Latest Posts

Stay in Touch With Us

For Advertising, media partnerships, sponsorship, associations, and alliances, please connect to us below


+91 40 230 552 15

540/6, 3rd Floor, Geetanjali Towers,
KPHB-6, Hyderabad 500072

Follow us on social

Understanding how 5G can Impact and Improve Cloud Robotics

  /  5G   /  Understanding how 5G can Impact and Improve Cloud Robotics
cloud robotics robot 5g iot

Understanding how 5G can Impact and Improve Cloud Robotics

How 5G and Cloud will change the Robotics Landscape in recent times?


It is said that Leonardo da Vinci had experimented with robotics during the Renaissance when he designed a mechanical lion to impress the King of France. Today, because of the fast development of technologies, numerous production systems, and large pools of data fields, robots have become increasingly advanced. As they have switched from a sci-fi concept to reality, expanding their use cases from drug research laboratories to manufacturing hubs to even restaurants, now researchers are looking to integrate robotics with the cloud via the 5G network, or commonly known as cloud robotics.

Last year, a team of researchers the NYU Tandon School of Engineering, started building the foundations of a wireless system that takes advantage of superfast fifth-generation (5G) wireless communications to outsource a mobile robots’ artificial intelligence (AI) functions to the edge cloud — the server in the cloud closest to the robot. The team included Ludovic Righetti, a professor in the Departments of Electrical and Computer Engineering and Mechanical and Aerospace Engineering; and Siddharth Garg, Sundeep Rangan, and Elza Erkip, professors in the Department of Electrical and Computer Engineering. The team will focus on solving issues of reliability, the safety of robotic operation under communication degradation, and scalability to multi-robot systems. The collaborators will also address challenges involved in making 5G networks a viable bridge between robot and server. As per the official statement by the team, shifting AI capabilities from the robot to a remote server provides enticing operational benefits, like allowing robots to perceive the environment, perform complex operations, and make decisions autonomously, all without incurring major energy and weight costs from onboard computational and power-generation equipment. The project received the support of the National Science Foundation’s National Robotics Initiative 2.0.

In 2016, Ericsson teamed up with The BioRobotics Institute and Zucchetti Centro Sistemi to develop robots for industrial applications that can be controlled from anywhere in the world and navigate by themselves. To achieve this, the controlling functionality (or the brains) of the robots was moved to the cloud, to utilize its massive computing power. And to make that possible 5G plays a pivotal role to aid robot to interact with the cloud environment in real-time because of its lower latency and higher bandwidth than other forms of wireless connectivity.

In cloud robotics, through the cloud, robots can be controlled dynamically and re-programmed to assist everywhere from hospitals to factories, which makes them easier to use and offers higher efficiency. It will also leverage edge computing technologies, like Mobile Edge Computing (MEC), along with commercial introduction of 5G New Radio (5GNR) technologies based on millimeter-wave (mmWave) frequencies. This buzzing technology is expected to drive a huge share of the growth of IoT technology over the next several years. The cloud robotics market is estimated to grow from US$ 2.21 billion in 2018 and is predicted to reach US$ 9.41 billion by 2026 at a CAGR of 13.4% during the forecast period. The growing adoption of connected services (IoT) in robotics by data sharing for offloaded computation and collaborated effort is a crucial factor in the development of the worldwide cloud robotics market.

Cloud robotics have a better edge than most of the earlier robots. This includes better information sharing using a cloud platform by collecting and transfers data, from-to all connected robots. Plus, information collected and processed on each robot will always be up to date and backed-up safely. This will also open up scopes for collaborations between two isolated robots. Further, by offloading to the cloud, data-intensive tasks such as voice and image recognition, voice generation, environmental mapping, and motion planning will lower the hardware requirements and power consumption of robots, making them lighter, smaller, and cheaper. Also, it leads the way to a much extensive array of robotics services across several industry verticals like healthcare, manufacturing, and many more.