Autonomous Mobile Robots On The Move in Manufacturing

As part of Machine Design’s 90th anniversary issue in January, we’ve asked industry experts to take a look at the present and future of technology and how it will impact the design and operation of manufacturing over the next decade.

Q: What products do you see that are currently solving design engineers’ problems?

Cloer: Autonomous Mobile Robots (AMRs) are more flexible than traditional guided vehicles and opening up new opportunities for automating material transport. This technology is SLAM based, meaning it creates a map of the surrounding environment in order to autonomously traverse the space.

This keeps the system self-contained and allows it to be controlled on-the-fly to any location within the environment. These are connected devices which allow users to control and mine information from/to their logistics systems such as WMS, ERP or MES.

Josh CloerQ: How are AMRs helping address these engineering and design issues?

Cloer: Logistics engineers can now use this flexible and adaptable technology to automate their material movement to accomplish many different tasks without being dedicated to specific paths. This is lowering the cost of integration and allowing robots to manage many different types of materials and goods.

Q: What are some of the near-term opportunities for AMRs? And what does the future hold?

Cloer: AMRs are solving more and more material transport needs in new form factors and capabilities. These devices are perceiving their environments with many different types of sensory inputs, allowing them to work in more dynamic areas and work alongside different types of autonomous platforms.

In the future, robots will utilize more sensor technology both onboard and remote to share large amounts of data across vehicles. This data will be more useful with the adoption of AI, cloud computing and the 5G network architecture which will together allow robots to fully perceive their environment in real-time. This will provide operational enhancements, allowing for a more efficient workflow with many different types of autonomous vehicles.

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