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How Can AI Robots See? Never Underestimate Robot

Robot seeing living room and matrix

Artificial Intelligence robots can used in a lot of different fields like drones, service robots and self-driving cars, but did you know how can they do these things? If no, you definitely need to know how they are able to receive visual data to do these things, so in this article you will get the sense of how they can "see" with actual images so can get the sense of how they see.

Computer Vision

First of all, you need to know what computer vision is as a whole.

Computer vision is an area of research and study that's dedicated to making computers capable of interpreting and comprehending visual information.

It involves forming algorithms and models which are capable of analyzing, dealing with and interpreting digital images and videos to pull out important details.

Computer vision methods are used in a variety of areas, such as self-driving cars, medical imaging, facial recognition, robotics, and many other things.

Different Methods for perceiving the visual data


Cameras are all the most common, but one of the most used methods to input visual data.

This works like this: The camera is taking pictures as we all know, but those pictures must be then lightning fast analyzed by the core AI system. First of all, needs to be analyzed the distances and all the geometrical objects so the robot knows how much space there is so it can then move based on that, then could be analyzed thousands and thousands of parameters which are depending on the specific use of the robot.

Computer vision


Lidar, short for Light Detection and Ranging, has quite the impressive ability to measure distances and build 3D models of the surroundings.

It works by sending out laser pulses and then measuring the amount of time it takes for them to return. From that it is able to generate some pretty precise 3D maps of the area.

These maps can help robots using AI to manoeuvre their environment and avoid objects. And it can also be used for recognizing and following objects since it gives detailed 3D info about them.

Computer vision - lasers


Radar works by sending out radio waves and detecting the signals that bounce back from objects in the environment. By measuring the amount of time it takes for the radio wave to return, radar can calculate how far away object is. It can also tell us what the object is like, its size and shape, and how fast it's moving based on the reflected signal.

It is commonly used in self-driving cars where they usually have radar sensors in front and back to detect cars, objects and obstacles in its path.



Sonar basically works by sending out sound waves using a transducer. These waves bounce off objects in your surroundings and the reflected sound waves go back to the transducer.

With this, you can calculate the distance of the object, plus the time it took for the wave to return can tell you the speed of the object.

In underwater robotics, sonar is used for things like obstacle detection and making maps of the underwater environment.

Sonar waves


Infrared sensors work by picking up the heat emitted from objects in the room.

Basically, anything with a temperature above zero degrees emits some kind of infrared radiation, which these sensors can detect and create an image. This means you can use them to pick up people or animals even in a total black-out.

They're often found in security systems and other kinds of surveillance.

Infrared sensor

Combining Sensing Methods

AI robots can also combine multiple sensing methods for a better understanding of their environment. For instance, take a self-driving car.

It may use a blend of camera, lidar and radar sensors to detect its environment and come up with driving decisions.

Merging data from several sensors enables AI robots to gain an in-depth, precise insight into the environment.


AI robots have a totally different way of "seeing" things compared to us humans. Instead of relying on our own visual system, they use a variety of methods to get the data they need. These methods include cameras, lidar, radar and computer vision.

This allows AI to interpret visual data using math models and algorithms and make decisions based on what they "see". This makes AI capable to "view" information in a way that we simply can't do.

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