Figure 1.12. Block diagram of the video and audio receiver
1.3.3. Smart home
Smart lighting is a very necessary requirement for smart homes, hotels, museums, etc. By incorporating VLC technology into lighting devices, not only does it create a smart lighting network. but also create wireless access points, helping users easily use entertainment services as well as access the Internet. Most importantly, users can control their home through this technology such as closing the door, automatically turning on music, automatically cleaning,...
1.3.4. Intelligent traffic system Maybe you are interested!
Maybe you are interested!
Visible light communication technology is not only used in indoor environments, but it is also applied in outdoor environments, especially in smart transportation systems. Vehicles can communicate with each other through VLC signal transceivers to minimize unfortunate accidents. In addition, vehicles can also connect to traffic lights or lights on both sides of the road to locate or access the Internet. Figure 1.13 illustrates a smart transportation system using VLC technology.
Figure 1.13. Intelligent traffic system
1.3.5. Positioning and navigation
Positioning and navigation are two very common problems in applications of smartphones or robots in indoor environments, such as e-mart systems (electronic supermarket systems) in supermarkets. Based on parameters such as receiving power, color, frequency or geometric factors,... we can easily apply VLC technology to solve the positioning problem.
Figure 1.14. E-mart navigation system in supermarkets
1.4. Summary of chapter one
In this chapter we have discussed the basics related to wireless communication technology using visible light – VLC has a wide frequency range from 400 (Hz) to 800 (Hz). The VLC system uses white LEDs as the source with its outstanding advantages compared to conventional light bulbs such as fluorescent and incandescent lights such as low power consumption, high brightness, and long life. high, easy to control brightness,... although it still has some disadvantages. The detailed model and basic characteristics of a VLC system are also described and discussed in detail in the content of chapter one. Some common applications of VLC technology will be listed in the final section of this chapter.
CHAPTER II – POSITIONING METHODS USING VLC TECHNOLOGY IN INDOOR ENVIRONMENTS
Positioning is one of the major challenges for scientists in the field of mobile robot research. It is the process of determining the exact position and direction of the robot in its working environment. When it comes to positioning, we will certainly think of the very popular GPS global positioning system. This can be a simple and effective choice for mobile devices in general and mobile robots in particular. However, GPS only works well in outdoor environments with errors up to a few meters, while for applications that require high accuracy in indoor environments, GPS is not an optimal solution. . That is one of the reasons why the issue of indoor robot positioning is always researched to come up with the most appropriate and effective solutions.
Up to now, there are many solutions that have been applied to indoor robot positioning such as systems using infrared sensors, lasers, ultrasonic sensors, radio waves, etc. Among them, identification by Radio waves (RFID) have been used as a main solution in robot positioning. Wifi positioning systems have also been researched and proven to be feasible through experiments.
In recent years, along with the rapid development of white LED manufacturing technology, robot positioning based on VLC technology - visible light communication is considered as a promising alternative solution. appointment with many advantages. Compared to other wireless communication technologies such as RF or Wifi, VLC technology has little impact on the user's health, and is also used for lighting purposes. In addition, white LEDs also have very high efficiency, wide coverage and allow increased transmission capacity. Another advantage of LED lights is that they have a very long lifespan, up to 1,000,000 hours of lighting, allowing cost savings when implementing positioning systems via VLC technology.
In this chapter, we will learn about some indoor robot positioning methods using VLC technology that have been proposed and researched so far. These positioning methods have in common that they all apply geometric models to the positioning process. Through detailed discussion of the
With this positioning method, we will analyze the advantages and disadvantages of each method.
2.1. Positioning method based on time of arrival (TOA)
In this method, the LEDs act as a signal source and the PD placed on the robot acts as a signal receiver. Based on the coordinates of the LEDs and the distance from the robot to the LEDs, we can find the robot's location. This distance is the light signal transmission distance calculated from the relationship between transmission time and light speed. To calculate the transmission distance, we only need to measure the arrival time of the light wave at the receiver due to the fixed speed of light c = 3.108 (m/s). However, light is emitted from LEDs in a cone shape, so there exists a set of points at which the received light arrival time is the same. This set of points is the locus of an imaginary circle centered on the perpendicular projection of the LED on the robot's moving floor (see figure 2.1).
Figure 2.1. The imaginary circle contains points that receive the same light transit time.
Thus, for each LED we will receive an imaginary circle equation. If the robot is located between the coverage of many LEDs then we will receive a set of equations of imaginary circles. Solving this system of equations will give us the robot's position. In other words, the robot's position is the intersection of the above circles.
Suppose, the robot's position is ( x, y ) and the given position of the ith transmitter is ( x i , y i ) , i = 1, 2… M ; where M is the number of transmitters. The distance from the ith transmitter to the robot (denoted as d i ) and the light signal transmission time (denoted as t i ) in the absence of interference are calculated as follows:
, i = 1.2…M
However, in reality, due to the influence of obstacles or heterogeneous environments,... it will cause errors in the measurement of light signal transmission time. Assuming the error affecting the above measurement is denoted as n i , then the formula (1*) will be rewritten as follows:
Then, the imaginary circles will not be able to intersect at a single point, but they will create an intersection area. In other words, the system of equations (2*) will have infinitely many solutions. Then, the robot will be in the intersection area of the imaginary circles.
Figure 2.2. Robot position in the intersection area of imaginary circles
The positioning method based on time of arrival (TOA) has a number of outstanding advantages such as: very simple hardware model required for both transmitter and receiver, good response in light wave environment. linear propagation (LOS). However, this method is not widely applied due to some limitations. First, because this is a positioning method based on the time of incoming light waves, to achieve high accuracy, the transmitter and receiver need to be synchronized with each other after every fixed period of time. Second, in small room models (a few square meters in size), the time that light is transmitted from the emitter to the receiver is very short (only a few nanoseconds). This makes measuring light wave propagation time very difficult, requiring high-speed hardware. In addition, this method also requires many emitters to create the intersection area. We need to use at least three different transmitters to provide information to the receiver in this case.
2.2. Positioning method based on time difference of incident light waves (TDOA)
The TDOA positioning method is applied to applications that require high accuracy in positioning. Similar to the TOA method, the TDOA method also determines the robot position through the relationship between light signal transmission distance and transmission time. However, the TDOA method does not calculate the direct light signal transmission distance from the transmitter to the receiver, but instead calculates the difference between the transmission distances from the transmitter to the receiver (see Figure 2.3). . Set
The receiver will measure the arrival times of light waves emitted from at least three different LEDs. Because the speed of light is constant, we can easily calculate the robot's position based on the difference in distance from the transmitter to the receiver.
Figure 2.3. System model of TDOA method
The idea of this method is quite simple: compare the arrival time of the received signals in pairs:
d ij is the distance difference between the transmitter and the receiver; c is
the speed of light; ij is the difference in light signal transmission time; ( x, y ) are coordinates
of robots and
( x i , y i ), ( x j , y j )
are the coordinates of the i and j emitters, respectively .
The above equation has the form of a hyperbola with the two foci being the coordinates of the i and j emitters, respectively . Therefore, the TDOA method is also known as the hyperbolic positioning method (see figure 2.4). The robot's position is calculated by finding the intersection of these hyperbolas.
Figure 2.4. Hyperbolic positioning method
Because they are based on the arrival time of the light signal, both TDOA and TOA methods have similar advantages and limitations. However, in the TDOA method, we only need to synchronize all emitters to send light signals at the same time. The biggest limitation of both of these methods is that the time the light signal reaches the receiver is very short (only a few nanoseconds). For this reason, the hardware must have high processing speed and the ability to calculate in a short time.
2.3. Positioning method based on received signal strength (RSS)
Suppose, we have a wireless transmission channel using visible light as detailed in section 1.2.4. Then, we can locate the robot's position by measuring the power of the optical signal received at the PD. The receiver then calculates its distance from the transmitter (the LEDs) based on the signal transmission model through the visible light channel.
Then, the optical power P r of the visible light transmission channel is received at
We can easily see that the angle of incident light ψ is equal to the illumination angle of light ϕ in figure 2.5. Therefore, formula (3*) is rewritten as follows: