We think robotics research is about creating gadgets that can physically interact with their surroundings. Most useful robots can be accurate, robust, repetitive, relentless, rapid, and even intelligent if sophisticated enough. Only a decade ago, the public was familiar with robots found in automobile plants, assisting in the assembly of autos by wielding or screwing on a car part.

Today, robots have permeated every sector, performing various jobs, including crucial labor such as surgery. Perhaps it won't be long until we have a functional and live Wall-E and R2D2 among us. Isn't it fascinating? Let's delve deeper into the field of robots and see how Data Science education has played a significant role.

What exactly are Robots? 

Robotics is an interdisciplinary discipline that combines science, technology, and engineering to aid in creating robots. What mechanical construction, electrical components, and the vast amount of code do all robots have in common, regardless of their nature or job? They are just devices that are capable of emulating one or more human-like movements and, if feasible, emotions.

When Was the Concept of Robotics First Introduced?

However, the first contemporary robot may be traced back to 1950, when George C. Devol invented a particular "Unimate," which stood for universal automation. When Joseph Engelberger discovered Devol's first-ever robot in the late 1960s, he updated it to a more industrial working form, garnering him renown and the title "Father of Robotics." However, his attempts to persuade Unimate to sell to the rest of the globe were unsuccessful until Engelberger. However, this is the narrative of the contemporary robot's creation.

Robotics and Data Science

Today, the fast-changing world of robots and data science has become intangible. Before delving into how Data Science significantly influences robotics, let us first define Data Science.

Data Science, like Robotics, is an interdisciplinary area in which scientific methodologies, statistics, mathematical algorithms, and computer systems collaborate to create a solution to an ongoing problem, find a future shopping trend, anticipate probable future business dangers, and so on. Data Science, like Robotics, heavily relies on Artificial Intelligence and Machine Learning to generate "actionable insights" for various applications. The future does not have to be a game of chance, but it may be. To know more about the applications of AI tools in robots and automation, refer to the Artificial Intelligence course in Delhi.

The Importance of Data Science in Robotics

As previously said, robotics is a continually evolving field of study. But how can this quick shift occur? During the early days of robotics discovery, scientists had difficulty working on the blatantly complicated data needed for real-time jobs, particularly vision-oriented activities. Understanding or forecasting the robot's next move will also be tough for scientists.

Reprogramming a robot for a new function or preparing for a new real-time trend involving vision-oriented duties was time-consuming. This is when Data Science comes into play and saves the day. Data Scientists who rely on AI and Machine Learning are trained to deal with robots that would change over time, acquire newer behavior through labeled data, evolve after learning to find errors in existing data, and so on. As a result, the scientist's role becomes easier, and robots can develop with little human assistance.

Conclusion

Data Science and Robotics are both incredibly excellent subjects of study. If you can't decide between the two, realize that it doesn't have to be a compromise. Data Scientists working in Robotics are also improving their Data Science skills to work in a data-driven world. You can upskill yourself with the top Data Science Course in Delhi, designed for industry. Learn how data science and AI tools are used in robotics.