A multi-lamp cooperative control method and system based on ultra-wideband space positioning

Abstract

This invention relates to the field of intelligent lighting control technology, and discloses a multi-lamp collaborative control method and system based on ultra-wideband spatial positioning. The method includes acquiring ultra-wideband ranging data between lamps in a target lighting system; constructing a distance matrix based on the ultra-wideband ranging data, and reconstructing the spatial coordinates of each lamp using a spatial positioning method; acquiring luminous efficacy template parameters, and calculating the target luminous efficacy state function of each lamp based on its spatial coordinates and luminous efficacy template parameters; exchanging state information with neighboring lamps using a distributed consensus collaborative method and iteratively updating the state information until convergence conditions are met; and controlling the luminous efficacy output of the corresponding lamp based on the converged state information of each lamp. This invention enables high-precision multi-lamp linkage control without relying on real-time scheduling by a central controller, significantly improving the intelligence level, deployment efficiency, and user experience of the lighting system.

Description

Technical Field

[0001] This invention relates to the field of intelligent lighting control technology, specifically to a multi-lamp collaborative control method and system based on ultra-wideband spatial positioning. Background Technology

[0002] With the rapid development of smart homes and commercial lighting, users' demands for multi-lamp linkage and ambient lighting effects are increasing. Traditional multi-lamp collaborative control solutions mostly only support independent control of individual lamps or simple grouping, failing to obtain the precise relative positional relationships between lamps. When achieving lighting effects that rely on spatial layout, such as wave-like, gradient, or flowing effects, professionals must use laser rangefinders to locate each lamp individually and manually input their coordinates, a tedious and time-consuming process. Although some solutions attempt to use Bluetooth signal strength for rough positioning, these signals are easily affected by environmental interference, resulting in positioning errors typically ranging from 1 to 3 meters, which cannot meet the needs of spatial lighting effect arrangement requiring centimeter-level accuracy. Summary of the Invention

[0003] To address the problems of insufficient spatial perception capability, inadequate positioning accuracy, and complex deployment of existing lighting fixtures, this invention provides a multi-lamp collaborative control method and system based on ultra-wideband spatial positioning.

[0004] To achieve the above-mentioned objectives, the technical solution adopted by this invention is as follows:

[0005] In a first aspect, this invention proposes a multi-lamp cooperative control method based on ultra-wideband spatial positioning, comprising the following steps:

[0006] Acquire ultrawideband ranging data between luminaires in the target lighting system;

[0007] A distance matrix is ​​constructed based on ultra-wideband ranging data, and the spatial coordinates of each lamp are reconstructed using a spatial positioning method;

[0008] Obtain the light effect template parameters, and calculate the target light effect state function of each lamp based on the spatial coordinates of each lamp and the light effect template parameters;

[0009] A distributed consensus collaborative method is used to exchange state information with neighboring lamps and iteratively update the information until the convergence condition is met.

[0010] The luminous efficacy output of each lamp is controlled based on the converged state information of each lamp.

[0011] Furthermore, a distance matrix is ​​constructed based on the ultra-wideband ranging data, and the spatial coordinates of each luminaire are reconstructed using a spatial positioning method, including:

[0012] After each lamp is powered on, it automatically enters calibration mode, broadcasts its own identifier, and establishes an initial neighbor list.

[0013] The distance between each pair of lights is obtained through an ultra-wideband two-way ranging protocol.

[0014] A distance matrix is ​​constructed based on the distance between each pair of lamps, and the shortest path method is used to estimate the distance for lamp pairs that have not been directly measured.

[0015] The three-dimensional spatial coordinates of each lamp are reconstructed using a spatial positioning method;

[0016] The reconstructed 3D spatial coordinates are distributed to each luminaire, and each luminaire stores its own coordinates and a list of neighbors determined based on a distance threshold.

[0017] Furthermore, the spatial coordinates of each lamp are reconstructed using spatial positioning methods, including:

[0018] Calculate the centralized matrix based on the number of lamps. ,in It is the identity matrix. For the number of light fixtures, It is a vector consisting entirely of 1s;

[0019] Calculate the inner product matrix based on the centered matrix. ,in It is a squared distance matrix;

[0020] Perform eigenvalue decomposition on the inner product matrix and extract the top three largest eigenvalues. and its corresponding eigenvectors ;

[0021] Based on the largest eigenvalue and its corresponding eigenvectors Constructing a three-dimensional coordinate matrix .

[0022] Furthermore, the calculation of the target luminous efficacy state function for each luminaire based on its spatial coordinates and luminous efficacy template parameters also includes:

[0023] Obtain the local pedestrian flow direction vector and pedestrian flow density in the coverage area of ​​each lighting fixture;

[0024] A distributed average consensus method is used to iteratively smooth the local pedestrian flow direction vector of each lamp to generate the main spatial direction field;

[0025] The direction of light effect flow is determined based on the main spatial direction field or the preset guiding direction, and the parameters of the light effect template are adjusted using the density of people.

[0026] The directionally constrained target luminous efficacy function is calculated based on the luminous efficacy flow direction, the adjusted luminous template efficacy parameters, and the luminaire's spatial coordinates.

[0027] Furthermore, obtaining the local pedestrian flow direction vectors for the coverage areas of each lighting fixture includes:

[0028] Detect the movement trajectory of targets within the coverage area using millimeter-wave radar or passive infrared sensors;

[0029] The Kalman filter tracking method is used to obtain the motion trajectory of each target;

[0030] Within a time window, the average direction and speed of all targets are statistically analyzed and normalized to obtain a local unit vector of pedestrian flow direction.

[0031] A distributed average consensus method is used to iteratively smooth the local pedestrian flow direction unit vector of each lamp.

[0032] Furthermore, crowd density is determined in the following ways:

[0033] ;

[0034] in, For lighting fixtures Population density in the covered area The passage of light fixtures per unit time The cumulative number of people in the testing area This is the preset saturation flow threshold;

[0035] First-order low-pass filtering is applied to the pedestrian density to eliminate instantaneous fluctuations.

[0036] Furthermore, the directionally constrained target light effect function is specifically as follows:

[0037] ;

[0038] in, For lighting fixtures In time Direction-constrained target light efficacy function value, The amplitude is determined based on the population density. For lighting fixtures Projected coordinates in the direction of light flow. The flow velocity is determined based on the population density. For wavelength, The baseline brightness is adapted to ambient light.

[0039] Furthermore, when using a distributed consensus coordination method to exchange state information with neighboring lamps and perform iterative updates for each lamp, the process also includes:

[0040] Acquire the intensity of crowd activity and ambient illuminance in the areas covered by each lighting fixture;

[0041] In the iterative process of the distributed consensus coordination method, a response term based on the intensity of crowd activity is introduced, specifically:

[0042]

[0043] in, For the first In the next iteration, the lighting fixtures The control status value, For the first In the next iteration, the lighting fixtures The control status value, For consistent step size, For adjacency weight, For the first In the next iteration, the lighting fixtures The control status value, As a tracking factor, For lighting fixtures In time Direction-constrained target light efficacy function value, For lighting fixtures A collection of neighboring light fixtures;

[0044] The baseline brightness parameter of the target state function is adaptively adjusted using ambient illuminance, specifically as follows:

[0045]

[0046] in, To adapt to baseline brightness, Baseline brightness, This is the ambient light suppression coefficient. For ambient light intensity, For maximum ambient light intensity, This is the density bias. For lighting fixtures Population density in the covered area.

[0047] Furthermore, while controlling the luminous efficacy output of the corresponding lamps based on the converged state information of each lamp, it also includes:

[0048] Monitor the communication status between each lamp and its neighbors. If no status information is received from a neighbor's lamp for several consecutive cycles, mark the neighbor's lamp as offline and update the local neighbor list and adjacency weight.

[0049] When the main light fixture goes offline, the remaining lights are used to automatically elect a new main light fixture according to preset rules, and the notification is broadcast to the entire network.

[0050] The entire network is measured according to a preset cycle, and the spatial coordinates of each lamp are corrected based on the measurement results.

[0051] Secondly, this invention proposes a multi-lamp cooperative control system based on ultra-wideband spatial positioning, which applies the aforementioned multi-lamp cooperative control method based on ultra-wideband spatial positioning, including:

[0052] Multiple light fixtures, each integrating at least:

[0053] Ultra-wideband ranging module is used to acquire ultra-wideband ranging data between lamps in the target lighting system;

[0054] The local decision unit is used to construct a distance matrix based on ultra-wideband ranging data and reconstruct the spatial coordinates of each lamp using a spatial positioning method; calculate the target state function of each lamp based on its spatial coordinates and luminous efficacy template parameters; and exchange state information with neighboring lamps using a distributed consensus collaborative method and perform iterative updates until the convergence condition is met.

[0055] The light effect execution unit is used to control the light effect output of the corresponding lamps based on the converged state information of each lamp.

[0056] It also includes a central coordinator that communicates with multiple luminaires to provide each luminaire with its own luminous efficacy template parameters.

[0057] The present invention has the following beneficial effects:

[0058] This invention automatically constructs a distance matrix and reconstructs spatial coordinates for each lamp through ultra-wideband bilateral bidirectional ranging. Based on the spatial coordinates and luminous efficacy template parameters, it calculates the target state function of each lamp. Then, it exchanges state information with neighboring lamps through a distributed consensus collaborative algorithm and iteratively updates the state until convergence. Finally, it controls the luminous efficacy output of the corresponding lamp based on the converged state, realizing high-precision linkage control of multiple lamps without relying on real-time scheduling by a central controller. This significantly improves the intelligence level, deployment efficiency, and user experience of the lighting system. Attached Figure Description

[0059] Figure 1 This is a schematic diagram of a multi-lamp collaborative control method based on ultra-wideband spatial positioning according to the present invention. Detailed Implementation

[0060] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0061] like Figure 1As shown, an embodiment of the present invention provides a multi-lamp cooperative control method based on ultra-wideband spatial positioning, comprising the following steps S1 to S5:

[0062] S1. Acquire ultra-wideband ranging data between each lamp in the target lighting system;

[0063] In an optional embodiment of the present invention, step S1 involves acquiring ultra-wideband ranging data between the luminaires in a target lighting system composed of multiple luminaires and a central coordinator. The central coordinator communicates with each luminaire via Wi-Fi or Ethernet and is responsible for managing lighting effect templates, task orchestration, and parameter distribution. The central coordinator does not participate in the real-time control process, and its failure does not affect the continuous operation of lighting effect tasks already distributed to the local luminaires. The luminaires exchange ranging and status information through their own ultra-wideband bilateral bidirectional ranging protocols, supplemented by low-power Bluetooth mesh or Wi-Fi technology for lighting effect task distribution and system configuration.

[0064] S2. Construct a distance matrix based on ultra-wideband ranging data, and reconstruct the spatial coordinates of each lamp using a spatial positioning method;

[0065] In an optional embodiment of the present invention, step S2, which involves constructing a distance matrix based on ultra-wideband ranging data and reconstructing the spatial coordinates of each lamp using a spatial positioning method, includes:

[0066] After each lamp is powered on, it automatically enters calibration mode, broadcasts its own identifier, and establishes an initial neighbor list.

[0067] The distance between each pair of lights is obtained through an ultra-wideband two-way ranging protocol.

[0068] A distance matrix is ​​constructed based on the distance between each pair of lamps, and the shortest path method is used to estimate the distance for lamp pairs that have not been directly measured.

[0069] The three-dimensional spatial coordinates of each lamp are reconstructed using a spatial positioning method;

[0070] The reconstructed 3D spatial coordinates are distributed to each luminaire, and each luminaire stores its own coordinates and a list of neighbors determined based on a distance threshold.

[0071] This embodiment addresses the problems of complex deployment and low efficiency caused by manual coordinate measurement and input by employing a fully automatic spatial self-calibration method for lighting fixtures. After power-on, the lighting fixtures automatically enter calibration mode and broadcast identifiers to establish an initial neighbor list. Precise distances between each pair of lighting fixtures are obtained through an ultra-wideband bilateral bidirectional ranging protocol. A complete distance matrix is ​​constructed based on the ranging results (shortest path estimation is used for lighting fixture pairs not directly measured), and the three-dimensional spatial coordinates of each lighting fixture are reconstructed using spatial positioning methods. The master lighting fixture broadcasts and distributes the coordinate matrix to all lighting fixtures. Each lighting fixture stores its own coordinates and a neighbor list determined based on a distance threshold, providing a spatial topology foundation for subsequent distributed collaborative control.

[0072] Specifically, initialization is performed first. After all lights are powered on, they automatically enter calibration mode, broadcast their own identifiers, and establish an initial neighbor list. Then, bilateral, bidirectional ranging is performed. Light A sends a ranging request message to light B, and the sending time is recorded. Light fixture B receives the request and records the time of receipt. Then reply with a response message, which contains and response sending time Light fixture A receives the response and records the moment of reception. ; calculate flight time based on all recorded moments. ; Calculate distance based on flight time , The speed is the speed of light. Next, a distance matrix is ​​constructed; the main light fixture collects all ranging results and constructs... The distance matrix is ​​used, where the diagonal elements are zero. For light pairs that were not directly measured, the shortest path method is used for estimation: if a path exists... ,but Next, spatial positioning is performed, and a centralized matrix is ​​calculated based on the number of lights. ,in It is the identity matrix. For the number of light fixtures, It is a vector of all 1s; calculate the inner product matrix based on the centered matrix. ,in The inner product matrix is ​​the distance squared matrix; perform eigenvalue decomposition on the inner product matrix and extract the top 3 largest eigenvalues. and its corresponding eigenvectors Based on the largest eigenvalue and its corresponding eigenvectors Constructing a three-dimensional coordinate matrix , matrix number The line represents the lighting fixtures coordinates Finally, coordinates are distributed and stored. The main light fixture (set) broadcasts the coordinate matrix to all lights, and each light fixture stores its own coordinates and a list of neighbors (neighbors are defined as those less than a preset threshold). (For lighting fixtures), when using certain default lighting templates, they can be automatically assigned through a pre-built coordinate matrix table.

[0073] S3. Obtain the light effect template parameters, and calculate the target light effect state function of each lamp based on the spatial coordinates of each lamp and the light effect template parameters;

[0074] This embodiment first performs initial template setup. A central coordinator selects a light effect template (e.g., wave, breathing, or radiating) and sets parameters. Task description information is broadcast to all luminaires. Then, the target state function is calculated. The calculation method for the wave-shaped light effect template is as follows: Let the propagation direction unit vector be... Light fixture projection coordinates The target brightness function is: ,in For amplitude, For speed, For wavelength, The base brightness is used. The calculation method for the breathing-type light effect template is as follows: The target brightness function is: The calculation method for the radiative light effect template is as follows: Let the center point be... ,distance The target brightness function is: ,in The attenuation radius is [value].

[0075] In an optional embodiment of the present invention, step S3, which calculates the target luminous efficacy state function of each lamp based on its spatial coordinates and luminous efficacy template parameters, further includes:

[0076] Obtain the local pedestrian flow direction vector and pedestrian flow density in the coverage area of ​​each lighting fixture;

[0077] A distributed average consensus method is used to iteratively smooth the local pedestrian flow direction vector of each lamp to generate the main spatial direction field;

[0078] The direction of light effect flow is determined based on the main spatial direction field or the preset guiding direction, and the parameters of the light effect template are adjusted using the density of people.

[0079] The directionally constrained target luminous efficacy function is calculated based on the luminous efficacy flow direction, the adjusted luminous template efficacy parameters, and the luminaire's spatial coordinates.

[0080] This embodiment addresses the need for crowd guidance and density indication in large indoor public places (stations, shopping malls, etc.) by employing a dynamic guidance lighting effect control method based on crowd detection data. Each luminaire uses sensors to detect the local pedestrian flow direction vector and density within its coverage area. A distributed average consensus algorithm iteratively smooths the local pedestrian flow direction of each luminaire, generating a continuous spatial main direction field. The lighting effect flow direction is determined based on the spatial main direction field or a preset guidance direction, and lighting effect parameters (flow velocity, brightness, amplitude) are adjusted based on pedestrian density. Finally, a direction-constrained target lighting effect function is output. This embodiment aims to utilize ultra-wideband spatial positioning and crowd detection data to achieve dynamic lighting effects with directional guidance and pedestrian density indication functions. The lighting effect changes in real time with the pedestrian flow direction, and the brightness or color saturation maps the local congestion level, providing passengers with intuitive path guidance and safety prompts.

[0081] Specifically, each lamp first acquires real-time data on crowd movement within its coverage area using integrated passive infrared sensors or millimeter-wave radar; then, the sensor signals are preprocessed to extract local pedestrian velocity vectors. The specific steps include:

[0082] (1) Based on the distance, angle and radial velocity of the target point output by the millimeter-wave radar, a lightweight Kalman filter tracking algorithm is executed to detect and track the target and obtain the motion trajectory of each target.

[0083] (2) Calculate the local flow vector based on the motion trajectory of each target, specifically: within the time window Within (e.g., 2 seconds), count the number of lights. The average motion direction and velocity of all detected targets, after normalization, yield the local pedestrian flow direction unit vector. Define lighting fixtures Population density in the covered area ,in The cumulative number of people passing through the detection area of ​​the lamp per unit time (which can be calculated from the number of radar targets or the frequency of infrared triggering). This is the preset saturation flow threshold. To eliminate instantaneous fluctuations, the density value is processed by a first-order low-pass filter. .

[0084] (3) To avoid image fragmentation caused by noise from individual lamps, a distributed average consensus algorithm is used to smooth the orientation field. After several iterations, the detection directions of adjacent lamps tend to be consistent, forming a continuous spatial direction field. Finally, each lamp obtains a smoothed principal direction vector. .

[0085] (4) Two guidance modes can be selected through the central coordinator: pedestrian flow following mode and path guidance mode. In pedestrian flow following mode, the direction of light effect flow is consistent with the actual direction of pedestrian flow, providing passengers with intuitive feedback on the level of congestion ahead. The flow direction is equal to the smoothed main direction. Flow velocity is based on a mapping relationship. ,in Based on the base flow velocity (e.g., 1.0 m / s). This represents velocity gain (e.g., 0.5 m / s). Higher density indicates faster light flow, suggesting the speed of crowd movement or a sense of urgency. Baseline brightness. Adjusted with density Simultaneously, the color temperature can gradually change from warm white (low density, 3000K) to cool white (high density, 5000K) with density, providing visual warnings. In path guidance mode, the light effect flows in a preset guidance direction, unaffected by actual pedestrian flow, and is used to fix evacuation routes or guide transfers. The flow direction uses a preset guidance vector. The configuration is issued by the central coordinator based on the station layout plan. The basic flow direction of the light effect is... However, the brightness of the lamps is still based on local density. Adjustments have been made. Brightness has been increased in high-density areas to alert passengers to congestion ahead.

[0086] (5) The final target state function of the luminaire is extended from the wave-shaped light effect to a directional constraint wave-shaped function. Let the luminaire's projected coordinates be... Define the global flow direction vector as the scalar position along the flow direction. (in the flow-following mode) or in path guidance mode ), Lighting fixture projection coordinates: The target brightness function is ,in Amplitude, related to density. , Setting it to 0.2 makes the dynamic changes in the high-density area more significant; Ambient light adaptive baseline brightness, while simultaneously superimposed with density bias: , Take 30% of the baseline brightness; Wavelength (spatial period), recommended 2~5 meters. Flow velocity is determined by the mapping rules mentioned above. Each luminaire is calculated independently. Afterwards, a smooth transition is still achieved through a consistent collaborative iterative method to ensure continuous light efficiency.

[0087] S4. Use a distributed consensus collaboration method to exchange state information with neighboring lamps and perform iterative updates until the convergence condition is met.

[0088] In an optional embodiment of the present invention, step S4 involves each lamp using a distributed consensus coordination method to exchange state information with neighboring lamps and performing iterative updates. The iterative formula is as follows: Adjacency weight: Consistent step size Set to 0.3, tracking factor Set the threshold to 0.1. The convergence condition is that the maximum value of the state changes of all lamps is less than the threshold value. ( It is recommended to use 0.01).

[0089] In an optional embodiment of the present invention, when step S4 involves exchanging state information with neighboring lamps using a distributed consensus coordination method and performing iterative updates, it further includes:

[0090] Acquire the intensity of crowd activity and ambient illuminance in the areas covered by each lighting fixture;

[0091] In the iterative process of the distributed consensus coordination method, a response term based on the intensity of crowd activity is introduced, specifically:

[0092]

[0093] in, For the first In the next iteration, the lighting fixtures The control status value, For the first In the next iteration, the lighting fixtures The control status value, For consistent step size, For adjacency weight, For the first In the next iteration, the lighting fixtures The control status value, As a tracking factor, For lighting fixtures In time Direction-constrained target light efficacy function value, For lighting fixtures A collection of neighboring light fixtures;

[0094] The baseline brightness parameter of the target state function is adaptively adjusted using ambient illuminance, specifically as follows:

[0095]

[0096] in, To adapt to baseline brightness, Baseline brightness, This is the ambient light suppression coefficient. For ambient light intensity, For maximum ambient light intensity, This is the density bias. For lighting fixtures Population density in the covered area.

[0097] This embodiment addresses the problem that existing collaborative lighting effects cannot adapt to changes in crowd distribution and fluctuations in ambient light. It introduces a dynamic adaptive adjustment mechanism based on distributed consistent collaborative control. Human activity intensity in the coverage area is obtained through human detection sensors integrated into each lamp, and the current illuminance is obtained through an ambient light sensor. During the consistent collaborative iteration process, a response term based on crowd activity intensity is introduced, automatically increasing the brightness in areas where crowds gather. Simultaneously, the baseline brightness parameter of the target state function is adaptively adjusted based on the ambient light illuminance, enabling the lighting effect to dynamically change with the scene.

[0098] Specifically, passive infrared sensors or millimeter-wave radars are integrated into lighting fixtures to detect the intensity of crowd activity in localized areas. (Values ​​range from 0 to 1). The iterative formula is extended to: , among which response factor A value of 0.3 is recommended. An ambient light sensor should also be integrated to measure the current illuminance. Adaptive baseline brightness adjustment The adjustment coefficient 0.5 can be used (can be adjusted manually). This represents the upper limit of the sensor's measurement range.

[0099] S5. Control the luminous efficacy output of the corresponding lamps based on the converged state information of each lamp.

[0100] In an optional embodiment of the present invention, step S5 converts the state value into a PWM duty cycle, drives the LED to output the corresponding light effect, and broadcasts its current state to neighboring lights.

[0101] In an optional embodiment of the present invention, while controlling the luminous efficacy output of the corresponding lamps based on the converged state information of each lamp, the invention also includes:

[0102] Monitor the communication status between each lamp and its neighbors. If no status information is received from a neighbor's lamp for several consecutive cycles, mark the neighbor's lamp as offline and update the local neighbor list and adjacency weight.

[0103] When the main light fixture goes offline, the remaining lights are used to automatically elect a new main light fixture according to preset rules, and the notification is broadcast to the entire network.

[0104] The entire network is measured according to a preset cycle, and the spatial coordinates of each lamp are corrected based on the measurement results.

[0105] This embodiment addresses the issues of communication interruptions, main light fixture failures, and coordinate cumulative drift encountered by distributed lighting systems during long-term operation by employing a distributed fault-tolerant and self-maintaining mechanism. Each light fixture continuously monitors its communication status with neighboring lights. When no status information is received from a neighbor for several consecutive cycles, that neighbor is marked as offline, and the local neighbor list and collaboration weight are updated. When a main light fixture goes offline, the remaining lights automatically elect a new main light fixture according to preset rules and complete a network-wide notification. The system periodically performs network-wide ranging and corrects the spatial coordinates of each light fixture based on the ranging results to eliminate accumulated errors and ensure long-term operational reliability.

[0106] Specifically, if no status information is received from a neighboring light fixture for five consecutive cycles, that neighbor is marked as offline, and the local neighbor list and weights are updated. When the main light fixture goes offline, the remaining lights automatically elect a new main light fixture based on the principle of minimum identifier, and the network-wide notification is completed via broadcast mechanism. Network-wide ranging is performed every 24 hours, and a Kalman filter algorithm is used to smooth coordinate changes to eliminate accumulated errors. The prediction step is... , The update step is... , , .

[0107] Secondly, this invention proposes a multi-lamp cooperative control system based on ultra-wideband spatial positioning, which applies the aforementioned multi-lamp cooperative control method based on ultra-wideband spatial positioning, including:

[0108] Multiple light fixtures, each integrating at least:

[0109] Ultra-wideband ranging module is used to acquire ultra-wideband ranging data between lamps in the target lighting system;

[0110] The local decision unit is used to construct a distance matrix based on ultra-wideband ranging data and reconstruct the spatial coordinates of each lamp using a spatial positioning method; calculate the target state function of each lamp based on its spatial coordinates and luminous efficacy template parameters; and exchange state information with neighboring lamps using a distributed consensus collaborative method and perform iterative updates until the convergence condition is met.

[0111] The light effect execution unit is used to control the light effect output of the corresponding lamps based on the converged state information of each lamp.

[0112] It also includes a central coordinator that communicates with multiple luminaires to provide each luminaire with its own luminous efficacy template parameters.

[0113] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0114] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0115] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0116] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

[0117] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of this invention.

Claims

1. A multi-lamp cooperative control method based on ultra-wideband spatial positioning, characterized in that, Includes the following steps: Acquire ultrawideband ranging data between luminaires in the target lighting system; A distance matrix is ​​constructed based on ultra-wideband ranging data, and the spatial coordinates of each lamp are reconstructed using spatial positioning methods; Obtain the light effect template parameters, and calculate the target light effect state function of each lamp based on the spatial coordinates of each lamp and the light effect template parameters; A distributed consensus collaborative method is used to exchange state information with neighboring lamps and iteratively update the information until the convergence condition is met. The luminous efficacy output of each lamp is controlled based on the converged state information of each lamp.

2. The multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 1, characterized in that, A distance matrix is ​​constructed based on ultra-wideband ranging data, and the spatial coordinates of each lamp are reconstructed using spatial positioning methods, including: After each lamp is powered on, it automatically enters calibration mode, broadcasts its own identifier, and establishes an initial neighbor list. The distance between each pair of lights is obtained through an ultra-wideband two-way ranging protocol. A distance matrix is ​​constructed based on the distance between each pair of lamps, and the shortest path method is used to estimate the distance for lamp pairs that have not been directly measured. The three-dimensional spatial coordinates of each lamp are reconstructed using a spatial positioning method; The reconstructed 3D spatial coordinates are distributed to each luminaire, and each luminaire stores its own coordinates and a list of neighbors determined based on a distance threshold.

3. The multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 1, characterized in that, The spatial coordinates of each lamp were reconstructed using spatial positioning methods, including: Calculate the centralized matrix based on the number of lamps. ,in It is the identity matrix. For the number of light fixtures, It is a vector consisting entirely of 1s; Calculate the inner product matrix based on the centered matrix. ,in It is a squared distance matrix; Perform eigenvalue decomposition on the inner product matrix and extract the top three largest eigenvalues. and its corresponding eigenvectors ; Based on the largest eigenvalue and its corresponding eigenvectors Constructing a three-dimensional coordinate matrix .

4. The multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 1, characterized in that, The calculation of the target luminous efficacy state function for each luminaire, based on its spatial coordinates and luminous efficacy template parameters, also includes: Obtain the local pedestrian flow direction vector and pedestrian flow density in the coverage area of ​​each lighting fixture; A distributed average consensus method is used to iteratively smooth the local pedestrian flow direction vector of each lamp to generate the main spatial direction field; The direction of light effect flow is determined based on the main spatial direction field or the preset guiding direction, and the parameters of the light effect template are adjusted using the density of people. The directionally constrained target luminous efficacy function is calculated based on the luminous efficacy flow direction, the adjusted luminous template efficacy parameters, and the luminaire's spatial coordinates.

5. A multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 4, characterized in that, Obtaining the local pedestrian flow direction vectors for the coverage areas of each lighting fixture includes: Detect the movement trajectory of targets within the coverage area using millimeter-wave radar or passive infrared sensors; The Kalman filter tracking method is used to obtain the motion trajectory of each target; Within a time window, the average direction and speed of all targets are statistically analyzed and normalized to obtain a local unit vector of pedestrian flow direction. A distributed average consensus method is used to iteratively smooth the local pedestrian flow direction unit vector of each lamp.

6. A multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 4, characterized in that, Crowd density is determined in the following ways: ； in, For lighting fixtures Population density in the covered area The passage of light fixtures per unit time The cumulative number of people in the testing area This is the preset saturation flow threshold; First-order low-pass filtering is applied to the pedestrian density to eliminate instantaneous fluctuations.

7. A multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 4, characterized in that, The specific directional constraint target light effect function is as follows: ； in, For lighting fixtures In time Direction-constrained target light efficacy function value, The amplitude is determined based on the population density. For lighting fixtures Projected coordinates in the direction of light flow. The flow velocity is determined based on the population density. For wavelength, The baseline brightness is adapted to ambient light.

8. A multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 1, characterized in that, When using a distributed consensus collaboration method to exchange state information with neighboring luminaires and perform iterative updates, the process also includes: Acquire the intensity of crowd activity and ambient illuminance in the areas covered by each lighting fixture; In the iterative process of the distributed consensus coordination method, a response term based on the intensity of crowd activity is introduced, specifically: in, For the first In the next iteration, the lighting fixtures The control status value, For the first In the next iteration, the lighting fixtures The control status value, For consistent step size, For adjacency weight, For the first In the next iteration, the lighting fixtures The control status value, As a tracking factor, For lighting fixtures In time Direction-constrained target light efficacy function value, For lighting fixtures A collection of neighboring light fixtures; The baseline brightness parameter of the target state function is adaptively adjusted using ambient illuminance, specifically as follows: in, To adapt to baseline brightness, Baseline brightness, This is the ambient light suppression coefficient. For ambient light intensity, For maximum ambient light intensity, This is the density bias. For lighting fixtures Population density in the covered area.

9. A multi-lamp cooperative control method based on ultra-wideband spatial positioning according to claim 1, characterized in that, While controlling the luminous efficacy output of the corresponding lamps based on the converged state information of each lamp, it also includes: Monitor the communication status between each lamp and its neighbors. If no status information is received from a neighbor's lamp for several consecutive cycles, mark the neighbor's lamp as offline and update the local neighbor list and adjacency weight. When the main light fixture goes offline, the remaining lights are used to automatically elect a new main light fixture according to preset rules, and the notification is broadcast to the entire network. The entire network is measured according to a preset cycle, and the spatial coordinates of each lamp are corrected based on the measurement results.

10. A multi-lamp cooperative control system based on ultra-wideband spatial positioning, employing the multi-lamp cooperative control method based on ultra-wideband spatial positioning as described in any one of claims 1 to 9, characterized in that, include: Multiple light fixtures, each integrating at least: Ultra-wideband ranging module is used to acquire ultra-wideband ranging data between lamps in the target lighting system; The local decision unit is used to construct a distance matrix based on ultra-wideband ranging data and reconstruct the spatial coordinates of each lamp using a spatial positioning method; calculate the target state function of each lamp based on its spatial coordinates and luminous efficacy template parameters; and exchange state information with neighboring lamps using a distributed consensus collaborative method and perform iterative updates until the convergence condition is met. The light effect execution unit is used to control the light effect output of the corresponding lamps based on the converged state information of each lamp. It also includes a central coordinator that communicates with multiple luminaires to provide each luminaire with its own luminous efficacy template parameters.

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