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Cloud Robotics

The Industrial Revolution accelerated the broad use of industrial techniques throughout the nineteenth century. Labs and research facilities now have remote access thanks to the Technology Revolution, which sped up these operations in the 20th century.

Because of the advances made during the Robotics Revolution, robots can now carry out various tasks. However, there was still an issue with the necessary space and memory and the associated cost. Thus, cloud robots first appeared.

What is Cloud Robotics?

The term “cloud robotics” describes using remote computing resources to enhance robotics applications in areas like memory, processing power, collective learning, and connection.

Using internet technologies such as cloud computing, cloud storage, and other robotics-related tools is known as “cloud robotics.” An important benefit of cloud robotics is that it eliminates the need for robotic devices to store large volumes of data locally in their memory.

About Cloud Robotics:

Cloud computing is used to supplement the restricted local resources of a robot when its computational or storage requirements exceed those of the robot itself.

The development of cloud robotics is also a significant step forward for robot education. A group of 150 robots studying different elements of a subject may complete it in an hour, but it would take a single robot 150 hours to master the same task using its own AI resources.

The key differences between cloud robotics and traditional automation:

The use of cloud technology is the key differentiation between cloud robotics and traditional automation. The Robots-as-a-Service approach is well suited to cloud robotics as well. Cloud computing allows for the remote access of robotic equipment, and robotics businesses may lease their technology to others through the cloud in exchange for a monthly charge.

Components of Cloud Robotics:

Regarding cloud robotics, the platform itself consists of the servers that store the data. Everything about the robotics equipment, from operations to analysis, is managed by data saved on servers. In most cases, the following six parts make up cloud-based robotics:

  • Data sets of objects, locations, and maps from around the world. Geometry and mechanical characteristics, expert systems, and a database of information are common components.
  • Based on sample data, on-demand, massively parallel computing for statistical model building, job planning, multi-robot scheduling and cooperation, and coordination.
  • Support for robot learning, shared outcomes, trajectories, and dynamic control rules.
  • Easy-to-access “open-source” data, software, and prototyping and hardware development plans.
  • On-demand human review, training, and error-fixing.
  • Human-robot interaction with added enhancements.

Importance of Cloud Robotics:

The term “cloud robotics” refers to a new subfield of robotics that leverages the strengths of converged infrastructure and shared services by relying on cloud computing, cloud storage, and other Internet technologies.

By doing so, robots may use the vast computational, storage, and networking capabilities of today’s state-of-the-art data centers. Because of the elimination of costs associated with keeping custom middleware up-to-date and running, the use of such software is reduced.

By capitalizing on the dramatic increase in the speed at which data can be sent, cloud robotics frees up robots from the constraints of real-time deadlines, allowing them to do more tasks. This is particularly important for mobile robots since processing onboard requires more energy, which may reduce the robot’s battery life, restrict its range of motion, and increase its cost.

The robot may use the cloud’s storage, computing power, and networking options, transforming it into a lightweight, flexible, and inexpensive device with access to the cloud’s vast data repository.

Cloud Robotics Applications:

Industry sectors that may get the most benefits from the deployment of robots are increasingly using cloud robotics. A few of the common applications are listed below:

  1. Health Industry:

Disease archives, EHRs, PHMs, practice services, analytic services, and clinic solutions are all part of the medical cloud’s extensive array of available tools. Clinical services for patients and surgical assistance during real-time procedures are two examples of how healthcare robotic devices use the medical cloud.

  1. Manufacturing/ Industry:

As the complexity of robotic devices used in industry and production rises, the amount of data needed to successfully operate the robots quickly outgrow the capacity of their onboard memory. Work in tandem with a robot system hosted in the cloud. An order for a unique product may be handled, manufactured, and sent entirely by themselves, without the need for human workers, thanks to a network of industrial robots.

  1. Delivery/Shipping:

Robotic delivery systems may use online map databases like Google Street View or Mapbox to plan delivery routes. The collected information about the surrounding area and the roads may then be uploaded to the cloud and used to enhance the functionality of the services and other robotic devices as each autonomous mobile robot delivers.

Advantages of Cloud Robotics:

  1. More capacity for data storage and processing is accessible to the robot.
  2. Onboard, cloud-connected robots are not needed to perform challenging tasks. Coordination of design, object detection, voice recognition and synthesis, and computer vision are tasks that may be dynamically offloaded to the cloud.
  3. Using distributed computing or massively parallel computing, these operations may be completed quickly and in real time in the cloud.
  4. In addition to these characteristics, cloud infrastructure offers dependable and on-demand computing services.
  5. Simultaneous localization and mapping (SLAM) and other perception systems grow as robots collect sensors and other data, resulting in an enormous amount of data that cannot be stored locally on most robots owing to their limited storage capacity.
  6. In addition, robots using cloud storage have access to high-density storage spaces where they may store massive volumes of data for future use.
  7. Despite these favorable conditions, robots may access vast amounts of data, including object models, global maps, open-source procedures, and more code.
  8. In addition, when tackling complex problems, cloud robotics enables robots to interact and share knowledge by using human intelligence via crowdsourcing.
  9. As a result, robots will no longer be restricted in their capabilities and can use cloud infrastructure’s many advantages.
  10. The bulk of people’s interactions with robotic technology nowadays entail sitting at a desk or using a computer to operate the machine.

Conclusion:

Cloud robotics is a branch of the robotics field that focuses on updating automation functions using distributed computing. The end objective is to create a robot that can communicate with the cloud through the internet, combining cloud computing with robotics.

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