Multi-objective optimization coordinated control method for shelf lighting and related device thereof

Abstract

The application discloses a multi-target optimization cooperative control method for shelf lighting and a related device thereof, and belongs to the technical field of lighting control, and specifically comprises the following steps: a multi-wavelength grid detection pattern adaptive to the spacing between shelf layers is projected onto the surface of a shelf, the reflected light signals are collected, and the spatial distribution and spectral composition data are synchronously recorded; the grid node coordinates are extracted by processing the spatial data, the offset vector of the relative reference position is calculated, the wavelength components are analyzed by decomposing the spectral data, and the difference between the light intensity of each wavelength and the reference value is calculated; the light beam direction adjustment instruction is generated based on the direction and amplitude of the offset vector, the spectral compensation instruction is generated according to the light intensity difference, and the basic lighting system adjusts the lighting parameters accordingly; and the application realizes the multi-parameter cooperative optimization of the shelf lighting, and effectively improves the illumination quality in a complex environment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of lighting control, in particular to a multi-objective optimization collaborative control method for shelf lighting and a related device thereof. BACKGROUND

[0002] Shelf lighting plays an important role in large warehouse-style shopping malls and logistics and warehousing centers, not only affecting the display effect of goods, but also being closely related to the efficiency of warehousing operations and energy consumption. With the development of modern commercial space towards high-rise and densification, the shelf lighting system is facing multiple demands such as lighting uniformity, energy consumption control and visual comfort. The traditional shelf lighting scheme mainly relies on fixedly installed lamps, and realizes basic lighting function through zoning or timing dimming, which is difficult to adapt to complex and variable actual lighting environment.

[0003] In the prior art, in order to solve the problem of optimization control of shelf lighting, some lighting control schemes based on sensor feedback have appeared. For example, an illuminance sensor network is arranged to monitor the illuminance level of each area of the shelf, and the brightness of the lamp is adjusted by feedback in combination with a preset threshold; or an image sensor is used to collect the image of the shelf, and the shadow area is identified through image processing technology, and the local lighting is adjusted accordingly. To some extent, such schemes improve the pertinence of lighting control and realize dynamic adjustment of basic lighting parameters.

[0004] However, due to the three-dimensional complexity of the shelf structure and the randomness of the goods display, a single type of sensor is difficult to fully capture the spatial heterogeneity of the light distribution, and the control method based on threshold or simple image processing has limited processing capacity for light coupling effect, which is easy to cause local over-illumination or under-illumination phenomenon; the existing scheme relies on direct feedback control, lacks in-depth modeling of the light propagation law, and is difficult to realize multi-objective collaborative optimization. Therefore, a shelf lighting control method is needed which can more accurately perceive the light distribution characteristics, more effectively decouple the light interference, and realize multi-parameter collaborative optimization. SUMMARY

[0005] The purpose of the present application is to provide a multi-objective optimization collaborative control method for shelf lighting and a related device thereof, which solves the following technical problems:

[0006] The existing shelf lighting control method is difficult to effectively perceive the light distribution heterogeneity in a complex space and lacks in-depth modeling of the coupling effect of multiple parameters, which leads to local light imbalance when dealing with high shelf lighting scenes, and cannot realize multi-objective collaborative optimization.

[0007] The purpose of the present application can be achieved by the following technical solutions:

[0008] The multi-objective optimization collaborative control method for shelf lighting comprises the following steps:

[0009] S1, projecting a grid detection pattern containing multiple wavelength components to the surface of the shelf, the node spacing of the grid detection pattern is in proportional relationship with the shelf layer spacing;

[0010] S2, collecting the reflected light signal of the grid detection pattern on the surface of the shelf, and synchronously recording the spatial distribution data and the spectral composition data of the reflected light signal;

[0011] S3, processing the spatial distribution data, extracting the position coordinates of each node in the grid detection pattern, and calculating the offset vector of each node relative to the reference position;

[0012] S4, processing the spectral composition data, decomposing the wavelength components of the reflected light signal, and calculating the difference between the light intensity value of each wavelength component and the reference light intensity value;

[0013] S5, generating the light beam direction adjustment instruction of the basic lighting system according to the direction and amplitude of the offset vector, and generating the spectral compensation instruction of the basic lighting system according to the light intensity difference;

[0014] S6, the basic lighting system adjusts the lighting parameters according to the light beam direction adjustment instruction and the spectral compensation instruction.

[0015] As a further scheme of the application: in S1, the process of projecting a grid detection pattern containing multiple wavelength components to the surface of the shelf is:

[0016] Three coherent lights of red, green and blue wavelengths are generated, and the three coherent lights are input into a non-common-path interference structure, a multi-wavelength interference field is generated at the output end of the interference structure, and dynamic phase modulation is applied to the multi-wavelength interference field, the frequency of the dynamic phase modulation is consistent with the driving frequency of the acousto-optic modulator corresponding to each wavelength;

[0017] The phase-modulated interference field is converted into a grid-like light intensity distribution by a diffractive optical element, the grid-like light intensity distribution is projected to the surface of the shelf to form a grid detection pattern, and the phase delay of the acousto-optic modulator is changed synchronously during the projection process, the change range of the phase delay is zero to 2π, and the grid detection pattern light intensity distribution corresponding to each phase delay is recorded.

[0018] As a further scheme of the application: in S2, the specific process of collecting the reflected light signal is:

[0019] A monochromatic area array detector is used to collect the interference fringe images of the surface of the shelf, and during the projection of red, green and blue wavelengths in turn, interference fringe image sequences corresponding to the wavelengths are collected respectively, each interference fringe image sequence of a wavelength contains four interference patterns with a phase difference of π / 2, four-step phase shift calculation is performed on each interference fringe image sequence of a wavelength to obtain the phase principal value distribution of the wavelength;

[0020] The phase unwrapping operation is performed on the phase principal value distribution to obtain continuous phase distribution of the wavelength, and the continuous phase distribution of the three wavelengths is integrated into a full-color phase distribution map, which contains spatial distribution data and spectral composition data.

[0021] As a further scheme of the present application, in the S3, the specific process for processing the spatial distribution data is:

[0022] The complex amplitude information of each grid node is extracted from the full-color phase distribution map, the complex amplitude information contains amplitude component and phase component, the coherence matrix of the complex amplitudes of adjacent grid nodes is calculated, the polarization state distribution is obtained by eigenvalue decomposition of the coherence matrix, the mapping relationship between the polarization state distribution and the surface normal vector is established, the surface normal field is reconstructed according to the mapping relationship, the surface height distribution is obtained by the surface normal field through the curvilinear integral, and the elevation difference field between the surface height distribution and the reference height distribution is calculated;

[0023] The elevation difference field is decomposed by spherical harmonic function, the first sixteen spherical harmonic coefficients are extracted, and the three-dimensional displacement vector of each grid node is calculated according to the spherical harmonic coefficients, the direction of the three-dimensional displacement vector is determined by the first-order spherical harmonic coefficient, and the amplitude of the three-dimensional displacement vector is determined by the second-order spherical harmonic coefficient.

[0024] As a further scheme of the present application, in the S4, the specific process for processing the spectral composition data is:

[0025] The Stokes parameters of each wavelength are separated from the full-color phase distribution map, the Stokes parameters contain four polarization components, the Mueller matrix representation of the Stokes parameters of each wavelength is calculated, the depolarization coefficient distribution is obtained by singular value decomposition of the Mueller matrix, the corresponding relationship between the depolarization coefficient and the surface roughness is established, and the bidirectional reflectance distribution function of the surface is calculated according to the corresponding relationship;

[0026] The bidirectional reflectance distribution function is compared with the reference bidirectional reflectance distribution function to obtain the reflectivity change of each wavelength, the light intensity difference of each wavelength is calculated according to the reflectivity change, the light intensity difference is the product of the reflectivity change and the reference light intensity value, and the numerical value and sign of the light intensity difference of each wavelength are recorded.

[0027] As a further scheme of the present application, in the S5, the specific process for generating the light beam direction adjustment instruction of the basic lighting system according to the direction and amplitude of the displacement vector is:

[0028] The mapping relationship between the three-dimensional displacement vector and the illumination light beam direction is established, the mapping relationship is based on the orthogonal decomposition of the spherical harmonic function coefficient, the three-dimensional displacement vector is projected into the azimuth angle dimension and the zenith angle dimension in the spherical coordinate system, the difference between the projection component of the azimuth angle dimension and the reference azimuth angle is calculated to obtain the horizontal deflection adjustment amount, and the difference between the projection component of the zenith angle dimension and the reference zenith angle is calculated to obtain the pitch adjustment amount.

[0029] The beam divergence angle adjustment amount is calculated according to the amplitude component of the spherical harmonic function coefficient, the horizontal deflection adjustment amount, the pitch adjustment amount and the beam divergence angle adjustment amount are encoded into the beam direction adjustment instruction, and the beam direction adjustment instruction contains the numerical value and the sign of each adjustment amount.

[0030] As a further scheme of the present application: in S5, the specific process of generating the spectral compensation instruction of the basic lighting system according to the light intensity difference value is:

[0031] The corresponding relationship between the light intensity difference value and the spectral power distribution is established, the corresponding relationship is based on the eigenvector analysis of the Mueller matrix, the light intensity difference value of each wavelength is input into the spectral reconstruction algorithm, the spectral reconstruction algorithm outputs the target spectral power distribution, the relative difference between the target spectral power distribution and the reference spectral power distribution is calculated, the intensity adjustment coefficient of each wavelength component is calculated according to the relative difference, and the intensity adjustment coefficient is proportional to the singular value of the Mueller matrix;

[0032] The intensity adjustment coefficient is converted into the driving current adjustment amount, the driving current adjustment amount is linearly related to the intensity adjustment coefficient, and the driving current adjustment amount corresponding to each wavelength is encoded into the spectral compensation instruction.

[0033] As a further scheme of the present application: in S6, the specific process of adjusting the lighting parameters of the basic lighting system according to the beam direction adjustment instruction and the spectral compensation instruction is:

[0034] The horizontal deflection adjustment amount, the pitch adjustment amount and the beam divergence angle adjustment amount in the beam direction adjustment instruction are analyzed, the horizontal deflection mechanism of the lighting unit is adjusted according to the horizontal deflection adjustment amount, the rotation angle of the horizontal deflection mechanism is proportional to the horizontal deflection adjustment amount, the pitch adjustment mechanism of the lighting unit is adjusted according to the pitch adjustment amount, the rotation angle of the pitch adjustment mechanism is proportional to the pitch adjustment amount, and the optical focusing system of the lighting unit is adjusted according to the beam divergence angle adjustment amount, and the lens spacing change amount of the optical focusing system is proportional to the beam divergence angle adjustment amount

[0035] The wavelength driving current adjustment amount in the spectral compensation instruction is analyzed, the driving current of each wavelength light emitting element of the lighting unit is adjusted according to the driving current adjustment amount, the change amount of the driving current is proportional to the driving current adjustment amount, and each adjustment operation is executed in the order of direction adjustment first and spectral adjustment second.

[0036] As a further scheme of the present application: the grid detection pattern containing multiple wavelength components is projected onto the surface of the goods shelf based on an auxiliary detection unit, the light emitting direction of the light source assembly of the auxiliary detection unit is consistent with the light emitting direction of the basic lighting system, and the optical sensor of the auxiliary detection unit is data-connected with the control unit of the basic lighting system.

[0037] In the detection stage, the light source assembly of the auxiliary detection unit projects a grid detection pattern, and the optical sensor collects the reflected light signal; in the lighting adjustment stage, the control unit of the basic lighting system generates lighting parameter adjustment instructions according to the processing result of the reflected light signal.

[0038] The application also includes a multi-objective optimization collaborative control device for shelf lighting, which is used to implement the multi-objective optimization collaborative control method for shelf lighting described above, and includes:

[0039] A light source assembly is used to project a grid detection pattern containing multiple wavelength components to the shelf surface, and the node spacing of the grid detection pattern is in a proportional relationship with the shelf layer spacing.

[0040] An optical sensor is used to collect the reflected light signal of the grid detection pattern on the shelf surface, and to synchronously record the spatial distribution data and the spectral composition data of the reflected light signal.

[0041] A signal processing unit is used to process the spatial distribution data, extract the position coordinates of each node in the grid detection pattern, and calculate the offset vector of each node relative to the reference position; and to process the spectral composition data, decompose the wavelength components of the reflected light signal, and calculate the difference between the light intensity value of each wavelength component and the reference light intensity value.

[0042] A control unit is used to generate the light beam direction adjustment instruction of the basic lighting system according to the direction and amplitude of the offset vector, and to generate the spectral compensation instruction of the basic lighting system according to the light intensity difference.

[0043] A basic lighting system is used to adjust the lighting parameters according to the light beam direction adjustment instruction and the spectral compensation instruction.

[0044] The beneficial effects of the application are:

[0045] The application projects a special multi-wavelength grid pattern to the shelf surface, accurately captures the light distribution of the shelf surface using the principle of optical interference, and effectively solves the problem that the traditional method cannot accurately perceive the complex spatial light distribution. By analyzing the interference fringes formed by the reflected light, the system can simultaneously obtain spatial position information and spectral characteristics, and establish an accurate correspondence between surface deformation and lighting parameters. Based on the calculation of three-dimensional offset vectors and spectral differences, the system generates adjustment instructions for lighting direction and spectral composition respectively, so that the lighting device can simultaneously optimize the light beam angle and the spectral composition. This method breaks through the limitations of traditional single parameter adjustment, realizes the collaborative compensation of shadow areas and overly bright areas, and significantly improves the uniformity of high shelf lighting. The whole system ensures the accuracy and timeliness of lighting adjustment through the workflow of detection first and then execution, and provides a more accurate and reliable lighting solution for complex warehouse environments. BRIEF DESCRIPTION OF DRAWINGS

[0046] The application will be further described below with reference to the drawings.

[0047] Figure 1 is a flowchart of the multi-objective optimization collaborative control method for shelf lighting of the application;

[0048] Figure 2 is a structural schematic diagram of the multi-objective optimization collaborative control device for shelf lighting of the application. DETAILED DESCRIPTION

[0049] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the application.

[0050] Please refer to Figure 1 The application is a multi-objective optimization collaborative control method for shelf lighting, which comprises the following steps:

[0051] S1, projecting a grid detection pattern containing multiple wavelength components onto the surface of the shelf, the node spacing of the grid detection pattern being in a proportional relationship with the shelf layer spacing;

[0052] S2, collecting the reflected light signal of the grid detection pattern on the surface of the shelf, and synchronously recording the spatial distribution data and the spectral composition data of the reflected light signal;

[0053] S3, processing the spatial distribution data, extracting the position coordinates of each node in the grid detection pattern, and calculating the offset vector of each node relative to the reference position;

[0054] S4, processing the spectral composition data, decomposing the wavelength components of the reflected light signal, and calculating the difference between the light intensity value of each wavelength component and the reference light intensity value;

[0055] S5, generating the light beam direction adjustment instruction of the basic lighting system according to the direction and amplitude of the offset vector, and generating the spectral compensation instruction of the basic lighting system according to the light intensity difference;

[0056] S6, the basic lighting system adjusts the lighting parameters according to the light beam direction adjustment instruction and the spectral compensation instruction.

[0057] In the S1, the process of projecting the grid detection pattern containing multiple wavelength components onto the surface of the shelf is as follows:

[0058] The projection of the multi-wavelength grid detection pattern relies on a high-precision optical emission system, which first generates three coherent lights of red, green and blue wavelengths. The coherent light generation unit usually uses a narrow-line-width semiconductor laser, in which the center wavelength of the red wavelength laser source is generally selected as 635 nm or 650 nm, the center wavelength of the green wavelength laser source is selected as 532 nm, and the center wavelength of the blue wavelength laser source is selected as 450 nm or 473 nm. Each laser source needs to pass through an optical isolator to suppress the interference of backscattered light and ensure the phase stability of the output light beam, and at the same time, a collimating lens is used to calibrate the exiting light beam into parallel light, so that the beam cross-sectional size of the three light beams matches the incident port of the subsequent optical structure.

[0059] After the generation of the three coherent lights, they are guided to the non-common-path interference structure through a fiber coupler or a mirror group. The core feature of the non-common-path interference structure is that the three lights propagate independently in the interference front, and each light path is equipped with a precision displacement stage to fine-tune the optical path difference, so as to avoid crosstalk caused by overlapping of different wavelength beams during propagation. A beam splitter and a beam combiner are arranged in the interference cavity of the structure. The beam splitter divides each coherent light into reference light and object light, the reference light directly enters the beam combiner, and the object light is combined with the reference light after a specific optical path adjustment, and finally a multi-wavelength interference field is formed at the output end of the interference structure. In the multi-wavelength interference field, the interference fringes of different wavelengths are superimposed on each other to form an initial light intensity distribution with wavelength discrimination characteristics.

[0060] To realize dynamic phase control, the multi-wavelength interference field needs to pass through a phase modulation unit composed of an acousto-optic modulator. Each wavelength corresponds to an independent acousto-optic modulator, and the driving frequency of the acousto-optic modulator needs to match the frequency parameter of the corresponding wavelength laser source to ensure that the modulation signal can accurately act on the target wavelength beam. The core of dynamic phase modulation is to change the radio frequency driving signal of the acousto-optic modulator to produce a controllable phase delay when the light beam passes through the acousto-optic medium. During the modulation process, the phase delay needs to be adjusted from 0 to 2π step by step, and the adjustment step is set according to the detection accuracy requirement, usually controlled between 0.01π and 0.05π. At the same time of changing the phase delay, the data acquisition module needs to record the light intensity distribution of the grid detection pattern under each phase delay, including the light intensity value of each pixel point and the corresponding phase delay parameter, to form a complete phase-light intensity mapping data set, which provides a reference for subsequent analysis of the reflected light signal.

[0061] The phase-modulated interference field needs to be converted into a grid-like light intensity distribution by a diffractive optical element. The diffractive optical element is made by binary optics technology, and its surface is etched with a periodic grid structure. The period of this structure (i.e. the grid node spacing) needs to be proportional to the shelf plate spacing. The proportional coefficient is usually determined according to the shelf height, for example, when the shelf plate spacing is 30 cm, the grid node spacing can be set to 3 cm or 5 cm, ensuring that the grid pattern can completely cover the surface of each layer of the shelf and the node density is sufficient to reflect the local light difference. The diffractive optical element decomposes the incident interference field into multiple diffraction orders propagating in a specific direction. These diffraction orders intersect in space to form a regular grid-like light intensity distribution. This distribution is focused by a projection lens and projected onto the shelf surface in the form of parallel light, finally forming a grid detection pattern for detection.

[0062] In S2, the specific process of collecting the reflected light signal is as follows:

[0063] The collection of the reflected light signal relies on a monochrome area array detector. The detector type is usually selected from scientific grade CMOS or CCD image sensors. The spectral response range of the detector needs to cover the red, green and blue wavelength intervals, and it needs to have high frame rate and high dynamic range characteristics to capture weak interference fringe signals and avoid light intensity saturation. The pixel resolution of the detector needs to match the node density of the grid detection pattern, ensuring that each grid node corresponds to at least one pixel unit of the detector. At the same time, the imaging magnification is adjusted by the lens module to ensure that the grid pattern on the shelf surface is completely imaged on the effective light-sensitive area of the detector.

[0064] The collection process needs to be synchronized with the wavelength projection timing in S1, that is, during the projection of red, green and blue wavelengths in turn, the detector collects the interference fringe image sequence corresponding to each wavelength. The projection time of each wavelength needs to meet the requirement of collecting four images by the detector, and the collection interval of adjacent two images needs to be coordinated with the phase adjustment period of the acousto-optic modulator to ensure that the phase difference corresponding to the four images is strictly π / 2. Specifically, the phase delay of the acousto-optic modulator corresponding to the first image is set to 0, the phase delay of the acousto-optic modulator corresponding to the second image is set to π / 2, the phase delay of the acousto-optic modulator corresponding to the third image is set to π, and the phase delay of the acousto-optic modulator corresponding to the fourth image is set to 3π / 2, forming a four-step phase-shifted image sequence. During the collection process, the exposure parameters of each image need to be kept consistent by shutter control or gain adjustment to avoid interference of exposure difference on subsequent phase calculation.

[0065] After the sequence of interference fringe images of each wavelength is obtained, four-step phase shift calculation is performed to obtain the phase principal value distribution of the wavelength. The core of the four-step phase shift calculation is to use four images with different phase shifts to extract the phase information by light intensity superposition and difference operation. During the calculation process, first, the light intensity values of the corresponding pixel points of the four images are normalized to eliminate the influence of the dark current of the detector and the background light. Then, according to the principle of phase shift interference, the phase principal value of each pixel point is obtained by combining the light intensity values of the four images.

[0066] The phase unwrapping operation adopts the region growing method or the least square method, and the core idea is to start from a seed region with continuous phase, gradually expand to the entire image region, and obtain a continuous phase distribution covering the entire imaging region by correcting the phase jump (subtracting 2π from the phase difference exceeding π, and adding 2π to the phase difference below -π). In the continuous phase distribution, the phase value of each pixel point corresponds to the spatial position of the point on the shelf surface, and the phase change reflects the height difference of the spatial position.

[0067] After the continuous phase distributions of the three wavelengths are calculated, they need to be combined into a full-color phase distribution map. The synthesis process adopts the RGB color space mapping method, that is, the continuous phase distribution of the red wavelength is mapped to the red channel of the RGB space, the continuous phase distribution of the green wavelength is mapped to the green channel, and the continuous phase distribution of the blue wavelength is mapped to the blue channel. The phase value of each channel needs to be converted to a gray value (usually the phase range of -π to π is mapped to the gray range of 0 to 255), and then a full-color image is generated through a color synthesis algorithm. In the full-color phase distribution map, the gray level changes of different color channels reflect the spectral composition data, and the association of the spatial coordinates of the pixel points and the phase gray values carries the spatial distribution data, realizing the unified storage and subsequent call of the two core data.

[0068] In the S3, the specific process of processing the spatial distribution data is as follows:

[0069] The spatial distribution data processing takes the full-color phase distribution map as the input, and first needs to extract the complex amplitude information of each node in the grid detection pattern. The extraction process needs to first locate the nodes of the full-color phase distribution map, identify the node feature points (usually the intersection points of the fringes) in the grid pattern through an image edge detection algorithm, and determine the pixel coordinates of each node. For each node, the light intensity value and the phase value are extracted from the red, green and blue channels, respectively, wherein the light intensity value is normalized to be the amplitude component of the complex amplitude, and the phase value is directly taken as the phase component of the complex amplitude, so as to construct the complex amplitude parameter of each node.

[0070] After obtaining the complex amplitude information of each node, the coherence matrix of the complex amplitude of the adjacent grid nodes is calculated. The coherence matrix is a 2x2 complex matrix, and the elements thereof are composed of the complex amplitudes of the two adjacent nodes. Specifically, the diagonal elements of the matrix are the squares of the amplitudes of the complex amplitudes of the two nodes (i.e., the light intensity), and the non-diagonal elements are the combination of the product of the complex amplitudes of the two nodes and the conjugate thereof. The matrix can quantify the correlation of the light field and the polarization correlation characteristics between the adjacent nodes.

[0071] By performing eigenvalue decomposition on the coherence matrix, two eigenvalues and corresponding eigenvectors can be obtained. The direction of the eigenvector reflects the polarization state distribution of the region. The polarization state distribution has an inherent mapping relationship with the normal vector of the surface of the shelf, because the normal vector of the surface determines the change trend of the polarization state of the reflected light - when the angle between the normal vector of the surface and the direction of the incident light changes, the amplitude ratio of the p-polarization component and the s-polarization component of the reflected light will change, thereby causing the polarization state to shift. Based on this physical law, a correspondence model of the polarization state parameter and the normal vector of the surface needs to be established through a pre-calibration experiment. During the calibration process, a standard plane sample is used, and the polarization state data at different normals is recorded by adjusting the inclination of the sample to change the surface normal. Finally, a mapping relationship database is formed.

[0072] According to the established mapping relationship, the polarization state distribution of all grid nodes in the full-color phase distribution map is analyzed, and the surface normal vector corresponding to each node is obtained, and then the surface normal field of the entire shelf surface is reconstructed. The surface normal field is a vector field that describes the macroscopic morphology of the shelf surface, and the direction of each vector of the surface normal field is perpendicular to the tangent direction of the surface at the corresponding position. In order to convert the surface normal field into a surface height distribution that can be directly used for position analysis, a surface integral operation needs to be performed on the surface normal field. The surface integral process takes a predetermined reference plane as the integral reference surface, and through integral accumulation along the tangent direction of the surface, the change in the direction of the normal vector is converted into the change in the height coordinate, and finally the height value of each grid node in the three-dimensional space is output, forming the surface height distribution data.

[0073] The surface height distribution data needs to be compared with the reference height distribution to obtain the elevation difference field. The reference height distribution is the preset height data of the shelf in the unloaded or standard display state, which is stored in the system database through pre-measurement. The calculation method of the elevation difference field is to subtract the reference height value from the actual height value of each grid node, and the result can be positive or negative. A positive value indicates that the actual height of the node is higher than the reference, and a negative value indicates that it is lower than the reference. The absolute value of the difference reflects the size of the height deviation.

[0074] To extract the effective position offset information from the height difference field, it needs to be decomposed by spherical harmonics. The spherical harmonic decomposition is to expand the irregular three-dimensional field distribution into a linear combination of a series of orthogonal spherical harmonics. During the decomposition process, the expansion order needs to be determined according to the spatial scale and detail characteristics of the height difference field. Here, the first sixteen spherical harmonic coefficients are selected as the characteristic parameters. The reason is that the low-order spherical harmonic coefficients (1-4 orders) mainly reflect the overall trend of the height difference field, the middle-order spherical harmonic coefficients (5-16 orders) reflect the local detail changes, and the high-order coefficients (16 orders and above) are mostly noise interference, which can improve the subsequent calculation accuracy after being removed.

[0075] The three-dimensional offset vector of each grid node is calculated according to the extracted first sixteen spherical harmonic coefficients. Among them, the first-order spherical harmonic coefficient corresponds to the overall tilt direction of the height difference field, and its vector direction determines the direction of the three-dimensional offset vector; the second-order spherical harmonic coefficient corresponds to the curvature change and amplitude distribution of the height difference field, and its numerical value is positively correlated with the amplitude of the three-dimensional offset vector. The second-order spherical harmonic coefficient can be converted into a specific offset amplitude value through a preset proportional coefficient. Finally, the three-dimensional offset vector of each grid node contains two key parameters, direction and amplitude, which provides the position basis for the generation of subsequent beam direction adjustment instructions.

[0076] In the S4, the specific process of processing the spectral composition data is:

[0077] The spectral composition data processing also takes the full-color phase distribution map as input. The first step is to separate the Stokes parameters of each wavelength. The Stokes parameter is a four-dimensional parameter that describes the polarization characteristics of light, which includes four polarization components: total light intensity (H0), horizontal linearly polarized light and vertical linearly polarized light intensity difference (H1), 45-degree linearly polarized light and 135-degree linearly polarized light intensity difference (H2), and right circularly polarized light and left circularly polarized light intensity difference (H3). During the separation process, the red, green, and blue channels of the full-color phase distribution map need to be processed separately: for each channel, through the image polarization analysis algorithm, combined with the polarization imaging characteristics of the detector (if the detector has no built-in polarizer, multiple groups of images need to be collected through external polarizer rotation), the H0, H1, H2, and H3 four component values of each grid node are calculated to form a Stokes parameter matrix independent of each wavelength.

[0078] After the determination of the Stokes parameters of each wavelength, the Mueller matrix representation thereof needs to be calculated. The Mueller matrix is a 4x4 real matrix describing the change of the polarization state of light during the propagation or reflection process, and the elements thereof are derived from the transformation relationship of the Stokes parameters. Specifically, standard polarized state incident light (such as horizontally linearly polarized light, vertically linearly polarized light, etc.) is selected, the outgoing Stokes parameters of the reflected light from the surface of the shelf after the incident light is recorded, and then the elements of the Mueller matrix are solved by linear equations. The Mueller matrix can completely characterize the polarization modulation characteristics of the shelf surface for a specific wavelength of light, and the singular values in the matrix structure thereof can reflect the intensity and stability of the polarization state modulation.

[0079] Through singular value decomposition of the Mueller matrix, three non-zero singular values (the rank of the Mueller matrix is 3) can be obtained, and the distribution characteristics of the singular values are quantitatively correlated with the depolarization coefficient. The depolarization coefficient is a parameter for measuring the degree of polarization state degradation of light after reflection, and the smaller the difference between the singular values of the Mueller matrix, the larger the depolarization coefficient, indicating that the polarization state of the reflected light is closer to natural light; on the contrary, the larger the difference between the singular values, the smaller the depolarization coefficient, indicating that the reflected light still maintains strong polarization characteristics. The calculation of the depolarization coefficient needs to be based on the statistical characteristics of the singular values, and the singular values are converted into specific depolarization coefficient values through a preset mathematical model, thereby forming a depolarization coefficient distribution covering the entire surface of the shelf.

[0080] The depolarization coefficient distribution has a clear corresponding relationship with the roughness of the surface of the shelf, because the roughness of the surface directly affects the scattering characteristics of the reflected light: the rougher the surface, the wider the scattering angle distribution of the reflected light, the more serious the polarization state degradation, and the larger the depolarization coefficient; the smoother the surface, the main reflection of the reflected light is specular reflection, the polarization state is better maintained, and the smaller the depolarization coefficient. This corresponding relationship needs to be established through pre-experiment calibration, and during the calibration process, standard samples with different roughness (such as Ra=0.1 μm, 0.5 μm, 1 μm, etc.) are used to measure the depolarization coefficients of the samples, a fitting curve of roughness and depolarization coefficient is constructed, and a corresponding relationship model is formed.

[0081] According to the corresponding relationship between the depolarization coefficient and the surface roughness, the bidirectional reflectance distribution function of the surface at each grid node can be calculated. The bidirectional reflectance distribution function (BRDF) is a function describing the relationship between the reflected light intensity and the incident light intensity, the incident angle, and the reflection angle when light is reflected on the surface of an object, and the numerical value thereof directly reflects the reflection ability of the surface for a specific wavelength of light. During the calculation process, the angle parameters of the incident light (determined by the projection system parameters in S1) and the roughness data corresponding to the depolarization coefficient need to be combined, and substituted into a preset BRDF model (such as the Phong model, the Cook-Torrance model, etc.), to obtain the BRDF numerical value of each grid node at the corresponding wavelength.

[0082] To obtain the light intensity difference, the calculated bidirectional reflectance distribution function (BRDF) needs to be compared with a reference BRDF. The reference BRDF is the preset value of the shelf under standard lighting conditions (such as target lighting intensity and standard display status), which is measured and stored through previous calibration experiments. The comparison process involves subtracting the reference BRDF value from the actual BRDF value of each grid node to obtain the reflectance change at each wavelength. The product of the reflectance change and the reference light intensity value is the light intensity difference, where the reference light intensity value is the system's preset target lighting intensity, usually set according to shelf lighting standards (e.g., 500-800 lux for shopping mall shelf lighting).

[0083] Finally, the numerical values ​​and signs of the light intensity differences at each wavelength need to be recorded. The magnitude of the value reflects the degree to which the light intensity deviates from the target value, while the sign reflects the direction of deviation: a positive sign indicates that the reflected light intensity at that node is higher than the reference light intensity, and a negative sign indicates that the reflected light intensity is lower than the reference light intensity. This data will be directly used to generate subsequent spectral compensation commands, ensuring that the compensation operation can accurately correct the light intensity deviation and achieve spectral-level illumination optimization.

[0084] In step S5, the specific process of generating the beam direction adjustment command for the basic lighting system based on the direction and magnitude of the offset vector is as follows:

[0085] A mapping relationship between the three-dimensional offset vector and the illumination beam direction is established. This mapping relationship is constructed based on the orthogonal decomposition of spherical harmonic coefficients. Previously, S3 extracted the first sixteen spherical harmonic coefficients, where the first-order spherical harmonic coefficients characterize the overall directional features of the three-dimensional offset vector, and the second-order spherical harmonic coefficients characterize the spatial distribution of the offset amplitude. Together, they constitute the core parameters of the mapping relationship. The orthogonal decomposition process is completed by substituting the first sixteen spherical harmonic coefficients into the orthogonal basis function set. The orthogonality of the spherical harmonic functions ensures that each three-dimensional offset vector corresponds to a unique illumination beam direction parameter, avoiding confusion in direction mapping under different offset states.

[0086] After establishing the mapping relationship, the three-dimensional offset vector needs to be projected onto the azimuth and zenith dimensions of the spherical coordinate system. The spherical coordinate system uses the installation origin of the basic lighting system as its pole. The azimuth angle is defined as the angle between the light beam on the horizontal plane and a preset reference direction (such as the direction of the main aisle of the shelf), and the zenith angle is defined as the angle between the light beam and the horizontal plane. The projection process is achieved through vector dot product operations. The three-dimensional offset vector is multiplied by the unit vectors corresponding to the azimuth and zenith angles in the spherical coordinate system to obtain the projection components in the two dimensions. The reference azimuth and reference zenith angles are preset standard lighting direction parameters of the system and need to be pre-calibrated according to the shelf layout and lighting standards. For example, when the shelves are arranged along the north-south direction, the reference azimuth angle can be set to 0 degrees (pointing due north), and the reference zenith angle can be set to 45 degrees (ensuring that the light covers the middle layer of the shelf). By calculating the difference between the projection components and the corresponding reference values, the horizontal deflection adjustment and pitch adjustment can be obtained respectively. A positive difference indicates that adjustment needs to be made in the positive direction of that dimension, and a negative difference indicates adjustment in the negative direction.

[0087] The calculation of the beam divergence angle adjustment is based on the amplitude component of the spherical harmonic function coefficients. The amplitude component of the spherical harmonic function coefficients reflects the distribution range of the three-dimensional offset vector in space. The larger the amplitude, the more concentrated the height deviation of the shelf surface in that area, requiring a smaller beam divergence angle to achieve precise local illumination; the smaller the amplitude, the more dispersed the deviation distribution, requiring a larger beam divergence angle to cover a wider area. In the calculation process, the statistical mean of the amplitude component among the first sixteen spherical harmonic coefficients is selected as the core parameter. Through the previously calibrated "mean amplitude - divergence angle adjustment" curve, the mean amplitude is converted into a specific beam divergence angle adjustment. For example, a mean amplitude of 0.5 corresponds to a 2-degree increase in the divergence angle, and a mean amplitude of 1.2 corresponds to a 3-degree decrease in the divergence angle.

[0088] After calculating the three adjustment values, they need to be encoded into beam direction adjustment commands that the basic lighting system can resolve. The encoding uses a system-defined binary frame structure. The frame header contains a command type identifier (used to distinguish beam direction commands from spectral compensation commands). The frame body is divided into three fields, corresponding to the horizontal deflection adjustment, pitch adjustment, and beam divergence angle adjustment, respectively. Each field contains a numerical bit and a sign bit. The numerical bit uses 16 bits to represent the absolute value of the adjustment (in degrees), and the sign bit uses 1 bit to represent the direction (0 for positive, 1 for negative). A check bit is set at the end of the frame to ensure the accuracy of the command transmission. The encoded command is transmitted through the communication interface between the control unit and the basic lighting system (such as a CAN bus or industrial Ethernet), awaiting a response from the actuator.

[0089] In step S5, the specific process of generating the spectral compensation command for the basic lighting system based on the light intensity difference is as follows:

[0090] A correspondence between light intensity difference and spectral power distribution is established. This correspondence is constructed based on the eigenvector analysis of the Mueller matrix. Previously, S4 obtained the depolarization coefficient distribution through singular value decomposition of the Mueller matrix, while the eigenvectors of the Mueller matrix further reflect the polarization state evolution of light at different wavelengths during reflection. In the eigenvector analysis process, three non-zero eigenvectors of the Mueller matrix are extracted, each corresponding to a spectral response mode for a wavelength. By performing correlation calculations between the light intensity difference and the eigenvectors, a mapping model between the light intensity difference and the spectral power at that wavelength is established, ensuring that the light intensity deviation can be accurately converted into the adjustment requirements of the spectral power.

[0091] The intensity differences of each wavelength are input into the spectral reconstruction algorithm. This algorithm employs a linear superposition reconstruction model, using a pre-set reference spectral power distribution as the initial template. It then combines this with the power adjustment requirements corresponding to the intensity differences to output the target spectral power distribution. The reference spectral power distribution must meet the color temperature and color rendering index requirements of shelf lighting. For example, supermarket shelf lighting typically requires a neutral color temperature of 4000K and a color rendering index above 80; the reference distribution is set according to this standard. During the spectral reconstruction process, the algorithm adjusts the power proportion of the corresponding wavelength based on the sign of the intensity difference. For instance, when the intensity difference of the red wavelength is negative (lower than the reference), the algorithm increases the power proportion of red light in the target spectrum; conversely, it decreases it. The final output target spectral power distribution must simultaneously meet the requirements of intensity balance and chromaticity parameters.

[0092] The relative difference between the target spectral power distribution and the reference spectral power distribution is calculated. This relative difference is calculated as (target power - reference power) / reference power, and the result reflects the relative adjustment ratio of the power at each wavelength. Based on this relative difference, the intensity adjustment coefficient for each wavelength component is calculated. The intensity adjustment coefficient is equal to the product of the relative difference and the correction coefficient, where the correction coefficient is proportional to the singular value of the Mueller matrix. The singular value of the Mueller matrix characterizes the polarization modulation intensity of light at that wavelength. A larger singular value indicates that the polarization state of the reflected light at that wavelength is more significantly affected by surface roughness, requiring a larger correction coefficient to ensure that the intensity adjustment can offset the intensity deviation caused by polarization. For example, when the singular value of the Mueller matrix for blue light wavelength is 0.8, the correction coefficient is set to 1.2; when the singular value is 0.5, the correction coefficient is set to 0.9.

[0093] The intensity adjustment factor is converted into a drive current adjustment based on the current-luminous intensity characteristic curve of the light-emitting element. Shelf lighting systems typically use RGB tri-color LEDs as light-emitting elements. The current-luminous intensity curves of different colored LEDs exhibit a linear relationship. For example, for red LEDs in the 200mA to 500mA range, the linear correlation coefficient between luminous intensity and current is greater than 0.98. During the conversion process, the required change in luminous intensity is calculated based on the intensity adjustment factor. Then, through the inverse operation of the current-luminous intensity curve, the change in luminous intensity is converted into a drive current adjustment. For example, if the intensity adjustment factor for red light is 0.2 (requiring a 20% increase in luminous intensity), the corresponding current adjustment is 40mA (increasing from 200mA to 240mA).

[0094] Finally, the drive current adjustment amounts corresponding to each wavelength are encoded into spectral compensation commands. The commands employ a binary frame structure compatible with beam direction commands. The frame header contains a unique command type identifier, and the frame body is divided into three fields according to wavelength order (red, green, blue). Each field contains the numerical value, sign bit, and wavelength identifier bit for the drive current adjustment amount at that wavelength. A check bit is also set at the end of the frame. The encoded commands are transmitted to the drive module of the basic lighting system through the control unit's communication interface, providing a basis for subsequent current adjustment.

[0095] In S6, the specific process by which the basic lighting system adjusts the lighting parameters according to the beam direction adjustment command and the spectral compensation command is as follows:

[0096] The basic lighting system first parses the beam direction adjustment command. The command parsing module built into the control unit breaks down the command according to a preset frame structure, extracting the values ​​and signs of the horizontal deflection adjustment, pitch adjustment, and beam divergence angle adjustment. During the parsing process, the module first verifies the frame end check bit to ensure that the command has not been erroneous during transmission. If the verification passes, the three adjustment values ​​are converted into control signals that the actuator can recognize. If the verification fails, the command is requested to be retransmitted.

[0097] The horizontal deflection mechanism of the lighting unit is adjusted according to the horizontal deflection adjustment amount. This mechanism consists of a stepper motor and a gear transmission assembly. The rotation angle of the stepper motor is proportional to the horizontal deflection adjustment amount. This proportion needs to be determined through prior calibration. For example, every 1 degree of horizontal deflection adjustment corresponds to 100 steps of stepper motor rotation. The control unit outputs pulse signals to the stepper motor controller. The number of pulses is calculated from the adjustment amount and the proportional coefficient. The motor drives the lighting unit to rotate around the vertical axis through gear transmission, realizing the horizontal beam deflection. During the adjustment process, the built-in angle sensor will provide real-time feedback on the actual rotation angle and compare it with the target adjustment amount. Adjustment stops when the deviation is less than 0.1 degrees.

[0098] The tilt adjustment mechanism of the lighting unit adjusts according to the tilt adjustment amount. This mechanism is also driven by a stepper motor, but its rotation axis is a horizontal axis, used to change the vertical illumination angle of the beam. The rotation angle of the tilt adjustment mechanism is also proportional to the tilt adjustment amount, and the proportional coefficient is set according to the transmission ratio of the mechanism. For example, every 1 degree of tilt adjustment corresponds to 120 motor rotations. During the adjustment process, the control unit outputs a pulse signal according to the tilt adjustment amount, and the motor drives the lighting unit to rotate around the horizontal axis. At the same time, the vertical angle sensor collects the actual angle in real time and performs closed-loop control with the target adjustment amount to ensure that the final tilt angle deviation is controlled within 0.1 degrees, avoiding the displacement of the illuminated area due to angle deviation.

[0099] The optical focusing system of the illumination unit adjusts the beam divergence angle based on the adjustment amount. This system consists of two sets of movable lenses and an electrically adjustable assembly. The change in the lens spacing is directly proportional to the adjustment amount of the beam divergence angle. When it is necessary to increase the divergence angle, the electrically adjustable assembly (usually a piezoelectric ceramic actuator) pushes the two sets of lenses away from each other, increasing the lens spacing; when it is necessary to decrease the divergence angle, the adjustable assembly pulls the lenses closer together, decreasing the lens spacing. The proportional relationship between the lens spacing and the divergence angle needs to be determined through optical simulation and experimental calibration. For example, every 0.5 mm increase in lens spacing corresponds to a 1 degree increase in divergence angle, and every 0.5 mm decrease corresponds to a 1 degree decrease in divergence angle. During the adjustment process, the lens position sensor provides real-time feedback of the spacing data, and the control unit fine-tunes the adjusting assembly based on the feedback value until the divergence angle reaches the target value.

[0100] After beam direction adjustment is completed, the basic lighting system analyzes the spectral compensation command. The command analysis module extracts the drive current adjustment amount, symbol, and wavelength identifier for each wavelength according to the frame structure. After verifying that the check bits are correct, it allocates the current adjustment requirements for each wavelength to the corresponding LED driver circuit. Each wavelength of LED is equipped with an independent constant current drive circuit. The control unit outputs an analog voltage signal (or digital control signal) to the drive circuit, and the drive circuit adjusts the output current according to the signal. The change in current is strictly proportional to the drive current adjustment amount. For example, when the red light drive current adjustment amount is 40mA (positive adjustment), the drive circuit increases the output current from 200mA to 240mA; when the blue light adjustment amount is -20mA (negative adjustment), the drive circuit reduces the current from 220mA to 200mA. During the current adjustment process, the current sampling resistor built into the drive circuit monitors the output current in real time, forming a closed-loop control to ensure that the current accuracy error is less than 1mA.

[0101] All adjustments must be performed in the strict order of "direction adjustment first, then spectral adjustment." The core reason for this sequence is that adjusting the beam direction changes the incident position and angle of light on the shelf surface, directly affecting the distribution of reflected light intensity. If spectral adjustment is performed first, subsequent direction adjustments may lead to new light intensity deviations, requiring repeated adjustments. Completing direction adjustment first ensures that the lighting position and angle meet requirements, and then spectral compensation corrects for light intensity deviations, enabling optimization of lighting parameters in one step, reducing the number of adjustments, and improving system response efficiency.

[0102] Furthermore, the projection of a multi-wavelength grid detection pattern onto the shelf surface is accomplished by an auxiliary detection unit, which mainly consists of a light source assembly and optical sensors. The core components of the light source assembly include an RGB three-color narrow-linewidth laser, an acousto-optic modulator, a non-common-path interference structure, and diffractive optical elements; its hardware configuration is completely matched to the projection system described in S1. To ensure that the detection pattern aligns with the illumination area of ​​the basic lighting system, the light output direction of the light source assembly must be consistent with that of the basic lighting system. This is achieved by fixing both to the same mounting plane using a mechanical bracket and calibrating the light output axis using a laser collimator, ensuring that the deviation between the light output axes of the two systems within a 10-meter range is less than 0.5 degrees, thus ensuring that the detection pattern accurately covers the illumination area of ​​the basic lighting.

[0103] The optical sensor of the auxiliary detection unit establishes a stable data connection with the control unit of the basic lighting system. The connection method adopts industrial Ethernet (such as Profinet or EtherNet / IP), with a communication rate of no less than 100Mbps to meet the real-time transmission requirements of reflected light signals. During the data connection process, the IP address and communication protocol of the sensor need to be configured in the control unit to ensure that the two can achieve bidirectional data interaction. The optical sensor can transmit the collected reflected light signal data (including spatial distribution data and spectral composition data) to the control unit, and the control unit can send acquisition trigger signals and parameter configuration commands (such as exposure time and acquisition frame rate) to the sensor.

[0104] During the detection phase, the workflow of the auxiliary detection unit is uniformly scheduled by the control unit. The control unit first sends a start command to the light source assembly. The light source assembly generates multi-wavelength coherent light according to the parameters in S1. After interference structure and phase modulation, the light is projected onto the shelf surface through diffractive optical elements to form a grid detection pattern. Simultaneously with the projection start, the control unit sends a acquisition trigger signal to the optical sensor. The sensor, according to the requirements in S2, acquires the corresponding interference fringe image sequence during the sequential projection of each wavelength. During acquisition, the sensor compresses the image data in real time (using a lossless compression algorithm) and transmits it to the control unit. The control unit temporarily stores the data in a buffer, awaiting retrieval by the signal processing unit.

[0105] Upon entering the lighting adjustment phase, the control unit of the basic lighting system first sends the reflected light signal data from the buffer area to the signal processing unit, triggering the data analysis processes S3 and S4. After calculating the three-dimensional offset vector and the light intensity difference, the signal processing unit feeds the results back to the control unit. Based on these results, the control unit generates the beam direction adjustment command and spectral compensation command in S5, and then sends the commands to the actuator of the basic lighting system, triggering the parameter adjustment operation in S6. After the adjustment operation is completed, the control unit sends a secondary detection command to the auxiliary detection unit. The auxiliary detection unit repeats the detection process, collecting the adjusted reflected light signal. The control unit determines whether the lighting parameters meet the standards based on the secondary detection results. If not, the adjustment process is repeated until the illumination uniformity and light intensity meet the preset standards, forming a complete closed-loop control.

[0106] Please see Figure 2 As shown, the present invention also includes a multi-objective optimization collaborative control device for shelf lighting, used to implement the above-described multi-objective optimization collaborative control method for shelf lighting, comprising:

[0107] The light source assembly is used to project a grid detection pattern containing multi-wavelength components onto the shelf surface. The node spacing of the grid detection pattern is proportional to the shelf shelf spacing.

[0108] An optical sensor is used to collect the reflected light signal from the shelf surface to the grid detection pattern, and simultaneously record the spatial distribution data and spectral composition data of the reflected light signal;

[0109] The signal processing unit is used to process spatial distribution data, extract the position coordinates of each node in the grid detection pattern, calculate the offset vector of each node relative to the reference position; and process spectral composition data, decompose the wavelength components of the reflected light signal, and calculate the difference between the light intensity value of each wavelength component and the reference light intensity value.

[0110] The control unit is used to generate beam direction adjustment commands for the basic lighting system based on the direction and magnitude of the offset vector, and to generate spectral compensation commands for the basic lighting system based on the light intensity difference.

[0111] The basic lighting system is used to adjust lighting parameters according to beam direction adjustment commands and spectral compensation commands.

[0112] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A multi-objective optimization collaborative control method for shelf lighting, characterized in that, Includes the following steps: S1. Project a grid detection pattern containing multi-wavelength components onto the shelf surface. The node spacing of the grid detection pattern is proportional to the shelf shelf spacing. S2. Collect the reflected light signal of the grid detection pattern on the shelf surface, and simultaneously record the spatial distribution data and spectral composition data of the reflected light signal; S3. Process spatial distribution data, extract the position coordinates of each node in the grid detection pattern, and calculate the offset vector of each node relative to the reference position. S4. Process the spectral composition data, decompose the wavelength components of the reflected light signal, and calculate the difference between the light intensity value of each wavelength component and the reference light intensity value. S5. Generate beam direction adjustment instructions for the basic lighting system based on the direction and amplitude of the offset vector, and generate spectral compensation instructions for the basic lighting system based on the light intensity difference. S6. The basic lighting system adjusts the lighting parameters according to the beam direction adjustment command and the spectral compensation command.

2. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, In step S1, the process of projecting a grid detection pattern containing multi-wavelength components onto the shelf surface is as follows: Three coherent beams of light with red, green and blue wavelengths are generated and input into a non-common-path interference structure. A multi-wavelength interference field is generated at the output of the interference structure. Dynamic phase modulation is applied to the multi-wavelength interference field. The frequency of the dynamic phase modulation is consistent with the driving frequency of the acousto-optic modulator corresponding to each wavelength. The phase-modulated interference field is converted into a grid-like light intensity distribution by a diffractive optical element. The grid-like light intensity distribution is projected onto the shelf surface to form a grid detection pattern. During the projection process, the phase delay of the acousto-optic modulator is changed synchronously. The phase delay ranges from zero to 2π. The light intensity distribution of the grid detection pattern corresponding to each phase delay is recorded.

3. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, In step S2, the specific process of acquiring the reflected light signal is as follows: Interference fringe images of the shelf surface are acquired using a monochromatic area array detector. During the sequential projection of red, green, and blue wavelengths, interference fringe image sequences of the corresponding wavelengths are acquired. Each wavelength interference fringe image sequence contains four frames of interferograms with a phase difference of π / 2. Four-step phase shift calculations are performed on the interference fringe image sequence of each wavelength to obtain the phase principal value distribution of that wavelength. Phase unwrapping operation is performed on the principal phase value distribution to obtain the continuous phase distribution of the wavelength. The continuous phase distributions of the three wavelengths are then combined into a full-color phase distribution map, which contains spatial distribution data and spectral composition data.

4. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, In step S3, the specific process for processing spatially distributed data is as follows: Complex amplitude information of each grid node is extracted from the full-color phase distribution map. The complex amplitude information includes amplitude components and phase components. The coherence matrix of the complex amplitude of adjacent grid nodes is calculated. The polarization state distribution is obtained by eigenvalue decomposition of the coherence matrix. The mapping relationship between the polarization state distribution and the surface normal vector is established. The surface normal field is reconstructed according to the mapping relationship. The surface normal field is integraled with the surface normal field to obtain the surface height distribution. The elevation difference field between the surface height distribution and the reference height distribution is calculated. The elevation difference field is decomposed by spherical harmonic function, and the first sixteen spherical harmonic coefficients are extracted. The three-dimensional offset vector of each grid node is calculated based on the spherical harmonic coefficients. The direction of the three-dimensional offset vector is determined by the first-order spherical harmonic coefficients, and the amplitude of the three-dimensional offset vector is determined by the second-order spherical harmonic coefficients.

5. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, In step S4, the specific process for processing the spectral composition data is as follows: The Stokes parameters for each wavelength are separated from the full-color phase distribution map. The Stokes parameters contain four polarization components. The Mueller matrix representation of the Stokes parameters for each wavelength is calculated. The depolarization coefficient distribution is obtained through the singular value decomposition of the Mueller matrix. The correspondence between the depolarization coefficient and the surface roughness is established. The bidirectional reflection distribution function of the surface is calculated based on the correspondence. The bidirectional reflectance distribution function is compared with the reference bidirectional reflectance distribution function to obtain the reflectance change at each wavelength. The light intensity difference at each wavelength is calculated based on the reflectance change. The light intensity difference is the product of the reflectance change and the reference light intensity value. The value and sign of the light intensity difference at each wavelength are recorded.

6. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, In step S5, the specific process of generating the beam direction adjustment command for the basic lighting system based on the direction and magnitude of the offset vector is as follows: Establish a mapping relationship between the three-dimensional offset vector and the direction of the illumination beam. The mapping relationship is based on the orthogonal decomposition of the coefficients of the spherical harmonic function. Project the three-dimensional offset vector onto the azimuth and zenith dimensions in the spherical coordinate system. Calculate the difference between the projection component of the azimuth dimension and the reference azimuth to obtain the horizontal deflection adjustment amount. The pitch adjustment is obtained by calculating the difference between the projected component of the zenith angle dimension and the reference zenith angle. The beam divergence angle adjustment is calculated based on the amplitude component of the spherical harmonic function coefficients. The horizontal deflection adjustment, pitch adjustment, and beam divergence angle adjustment are encoded into beam direction adjustment commands, which include the numerical value and sign of each adjustment.

7. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, In step S5, the specific process of generating the spectral compensation command for the basic lighting system based on the light intensity difference is as follows: A correspondence between light intensity difference and spectral power distribution is established. The correspondence is based on the eigenvector analysis of the Mueller matrix. The light intensity difference of each wavelength is input into the spectral reconstruction algorithm. The spectral reconstruction algorithm outputs the target spectral power distribution. The relative difference between the target spectral power distribution and the reference spectral power distribution is calculated. The intensity adjustment coefficient of each wavelength component is calculated based on the relative difference. The intensity adjustment coefficient is proportional to the singular value of the Mueller matrix. The intensity adjustment coefficient is converted into a drive current adjustment amount, which is linearly related to the intensity adjustment coefficient. The drive current adjustment amount corresponding to each wavelength is encoded as a spectral compensation command.

8. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, In step S6, the specific process by which the basic lighting system adjusts the lighting parameters according to the beam direction adjustment command and the spectral compensation command is as follows: The analysis focuses on the horizontal deflection adjustment, pitch adjustment, and beam divergence angle adjustment in the beam direction adjustment command. Based on the horizontal deflection adjustment, the horizontal deflection mechanism of the illumination unit is adjusted; the rotation angle of the horizontal deflection mechanism is proportional to the horizontal deflection adjustment. Similarly, based on the pitch adjustment, the pitch adjustment mechanism of the illumination unit is adjusted; the rotation angle of the pitch adjustment mechanism is proportional to the pitch adjustment. Finally, based on the beam divergence angle adjustment, the optical focusing system of the illumination unit is adjusted; the change in the lens spacing of the optical focusing system is proportional to the beam divergence angle adjustment. The drive current adjustment amount for each wavelength in the spectral compensation command is analyzed. The drive current of each wavelength light-emitting element in the lighting unit is adjusted according to the drive current adjustment amount. The change in drive current is proportional to the drive current adjustment amount. Each adjustment operation is executed in the order of directional adjustment first and then spectral adjustment.

9. The multi-objective optimization and collaborative control method for shelf lighting according to claim 1, characterized in that, The projection of a grid detection pattern containing multi-wavelength components onto the shelf surface is based on an auxiliary detection unit. The light emission direction of the light source component of the auxiliary detection unit is consistent with the light emission direction of the basic lighting system, and the optical sensor of the auxiliary detection unit establishes a data connection with the control unit of the basic lighting system. During the detection phase, the light source component of the auxiliary detection unit projects a grid detection pattern, and the optical sensor collects the reflected light signal; During the lighting adjustment phase, the control unit of the basic lighting system generates lighting parameter adjustment instructions based on the processing results of the reflected light signals.

10. A multi-objective optimization collaborative control device for shelf lighting, used to implement the multi-objective optimization collaborative control method for shelf lighting as described in any one of claims 1-9, characterized in that, include: The light source assembly is used to project a grid detection pattern containing multi-wavelength components onto the shelf surface. The node spacing of the grid detection pattern is proportional to the shelf shelf spacing. An optical sensor is used to collect the reflected light signal from the shelf surface to the grid detection pattern, and simultaneously record the spatial distribution data and spectral composition data of the reflected light signal; The signal processing unit is used to process spatially distributed data, extract the position coordinates of each node in the grid detection pattern, and calculate the offset vector of each node relative to the reference position. It also processes spectral composition data, decomposes the wavelength components of the reflected light signal, and calculates the difference between the light intensity value of each wavelength component and the reference light intensity value. The control unit is used to generate beam direction adjustment commands for the basic lighting system based on the direction and magnitude of the offset vector, and to generate spectral compensation commands for the basic lighting system based on the light intensity difference. The basic lighting system is used to adjust lighting parameters according to beam direction adjustment commands and spectral compensation commands.

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