Robotic Refactoring the Workplace
Role of Technology in Robotics
Position Sensors for Robotics
Robot-Proof: Higher Education in the Age of Artificial Intelligence
Joseph E. Aoun, President, Northeastern University
From Robotics to Big Data, What the Future Holds for Manufacturing
Karl Rosenblum, Head of Global Capacity and Risk Strategy, Alcon
Robots: A New Source of Business Data
John Santagate, Research Director, Service Robotics, IDC
Deep Learning and Future of Healthcare
Sanjib Basak, Former Director of Data Science & Artificial Intelligence, Carlson Wagonlit Travel
Thank you for Subscribing to CIO Applications Weekly Brief
Fog Robotics for a Better Robot-human Connection
Fog robotics can be defined as an architecture consisting of storage, networking, and decentralized computing control closer to robots. Due to a large amount of data and traffic, cloud robotics (CR) faces latency issues and security breaches. In order to overcome these issues and improve human-robot interactions, fog robotics has been introduced. The fog robotics concept was introduced by the researchers of the University of Technology, Sydney, at the Innovation and Research Laboratory which is called as Magic Lab.
The idea of fog robotics emerged when the researchers saw a high latency in robots communication. Siva Leela Krishna Chand Gudi, one of the study researchers of fog robotics said that they wondered what could happen in the near future when robots are serving everywhere because this lag would most probably continue to grow. They coined the term fog robotics by a heritage of the features of fog computing and by making cloud robotics their companion at the IROS 2017 conference.
The primary objective of the researchers was to deliver fluent, robust, and efficient interactions between humans and robots with low latency. They also wanted to allow robots to communicate and cooperate with people while performing tasks, sharing their results or activities in the same robot family.
One of the main advantages of the fog robot is that it allows a robot to interact and exchange data with another robot. This can be understood with an example of how multiple robots can help people in an airport. In the scenario described, a traveler asks a robot where his departure gate is located. The robot would lead the passenger to the escalator and hand over the task to another robot that will be found on the other side of the escalator. To recognize the traveler as he/she approaches the other end of the escalator, the second robot requires information on the name, identity, gender, and appearance of the person. In order to complete this task, the FR allows two robots to communicate and exchange the necessary data. Similar, the technique can be used in hotels, universities, subways, bus terminals, train stations, and even homes. The world is now closer to certainly witnessing a better robot-humans connection with such advancements.