Robotics

Choosing the right robot for warehousing, manufacturing operations

Automated guided vehicles (AGVs), autonomous mobile robots (AMRs) and static robots have different needs and abilities. Knowing the difference is critical to understand which choice will be the best fit.

By Jeff Huerta August 15, 2021
Courtesy: Vecna Robotics

Evaluating very large robots and other motion control options: If you need to move large things from here to there, how should that happen? Can a very large robot help or should other motion control options should be considered?

There are a few options for distribution, warehousing and manufacturing organizations to consider when looking to move large items from point A to point B. Under the category of industrial mobile robots, there are automated guided vehicles (AGVs), autonomous mobile robots (AMRs) and static robots.

While each option suits various needs, knowing the difference between the capabilities of each offering is critical to understand which choice will be the best fit. The two most popular options are AGVs and AMRs, and the unique capabilities of each are often mistaken.

Figure 1: Automated guided vehicles (AGVs) are path followers, while autonomous mobile robots (AMRs) are path planners. A Vecna Robotics AMR is shown. Courtesy: Vecna Robotics

Figure 1: Automated guided vehicles (AGVs) are path followers, while autonomous mobile robots (AMRs) are path planners. A Vecna Robotics AMR is shown. Courtesy: Vecna Robotics

Automated guided vehicle versus autonomous mobile robot

Here are the key differences between AGVs and AMRs, and why it matters.

Many companies rely on AGVs for materials handling capabilities, including moving large and small loads and lifting materials multiple racks high. One key detail to consider when evaluating AGV solutions is these vehicles follow pre-programmed paths. Historically, these paths were defined either by marked lines or wires on the floor. Today, they take a teach-and-repeat approach where an operator manually drives a robot on the route that they anticipate will work best and then the robot can only drive that route over and over again. While this may work for some companies, others might need a more flexible option.

Figure 2: With the addition of continuous learning, autonomous mobile robots (AMRs) can react in real-time and adapt workflows to run through diverse levels of demand and operational changes efficiently.  A Vecna Robotics AMR is shown. Courtesy: Vecna Robotics

Figure 2: With the addition of continuous learning, autonomous mobile robots (AMRs) can react in real-time and adapt workflows to run through diverse levels of demand and operational changes efficiently.  A Vecna Robotics AMR is shown. Courtesy: Vecna Robotics

Path planning advantages for AMR

This is where AMRs come in. While high-capacity AMRs have the same payload capabilities as AGVs, they are path planners versus path followers. This fundamental difference takes AMRs to the next level, providing added intelligence that allows robots to reroute in real-time and navigate freely around obstacles. Although the form factor may look the same, the adaptability to dynamic environments is what makes it a more viable and safe solution for many.

Both solutions use multiple sensors and a fusion of the various inputs for safe autonomous operation. However, with the addition of continuous learning, AMRs can react in real-time and adapt workflows to run through diverse levels of demand and operational changes efficiently. Further, through orchestration, AMRs can share information across people, robots and associated systems and integrate seamlessly with legacy automation, piece-picking robots, warehouse management systems (WMS) and enterprise resource planning (ERP) systems to improve overall warehouse efficiency.

Figure 3: Unlike path-following robots, autonomous mobile robots (AMRs) can navigate obstacles and understand surroundings to flexibly adapt to changes and tasks. Rather than blindly moving to pick up where they believe a pallet should be, they verify its location. Courtesy: Vecna Robotics

Figure 3: Unlike path-following robots, autonomous mobile robots (AMRs) can navigate obstacles and understand surroundings to flexibly adapt to changes and tasks. Rather than blindly moving to pick up where they believe a pallet should be, they verify its location. Courtesy: Vecna Robotics

Human logic examples for AMR navigation

So, AMRs evaluate the circumstances to make decisions, similar to how a human would. For example, if an individual wants to go to the kitchen to get a bottle of water, they do not think that they have to walk 27 feet before turning right into the kitchen. A human knows the general direction to travel and the landmarks to look for along the way. Additionally, as a person walks down the hall, there are certain obstacles, such as benches, shoes, and pets, that they need to navigate around. Likewise, when a person arrives in the kitchen, they first look where the bottle should be and verify that it’s there before they pick it up.

The same is true for AMRs in the warehouse. Unlike path-following robots, AMRs can navigate obstacles and understand surroundings to flexibly adapt to changes and tasks. Rather than blindly moving to pick up where they believe a pallet should be, they verify its location.

All of these aspects are crucial to consider when determining which solution will work best with the company’s needs.

Jeff Huerta is senior vice president of sales at Vecna Robotics. Edited by Chris Vavra, web content manager, Control Engineering, CFE Media and Technology, cvavra@cfemedia.com.

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Keywords: Automated guided vehicle, AGV, autonomous mobile robot, AMR,

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Jeff Huerta
Author Bio: Jeff Huerta, senior vice president of sales at Vecna Robotics