If SLAM is a new term to you and you want to know more about it, you are on the right page. SLAM is a new technology that is employed to enable a mobile robot for vehicles to detect the surrounding environment. The idea is to spot its position on the map. Primarily, this technology is associated with robotics, but it can also be employed in a lot of other devices and machines, such as drones, automatic aerial vehicles, automatic forklifts, and robot cleaners just to name a few. Let’s get a deeper insight into this technology.
The Advent of SLAM
In 1995, SLAM was introduced for the first time at the International Symposium on Robotics Research. In 1986, a mathematical definition was presented at the IEEE Robotics and Automation Conference. After the conference, studies were carried out in order to find more about the navigation devices and statistical theories.
After more than a decade, experts introduced a method to implement one 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 in order to get a three-dimensional position.
Without any doubt, this was a great achievement of that era. Since then, we have seen the application of these systems in a number of areas.
The Core, Mapping, and localization of SLAM
Now, let’s find out more about mapping, localization, and the core of SLAM systems. This will help you find out more about this technology and have a better understanding of how it is proven beneficial.
Localization can help you figure out where you are. Basically, SLAM gives you an estimation of the location on the basis of visual information. It is like when you come across a weird place for the first time.
Since we humans do not have a clear sense of defense and distance, we may get lost. The great thing about SLAM-based robots is that they can easily figure out the direction with respect to the surrounding environment. However, it is important that the map should be highly trained in order to spot your location.
Mapping refers to a process that helps analyze information collected by the robot through a sensor. Generally, vision-based systems make use of cameras as sensitive sensors. After the creation of enough motion parallax, amidst two-dimensional locations, triangulation techniques are deployed to get a three-dimensional location.
The beauty of augmented reality is that it can help obtain information from virtual images in a real environment. However, augmented reality requires certain technologies in order to recognize the environment around it and spot the relative position of cameras.
So, you can see that SLAM plays a very important role in a number of areas like location interaction, interface, graphics, display, and tracking.