Cloud Robotics

Cloud robotics is the use of cloud computing, cloud storage, and other internet technologies in the field of robotics. One of the main advantages of cloud robotics is its ability to provide vast amounts of data to robotic devices without having to incorporate it directly via onboard memory.

What is cloud robotics?

The term “cloud robotics” was created in 2010 by a research scientist at Google named James Kuffner. The concept was simple: bulk of processing for devices would take place in the cloud, enabling robot manufacturers to create lighter, cheaper devices and leverage the power of cloud infrastructure.

In 1994, the first industrial robot was connected to the internet via an intuitive graphical user interface. This interface allowed human operators to teleoperate the robot via any internet browser around the world. These advancements in robotics and networking technology led to the creation of the IEEE Robotics and Automation Society’s Technical Committee on Networked Robots in May 2001.

There are many advantages to cloud robotics. The first is its ability to provide vast amounts of data to robotic devices without having to incorporate it directly via onboard memory. The data used for operation, maintenance, and more are stored in a cloud-based database system that can be accessed remotely. Next is the ability for robots and systems to share information across the entire system to support collective learning. And finally, the cloud-based system and open-source software structure make it easy to share information between human operators to help improve the robotic devices and operational software.

The Six Components of Cloud Robotics

A cloud robotics platform is comprised of secure servers that host vast databases of information. The data stored in servers controls every aspect of the robotics machinery, from operations to analysis. Cloud robotics typically includes the following six components:

  1. A global library of images, maps, and object data. It often includes geometry and mechanical properties, expert systems, and knowledge base;
  2. Massively-parallel computation on-demand to allow sample-based statistical modeling and motion planning, task planning, multi-robot collaboration, scheduling, and coordination;
  3. Shared outcomes, trajectories, and dynamic control policies as well as robot learning support;
  4. “Open-source” code, data, and designs for easy programming, experimentation, and hardware construction;
  5. On-demand human guidance and assistance for evaluation, learning, and error recovery;
  6. Augmented human-robot interaction

How does cloud robotics differ from general automation?

The main differentiator between cloud robotics and general automation is the reliance on cloud technologies. Cloud robotics also lends itself to the Robots-as-a-Service business model. The cloud-based infrastructure is designed for remote access of robotic devices, and robotics companies can lease their technology via the cloud to others for a recurring fee.

Applications of Cloud Robotics

Cloud robotics is increasingly used across a variety of industries that benefit from robotics, including:


The medical cloud infrastructure includes services like disease archives, electronic medical records, patient health management systems, practice services, analytics services, and clinic solutions. For example, the healthcare robotic device accesses the medical cloud infrastructure to provide clinical services to patients and assist surgeons in live surgeries.


As industrial and manufacturing robotic devices become increasingly complex, the data required for operating the robotic machines exceeds the limited space available in the onboard memory. Cloud-based robot systems are capable of collaborative tasks. For example, a series of industrial robotic devices can process a custom order, manufacture the order, and deliver it all on its own—without human operators.


Robotic devices can tap into cloud-based databases of maps like Google Streetview or Mapbox to map out the path for delivering goods. Then, as each autonomous mobile robot makes its deliveries, it can share the data they collect about the environment and road conditions to the cloud, improving the performance of the services and other robotic devices.

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