What is robotics?
Robotics is a branch of engineering that involves the conception, design, manufacture and operation of robots. The objective of the robotics field is to create intelligent machines that can assist humans in a variety of ways.
Robotics can take on a number of forms. A robot may resemble a human, or it may be in the form of a robotic application, such as robotic process automation (RPA), which simulates how humans engage with software to perform repetitive, rules-based tasks.
While the field of robotics and exploration of the potential uses and functionality of robots have grown substantially in the 20th century, the idea is certainly not a new one.
The early history of robotics
The term robotics is an extension of the word robot. One of its first uses came from Czech writer Karel Čapek, who used the word in his play, Rossum's Universal Robots, in 1920.
However, it is science fiction author Isaac Asimov who has been given credit for being the first person to use the term in the 1940s by Oxford English Dictionary.
In Asimov's story, he suggested three principles to guide the behavior of autonomous robots and smart machines.
Asimov's Three Laws of Robotics have survived to the present:
- Robots must never harm human beings.
- Robots must follow instructions from humans without violating rule 1.
- Robots must protect themselves without violating the other rules.
However, it wasn't until a couple of decades later in 1961 -- based on designs from the '50s -- that the first programmable robot, Unimate, was created to move scalding metal pieces from a die-cast machine.
Today, industrial robots, as well as many other types of robots, are used to perform repetitive tasks. They may take the form of a robotic arm, robotic exoskeleton or traditional humanoid robots.
Industrial robots and robot arms are used by manufacturers and warehouses, such as those owned by Amazon, Devol, Best Buy and more.
To function, a combination of computer programming and algorithms, a remotely controlled manipulator, actuators, control systems -- action, processing and perception -- real-time sensors and an element of automation helps to inform what a robot or robotic system does.
Some additional applications for robotics are the following:
- home electronics -- see Honda's ASIMO
- computer science/computer programming
- artificial intelligence
- data science
- law enforcement/military
- mechanical engineering -- see Massachusetts Institute of Technology Robotics
- aerospace -- see National Aeronautics and Space Administration's Urbie
Machine learning in robotics
Machine learning and robotics intersect in a field known as robot learning. Robot learning is the study of techniques that enable a robot to acquire new knowledge or skills through machine learning algorithms.
Some applications that have been explored by robot learning include grasping objects, object categorization and even linguistic interaction with a human peer. Learning can happen through self-exploration or via guidance from a human operator.
To learn, intelligent robots must accumulate facts through human input or sensors. Then, the robot's processing unit will compare the newly acquired data to previously stored information and predict the best course of action based on the data it has acquired.
However, it's important to understand that a robot can only solve problems that it is built to solve. It does not have general analytical abilities.
The pros and cons of robotics
Robotic systems are coveted in many industries because they can increase accuracy, reduce cost and increase safety for human beings.
In fact, safety is arguably one of robotics' greatest benefits, as many dangerous or unhealthy environments no longer require the human element. Examples include the nuclear industry, space, defense, maintenance and more.
With robots or robotic systems, workers can avoid exposure to hazardous chemicals and even limit psychosocial and ergonomic health risks. However, despite these benefits, there are several drawbacks to robotics as well.
There are certain tasks that are simply better suited for humans -- for example, those jobs that require creativity, adaptability and critical decision-making skills.