Simultaneous mapping and locating is called SLAM. This process helps create a map with the help of an unmanned vehicle, such as a robot. This machine navigates the environment according to the generated map. In fact, this technology is used in robotic mapping or robot mapping. This process uses various sensory inputs, algorithms, and calculations to navigate an unfamiliar environment. In this article, we will discover more about the role of SLAM in robotic mapping.
How do SLAM robots navigate?
In simple terms, SLAM works the same as trying to find your way when you are in an unfamiliar place. You try to look around in the hope of finding a familiar sign or mark. Based on this mark or sign, try to find out where it is. If you don’t recognize any sign or landmark, you may get lost.
Similarly, SLAM robots try to generate a map of an unknown environment, as well as its location. In fact, the robot has to detect its location before finding out more about the environment. Apart from this, the robot tries to find the location without a map.
Simultaneous localization and mapping can help solve this problem with the help of special techniques and equipment. This process begins with an autonomous vehicle. The fact is that these types of machines enjoy great odometry performance. Basically, audiometry helps a robot get an approximation of its own location. In most cases, this is calculated based on the position of the wheels.
To measure range, these devices use a laser scanner. One of the most common units used for this purpose is known as LiDAR. These devices are quite accurate and easy to use. But the downside is that they cost a lot of money to buy. The good news is that there are other good alternatives too. For example, sonar is a good alternative, especially when generating a map of underwater environments. Furthermore, imaging devices are also a good option for SLAM. You can find them in 3D or 2D formats. These units depend on many variables, such as availability, cost, and preferences.
In the process of simultaneous localization and mapping, another main component is the collection of data from the environment. The autonomous device uses landmarks to determine location with the help of lasers and sensors. But the problem is that robots have a difficult time determining location if the reference points are not stationary. Apart from this, the reference points must be unique so that the robot can differentiate them.
Simply put, this was an introduction to robotic mapping when it comes to simultaneous location and mapping.