Shadowless lamp remote control system and method based on multi-source fusion

Abstract

The present invention discloses a remote control system and method for a shadowless lamp based on multi-source fusion, which belongs to the field of shadowless lamp control. The system includes: a taboo area creation module for establishing taboo areas; an identification segmentation module for establishing important identifications of the area; an illumination constraint reconstruction module for reconstructing the illumination constraints of the shadowless lamp; a fitness function construction module for establishing a fitness function; an initialization module for creating multiple groups of lighting configurations; an evaluation module for establishing fitness analysis results; an iteration module for establishing optimization parameters based on updated iteration results; and a remote control module for remotely controlling the shadowless lamp. This application solves the technical problem in the prior art that shadowless lamps have poor illumination effects and are difficult to meet the precise lighting requirements in complex scenes, and achieves the technical effect of intelligent and precise remote control of shadowless lamps in complex environments.

Description

Technical Field Technical Field

[0002] The present invention relates to the field of shadowless lamp control, and in particular to a shadowless lamp remote control system and method based on multi-source fusion. Background Art

[0003] As an important lighting equipment in the operating room, the illumination effect of the shadowless lamp directly affects the accuracy and safety of the surgical operation. The traditional control method of the shadowless lamp usually relies on manual adjustment, which is not only cumbersome to operate, but also difficult to adapt to the lighting needs of complex surgical environments. Although there are some solutions for the automatic control of shadowless lamps in the prior art, the following deficiencies still exist: First, the existing shadowless lamp control solution lacks comprehensive consideration of factors such as obstructions and key illumination areas in the surgical environment, and cannot achieve precise adaptation to complex environments; second, the control of the shadowless lamp by the existing solution is usually based on preset modes or parameters, which lacks flexibility and adaptability, and it is difficult to meet the requirements for dynamic adjustment of lighting conditions during surgery; third, the existing solution lacks an intelligent optimization mechanism, and cannot achieve the optimal illumination effect when multiple lamps work together. Therefore, there are technical problems in the prior art that the shadowless lamp illumination effect is poor and it is difficult to meet the precise lighting needs in complex scenes. Summary of the Invention

[0004] This application provides a remote control system and method for a shadowless lamp based on multi-source fusion, aiming to solve the technical problems in the prior art that shadowless lamps have poor illumination effects and are difficult to meet the precise lighting requirements in complex scenes.

[0005] In view of the above problems, the present application provides a remote control system and method for a shadowless lamp based on multi-source fusion.

[0006] The first aspect disclosed in the present application provides a remote control system for a shadowless lamp based on multi-source fusion, the system comprising: a taboo area creation module for establishing a regional data set of a target area, and constructing the spatial coordinates of an obstruction based on the regional data set to establish a taboo area; an identification segmentation module for obtaining user input information, parsing the input information, dividing the target area into regions according to the parsed results of the input information, and establishing important regional identifications; an illumination constraint reconstruction module for reading shadowless lamp information, the shadowless lamp information including brightness limit value, position limit value, and adjustment angle limit value, and reconstructing the illumination constraint of the shadowless lamp according to the shadowless lamp information and the taboo area; a fitness function construction module for Establish the light intensity fitting of the location point, the light intensity fitting is the light intensity fitting under the collaboration of multiple shadowless lamps, and establish a fitness function based on the light intensity fitting and the regional importance identification; the initialization module is used to set the parameter limit values of the shadowless lamp according to the shadowless lamp information, and create multiple groups of lighting configurations within the parameter limit values; the evaluation module is used to optimize the fitness function through illumination constraints, perform fitness analysis of multiple groups of lighting configurations, and establish fitness analysis results; the iteration module is used to optimize and update multiple groups of lighting configurations according to the fitness analysis results, perform update iterations, and establish optimization parameters according to the update iteration results; the remote control module is used to remotely control the shadowless lamp through optimized parameters.

[0007] Another aspect disclosed in the present application provides a remote control method for a shadowless lamp based on multi-source fusion, the method comprising: establishing a regional data set of a target area, and constructing the spatial coordinates of an obstruction based on the regional data set, and establishing a taboo area; obtaining user input information, and parsing the input information, dividing the target area into regions according to the parsed results of the input information, and establishing regional importance identification; reading shadowless lamp information, the shadowless lamp information including brightness limit value, position limit value, and adjustment angle limit value, and reconstructing the illumination constraint of the shadowless lamp according to the shadowless lamp information and the taboo area; establishing illumination intensity fitting of a position point, the illumination intensity fitting is illumination intensity fitting under the collaboration of multiple shadowless lamps, and establishing a fitness function according to the illumination intensity fitting and the regional importance identification; setting parameter limit values of the shadowless lamp according to the shadowless lamp information, and creating multiple groups of lighting configurations within the parameter limit values; after optimizing the fitness function through illumination constraints, performing fitness analysis of the multiple groups of lighting configurations, and establishing fitness analysis results; optimizing and updating the multiple groups of lighting configurations according to the fitness analysis results, performing update iterations, and establishing optimization parameters according to the update iteration results; and remotely controlling the shadowless lamp through the optimized parameters.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] By using the taboo area creation module to establish a regional data set of the target area, and constructing the spatial coordinates of the obstruction based on the regional data set, a taboo area is established, thereby accurately calibrating the position of the obstruction in the surgical environment, providing boundary constraints for subsequent shadowless lamp irradiation control; the user's input information is obtained through the identification segmentation module, and the input information is analyzed. The target area is divided according to the input information analysis results, and important regional identification is established, thereby finely dividing the surgical area, calibrating the key irradiation areas, and achieving accurate expression of lighting requirements; the shadowless lamp information is read through the illumination constraint reconstruction module, including brightness limit value, position limit value, and adjustment angle limit value, and the illumination constraint of the shadowless lamp is reconstructed according to the shadowless lamp information and taboo area. Taking into account the shadowless lamp performance parameters and environmental constraints, the feasible working state space of the shadowless lamp is limited, providing a basis for subsequent optimization control; the light intensity fitting of the position point is established through the fitness function construction module. The light intensity fitting is the light intensity fitting under the collaboration of multiple shadowless lamps, and the fitness function is established according to the light intensity fitting and regional importance identification. A mapping relationship between the illumination parameters of the shadowless lamp and the illumination effect is established and expressed as a mathematical model to provide an objective function for subsequent intelligent optimization; the initialization module sets the parameter limit values of the shadowless lamp according to the information of the shadowless lamp, and creates multiple sets of lighting configurations within the parameter limit values, generates an initial feasible solution in the constraint space, and provides a starting point for subsequent optimization; after optimizing the fitness function through the evaluation module, fitness analysis of multiple sets of lighting configurations is performed, and fitness analysis results are established. The candidate solutions are evaluated through the fitness function to screen out lighting configurations with excellent performance; the iteration module searches for the optimal update of multiple sets of lighting configurations according to the fitness analysis results, performs update iterations, establishes optimization parameters according to the update iteration results, and finds the optimal lighting configuration parameters through iterative search; the remote control module uses the optimized parameters to remotely control the shadowless lamp, and sends the optimal control parameters to the shadowless lamp to achieve dynamic adjustment and meet the lighting needs. The technical solution solves the technical problems in the existing technology that the shadowless lamp has poor illumination effect and is difficult to meet the precise lighting needs in complex scenes, and achieves the technical effect of intelligent and precise remote control of the shadowless lamp in a complex environment.

[0010] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A structural schematic diagram of a shadowless lamp remote control system based on multi-source fusion is provided for an embodiment of the present application.

[0012] Figure 2A flowchart of a remote control method for a shadowless lamp based on multi-source fusion is provided for an embodiment of the present application;

[0013] Explanation of the reference numerals: taboo region creation module 11 , identification segmentation module 12 , irradiation constraint reconstruction module 13 , fitness function construction module 14 , initialization module 15 , evaluation module 16 , iteration module 17 , remote control module 18 . DETAILED DESCRIPTION

[0014] The overall idea of the technical solution provided by this application is as follows:

[0015] The embodiment of the present application provides a remote control system and method for a shadowless lamp based on multi-source fusion. The surgical environment is refined by the taboo area creation module and the identification segmentation module, the performance parameters of the shadowless lamp are limited by the illumination constraint reconstruction module, the optimization objective function is established by the fitness function construction module, and intelligent optimization is achieved through the initialization module, the evaluation module and the iteration module. Finally, the optimal parameters are applied to the shadowless lamp adjustment through the remote control module to form an intelligent control solution for the shadowless lamp. The intelligent and refined control of the shadowless lamp is achieved through the fusion processing of multi-source heterogeneous information, which effectively improves the quality of surgical lighting.

[0016] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the drawings in the specification.

[0017] Example 1

[0018] like Figure 1 As shown, the embodiment of the present application provides a remote control system for a shadowless lamp based on multi-source fusion, the system comprising:

[0019] The taboo area creation module 11 is used to establish a regional data set of the target area, and construct the spatial coordinates of the obstruction based on the regional data set to establish the taboo area.

[0020] Specifically, the target area is the surgical field, the area that requires shadowless lighting. The surgical field may be obstructed by various objects, such as surgical instruments and the hands of medical staff. These obstructions can block the light from the shadowless lamp, casting shadows within the surgical area and affecting the surgeon's field of view. Therefore, the locations of these obstructions are identified and the areas within them are marked as prohibited areas.

[0021] First, the taboo area creation module 11 establishes a regional dataset for the target area. A regional dataset is a collection of data representing the spatial information of the target area. Images or data of the surgical area are collected by cameras, sensors, and other equipment installed in the operating room. This dataset contains information such as the spatial position and shape of objects within the target area, forming the regional dataset and providing the data foundation for subsequent identification of obstructions. After obtaining the regional dataset, the taboo area creation module 11 constructs the spatial coordinates of the obstructions based on the regional dataset, representing their positions in three-dimensional space. To obtain the spatial coordinates of the obstructions, an object detection algorithm is used to identify specific objects, such as surgical instruments and hands, from the regional dataset. After identifying the obstructions, the pixel coordinates are obtained. Combining the camera's internal and external parameters, the pixel coordinates are converted into spatial coordinates to determine the obstructions' specific positions in three-dimensional space. After obtaining the spatial coordinates of the obstructions, the taboo area creation module 11 marks the area containing the obstructions as a taboo area. The taboo area is represented as a three-dimensional spatial region within which the shadowless light must avoid. Based on the shape of the obstructions, a buffer zone is set around them to form the taboo area. In this way, the shadowless lamp can not only avoid directly irradiating the obstruction, but also avoid irradiating the area near the obstruction, preventing shadows.

[0022] The identification segmentation module 12 is used to obtain user input information, analyze the input information, divide the target area into regions according to the analysis results of the input information, and establish important regional identifications.

[0023] Specifically, during surgery, different locations within the target area may have different lighting requirements for shadowless lamps. For example, the surgical incision requires stronger lighting, while the surrounding area requires relatively lower lighting intensity. To achieve more refined shadowless lamp control, the surgical area is divided and the lighting requirements of different areas are identified.

[0024] First, the user can input information about the division of the surgical area through various input devices, such as mobile phone terminals, computer terminals, etc., and the identification and segmentation module 12 receives the user's input information. For example, the user draws different areas on the image of the surgical area and sets lighting requirements for each area. After obtaining the user input, the identification and segmentation module 12 parses the input information. For example, based on the image processing algorithm, the different areas drawn by the user are identified; for example, the text information input by the user is analyzed, keywords are extracted, and the lighting requirements of each area are understood. Based on the results of the input information analysis, the identification and segmentation module 12 divides the target area into regions. Each sub-region after division has clear boundaries and lighting requirements. These sub-regions can be surgical wounds, instrument placement areas, surrounding areas, etc., with different lighting requirements.

[0025] After completing the area division, the identification segmentation module 12 establishes an area importance indicator for each sub-area. The area importance indicator is a numerical value that indicates the lighting requirement for that area. A higher value indicates a more intense, concentrated lighting requirement. The identification segmentation module 12 calculates the importance indicator for each sub-area based on the user input. For example, an area marked as a surgical wound by the user will have its importance indicator set to a higher value.

[0026] Through processing by the marker segmentation module 12, the target area is divided into multiple sub-areas, each with clear lighting requirements and importance. This provides more detailed reference information for subsequent shadowless lamp control, allowing for flexible adjustment of light intensity and direction based on important markers in different areas, achieving more refined lighting control. Compared with traditional indiscriminate lighting, this can achieve more precise and practical shadowless lamp control, providing a better lighting environment.

[0027] The irradiation constraint reconstruction module 13 is used to read the shadowless lamp information, which includes brightness limit value, position limit value, and adjustment angle limit value, and reconstruct the irradiation constraint of the shadowless lamp according to the shadowless lamp information and the taboo area.

[0028] Specifically, shadowless lamps are surgical lighting devices, and their performance parameters, such as brightness, position, and adjustment angle, are subject to certain restrictions. Furthermore, restricted areas also impose constraints on the illumination behavior of shadowless lamps, and shadowless lamps must avoid directly irradiating restricted areas.

[0029] First, the illumination constraint reconstruction module 13 obtains shadowless lamp information by reading the product manual, parameter table, etc., including parameters such as brightness limit, position limit, and adjustment angle limit, which describe the upper and lower limits of various performance indicators of the shadowless lamp. Among them, the brightness limit defines the adjustable range of the shadowless lamp's illumination intensity; the position limit defines the spatial boundary within which the shadowless lamp can move; and the adjustment angle limit defines the adjustable angle range of the shadowless lamp's illumination direction. These limit values can be obtained through a method. After obtaining the shadowless lamp information, the illumination constraint reconstruction module 13 combines the taboo area information to reconstruct the illumination constraints of the shadowless lamp. Specifically, the illumination constraint reconstruction module 13 further introduces taboo area restrictions based on the original performance limits of the shadowless lamp, so that when adjusting the brightness, position, and angle of the shadowless lamp, not only does it meet its own performance limits, but it also avoids direct light exposure to the taboo area. For example, assume that the position limit of the shadowless lamp defines its movable spatial boundary. At the same time, the taboo area creation module demarcates the taboo area where a certain surgical instrument is located. When reconstructing the constraints, the illumination constraint reconstruction module 13 deducts the taboo area from the movable range of the shadowless lamp. This prevents the shadowless lamp from entering the taboo area during movement, thus preventing direct exposure to surgical instruments. Similarly, when adjusting the brightness and angle, the shadowless lamp also avoids direct light into the taboo area.

[0030] Through the processing of the illumination constraint reconstruction module 13, the illumination constraints of the shadowless lamp are reconstructed and optimized. The reconstructed illumination constraints not only take into account the performance limits of the shadowless lamp itself, but also incorporate the restrictions of taboo areas. This allows the shadowless lamp to meet its own performance requirements while avoiding interfering illumination of obstructions within the surgical area, thereby better adapting to the needs of the surgical environment. Compared with traditional shadowless lamp control methods, it can better adapt to the complex constraints of the surgical environment, reduce interference with surgical operations, and provide higher-quality lighting assurance.

[0031] The fitness function building module 14 is used to establish a light intensity fitting of a location point, wherein the light intensity fitting is a light intensity fitting under the cooperation of multiple shadowless lamps, and a fitness function is established according to the light intensity fitting and the regional importance identifier.

[0032] Specifically, the fitness function construction module 14 first establishes a light intensity fitting for the position point. This fitting estimates the light intensity that can be obtained under a given shadowless lamp configuration for each position point in the operating area. In actual surgery, multiple shadowless lamps are often deployed for collaborative lighting to obtain a more uniform and sufficient lighting effect. Therefore, the fitting process of the fitness function construction module 14 combines the position, angle, brightness and other parameters of multiple shadowless lamps to calculate the light intensity that can be obtained at each position point under the joint action of these shadowless lamps. Among them, the light intensity fitting can be implemented using different mathematical models, such as radiometric models, Monte Carlo ray tracing models, etc. Through these models, the luminous flux received by each position point is estimated by considering factors such as the propagation, attenuation, and reflection of light in space. The light intensity distribution obtained by fitting reflects the actual light level of each position in the operating area under the current shadowless lamp configuration.

[0033] After completing the light intensity fitting, the fitness function construction module 14 establishes a fitness function in combination with the regional importance identifier. The regional importance identifier is generated by the aforementioned identifier segmentation module, which characterizes the degree of demand for light intensity in different areas within the surgical area. The role of the fitness function is to evaluate the degree of match between the light intensity distribution and the regional importance identifier. Specifically, the fitness function comprehensively considers two factors: light intensity and regional importance. For example, the fitness function calculates the weighted difference between the light intensity of each position point and the importance of the area where it is located, and then accumulates or averages the difference values of all position points. The smaller the difference, the more the lighting effect of the shadowless lamp matches the regional requirements, and the higher the value of the fitness function.

[0034] Through the processing of the fitness function construction module 14, a fitness function for evaluating the shadowless lamp lighting scheme is obtained to quantitatively evaluate the lighting effect under any set of shadowless lamp configuration parameters, providing a target basis for the optimization control of the shadowless lamp.

[0035] The initialization module 15 is used to set parameter limits of the shadowless lamp according to the shadowless lamp information, and create multiple groups of lighting configurations within the parameter limits.

[0036] Specifically, before using the fitness function to optimize the shadowless lamp configuration, the optimization algorithm first sets the initial conditions and search space. Initialization module 15 sets the value range of its adjustable parameters based on the inherent properties of the shadowless lamp and generates an initial set of lighting configurations within this range, providing a starting point for the subsequent optimization search.

[0037] First, the initialization module 15 sets the parameter limits of the shadowless lamp based on the shadowless lamp information. The shadowless lamp information includes brightness limits, position limits, adjustment angle limits, etc., reflecting the adjustable range of the various performance parameters of the shadowless lamp. The initialization module 15 reads these limits from the shadowless lamp information and uses them as constraints for the optimization control of the shadowless lamp, defining the value boundaries of the shadowless lamp parameters. The optimization algorithm cannot cross these boundaries during the search process to avoid generating configuration solutions that are unfeasible or may damage the equipment. After setting the parameter limits, the initialization module 15 creates multiple sets of lighting configurations within the limit range. A lighting configuration is a combination of a set of shadowless lamp parameters, including the position coordinates, angle, brightness, etc. of each shadowless lamp. A lighting configuration corresponds to a lighting solution for the shadowless lamp. The initialization module 15 uses random number generation to generate a certain number of lighting configurations under the constraints of the parameter limits. Multiple sets of lighting configurations cover different areas within the parameter space and provide a starting point for the optimization search.

[0038] Initialization module 15 sets the starting conditions and search space for the shadowless lamp optimization control. Based on the lamp information, initialization module 15 sets the value boundaries for the optimization parameters and generates multiple sets of initial configurations distributed within the parameter space. This provides the necessary prior conditions for the optimization algorithm to run, helping to quickly and efficiently find the optimal shadowless lamp configuration solution.

[0039] The evaluation module 16 is configured to perform fitness analysis on multiple groups of lighting configurations after optimizing the fitness function using the illumination constraints, and to establish fitness analysis results.

[0040] Specifically, after the initialization module generates multiple lighting configurations, it evaluates the pros and cons of each configuration to select the optimal solution. The evaluation module 16 uses a fitness function to score each lighting configuration and obtain a corresponding fitness value, which provides a basis for subsequent optimization and screening.

[0041] First, the evaluation module 16 performs illumination constraint optimization on the fitness function. The so-called illumination constraint optimization means that when calculating the fitness function value, the illumination constraints of the shadowless lamp need to be considered. Irradiation constraints include parameter limit constraints and taboo area constraints. Parameter limit constraints ensure that the shadowless lamp parameters in the lighting configuration do not exceed the equipment capability range; taboo area constraints prevent the shadowless lamp from directly irradiating obstructions within the surgical area. During the calculation of the fitness function, the evaluation module 16 checks whether each set of lighting configurations meets these constraints. For configurations that violate the constraints, the evaluation module 16 directly sets its fitness value to 0 or a negative number, indicating that it is an infeasible solution.

[0042] After optimizing the illumination constraints, the evaluation module 16 performs a fitness analysis on multiple lighting configurations. Each lighting configuration is substituted into the optimized fitness function to calculate its fitness value. The fitness function comprehensively considers the degree to which the configuration's light intensity distribution matches the surgical area's requirements. A higher fitness value indicates a configuration that better meets surgical lighting requirements. Using the fitness function, the evaluation module 16 quantifies the performance of each lighting configuration into a numerical metric for easy comparison and screening.

[0043] For example, suppose the initialization module generates 100 sets of lighting configurations, each of which contains the position, angle, and brightness parameters of three shadowless lamps. The evaluation module 16 first checks whether the parameters in each set of configurations meet the equipment limit constraints. For configurations that exceed the range, the fitness value is set to 0. Then, the evaluation module 16 checks whether the configured lighting area covers the taboo area. For configurations that directly illuminate the taboo area, the fitness value is also set to 0. Finally, the evaluation module 16 substitutes the configuration that meets the constraints into the fitness function and calculates its fitness value. The evaluation module 16 summarizes the fitness values of all configurations to obtain the fitness analysis results, which provide a basis for the next optimization iteration.

[0044] Each candidate lighting configuration receives a quantitative fitness assessment through evaluation module 16. By optimizing the fitness function and illumination constraints, evaluation module 16 comprehensively considers the configuration's feasibility and lighting performance, producing objective and accurate fitness analysis results that reflect the strengths and weaknesses of each configuration and serve as the basis for optimization, screening, and iterative updates.

[0045] The iteration module 17 is used to optimize and update the multiple lighting configurations according to the fitness analysis results, perform update iterations, and establish optimization parameters according to the update iteration results.

[0046] Specifically, after the evaluation module calculates the fitness value of each lighting configuration, the configuration scheme is optimized and improved based on the fitness analysis results. The iteration module 17 iteratively updates the lighting configuration, continuously improving its fitness until the optimal shadowless lamp control parameters are found.

[0047] First, iterative module 17 optimizes and updates multiple lighting configurations based on the fitness analysis results. Based on the fitness values, it adjusts the shadowless lamp parameters within the lighting configurations to improve the lighting performance of the configurations. Iterative module 17 uses an optimization algorithm to achieve this optimization update, such as a genetic algorithm, a particle swarm optimization algorithm, or a simulated annealing algorithm. Through repeated iteration and searching, it finds the point with the highest fitness within the parameter space. Using a genetic algorithm as an example, iterative module 17 treats each lighting configuration as an individual, with the shadowless lamp parameters as the individual's genes. Based on the fitness analysis results, iterative module 17 selects configurations with higher fitness as high-quality individuals. It then performs genetic operations such as crossover and mutation on the parameters of these high-quality individuals to generate new offspring individuals. These offspring inherit the high-quality genes of their parents while also introducing new mutations, potentially achieving even higher fitness. Iterative module 17 repeats this process, eliminating low-fitness individuals from the current population, retaining high-fitness individuals and generating new offspring, thereby continuously improving the fitness level of the entire population. After completing a round of optimization and update, iterative module 17 evaluates the update results and decides whether to continue iterating. At the same time, the iteration module 17 sets a fitness threshold or a maximum number of iterations as a termination condition. When the fitness of the updated lighting configuration exceeds the threshold, or the number of iterations reaches a preset upper limit, the iteration module 17 stops updating and outputs the current optimal configuration as the optimization parameter.

[0048] Through iterative module 17, the fitness analysis results are used to intelligently adjust and search the shadowless lamp parameters, allowing the configuration scheme to continuously evolve towards high fitness, thereby efficiently and reliably finding the optimal shadowless lamp control parameter combination. Compared with manual parameter adjustment, this method can more efficiently and accurately find the optimal solution in a complex parameter combination space, thereby maximizing the lighting performance of the shadowless lamp.

[0049] The remote control module 18 is used to remotely control the shadowless lamp using the optimized parameters.

[0050] Specifically, after the iterative module generates the optimized parameters, the optimized parameters are applied to the actual shadowless lamp equipment to improve the surgical lighting effect.

[0051] First, the remote control module 18 establishes a communication connection with the shadowless lamp. This connection can be wired, such as Ethernet or a serial port, or wireless, such as WiFi, Bluetooth, or Zigbee. Using standardized communication protocols, the remote control module 18 establishes a channel for data transmission and control command exchange with the shadowless lamp, providing the basis for remote adjustment of the lamp's operating parameters. After establishing the communication connection, the remote control module 18 transmits the optimized parameters generated by the iteration module to the shadowless lamp, including the position coordinates, angle, and brightness of each lamp. After the shadowless lamp receives the optimized parameters, the remote control module 18 triggers the lamp to perform adjustments. For each parameter, the lamp's actuators begin to operate, adjusting the device's position, angle, and brightness. For example, the lamp's pitch motor rotates the lamp according to the angle parameter value to achieve the specified pitch angle; the lamp's stepper motor drives the lamp along the guide rail according to the position coordinate value to achieve the specified spatial position; and the lamp's dimming circuit adjusts the LED current according to the brightness parameter value to achieve the specified light intensity. During the operation, the control unit of the shadowless lamp monitors the status of each actuator in real time to ensure accurate and precise adjustments. Once all adjustments are complete, the optimal lighting effect in the surgical area is achieved. Simultaneously, the remote control module 18 monitors the feedback signals from each lamp to verify that the adjustment results match the optimized parameters. If any deviation occurs, the remote control module 18 issues a correction command, instructing the lamp to make fine adjustments until the lighting effect meets the requirements.

[0052] Furthermore, the fitness function building module also includes:

[0053] Construct the light intensity fitting formula as follows:

[0054] ;

[0055] in, Characterization Point The light intensity, is the total number of shadowless lamps, Indicates the A shadowless lamp, For the The brightness of a shadowless lamp, Characterization The position of a shadowless lamp, For the Shadowless lamp to point The light is perpendicular to The angle of the surface, is a constant, is the light attenuation coefficient in space;

[0056] Configure the illumination uniformity index, the impact minimization index and the lighting efficiency index, construct the illumination point fitness by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the light intensity, optimize the illumination point fitness by the regional importance identification, and construct a fitness function.

[0057] In a feasible implementation, when constructing the fitness function, the fitness function construction module 14 first constructs a light intensity fitting formula: . Among them, the right side of the equation is Sum up the light intensity contributions of the shadowless lamps. A shadowless lamp, Indicates the The brightness parameter of a shadowless lamp reflects the luminous flux of the lamp; Indicates the The cosine of the incident angle of the shadowless lamp light; For the Shadowless lamp to point The light and The angle between the normal and the plane; Indicates a point To Shadowless lamp position distance, The denominator of reflects the attenuation law that the light intensity is inversely proportional to the square of the distance. is a constant to avoid the denominator being zero; It represents the exponential attenuation caused by the absorption of the medium during the propagation of light in space. is the absorption coefficient of the medium, which reflects the attenuation ratio of light intensity after propagating a certain distance in space; the formula for fitting light intensity is based on the coordinates of the position point in the surgical area. As the independent variable, calculate the illumination intensity of the point under the joint illumination of multiple shadowless lamps Through the formula for light intensity fitting, the fitness function construction module 14 can calculate the light intensity at any position within the surgical area under given shadowless lamp parameters, laying the foundation for the subsequent construction of the fitness function.

[0058] After constructing the formula for fitting the light intensity, the fitness function construction module 14 is configured with three lighting performance indicators, namely the illumination uniformity index, the impact minimization index and the lighting efficiency index. Among them, the illumination uniformity index reflects the uniformity of the light intensity distribution in the target area; the impact minimization index reflects the degree of occlusion and interference of the shadowless lamp beam on the surgical field of view; and the lighting efficiency index reflects the energy consumption ratio of the shadowless lamp system. The fitness function construction module 14 constructs the fitness function of the lighting point through these three indicators and the aforementioned light intensity fitting formula, and comprehensively evaluates the performance of the lighting point with the light intensity, uniformity, impact and efficiency of the lighting point as parameters. Finally, the fitness function construction module 14 further optimizes the fitness function of the lighting point in combination with the importance identification of the surgical area. The importance identification reflects the difference in weights of the lighting requirements of different positions in the surgical area. Through importance weighting, the fitness function can focus on meeting the lighting needs of key areas and achieve more refined optimization control of the shadowless lamp.

[0059] Furthermore, the embodiment of the present application also includes:

[0060] The calculation formulas for the illumination uniformity index, impact minimization index, and lighting efficiency index are established as follows:

[0061] ;

[0062] ;

[0063] ;

[0064] in, is the illumination uniformity index, Characterize the area under consideration The light intensity at all points within The minimum value of Characterize the area under consideration The light intensity at all points within The average value of To minimize the impact of the index, Characterize the abnormal shadow area, Characterizes the total irradiated area, is the lighting efficiency index, is the total power consumption of the lighting system;

[0065] The weights of illumination uniformity index, impact minimization index and lighting efficiency index are established, and the adaptability of illumination points is configured according to the weights.

[0066] In a preferred embodiment, when the fitness function construction module 14 constructs the fitness of the illumination point by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the illumination intensity, the fitness function construction module 14 establishes the calculation formulas of the uniformity index, the impact minimization index and the lighting efficiency index.

[0067] The calculation formula for the illumination uniformity index is: .in, is the illumination uniformity index, Indicates the surgical area The minimum light intensity of all points in the Represents the average light intensity of all locations in the area. The value range is from 0 to 1. The closer it is to 1, the more uniform the illumination distribution in the area.

[0068] The calculation formula of the impact minimization index is: .in, Indicates the area of abnormal shadows within the surgical area. Represents the area of the entire surgical field. The value range is from 0 to 1. The closer it is to 1, the smaller the proportion of abnormal shadow area is, and the smaller the impact on the surgical field of view is.

[0069] The calculation formula of lighting efficiency index is: .in, Indicates the total power consumption of the shadowless lamp system. The physical meaning of is the average luminous flux per unit power consumption, which reflects the energy efficiency of the shadowless lamp. The larger the value, the more efficient the lighting system.

[0070] Through the calculation formulas of the above three indicators, the fitness function construction module 14 can quantitatively evaluate the lighting uniformity, shadow impact and energy efficiency under any set of shadowless lamp parameters, laying a quantitative indicator foundation for constructing the fitness of the lighting point.

[0071] After obtaining the above three indicators, the fitness function construction module 14 introduces indicator weights. By setting different weights, the relative importance of the three indicators in fitness evaluation is adjusted. For example, if the surgery requires higher uniformity of light, If you value the energy efficiency of the shadowless lamp more, then increase By weighted averaging the three indicators, the fitness function construction module 14 obtains a quantified fitness value of the lighting point, which comprehensively reflects the lighting performance of the lighting point.

[0072] Furthermore, the initialization module also includes:

[0073] Creating a search space based on the parameter limit values, wherein the search space is a search space for multiple sets of lighting configurations and optimization updates;

[0074] Establish the distribution ratio of random solutions and preset solutions, and set the initial solution size;

[0075] Performing an optimal solution matching search in the search space according to the distribution ratio to establish an initial preset solution, and performing a random search under a non-initial preset solution in the search space according to the distribution ratio to establish an initial random solution;

[0076] A plurality of lighting configurations are created according to the initial preset solution and the initial random solution.

[0077] In one feasible implementation, when creating multiple sets of initial lighting configurations, the initialization module 15 first establishes a parameter search space based on the parameter limits of the shadowless lamp. This search space is a multi-dimensional continuous parameter domain, with each dimension corresponding to an adjustable parameter of the shadowless lamp, such as the lamp's position coordinates, angle, and brightness. The parameter range is determined by the physical limits of the shadowless lamp and constitutes the boundaries of the search space. This search space covers all possible lighting configuration combinations and serves as the basis for subsequent generation and optimization of multiple sets of initial solutions. Secondly, when generating initial solutions within the search space, the initialization module 15 adopts a hybrid strategy of random solutions and preset solutions. The initialization module 15 first establishes the distribution ratio of random solutions to preset solutions and sets the total number of initial solutions. Random solutions are configurations generated completely randomly within the search space and are highly exploratory; preset solutions are configurations generated based on prior knowledge or empirical rules and are more targeted. By setting the ratio between the two, a balance is achieved between exploration and utilization. After determining the number of random solutions and preset solutions, the initialization module 15 begins generating specific initial configurations within the search space. For preset solutions, Initialization Module 15 employs an optimal solution matching search strategy. Based on existing optimal lighting configuration samples, it searches for similar configurations in the search space as the initial preset solution. This similarity-based matching search leverages existing knowledge of high-quality configurations and quickly identifies promising solution regions. For random solutions, Initialization Module 15 performs purely random sampling within non-preset solution regions to evenly cover the rest of the solution space and explore new possibilities. Initialization Module 15 then combines the generated preset and random solutions to form multiple sets of initial lighting configurations. These configurations cover different characteristic regions of the solution space, providing high-quality search starting points for subsequent optimization, accelerating optimization convergence and improving search efficiency.

[0078] By constructing a parameter search space and generating a mix of random and preset solutions, an initialization strategy was implemented that balances exploratory and targeted approaches. This strategy fully leverages prior information and empirical knowledge about shadowless lamp parameters while also allowing for sufficient freedom and novelty in the optimization search. Compared to simple random initialization, the resulting sets of lighting configurations are of higher quality and more rationally distributed, significantly improving the search efficiency and optimization performance of the optimization algorithm.

[0079] Furthermore, the iteration module also includes:

[0080] Get the lighting configuration corresponding to the maximum fitness in the fitness analysis results;

[0081] Taking the lighting configuration as an optimization target, performing position updates of multiple lighting configurations at preset step sizes;

[0082] Update multiple lighting configurations based on the position update results to complete a round of optimization update.

[0083] In a preferred embodiment, the iteration module 17 first obtains the lighting configuration corresponding to the maximum fitness value from the fitness analysis results output by the evaluation module 16. This represents the lighting configuration with the best overall performance among all current candidate solutions and represents the optimal configuration found during the search process. The iteration module 17 uses this as the target for this round of optimization update and, with it as the center, conducts a local fine-grained search in the solution space. Secondly, the iteration module 17 uses this optimal configuration as the starting point to perform position updates on multiple sets of candidate configurations. Position updates refer to fine-tuning the configuration along a specific direction and step size within the shadowless lamp parameter space. Position updates employ a preset step size strategy, where the iteration module 17 pre-sets the step size for each parameter dimension, such as a 10 cm step size for the position parameter, a 5 degree step size for the angle parameter, and a 0.1 step size for the brightness parameter. During the update, the iteration module 17 uses the optimal configuration as the center and explores each parameter dimension in both positive and negative directions according to the preset step size, generating a series of new candidate configurations. This local search based on the predetermined step size allows for fine-tuning near the optimal solution to find a configuration with higher performance.

[0084] Afterwards, iteration module 17 updates the existing multiple lighting configurations based on the results of the position update. For each existing configuration, iteration module 17 finds its corresponding newly generated configuration and compares the fitness values of the two. If the new configuration has a higher fitness, it replaces the existing one; otherwise, the existing one remains unchanged. Through this update strategy, iteration module 17 iteratively optimizes the candidate solution population, eliminating configurations with lower fitness and adding new configurations with better performance, thereby continuously enhancing the search capabilities of the entire population. After completing a round of position updates, iteration module 17 outputs the updated multiple lighting configurations, preparing for the next round of iterations.

[0085] By obtaining the optimal configuration, updating the position with a preset step size, and updating the population based on optimality, an iterative optimization strategy based on local fine search is implemented. This strategy focuses on potential areas around the optimal solution and continuously discovers higher-performance configurations through step size exploration, allowing the optimization search to continuously converge to the optimal solution in the solution space. Compared with strategies such as random search, this strategy is more efficient and accurate, and can obtain higher-quality shadowless lamp parameter combinations with fewer iterations.

[0086] Furthermore, the embodiment of the present application also includes:

[0087] Compare the fitness of the updated position result with the original position and establish a fitness decay penalty factor;

[0088] Determining whether the fitness decay penalty factor meets a continuous trigger threshold, and if the fitness decay penalty factor meets the continuous trigger threshold, generating a backtracking instruction;

[0089] Based on the backtracking instruction, the corresponding parameters are backtracked to the parameters for which no fitness decay penalty factor is generated.

[0090] In one feasible implementation, when updating the lighting configuration, iteration module 17 simultaneously compares the fitness of the updated position result with the original configuration. Specifically, for each newly generated configuration, iteration module 17 calculates its fitness value and compares it with the fitness of the corresponding original configuration. If the fitness of the new configuration is lower than that of the original configuration, this indicates that the position update has not resulted in performance improvement, but instead has caused fitness degradation. To address this situation, iteration module 17 establishes a fitness degradation penalty factor to quantify the negative impact of the update. The degradation penalty factor is a value between 0 and 1, with the greater the degradation, the larger the penalty factor. After generating the degradation penalty factor, iteration module 17 further determines whether it meets a preset continuous trigger threshold. The continuous trigger threshold refers to the upper limit of the number of fitness degradations that can occur during multiple consecutive updates. If the cumulative value or number of degradation penalties exceeds the threshold within a certain number of iterations, it indicates that the current update strategy has fallen into a localized poor performance area and requires strategy adjustment. In this case, iteration module 17 generates a backtracking instruction, initiating a parameter backtracking mechanism to self-correct the search process.

[0091] Afterwards, the iterative module 17 will backtrack the parameters that caused the fitness decay to the previous state according to the backtracking instruction. Specifically, the iterative module 17 finds the configuration that did not trigger the decay penalty the most recently, uses it as the new search starting point, and replaces the current decay configuration. Through such parameter backtracking, the iterative module 17 can jump out of the local bad area and restart the search direction with more potential. At the same time, in order to avoid the search from falling into a loop due to unlimited backtracking, the iterative module 17 will also record the number of backtrackings during the backtracking process and set a limit on the maximum number of backtrackings. When the number of backtrackings exceeds the limit, the iterative module 17 will end the current search process and return the optimal configuration found so far as the final result.

[0092] Adaptive optimization update strategies can adapt to complex and changing search environments, promptly identifying undesirable conditions during the search process and redirecting the search towards more promising areas. Compared to fixed search schemes, the ability to dynamically adjust strategies based on real-time feedback significantly improves optimization efficiency and success rate.

[0093] Furthermore, the embodiment of the present application also includes:

[0094] The multi-source feedback module is used to monitor the data of the target area through integrated sensors to build a monitoring data set, perform consistency authentication of the control through the monitoring data set and the optimization parameters, and generate abnormal feedback according to the consistency authentication result.

[0095] In a preferred embodiment, a multi-source feedback module is added to achieve real-time monitoring of the target area and control quality assessment, and generate abnormal feedback based on the assessment results to guide the shadowless lamp control to perform self-correction.

[0096] First, the multi-source feedback module uses integrated sensors to monitor data from the target area and construct a monitoring dataset. Integrated sensors refer to various sensing devices deployed within the target area, such as light intensity sensors, infrared thermal imagers, and visible light cameras. These sensors collect real-time data on the surgical site's status from different physical perspectives, forming a comprehensive, three-dimensional monitoring dataset. For example, light intensity sensors measure the actual illuminance distribution within the target area, thermal imagers detect temperature changes in the surgical field, and visible light cameras capture video images of the surgical scene. By integrating data from multiple sensors, the monitoring dataset can accurately and accurately reflect the actual effects of surgical lighting in a multi-dimensional and high-fidelity manner.

[0097] Secondly, the multi-source feedback module uses the monitoring data set to evaluate the actual control performance of the shadowless light. Specifically, the multi-source feedback module compares the monitoring data with the optimized parameters output by the iteration module and performs consistency verification. Consistency verification examines the degree of agreement between the actual lighting performance and the expected optimized performance. For example, the multi-source feedback module calculates the difference between the actual illuminance distribution monitored and the target illuminance distribution corresponding to the optimized parameters, generating an illuminance deviation value as the consistency verification result. Subsequently, the multi-source feedback module generates corresponding exception feedback based on the consistency verification result. If the consistency verification result indicates a significant deviation between the actual lighting performance and the expected performance, the multi-source feedback module generates a deviation alert, indicating that the current control performance does not meet the standard. The alert information includes the deviation amount, deviation type (such as uneven illumination, temperature anomaly, poor lighting effect), and deviation location, providing a basis for correcting the deviation in shadowless light control. Upon receiving the exception feedback, the iteration module quickly responds, restarting the optimization process and making targeted adjustments to the control parameters until the deviation is eliminated and quality requirements are met. Through closed-loop control with real-time monitoring and feedback correction, the shadowless light can continuously improve and maintain optimal lighting performance.

[0098] In summary, the shadowless lamp remote control system based on multi-source fusion provided by the embodiments of the present application has the following technical effects:

[0099] The taboo area creation module is used to establish a regional data set for the target area, and construct the spatial coordinates of the obstruction based on the regional data set to establish the taboo area, provide spatial constraints for the shadowless lamp illumination, and avoid the light beam being blocked. The identification segmentation module is used to obtain the user's input information and parse the input information. According to the results of the input information analysis, the target area is divided into regions, important regional identifications are established, and the lighting requirements are expressed in a refined manner to provide a basis for the subsequent optimization of the lighting intensity distribution. The illumination constraint reconstruction module is used to read the shadowless lamp information. The shadowless lamp information includes brightness limit values, position limit values, and adjustment angle limit values. The illumination constraints of the shadowless lamp are reconstructed according to the shadowless lamp information and the taboo area. The optimization space is reconstructed according to the equipment performance and environmental constraints to reduce the complexity of the problem solution. The fitness function construction module is used to establish the lighting intensity fitting of the position point. The light intensity fitting is the light intensity fitting under the collaboration of multiple shadowless lamps. The fitness function is established based on the light intensity fitting and the regional importance identification, and the lighting requirements are mathematized to provide optimization direction for the intelligent algorithm. The initialization module is used to set the parameter limits of the shadowless lamp according to the information of the shadowless lamp, and to create multiple sets of lighting configurations within the parameter limits to provide a search starting point for the optimization algorithm. The evaluation module is used to perform fitness analysis on multiple sets of lighting configurations after optimizing the fitness function through illumination constraints, establish fitness analysis results, and thus estimate the pros and cons of the current solution to guide the direction of subsequent iterative searches. The iteration module is used to optimize and update multiple sets of lighting configurations according to the fitness analysis results, perform update iterations, and establish optimization parameters based on the update iteration results, so as to effectively search the parameter space and find the global optimal point. The remote control module is used to remotely control the shadowless lamp by optimizing parameters, thereby realizing intelligent and precise remote control of the shadowless lamp in complex environments.

[0100] Example 2

[0101] Based on the same inventive concept as the shadowless lamp remote control system based on multi-source fusion in the aforementioned embodiment, Figure 2 As shown, an embodiment of the present application provides a remote control method for a shadowless lamp based on multi-source fusion, the method comprising:

[0102] Establishing a regional data set of the target area, constructing the spatial coordinates of the obstruction based on the regional data set, and establishing a taboo area;

[0103] Obtain user input information, parse the input information, divide the target area into regions based on the parsed results, and establish important regional identifiers;

[0104] Reading shadowless lamp information, the shadowless lamp information including a brightness limit value, a position limit value, and an adjustment angle limit value, and reconstructing the irradiation constraint of the shadowless lamp according to the shadowless lamp information and the taboo area;

[0105] Establishing a light intensity fitting for a location point, wherein the light intensity fitting is a light intensity fitting under the cooperation of multiple shadowless lamps, and establishing a fitness function according to the light intensity fitting and the regional importance identifier;

[0106] Setting parameter limits of the shadowless lamp according to the shadowless lamp information, and creating multiple groups of lighting configurations within the parameter limits;

[0107] After optimizing the fitness function using the illumination constraints, performing fitness analysis on multiple lighting configurations to establish fitness analysis results;

[0108] Based on the fitness analysis results, multiple lighting configurations are optimized and updated, and update iterations are performed, and optimization parameters are established based on the update iteration results;

[0109] The shadowless lamp is remotely controlled by using the optimized parameters.

[0110] Furthermore, the embodiment of the present application also includes:

[0111] Construct the light intensity fitting formula as follows:

[0112] ;

[0113] in, Characterization Point The light intensity, is the total number of shadowless lamps, Indicates the A shadowless lamp, For the The brightness of a shadowless lamp, Characterization The position of a shadowless lamp, For the Shadowless lamp to point The light is perpendicular to The angle of the surface, is a constant, is the light attenuation coefficient in space;

[0114] Configure the illumination uniformity index, the impact minimization index and the lighting efficiency index, construct the illumination point fitness by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the light intensity, optimize the illumination point fitness by the regional importance identification, and construct a fitness function.

[0115] Furthermore, the embodiment of the present application also includes:

[0116] The calculation formulas for the illumination uniformity index, impact minimization index, and lighting efficiency index are established as follows:

[0117] ;

[0118] ;

[0119] ;

[0120] in, is the illumination uniformity index, Characterize the area under consideration The light intensity at all points within The minimum value of Characterize the area under consideration The light intensity at all points within The average value of To minimize the impact of the index, Characterize the abnormal shadow area, Characterizes the total irradiated area, is the lighting efficiency index, is the total power consumption of the lighting system;

[0121] The weights of illumination uniformity index, impact minimization index and lighting efficiency index are established, and the adaptability of illumination points is configured according to the weights.

[0122] Furthermore, the embodiment of the present application also includes:

[0123] Creating a search space based on the parameter limit values, wherein the search space is a search space for multiple sets of lighting configurations and optimization updates;

[0124] Establish the distribution ratio of random solutions and preset solutions, and set the initial solution size;

[0125] Performing an optimal solution matching search in the search space according to the distribution ratio to establish an initial preset solution, and performing a random search under a non-initial preset solution in the search space according to the distribution ratio to establish an initial random solution;

[0126] A plurality of lighting configurations are created according to the initial preset solution and the initial random solution.

[0127] Furthermore, the embodiment of the present application also includes:

[0128] Get the lighting configuration corresponding to the maximum fitness in the fitness analysis results;

[0129] Taking the lighting configuration as an optimization target, performing position updates of multiple lighting configurations at preset step sizes;

[0130] Update multiple lighting configurations based on the position update results to complete a round of optimization update.

[0131] Furthermore, the embodiment of the present application also includes:

[0132] Compare the fitness of the updated position result with the original position and establish a fitness decay penalty factor;

[0133] Determining whether the fitness decay penalty factor meets a continuous trigger threshold, and if the fitness decay penalty factor meets the continuous trigger threshold, generating a backtracking instruction;

[0134] Based on the backtracking instruction, the corresponding parameters are backtracked to the parameters for which no fitness decay penalty factor is generated.

[0135] Furthermore, the embodiment of the present application also includes:

[0136] A monitoring data set is constructed by monitoring the target area through integrated sensors, consistency authentication of control is performed through the monitoring data set and the optimization parameters, and abnormality feedback is generated according to the consistency authentication result.

[0137] Any step of the method described above can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor to implement any method in the embodiments of the present application, without any unnecessary restrictions.

[0138] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application is intended to include these modifications and variations.

Claims

1. The remote control system of shadowless lamp based on multi-source fusion is characterized by: The system comprises: A taboo area creation module is used to establish a regional data set of the target area, and construct the spatial coordinates of the obstruction based on the regional data set to establish the taboo area; The identification segmentation module is used to obtain the user's input information, parse the input information, divide the target area into regions based on the input information parsing results, and establish important regional identification; An irradiation constraint reconstruction module is used to read shadowless lamp information, wherein the shadowless lamp information includes a brightness limit value, a position limit value, and an adjustment angle limit value, and reconstruct the irradiation constraint of the shadowless lamp according to the shadowless lamp information and the taboo area; A fitness function construction module is used to establish a light intensity fitting of a location point, wherein the light intensity fitting is a light intensity fitting under the cooperation of multiple shadowless lamps, and a fitness function is established according to the light intensity fitting and the regional importance identifier; an initialization module, configured to set parameter limits of the shadowless lamp according to the shadowless lamp information, and create multiple groups of lighting configurations within the parameter limits; an evaluation module, configured to perform fitness analysis on multiple lighting configurations after optimizing the fitness function using the illumination constraints, and establish fitness analysis results; The iteration module is used to optimize and update multiple lighting configurations based on the fitness analysis results, perform update iterations, and establish optimization parameters based on the update iteration results; The remote control module is used to remotely control the shadowless lamp through the optimized parameters.

2. The shadowless lamp remote control system based on multi-source fusion according to claim 1, characterized in that: The fitness function building module is also used to: Construct the light intensity fitting formula as follows: ； in, Characterization Point The light intensity, is the total number of shadowless lamps, Indicates the A shadowless lamp, For the The brightness of a shadowless lamp, Characterization The position of a shadowless lamp, For the Shadowless lamp to point The light is perpendicular to The angle of the surface, is a constant, is the light attenuation coefficient in space; Configure the illumination uniformity index, the impact minimization index and the lighting efficiency index, construct the illumination point fitness by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the light intensity, optimize the illumination point fitness by the regional importance identification, and construct a fitness function.

3. The remote control system for shadowless lamp based on multi-source fusion according to claim 2, characterized in that: The constructing of the illumination point adaptability by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the illumination intensity also includes: The calculation formulas for the illumination uniformity index, impact minimization index, and lighting efficiency index are established as follows: ； ； ； in, is the illumination uniformity index, Characterize the area under consideration The light intensity at all points within The minimum value of Characterize the area under consideration The light intensity at all points within The average value of To minimize the impact of the index, Characterize the abnormal shadow area, Characterizes the total irradiated area, is the lighting efficiency index, is the total power consumption of the lighting system; The weights of illumination uniformity index, impact minimization index and lighting efficiency index are established, and the adaptability of illumination points is configured according to the weights.

4. The remote control system for a shadowless lamp based on multi-source fusion according to claim 3, characterized in that: The initialization module is also used to: Creating a search space based on the parameter limit values, wherein the search space is a search space for multiple sets of lighting configurations and optimization updates; Establish the distribution ratio of random solutions and preset solutions, and set the initial solution size; Performing an optimal solution matching search in the search space according to the distribution ratio to establish an initial preset solution, and performing a random search under a non-initial preset solution in the search space according to the distribution ratio to establish an initial random solution; A plurality of lighting configurations are created according to the initial preset solution and the initial random solution.

5. The remote control system for shadowless lamp based on multi-source fusion according to claim 4, characterized in that: The iteration module is also used to: Get the lighting configuration corresponding to the maximum fitness in the fitness analysis results; Taking the lighting configuration as an optimization target, performing position updates of multiple lighting configurations at preset step sizes; Update multiple lighting configurations based on the position update results to complete a round of optimization update.

6. The shadowless lamp remote control system based on multi-source fusion according to claim 5, characterized in that: The updating of multiple lighting configurations according to the position update results to complete a round of optimization update also includes: Compare the fitness of the updated position result with the original position and establish a fitness decay penalty factor; Determining whether the fitness decay penalty factor meets a continuous trigger threshold, and if the fitness decay penalty factor meets the continuous trigger threshold, generating a backtracking instruction; Based on the backtracking instruction, the corresponding parameters are backtracked to the parameters for which no fitness decay penalty factor is generated.

7. The remote control system for shadowless lamp based on multi-source fusion according to claim 1, characterized in that: The system further comprises: The multi-source feedback module is used to monitor the data of the target area through integrated sensors to build a monitoring data set, perform consistency authentication of the control through the monitoring data set and the optimization parameters, and generate abnormal feedback according to the consistency authentication result.

8. The remote control method of shadowless lamp based on multi-source fusion is characterized by: The method comprises: Establishing a regional data set of the target area, constructing the spatial coordinates of the obstruction based on the regional data set, and establishing a taboo area; Obtain user input information, parse the input information, divide the target area into regions based on the parsed results, and establish important regional identifiers; Reading shadowless lamp information, the shadowless lamp information including a brightness limit value, a position limit value, and an adjustment angle limit value, and reconstructing the irradiation constraint of the shadowless lamp according to the shadowless lamp information and the taboo area; Establishing a light intensity fitting for a location point, wherein the light intensity fitting is a light intensity fitting under the cooperation of multiple shadowless lamps, and establishing a fitness function according to the light intensity fitting and the regional importance identifier; Setting parameter limits of the shadowless lamp according to the shadowless lamp information, and creating multiple groups of lighting configurations within the parameter limits; After optimizing the fitness function using the illumination constraints, performing fitness analysis on multiple lighting configurations to establish fitness analysis results; Based on the fitness analysis results, multiple lighting configurations are optimized and updated, and update iterations are performed, and optimization parameters are established based on the update iteration results; The shadowless lamp is remotely controlled by using the optimized parameters.

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