A visible light positioning system and method based on occlusion detection

Abstract

The application provides a visible light positioning system and method based on occlusion detection. The application calculates the normalized signal intensity change rate of each LED lamp in the current period; a world coordinate system is constructed in combination with the right-hand rule; the robot selects the corresponding occlusion threshold model to calculate the threshold of each LED lamp in the current period according to the discrimination result of the three-axis movement direction; the normalized signal intensity change rate of each LED lamp in the current period is combined with the threshold of each LED lamp in the current period to make a judgment, so that the occlusion state of each LED lamp in the current period is obtained; the robot vehicle selects the occlusion state of each LED lamp in the current period to obtain a plurality of un-occluded LED lamps in the current period, and the indoor positioning method based on the LED lamp signal intensity is used for positioning to obtain the position of the robot in the current period. Even in the case of serious light reflection effect or very short occlusion time, the application can still effectively eliminate the occluded light signal.

Description

Technical Field

[0001] This invention belongs to the field of indoor navigation and positioning, and particularly relates to a visible light positioning system and method based on occlusion detection. Background Technology

[0002] Visible light positioning technology is a novel high-precision indoor positioning technology that can provide centimeter-level or decimeter-level navigation and positioning services in indoor areas, and has advantages such as low cost, environmental friendliness, and low power consumption. In visible light positioning schemes, a common method is to use a photodiode (PD) to measure the intensity of the light signal emitted by an LED light, and then calculate the distance using a Lambertian model to determine the PD's position. This method requires only several modulated LED lights and one PD to complete the positioning, resulting in low cost and high accuracy. However, because light signals cannot penetrate opaque objects, the received signal strength (RSS) will significantly decrease if the direct line of sight is blocked.

[0003] To eliminate obstructed visible light observations, a straightforward approach is to determine if the observation is close to zero. However, in positioning schemes using frequency division multiple access (FDMA) to distinguish LED lights, the RSS (Resonance Segmentation) may not be close to zero even when obstructed in two situations: first, there is a significant light reflection effect in the environment, meaning reflected signals may be received even if direct light is not received; second, since visible light typically yields RSS data at different frequencies through Fourier transform, if the obstruction time is short, less than the Fourier transform window size, the RSS may not be close to zero. However, obstruction signals in both of these situations severely impact positioning accuracy. Therefore, a method for obstruction detection is needed to effectively eliminate obstructed visible light RSS data in dynamic and complex environments. Summary of the Invention

[0004] In order to effectively remove obstructed visible light RSS data and improve the positioning accuracy of indoor carriers, this invention proposes a visible light positioning system and method based on obstruction detection.

[0005] The technical solution of the present invention is a visible light positioning system based on occlusion detection, comprising:

[0006] The first LED light, the second LED light, ..., the Lth LED light, a photodiode receiver, and a robot car;

[0007] The first LED light, the second LED light, ..., the Lth LED light are installed on the indoor ceiling;

[0008] The photodiode receiver is placed on the robot vehicle;

[0009] The photodiode receiver is wired to the robot vehicle;

[0010] The robot vehicle needs to be able to provide the attitude angle of the photodiode receiver and determine the direction of movement;

[0011] The first Each LED light is wirelessly connected to a photodiode receiver. ∈[1,L];

[0012] The first The signal frequency of each LED light is F l ;

[0013] The technical solution of this invention is a visible light localization method based on occlusion detection, comprising:

[0014] Step 1: The photodiode receiver receives the mixed light signals from the previous and current LED periods and obtains the intensity of the mixed light signals from the previous and current periods through photoelectric conversion. The intensity of the mixed light signals from the previous and current periods is then transmitted to the robot vehicle. The robot vehicle uses FFT to transform the intensity of the mixed light signals from the previous and current periods to obtain the spectrum of the mixed light signals from the previous and current periods. It then searches sequentially on the spectrum of the mixed light signals from the previous period based on the signal frequency of each LED to obtain the signal intensity of each LED in the previous period. Similarly, it searches sequentially on the spectrum of the mixed light signals from the current period based on the signal frequency of each LED to obtain the signal intensity of each LED in the current period. Combining the signal intensities of each LED in the previous period, the current period, and the time interval between two adjacent periods, the normalized rate of change of the signal intensity of each LED in the current period is calculated.

[0015] Step 2: Select any corner of the room as point O, take the two sides of the ground where the corner is located as the X-axis and Y-axis, and take the column where the corner is located as the Z-axis. The X-axis, Y-axis and Z-axis satisfy the right-hand rule to construct a world coordinate system.

[0016] Step 3: Based on the discrimination results of the three-axis motion direction, the robot selects the corresponding occlusion threshold model to calculate the threshold of each LED light in the current time period;

[0017] Step 4: Combine the normalized signal strength change rate of each LED in the current time period with the threshold of each LED in the current time period to determine the occlusion status of each LED in the current time period.

[0018] Step 5: The robot selects the unobstructed LEDs based on their occlusion status during the current time period. The signal strength of the unobstructed LEDs is then used to determine the robot's position during the current time period using an indoor positioning method based on LED signal strength.

[0019] Preferably, the previous time period and the current time period mentioned in step 1 are both composed of multiple moments;

[0020] The normalized signal strength change rate of each LED in the current time period, as described in step 1, is calculated as follows:

[0021]

[0022] ∈[1,L], i ∈[1, I]

[0023] in, Indicates the first i +1 period Normalized rate of change of signal strength of each LED express i +1 period The received signal strength of each LED light Indicates the first i Time period The received signal strength of each LED light This represents the time difference between two adjacent time periods. Indicates the first The received signal strength of the nearest unobstructed LED light in the current time period is initialized to the received signal strength of the initial time period, and will change during subsequent positioning processes. i +1 indicates the current time period, the [number]th [period]. i The time period represents the previous time period, L represents the number of LED lights, and I represents the number of time periods;

[0024] Preferably, step 3 involves selecting the corresponding occlusion threshold model to calculate the threshold for each LED light in the current time period. The specific calculation process is as follows:

[0025] If the angle between the robot's direction of motion and the xoy plane is less than the angle threshold, the specific calculation is as follows:

[0026]

[0027] in, For the first i +1 period Threshold for each LED light and These represent the maximum values ​​of the robot's angular velocity and its speed, respectively. Indicates the first i +1 period The distance vector from each LED to the photodiode receiver. For the first i The unit normal vector on the plane where the photodiode receiver is located during the +1 time period. , , The first i The x and y components of the unit normal vector on the plane where the photodiode receiver is located during the +1 time period. for i +1 period The coordinates of the position of each LED light projected onto the xoy plane. for i The coordinates of the photodiode's position projected onto the xoy plane during the +1 time period. For the first The Lambertian coefficient of each LED light;

[0028] If the angle between the robot's direction of motion and the xoy plane is less than the angle threshold, and the angle between the plane containing the photosensitive area of ​​the photodiode and the xoy plane is always less than the angle threshold, then the specific calculation is as follows:

[0029]

[0030] If the robot can move in any direction, the specific calculation is as follows:

[0031]

[0032] in, for i +1 period The z-component of the plane containing each LED is a positive normal vector;

[0033] Preferably, step 4 involves combining the normalized signal strength change rate of each LED in the current time period with the threshold value of each LED in the current time period for judgment, as follows:

[0034] if If the result is 0, it indicates that occlusion has started and the detection result is occlusion.

[0035] if If the occlusion is removed, the detection result is non-occlusion;

[0036] if Then determine the current state: if it is in the process of occlusion, then it is determined to be occluded; if it is in the process of non-occlusion, then it is determined to be non-occluded, and the first... The received signal strength of the nearest unobstructed LED light in the current time period. Set as number i RSS value for +1 time period.

[0037] The advantage of this invention is that it can effectively eliminate blocked light signals even when the light reflection effect is severe or the blocking time is very short. Attached Figure Description

[0038] Figure 1 : Flowchart of the method according to an embodiment of the present invention. Detailed Implementation

[0039] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] In specific implementation, the method proposed in the technical solution of this invention can be automatically executed by those skilled in the art using computer software technology. System devices for implementing the method, such as computer-readable storage media storing the corresponding computer program of the technical solution of this invention and computer equipment including the computer program running the corresponding computer program, should also be within the protection scope of this invention.

[0041] The following is combined with Figure 1 The technical solution described in this invention is a visible light positioning system and method based on occlusion detection.

[0042] The technical solution of the system in this embodiment of the invention is a visible light positioning system based on occlusion detection, comprising:

[0043] The first LED light, the second LED light, ..., the Lth LED light, a photodiode receiver, and a robot car;

[0044] The first LED light, the second LED light, ..., the Lth LED light are installed on the indoor ceiling;

[0045] The photodiode receiver is placed on the robot vehicle;

[0046] The photodiode receiver is wired to the robot vehicle;

[0047] The robot vehicle needs to be able to provide the attitude angle of the photodiode receiver and determine the direction of movement;

[0048] No. Each LED light is wirelessly connected to a photodiode receiver. ∈[1, L], L=5;

[0049] The first The signal frequency of each LED light is F l ;

[0050] The model of the first LED, the second LED, ..., the Lth LED is CREE XM-L;

[0051] The photodiode receiver is model OPT101;

[0052] The model of the robot vehicle is Scout mini;

[0053] The technical solution of the method in this embodiment of the invention is a visible light positioning method based on occlusion detection, such as... Figure 1 As shown, the specific steps are as follows:

[0054] Step 1: The photodiode receiver receives the mixed light signals from the previous and current LED periods and obtains the intensity of the mixed light signals from the previous and current periods through photoelectric conversion. The intensity of the mixed light signals from the previous and current periods is then transmitted to the robot vehicle. The robot vehicle uses FFT to transform the intensity of the mixed light signals from the previous and current periods to obtain the spectrum of the mixed light signals from the previous and current periods. It then searches sequentially on the spectrum of the mixed light signals from the previous period based on the signal frequency of each LED to obtain the signal intensity of each LED in the previous period. Similarly, it searches sequentially on the spectrum of the mixed light signals from the current period based on the signal frequency of each LED to obtain the signal intensity of each LED in the current period. Combining the signal intensities of each LED in the previous period, the current period, and the time interval between two adjacent periods, the normalized rate of change of the signal intensity of each LED in the current period is calculated.

[0055] The previous time period and the current time period mentioned in step 1 are both composed of multiple moments.

[0056] The normalized signal strength change rate of each LED in the current time period, as described in step 1, is calculated as follows:

[0057]

[0058] ∈[1,L], i ∈[1, I]

[0059] in, Indicates the first i +1 period Normalized rate of change of signal strength of each LED express i +1 period The received signal strength of each LED light Indicates the first i Time period The received signal strength of each LED light This represents the time difference between two adjacent time periods. Indicates the first The received signal strength of the nearest unobstructed LED light in the current time period is initialized to the received signal strength of the initial time period, and will change during subsequent positioning processes. i +1 indicates the current time period, the [number]th [period]. i The time period represents the previous time period, L=5 represents the number of LED lights, and I=100 represents the number of time periods;

[0060] Step 2: Select any corner of the room as point O, take the two sides of the ground where the corner is located as the X-axis and Y-axis, and take the column where the corner is located as the Z-axis. The X-axis, Y-axis and Z-axis satisfy the right-hand rule to construct a world coordinate system.

[0061] Step 3: Based on the discrimination results of the three-axis motion direction, the robot selects the corresponding occlusion threshold model to calculate the threshold of each LED light in the current time period;

[0062] Step 3 involves selecting the corresponding occlusion threshold model to calculate the threshold for each LED light in the current time period. The specific calculation process is as follows:

[0063] If the angle between the robot's direction of motion and the xoy plane is less than the angle threshold, the specific calculation is as follows:

[0064]

[0065] in, For the first i +1 period Threshold for each LED light and These represent the maximum values ​​of the robot's angular velocity and its speed, respectively. Indicates the first i +1 period The distance vector from each LED to the photodiode receiver. For the first i The unit normal vector on the plane where the photodiode receiver is located during the +1 time period. , , The first iThe x and y components of the unit normal vector on the plane where the photodiode receiver is located during the +1 time period. for i +1 period The coordinates of the position of each LED light projected onto the xoy plane. for i The coordinates of the photodiode's position projected onto the xoy plane during the +1 time period. For the first The Lambertian coefficient of each LED light;

[0066] If the angle between the robot's direction of motion and the xoy plane is less than the angle threshold, and the angle between the plane containing the photosensitive area of ​​the photodiode and the xoy plane is always less than the angle threshold, then the specific calculation is as follows:

[0067]

[0068] If the robot can move in any direction, the specific calculation is as follows:

[0069]

[0070] in, for i +1 period The z-component of the plane containing each LED is a positive normal vector, and its value is... ;

[0071] Step 4: Combine the normalized signal strength change rate of each LED in the current time period with the threshold of each LED in the current time period to determine the occlusion status of each LED in the current time period.

[0072] Step 4 involves combining the normalized signal strength change rate of each LED in the current time period with the threshold value of each LED in the current time period for judgment, as detailed below:

[0073] if If the result is 0, it indicates that occlusion has started and the detection result is occlusion.

[0074] if If the occlusion is removed, the detection result is non-occlusion;

[0075] if Then determine the current state: if it is in the process of occlusion, then it is determined to be occluded; if it is in the process of non-occlusion, then it is determined to be non-occluded, and the first... The received signal strength of the nearest unobstructed LED light in the current time period. Set as number i RSS value for +1 time period.

[0076] Step 5: The robot selects the unobstructed LEDs based on their occlusion status during the current time period. The signal strength of the unobstructed LEDs is then used to determine the robot's position during the current time period using an indoor positioning method based on LED signal strength.

[0077] It should be understood that any parts not described in detail in this specification belong to the prior art.

[0078] It should be understood that the above description of the preferred embodiments is quite detailed, but it should not be considered as a limitation on the scope of protection of this invention. Those skilled in the art, under the guidance of this invention, can make substitutions or modifications without departing from the scope of protection of the claims of this invention, and all such substitutions or modifications fall within the scope of protection of this invention. The scope of protection of this invention should be determined by the appended claims.

Claims

1. A visible light positioning system based on occlusion detection, characterized in that, include: The first LED light, the second LED light, ..., the Lth LED light, a photodiode receiver, and a robot car; The first LED light, the second LED light, ..., the Lth LED light are installed on the indoor ceiling; The photodiode receiver is placed on the robot vehicle; The photodiode receiver is wired to the robot vehicle; The robot vehicle needs to be able to provide the attitude angle of the photodiode receiver and determine the direction of movement; No. Each LED light is wirelessly connected to a photodiode receiver. ∈[1,L]; The first The signal frequency of each LED light is F l ; The robot calculates the normalized rate of change of signal intensity for each LED light in the current time period; constructs a world coordinate system using the right-hand rule; and selects the corresponding occlusion threshold model to calculate the threshold for each LED light in the current time period based on the discrimination results of the three-axis motion direction. The occlusion status of each LED in the current time period is obtained by combining the normalized signal strength change rate of each LED in the current time period with the threshold of each LED in the current time period. The robot vehicle filters out the unobstructed LEDs based on their current occlusion status, and then uses an indoor positioning method based on LED signal strength to determine the robot's current position.

2. A visible light positioning method based on occlusion detection applied to the visible light positioning system based on occlusion detection as described in claim 1, characterized in that: Step 1: The photodiode receiver receives the mixed light signal of the LED lights from the previous time period and the current time period, and obtains the intensity of the mixed light signal of the LED lights from the previous time period and the current time period through photoelectric conversion. The intensity of the mixed light signal of the LED lights from the previous time period and the current time period is then transmitted to the robot vehicle. The robot vehicle obtains the signal strength of each LED light in the previous time period and the signal strength of each LED light in the current time period through a spectrum search method. By combining the signal strength of each LED in the previous time period, the signal strength of each LED in the current time period, and the time interval between two adjacent time periods, the normalized rate of change of signal strength of each LED in the current time period is obtained. Step 2: Select any corner of the room as point O, take the two sides of the ground where the corner is located as the X-axis and Y-axis, and take the column where the corner is located as the Z-axis. The X-axis, Y-axis and Z-axis satisfy the right-hand rule to construct a world coordinate system. Step 3: Based on the discrimination results of the three-axis motion direction, the robot selects the corresponding occlusion threshold model to calculate the threshold of each LED light in the current time period; Step 4: Combine the normalized signal strength change rate of each LED in the current time period with the threshold of each LED in the current time period to determine the occlusion status of each LED in the current time period. Step 5: The robot selects the unobstructed LEDs based on their occlusion status during the current time period. The signal strength of the unobstructed LEDs is then used to determine the robot's position during the current time period using an indoor positioning method based on LED signal strength.

3. The visible light positioning method based on occlusion detection according to claim 2, characterized in that: In step 1, the robot vehicle obtains the signal strength of each LED in the previous time period and the signal strength of each LED in the current time period using a spectrum search method, as detailed below: The robot vehicle obtains the LED light mixed light signal spectrum of the previous and current time periods by performing FFT transformation on the LED light mixed light signal intensity of the previous time period and the current time period respectively. It then searches sequentially on the LED light mixed light signal spectrum of the previous time period according to the signal frequency of each LED light to obtain the signal intensity of each LED light in the previous time period. Similarly, it searches sequentially on the LED light mixed light signal spectrum of the current time period according to the signal frequency of each LED light to obtain the signal intensity of each LED light in the current time period.

4. The visible light positioning method based on occlusion detection according to claim 3, characterized in that: The previous time period and the current time period mentioned in step 1 are both composed of multiple moments. The normalized signal strength change rate of each LED in the current time period, as described in step 1, is calculated as follows: ∈[1,L], i ∈[1,I] in, Indicates the first i +1 period Normalized rate of change of signal strength of each LED express i +1 period The received signal strength of each LED light, Indicates the first i Time period The received signal strength of each LED light, This represents the time difference between two adjacent time periods. Indicates the first The received signal strength of the nearest unobstructed LED light in the current time period is initialized to the received signal strength of the initial time period, and will change during subsequent positioning processes. i +1 indicates the current time period, the [number]th [period]. i The time period refers to the previous time period, L represents the number of LED lights, and I represents the number of time periods.

5. The visible light positioning method based on occlusion detection according to claim 4, characterized in that: Step 3 involves selecting the corresponding occlusion threshold model to calculate the threshold for each LED light in the current time period. The specific calculation process is as follows: If the angle between the robot's direction of motion and the xoy plane is less than the angle threshold, the specific calculation is as follows: in, For the first i +1 period Threshold for each LED light and These represent the maximum values ​​of the robot's angular velocity and its speed, respectively. Indicates the first i +1 period The distance vector from each LED to the photodiode receiver. For the first i The unit normal vector on the plane where the photodiode receiver is located during the +1 time period. , , The first i The x and y components of the unit normal vector on the plane where the photodiode receiver is located during the +1 time period. for i +1 period The coordinates of the position of each LED light projected onto the xoy plane. for i The coordinates of the photodiode's position projected onto the xoy plane during the +1 time period. For the first The Lambertian coefficient of each LED light; If the robot can move in any direction, the specific calculation is as follows: in, for i +1 period The z-component of the plane containing each LED is a positive normal vector.

6. The visible light positioning method based on occlusion detection according to claim 5, characterized in that: Step 4 involves combining the normalized signal strength change rate of each LED in the current time period with the threshold value of each LED in the current time period for judgment, as detailed below: if If the result is 0, it indicates that occlusion has started and the detection result is occlusion. if If the occlusion is removed, the detection result is non-occlusion; if If the current state is determined, then if it is in the process of occlusion, then it is determined to be occlusion; If it is in an unoccluded process, it is judged as unoccluded, and the first... The received signal strength of the nearest unobstructed LED light in the current time period. Set as number i RSS value for +1 time period.

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