it can also be reworked more flexibly and quickly to meet changing requirements in the future.
Even though their overall cost is slightly lower than that of AMRs, AGV systems are much more difficult to disassemble and replace.
■ Battery life and charging stations Both of these mobile robots are typically battery-powered, meaning they need to be charged or the batteries need to be replaced regularly.
If the robots operate in shifts, it may be convenient to assign workers the task of charging or replacing the batteries each evening.
However, if you have a lot of robots in use or are very busy, it may be worth investing in an automatic contact charging station or battery-swapping robot station.
Larger batteries last an entire shift, simplifying charging schedules, but they make the robot heavier and use more energy.
Depending on how much your robot is used, it may make sense to keep to a regular charging schedule or to stop working whenever the battery is low.
Operators can also choose opportunistic schedules where the robot takes breaks during its normal operation to rest or recharge.
■ Integration with existing systems Whether AGVs or AMRs, robotic vehicles must integrate data with existing warehouse management systems (WMS) or other on-premise software so that customers can use and extend their existing workflows rather than replacing them with entirely new processes.>
The use cases for AMR and AGV are likely to expand. In addition, integration with advanced technologies such as AI and the Industrial Internet of Things (IIoT) is expected to concretize the way AGV and AMR are used.
Both types of robots offer a variety of benefits, and the right match can improve employee productivity and provide a valuable return on investment.
■ Conclusion In an era of increasing industrial automation, facilities of all types are looking to automate transportation to streamline operations and reduce labor costs, and both AGVs and AMRs provide solutions for this automation.
Choosing between AGVs and AMRs depends on your facility's layout, operational requirements, and budget.
While AGVs are ideal for structured, predictable environments, AMRs offer flexibility and adaptability to dynamic spaces.
Carefully evaluating these factors will ensure that you get the robotics solution that best suits your facility’s needs and environment.
※ Contributor
Poornima Apte is an engineer-turned-writer with B2B expertise in robotics, AI, cybersecurity, smart technologies, and digital transformation.