Simultaneous localization and mapping is called SLAM. This process helps to create a map with the help of an unmanned vehicle, such as a robot. This machine navigates the environment based on the generated map. In fact, this technology is used in robotic cartography or robot mapping. This process uses various sensory inputs, algorithms, and calculations to navigate an unknown environment. In this article, we are going to learn more about the role of SLAM in robotic mapping.
How do SLAM robots navigate?
In simple terms, SLAM works like when you try to find your way when you are in an unknown place. He tries to look around in the hope of finding a familiar sign or mark. Based on this mark or sign, it tries to figure out where it is. If you don’t recognize any sign or landmark, you may get lost.
Similarly, SLAM bots 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. What happens is that this type of machine enjoys great odometric performance. Basically, audiometry helps a robot get an approximation of its own location. In most cases, this is determined 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 a 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 as well. For example, sonar is a good alternative, especially when it comes to generating a map of underwater environments. Furthermore, imaging devices are also a good option for SLAM. You can find them in 3D or 2D format. These units depend on many variables, such as availability, cost, and preferences.
In the simultaneous localization and mapping process, another major component is the collection of environmental data. The autonomous device uses landmarks to determine location with the help of lasers and sensors. But the problem is that the robots find it difficult to determine the location if the reference points are not fixed. Apart from this, the reference points must be unique so that the robot can differentiate between them.
Long story short, this was an introduction to robotic mapping as far as simultaneous localization and mapping is concerned.