Every child has tried walking around in short steps and rigid movements, talking slowly with halts in between words. Obviously, imitating a robot! Yeah, having a robot is a fascinating dream to imagine. It was considered science-fiction back in the 90s to claim that one in ten Americans will have robots in their homes by 2020.

Leonardo da Vinci designed the first robot in the shape of a knight in 1495

How far do robotics and cloud computing go?

The first industrial robots go back to UNIMATE funded by General Motors in 1961. By 1968, sensorized robots were introduced which could adopt their functions based on the changes in their surroundings. With the introduction of Ethernet during the 1980s, robot manufacturing had a huge burst, where industrial robot sales grew 80% more than previous years. The efficient automation of robotics is due to the smart collaboration of robots as a result of their connection to the mesh networks of shared intelligence. Centralized computing, as in connection of multiple users to a central mainframe server, goes back to the 1960s of course with regards to the technology of the time. However, the idea of cloud computing was only proposed by the late 1990s. Many believe that the first use of cloud computing in its modern context was in 2006 through introduction of data services on web instead of personal computers by Google and Amazon. Cloud computing can definitely be used by the robotics industry as robotics processing software can be provided through software as a service (SaaS) by cloud infrastructures. In fact, it is predicted that 60% of robots will depend on cloud computing SaaS by 2020.

Why cloud robotics?

The giant wave of enthusiasm in robotics has started and it is going to inspire not only the industry, but also house-holds, cities, E-commerce, transportation, and more! These are all due to the advances made in artificial intelligence (AI). Moving object recognition, simultaneous localization and mapping (SLAM), and robotic platforms are the fields that have been extensively gained attractions. To process such considerable computations, mobile robots by themselves would need to overcome some real-time constraints such as their limited on-board compute capability and storage capacity. Hence, cloud robotics can be used to push the barriers of individual mobile robots in AI applications. Employing cloud robotics would shortcut the need for complicated and sophisticated processors and storage hardware by offloading them on the huge backbones established by cloud providers.

Cloud robotics first launch.

“Cloud Robotics” as the major trend in today’s robotics does not go far back. Employing cloud as the processing and storage engine was introduced in 2010 by James Kuffner. It was followed by Steve Cousins paper in outlining the cloud robotics as “No robot is an island.” The cloud robotics introduction coincided with the emergence of the internet of things (IoT) in 2010 where a massive number of connected appliances with cheap processors could cooperate and share information. In 2011, the term “Industry 4.0” was announced in Germany presenting the outset of the fourth era in technology built on network connected industries. Cloud robotics began developing more as further projects emerged. In 2012, GE announced the “Industrial Internet”, to name its new efforts in connecting industrial appliances to communicate and share information.

Cloud robotics evolution.

Since its official launch in 2010, cloud robotics has drawn the attention of many academic and industrial entities. For instance, the RoboEarth was announced in 2015 as the result of a European research project. By creating a cloud-based knowledge base for robots that transforms a simple robot into an intelligent one, thanks to the web services provided. It uses a combination of SLAM and knowledge-based reasoning to benefit from cloud robotics. Also, Rospeex was presented in 2015 by Sugiura and Zettsu from the National Institute of Information and Communications Technology in Japan. Rospeex is a cloud robotics platform for human-robot multilingual spoken dialogues. Moreover, Dexterity Network (Dex-Net) 1.0 was presented in 2016 as a cooperation of Berkeley University automation laboratory and Google Inc. Dex-Net 1.0 a dataset of 3D object models and a sampling-based planning algorithm to explore how cloud robotics can be used for robust grasp planning.

Cloud robotics future.

The cloud robotics development is not limited to the projects denoted above, neither to the industry. In addition to technical applications within the industry, one vast area for cloud robotics to be developed in the near future through home automation applications, where cloud robotics can help in managing households, and even the daily tasks and chores.

In a nutshell.

Cloud robotics enables the connection of cheap, not-so-intelligent processors to huge infrastructures of information processing and storage provided by clouds. Hence, high-tech applications could be developed to automate and control conventional devices with the least cost and most efficiency.

References:

  • Envisioning the Future of Robotics Link
  • Cloud Computing History, Link
  • A Brief History of Cloud Computing, Link
  • Who Coined ‘Cloud Computing’?, Link
  • Kehoe, S. Patil, P. Abbeel, K. Goldberg, “A Survey of Research on Cloud Robotics and Automation,” in IEEE Trans. On Automation and Eng., VOL. 12, NO. 2, April 2015
  • Riazuelo et al. , “RoboEarth Semantic Mapping: A Cloud Enabled Knowledge-Based Approach,” in IEEE Trans. On Automation Science and Eng., VOL. 12, NO. 2, April 2015
  • Sugiura, K. Zettsu, “Rospeex: A Cloud Robotics Platform for Human-Robot Spoken Dialogues,” in IROS, Sept. 2015, pp. 6155-6060.
  • Mahler et al., “Dex-Net 1.0: A Cloud-Based Network of 3D Objects for Robust Grasp Planning Using a Multi-Armed Bandit Model with Correlated Rewards,” in ICRA, May 2016

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