If SLAM is a new term for you and you want to know more about it, you are on the right page. SLAM is a new technology used to enable a mobile vehicle robot to detect the surrounding environment. The idea is to locate your position on the map. Primarily this technology is associated with robotics, but it can also be employed in many other devices and machines, such as drones, automated aerial vehicles, automated forklifts, and robot cleaners, just to name a few. Let’s take a deeper look at this technology.

The advent of SLAM

In 1995, SLAM was presented for the first time at the International Robotics Research Symposium. In 1986, a mathematical definition was presented at the IEEE Robotics and Automation Conference. After the conference, studies were conducted to learn more about navigation devices and statistical theories.

After more than a decade, experts introduced a method to implement a camera to achieve the same goal instead of using multiple sensors. As a result, these efforts led to the creation of vision-based SLAM. This system used cameras to obtain a three-dimensional position.

Without a doubt, this was a great achievement of that time. Since then, we have seen the application of these systems in various areas.

The core, mapping and localization of SLAM

Now, let’s find out more about the mapping, localization and core of SLAM systems. This will help you learn more about this technology and better understand how it has been shown to be beneficial.

Location

Location can help you figure out where you are. Basically, SLAM gives you an estimate of the location based on visual information. It’s like when you meet a strange place for the first time.

Since humans don’t have a clear sense of defense and distance, we can get lost. The best thing about SLAM-based robots is that they can easily figure out the direction relative to the surrounding environment. However, it is important that the map is highly capable of detecting your location.

Mapping

Mapping refers to a process that helps to analyze the information collected by the robot through a sensor. Vision-based systems generally use cameras as sensitive sensors. After creating sufficient parallax of motion, amid two-dimensional locations, triangulation techniques are implemented to obtain a three-dimensional location.

The beauty of augmented reality is that it can help to obtain information from virtual images in a real environment. However, augmented reality requires certain technologies to recognize the environment around it and detect the relative position of the cameras.

So, you can see that SLAM plays a huge role in a number of areas like the interaction of location, interface, graphics, visualization, and tracking.

Simply put, this was an introduction to the technology behind SLAM and various areas where it is implemented.