Robotic Mapping: Simultaneous Localization and Mapping (SLAM)

Author : RyanFeest
Publish Date : 2021-02-06


Robotic Mapping: Simultaneous Localization and Mapping (SLAM)

Simultaneous Localisation and Mapping 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 based on the generated map. As a matter of fact, this technology is used in robotic cartography or robot mapping. This process uses several sensory inputs, algorithms, and computations to navigate around an unfamiliar environment. In this article, we are going to find out more about the role of SLAM in robotic mapping.

How do SLAM Robots Navigate?

In simple terms, SLAM works just like when you are trying to find your way when you are in an unfamiliar location. You try to look around in the hope of finding a familiar sign or mark. Based on this mark or sign, you try to find out where you are. If you fail to 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. As a matter of fact, the robot has to spot its location before finding out more about the environment. Apart from this, the robot tries to find the location without a map.

Simultaneous Localisation and Mapping can help solve this problem with the help of special techniques and equipment. This process starts with an autonomous vehicle. The thing 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 figured out based on the position of the wheels.

For range measurement, these devices use a laser scanner. One of the most common units that are used for this purpose is known as LiDAR. These devices are quite precise and easy to use. But the downside is that they cost a lot of money to purchase. The good news is that there are some other good alternatives as well. For example, sonar is a good alternative, especially when it comes to generating a map of underwater environments. Besides, imaging devices are also a good choice for SLAM. You can find them in 3D or 2D formats. These units are dependent on a lot of variables, such as availability, cost and preferences.

In the process of Simultaneous Localisation and Mapping, another primary component is collecting data from the environment. The autonomous device makes use of landmarks in order to determine the location with the help of lasers and sensors. But the problem is that robots find it difficult to determine the location if the landmarks are not stationary. Apart from this, landmarks must be unique so that the robot could differentiate between them.

Long story short, this was an introduction to robotic mapping as far as Simultaneous Localisation and Mapping is concerned.

Simultaneous Localisation and Mapping 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 based on the generated map. As a matter of fact, this technology is used in robotic cartography or robot mapping. This process uses several sensory inputs, algorithms, and computations to navigate around an unfamiliar environment. In this article, we are going to find out more about the role of SLAM in robotic mapping.

How do SLAM Robots Navigate?

In simple terms, SLAM works just like when you are trying to find your way when you are in an unfamiliar location. You try to look around in the hope of finding a familiar sign or mark. Based on this mark or sign, you try to find out where you are. If you fail to 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. As a matter of fact, the robot has to spot its location before finding out more about the environment. Apart from this, the robot tries to find the location without a map.

Simultaneous Localisation and Mapping can help solve this problem with the help of special techniques and equipment. This process starts with an autonomous vehicle. The thing 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 figured out based on the position of the wheels.

For range measurement, these devices use a laser scanner. One of the most common units that are used for this purpose is known as LiDAR. These devices are quite precise and easy to use. But the downside is that they cost a lot of money to purchase. The good news is that there are some other good alternatives as well. For example, sonar is a good alternative, especially when it comes to generating a map of underwater environments. Besides, imaging devices are also a good choice for SLAM. You can find them in 3D or 2D formats. These units are dependent on a lot of variables, such as availability, cost and preferences.

In the process of Simultaneous Localisation and Mapping, another primary component is collecting data from the environment. The autonomous device makes use of landmarks in order to determine the location with the help of lasers and sensors. But the problem is that robots find it difficult to determine the location if the landmarks are not stationary. Apart from this, landmarks must be unique so that the robot could differentiate between them.

Long story short, this was an introduction to robotic mapping as far as Simultaneous Localisation and Mapping is concerned.

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