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

Abstract

The invention discloses a shadowless lamp remote control system and method based on multi-source fusion, and belongs to the field of shadowless lamp control, and the system comprises a taboo area building module which is used for building a taboo area; the identifier segmentation module is used for establishing important regional identifiers; the irradiation constraint reconstruction module is used for reconstructing the irradiation constraint of the shadowless lamp; the fitness function building module is used for building a fitness function; the initialization module is used for creating multiple groups of light configurations; the evaluation module is used for establishing a fitness analysis result; the iteration module is used for establishing optimization parameters according to the updated iteration result; and the remote control module is used for remotely controlling the shadowless lamp. The technical problem that in the prior art, the irradiation effect of a shadowless lamp is poor, and the requirement for precise illumination in a complex scene is difficult to meet is solved, and the technical effect of intelligent and precise remote control over the shadowless lamp in the complex environment is achieved.

Description

Technical Field Technical Field

[0001] 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

[0002] 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 requirements of complex surgical environments. Although there are some solutions for the automatic control of shadowless lamps in the prior art, there are still the following deficiencies: First, the existing control scheme of the shadowless lamp lacks comprehensive consideration of factors such as obstructions and key irradiation areas in the surgical environment, and cannot achieve accurate adaptation to complex environments; second, the control of the shadowless lamp by the existing scheme 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 scheme lacks an intelligent optimization mechanism, and it is impossible to achieve the optimal illumination effect when multiple lamps work together. Therefore, there are technical problems in the prior art that the illumination effect of the shadowless lamp is poor and it is difficult to meet the precise lighting requirements in complex scenes. Summary of the invention

[0003] The present 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.

[0004] 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.

[0005] 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, used to establish a regional data set of a target area, and to construct the spatial coordinates of an obstruction based on the regional data set to establish a taboo area; an identification segmentation module, used to obtain user input information, and to parse the input information, and to divide the target area into regions according to the parsed results of the input information, and to establish important regional identifications; an illumination constraint reconstruction module, used to read shadowless lamp information, the shadowless lamp information including brightness limit values, position limit values, and adjustment angle limit values, and to reconstruct the illumination constraints of the shadowless lamp according to the shadowless lamp information and the taboo area; a fitness function construction module, used to Establish the light intensity fitting of the location point, the light intensity fitting is the light intensity fitting under the cooperation of multiple shadowless lamps, and establish the fitness function according to 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.

[0006] 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 a light intensity fitting for a position point, 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 identification; setting the parameter limit value of the shadowless lamp according to the shadowless lamp information, and creating multiple groups of lighting configurations within the parameter limit value; after optimizing the fitness function through the illumination constraint, 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 iteration, and establishing optimization parameters according to the update iteration results; and remotely controlling the shadowless lamp through the optimized parameters.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The taboo area creation module is used to establish a regional data set of the target area, and the spatial coordinates of the obstruction are constructed based on the regional data set to establish the taboo area, so as to accurately calibrate the position of the obstruction in the surgical environment, and provide boundary constraints for the 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 analysis results of the input information, and important regional identification is established, so as to finely divide the surgical area, calibrate the key irradiation area, and achieve accurate expression of lighting requirements; the shadowless lamp information is read through the illumination constraint reconstruction module, including the brightness limit value, the position limit value, and the adjustment angle limit value, and the illumination constraint of the shadowless lamp is reconstructed according to the shadowless lamp information and the taboo area. The shadowless lamp performance parameters and environmental constraints are comprehensively considered to limit the feasible working state space of the shadowless lamp, providing a basis for subsequent optimization control; the light intensity fitting of the position point is established through the fitness function construction module, and the light intensity fitting is the light intensity fitting under the cooperation of multiple shadowless lamps. The fitness function is established according to the light intensity fitting and the 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 groups 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 groups 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 groups 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. The technical solution to meet lighting needs solves the technical problems in the prior art that the illumination effect of the shadowless lamp is poor and it 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.

[0008] 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

[0009] 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.

[0010] Figure 2A flowchart of a shadowless lamp remote control method based on multi-source fusion is provided for an embodiment of the present application; 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

[0011] The overall idea of ​​the technical solution provided by this application is as follows: 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 finely modeled through the taboo area creation module and the identification segmentation module, the performance parameters of the shadowless lamp are limited through the illumination constraint reconstruction module, the optimization objective function is established through 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 adjustment of the shadowless lamp 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.

[0012] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically described below in conjunction with the drawings in the specification.

[0013] Embodiment 1 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: 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.

[0014] Specifically, the target area refers to the surgical area, that is, the area that needs to be illuminated by the shadowless lamp. There may be various obstructions in the surgical area, such as surgical instruments, the hands of medical staff, etc. These obstructions will block the light of the shadowless lamp, forming shadows in the surgical area, affecting the doctor's operating field. Therefore, the location of these obstructions is identified and the area where they are located is marked as a taboo area.

[0015] First, the taboo area creation module 11 establishes a regional data set for the target area, and the regional data set refers to a data set that characterizes the spatial information of the target area. The images or data of the surgical area are collected by the cameras, sensors and other equipment installed in the operating room, which contain the spatial position, shape and other information of the objects in the target area, forming a regional data set, which provides a data basis for the subsequent identification of the obstruction. After obtaining the regional data set, the taboo area creation module 11 constructs the spatial coordinates of the obstruction based on the regional data set to indicate the position of the obstruction in three-dimensional space. In order to obtain the spatial coordinates of the obstruction, a target detection algorithm is used to identify specific objects such as surgical instruments and hands from the regional data set. After the obstruction is identified, the pixel coordinates of the obstruction are obtained. Combined with the internal and external parameters of the camera, the pixel coordinates are converted into spatial coordinates to obtain the specific position of the obstruction in three-dimensional space. After obtaining the spatial coordinates of the obstruction, the taboo area creation module 11 marks the area where the obstruction is located as a taboo area. The taboo area is represented as a three-dimensional spatial area, and the positions in the area are all positions that the shadowless lamp needs to avoid. According to the shape of the obstruction, a certain buffer zone is set around it to form a 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 to prevent shadows.

[0016] The identification segmentation module 12 is used to obtain the user's 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.

[0017] Specifically, during surgery, different locations within the target area may have different requirements for shadowless lamp lighting. For example, the surgical incision requires stronger lighting, while the surrounding area has relatively lower lighting requirements. In order to achieve more refined shadowless lamp control, the surgical area is divided to identify the lighting requirements of different areas.

[0018] 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 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 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 another example, the text information input by the user is analyzed, keywords are extracted, and the lighting requirements of each area are understood. According to the results of the analysis of the input information, the identification 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.

[0019] After completing the area division, the identification segmentation module 12 establishes an area importance identification for each sub-area. The area importance identification is a numerical value indicating the degree of lighting demand of the area. The higher the numerical value, the more intense and concentrated lighting is needed in the area. The identification segmentation module 12 calculates the importance identification of each sub-area based on the information input by the user. For example, the importance identification of the area marked by the user as a surgical wound will be set to a higher value.

[0020] Through the processing of the identification segmentation module 12, the target area is divided into multiple sub-areas, each of which has clear lighting requirements and importance, providing more detailed reference information for the subsequent shadowless lamp control, so as to flexibly adjust the light intensity and direction according to the important identification of different areas, and realize more refined lighting control. Compared with traditional indiscriminate lighting, it can realize more accurate and practical shadowless lamp control and provide a better lighting environment.

[0021] The irradiation constraint reconstruction module 13 is used to read the shadowless lamp information, which 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.

[0022] Specifically, the shadowless lamp is a surgical lighting device, and its performance parameters such as brightness, position, adjustment angle, etc. have certain restrictions. In addition, the taboo area also imposes constraints on the irradiation behavior of the shadowless lamp, and the shadowless lamp needs to avoid directly irradiating the taboo area.

[0023] First, the irradiation constraint reconstruction module 13 obtains the information of the shadowless lamp by reading the product manual, parameter table, etc. of the shadowless lamp, including parameters such as brightness limit value, position limit value, and adjustment angle limit value, which describe the upper and lower limits of various performance indicators of the shadowless lamp. Among them, the brightness limit value defines the adjustable range of the illumination intensity of the shadowless lamp; the position limit value defines the movable spatial boundary of the shadowless lamp; and the adjustment angle limit value defines the adjustable angle range of the irradiation direction of the shadowless lamp. These limit values ​​can be obtained through the method. After obtaining the information of the shadowless lamp, the irradiation constraint reconstruction module 13 combines the taboo area information to reconstruct the irradiation constraints of the shadowless lamp. Specifically, the irradiation constraint reconstruction module 13 further introduces the restriction of the taboo area on the basis of the original performance limit of the shadowless lamp, so that the shadowless lamp not only meets its own performance limit when adjusting the brightness, position, and angle, but also avoids direct light exposure to the taboo area. For example, it is assumed that the position limit value of the shadowless lamp defines its movable spatial boundary. At the same time, the taboo area creation module calibrates the taboo area where a certain surgical instrument is located. When reconstructing the constraints, the irradiation constraint reconstruction module 13 deducts the taboo area from the movable range of the shadowless lamp. In this way, the shadowless lamp will not enter the taboo area when moving, avoiding direct irradiation of surgical instruments. Similarly, when adjusting the brightness and angle, the shadowless lamp also avoids generating light that directly hits the taboo area.

[0024] Through the processing of the illumination constraint reconstruction module 13, the illumination constraint of the shadowless lamp is reconstructed and optimized. The reconstructed illumination constraint not only takes into account the performance limit of the shadowless lamp itself, but also incorporates the restriction of the taboo area, so that the shadowless lamp can avoid interfering illumination of the obstructions in the surgical area while meeting its own performance requirements, thereby better adapting to the needs of the surgical environment. Compared with the traditional shadowless lamp control method, it can better adapt to the complex constraints of the surgical environment, reduce interference with surgical operations, and provide better lighting guarantees.

[0025] The fitness function building module 14 is used to establish the light intensity fitting of the location point, wherein the light intensity fitting is the light intensity fitting under the cooperation of multiple shadowless lamps, and the fitness function is established according to the light intensity fitting and the regional importance identification.

[0026] Specifically, the fitness function construction module 14 first establishes the light intensity fitting of 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 surgical 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 surgical area under the current shadowless lamp configuration.

[0027] 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.

[0028] 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.

[0029] The initialization module 15 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.

[0030] Specifically, before using the fitness function to optimize the shadowless lamp configuration, the initial conditions and search space are set for the optimization algorithm. The initialization module 15 sets the value range of its adjustable parameters according to the inherent properties of the shadowless lamp, and generates a set of initial lighting configurations within this range to provide a starting point for subsequent optimization search.

[0031] First, the initialization module 15 sets the parameter limit values ​​of the shadowless lamp according to the shadowless lamp information. The shadowless lamp information includes the brightness limit value, the position limit value, the adjustment angle limit value, etc., which reflects the adjustable range of various performance parameters of the shadowless lamp. The initialization module 15 reads these limit values ​​from the shadowless lamp information, uses them as the constraint conditions for the optimization control of the shadowless lamp, and defines the value boundaries of the shadowless lamp parameters. The optimization algorithm cannot cross these boundaries during the search process to avoid generating configuration schemes that are not feasible or may damage the equipment. After setting the parameter limit values, the initialization module 15 creates multiple groups of lighting configurations within the limit value range. The lighting configuration is a combination of a group of shadowless lamp parameters, including the position coordinates, angle, brightness, etc. of each shadowless lamp. A lighting configuration corresponds to a lighting scheme of a shadowless lamp. The initialization module 15 uses random number generation to generate a certain number of lighting configurations under the constraint of the parameter limit values. Multiple groups of lighting configurations cover different areas in the parameter space, providing a starting point for optimization search.

[0032] The initialization module 15 sets the starting conditions and search space for the optimization control of the shadowless lamp. The initialization module 15 sets the value boundaries of the optimization parameters according to the shadowless lamp information, and generates multiple groups of initial configurations distributed in the parameter space, which provides the necessary prior conditions for the operation of the optimization algorithm and helps to quickly and efficiently find the optimal shadowless lamp configuration solution.

[0033] The evaluation module 16 is used to perform fitness analysis of multiple groups of lighting configurations after optimizing the fitness function through the illumination constraints, and establish fitness analysis results.

[0034] Specifically, after the initialization module generates multiple sets of lighting configurations, the advantages and disadvantages of each set of configurations are evaluated to select the best solution. The evaluation module 16 uses the fitness function to score each set of lighting configurations and obtains the corresponding fitness value to provide a basis for subsequent optimization and screening.

[0035] First, the evaluation module 16 performs illumination constraint optimization on the fitness function. The so-called illumination constraint optimization means that the illumination constraints of the shadowless lamp need to be considered when calculating the fitness function value. Irradiation constraints include parameter limit constraints and taboo area constraints. Parameter limit constraints ensure that the shadowless lamp parameters in the lighting configuration will not exceed the equipment capability range; taboo area constraints prevent the shadowless lamp from directly irradiating obstructions in 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.

[0036] After completing the optimization of the illumination constraints, the evaluation module 16 performs fitness analysis on multiple groups of lighting configurations. Each group of lighting configurations is substituted into the optimized fitness function to calculate its fitness value. The fitness function comprehensively considers the matching degree between the configured light intensity distribution and the requirements of the surgical area. The larger the fitness value, the more the configuration can meet the surgical lighting requirements. The evaluation module 16 quantifies the performance of each group of lighting configurations into a numerical index through the fitness function, which is convenient for comparison and screening.

[0037] 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.

[0038] Each candidate lighting configuration is quantitatively evaluated for fitness through the evaluation module 16. The evaluation module 16 comprehensively considers the feasibility of the configuration and the lighting performance through the fitness function and illumination constraint optimization, and obtains an objective and accurate fitness analysis result, which reflects the advantages and disadvantages of each configuration scheme and is the basis for optimization screening and iterative update.

[0039] 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.

[0040] Specifically, after the evaluation module calculates the fitness value of each group of lighting configurations, the configuration scheme is optimized and improved according to the fitness analysis results. The iteration module 17 iteratively updates the lighting configurations to continuously improve their fitness until the optimal shadowless lamp control parameters are found.

[0041] First, the iteration module 17 optimizes and updates multiple groups of lighting configurations according to the fitness analysis results, and adjusts the shadowless lamp parameters in the lighting configuration according to the fitness value, in order to improve the lighting performance of the configuration. The iteration module 17 uses an optimization algorithm to achieve optimization and update, such as a genetic algorithm, a particle swarm algorithm, a simulated annealing algorithm, etc. Through repeated iteration and search, the point with the highest fitness is found in the parameter space. Taking the genetic algorithm as an example, the iteration module 17 regards each group of lighting configurations as an individual, and the shadowless lamp parameters are regarded as the genes of the individual. According to the fitness analysis results, the iteration module 17 selects configurations with higher fitness as high-quality individuals, performs genetic operations such as crossover and mutation on the parameters of the high-quality individuals, and generates new offspring individuals. The offspring inherits the high-quality genes of the parent generation, and also introduces new mutations, which are expected to obtain higher fitness. The iteration module 17 repeats this process continuously, eliminates low-fitness individuals from the current group, leaves high-fitness individuals and generates new offspring, so that the fitness level of the entire group is continuously improved. After completing a round of optimization and update, the iteration module 17 evaluates the update effect 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.

[0042] Through the iteration module 17, the parameters of the shadowless lamp are intelligently adjusted and searched using the fitness analysis results, so that the configuration scheme continuously evolves in the direction of high fitness, thereby efficiently and reliably finding the optimal combination of control parameters of the shadowless lamp. Compared with the manual parameter adjustment method, it is more efficient and accurate to find the best solution in the complex parameter combination space, thereby maximizing the lighting performance of the shadowless lamp.

[0043] The remote control module 18 is used to remotely control the shadowless lamp through the optimized parameters.

[0044] 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.

[0045] First, the remote control module 18 establishes a communication connection with the shadowless lamp. This connection can be a wired connection, such as Ethernet, serial port, etc.; it can also be a wireless connection, such as WiFi, Bluetooth, Zigbee, etc. Through a standardized communication protocol, the remote control module 18 establishes a channel for data transmission and control command interaction with the shadowless lamp, providing a basis for remote adjustment of the working parameters of the shadowless lamp. After establishing the communication connection, the remote control module 18 sends the optimization parameters generated by the iteration module to the shadowless lamp, including the position coordinates, angle, brightness, etc. of each shadowless lamp. After the shadowless lamp receives the optimization parameters, the remote control module 18 triggers the shadowless lamp to perform the adjustment action. For each parameter, the actuator of the shadowless lamp starts to act to adjust the position, angle and brightness of the device. For example, the pitch motor of the shadowless lamp rotates the lamp body according to the angle parameter value to reach the specified pitch angle; the stepper motor of the shadowless lamp drives the lamp body to move on the guide rail according to the position coordinate value to reach the specified spatial position; the dimming circuit of the shadowless lamp adjusts the current of the LED according to the brightness parameter value to emit light of a specified intensity. During the execution process, the control unit of the shadowless lamp monitors the status of each actuator in real time to ensure that the adjustment action is accurate. When the adjustment actions of all shadowless lamps are completed, the lighting effect of the surgical area reaches the optimal state. At the same time, the remote control module 18 monitors the feedback signals of each shadowless lamp to verify whether the adjustment result is consistent with the optimized parameters. If there is a deviation, the remote control module 18 issues a correction instruction to instruct the shadowless lamp to make fine adjustments until the lighting effect meets the requirements.

[0046] Furthermore, the fitness function building module also includes: The formula for constructing light intensity fitting is as follows: ; in, Characterization point The light intensity, is the total number of shadowless lamps, Indicates A shadowless lamp, For the The brightness of a shadowless lamp, Characterization The position of the 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; The illumination uniformity index, the impact minimization index and the lighting efficiency index are configured, and the fitness of the illumination point is constructed by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the light intensity. The fitness of the illumination point is optimized by the regional importance identification, and a fitness function is constructed.

[0047] In a feasible implementation manner, when constructing the fitness function, the fitness function construction module 14 first constructs a light intensity fitting formula as follows: . Among them, the right side of the equation is Sum the light intensity contributions of the shadowless lamps. A shadowless lamp, Indicates The brightness parameter of a shadowless lamp reflects the luminous flux of the lamp; Indicates 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 lines of the plane at Indicate point To Shadowless lamp position The 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 the light intensity after propagating a certain distance in space; the formula for fitting the 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 fitting the light intensity, the fitness function construction module 14 can calculate the light intensity at any position in the surgical area under the given shadowless lamp parameter conditions, laying the foundation for the subsequent construction of the fitness function.

[0048] 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; 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 formula for fitting the light intensity, 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 locations 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 shadowless lamps.

[0049] Furthermore, the embodiment of the present application also includes: The calculation formulas for the illumination uniformity index, the impact minimization index, and the lighting efficiency index are established as follows: ; ; ; in, is the illumination uniformity index, Characterize the area under consideration The light intensity at all points in The minimum value of Characterize the area under consideration The light intensity at all points in 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 lighting points is configured according to the weights.

[0050] In a preferred embodiment, when the fitness function construction module 14 constructs the fitness of the lighting point by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the light intensity, the fitness function construction module 14 establishes calculation formulas for the uniformity index, the impact minimization index and the lighting efficiency index.

[0051] The calculation formula of illumination uniformity index is: .in, is the illumination uniformity index, Indicates 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.

[0052] 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 abnormal shadow area is, and the smaller the impact on the surgical field of view is.

[0053] The calculation formula of lighting efficiency index is: .in, Indicates the total power consumption of the shadowless lamp system. The physical meaning 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 is.

[0054] Through the calculation formulas of the above three indicators, the fitness function construction module 14 can quantitatively evaluate the lighting uniformity, shadow influence and energy efficiency under any set of shadowless lamp parameters, laying a quantitative indicator foundation for constructing the fitness of the lighting point.

[0055] 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 illumination, If you value the energy efficiency of the shadowless lamp, you will increase By weighted average of the three indicators, the fitness function construction module 14 obtains a quantified fitness value of the illumination point, which comprehensively reflects the lighting performance of the illumination point.

[0056] Furthermore, the initialization module also includes: Creating a search space based on the parameter limit value, wherein the search space is a search space for multiple groups 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 groups of lighting configurations are created according to the initial preset solution and the initial random solution.

[0057] In a feasible implementation, when the initialization module 15 creates multiple groups of initial lighting configurations, first, based on the parameter limit values ​​of the shadowless lamp, a parameter search space is created. The search space is a multi-dimensional continuous parameter domain, and each dimension corresponds to an adjustable parameter of the shadowless lamp, such as the position coordinates, angle, brightness, etc. of the lamp. The range of parameter values ​​is determined by the physical limits of the shadowless lamp and constitutes the boundary of the search space. This search space covers all possible lighting configuration combinations and is the basis for subsequent generation and optimization of multiple groups of initial solutions. Secondly, when the initialization module 15 generates initial solutions in the search space, a hybrid strategy of random solutions and preset solutions is adopted. The initialization module 15 first establishes the distribution ratio of random solutions and preset solutions, and sets the total number of initial solutions. The random solution is a configuration generated completely randomly in the search space, which has a strong exploratory nature; the preset solution is a configuration generated based on prior knowledge or empirical rules, which has a strong pertinence. By setting the ratio of 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 to generate specific initial configurations in the search space. For preset solutions, the initialization module 15 adopts the strategy of optimal solution matching search. Based on the existing optimal lighting configuration samples, similar configurations are searched in the search space as the initial preset solution. Through similarity-based matching search, the existing high-quality configuration knowledge can be fully utilized to quickly lock in potential solution areas. For random solutions, the initialization module 15 performs pure random sampling in the non-preset solution area to evenly cover other solution spaces and explore new possibilities. Afterwards, the initialization module 15 combines the generated preset solutions and random solutions to form multiple groups of initial lighting configurations. These configurations cover different characteristic areas of the solution space, providing a high-quality search starting point for subsequent optimization, which can accelerate optimization convergence and improve search efficiency.

[0058] By constructing a parameter search space and generating a mixture of random solutions and preset solutions, an initialization strategy that takes into account both exploration and targeting is implemented, making full use of the prior information and empirical knowledge of the shadowless lamp parameters, while also reserving sufficient degrees of freedom and novelty for optimization search. Compared with simple random initialization, the generated multiple sets of lighting configurations are of higher quality and more reasonable distribution, which can significantly improve the search efficiency and optimization performance of the optimization algorithm.

[0059] Furthermore, the iteration module also includes: Get the lighting configuration corresponding to the maximum fitness in the fitness analysis results; Taking the lighting configuration as an optimization target, executing position updates of multiple sets of lighting configurations at preset step sizes; Update multiple sets of lighting configurations based on the position update results to complete a round of optimization update.

[0060] In a preferred embodiment, first, the iteration module 17 obtains the lighting configuration corresponding to the maximum fitness value from the fitness analysis result output by the evaluation module 16, indicating the best comprehensive performance among all the candidate solutions, and represents the best configuration found in the search process. The iteration module 17 takes it as the target of this round of optimization update, and performs local fine search in the solution space with it as the center. Secondly, the iteration module 17 takes the best configuration as the starting point and performs position update of multiple groups of candidate configurations. The so-called position update refers to fine-tuning the configuration along a specific direction and step length in the parameter space of the shadowless lamp. Among them, the position update adopts the strategy of preset step length, that is, the iteration module 17 pre-sets the step length value of each parameter dimension, such as the position parameter step length of the lamp is 10cm, the angle parameter step length is 5 degrees, and the brightness parameter step length is 0.1. During the update, the iteration module 17 takes the best configuration as the center, and explores in the positive and negative directions according to the preset step length on each parameter dimension to generate a series of new candidate configurations. Through local search based on a predetermined step length, fine tuning can be performed near the optimal solution to find a configuration with higher performance.

[0061] Afterwards, the iteration module 17 updates the original multiple groups of lighting configurations according to the results of the position update. For each original configuration, the iteration module 17 finds its corresponding newly generated configuration and compares the fitness values ​​of the two. If the fitness of the new configuration is higher, the new configuration replaces the original configuration; otherwise, the original configuration remains unchanged. Through the update strategy, the iteration module 17 realizes the iterative optimization of the candidate solution population, eliminates the configuration with lower fitness, and adds new configurations with better performance, so that the search ability of the entire population is continuously enhanced. After completing a round of position update, the iteration module 17 outputs the updated multiple groups of lighting configurations to prepare for the next round of iteration.

[0062] By obtaining the optimal configuration, updating the position with a preset step length, and updating the population based on the best, an iterative optimization strategy based on local fine search is implemented, focusing on the potential area around the optimal solution, and continuously discovering higher-performance configurations through step length exploration, so that the optimization search can continuously converge to the optimal solution in the solution space. Compared with strategies such as random search, it is more efficient and accurate, and can obtain a better combination of shadowless lamp parameters with fewer iterations.

[0063] Furthermore, the embodiment of the present application also includes: Compare the fitness of the updated position with that of the original position, and establish a fitness attenuation penalty factor; Determine whether the fitness decay penalty factor meets the continuous trigger threshold, and if the fitness decay penalty factor meets the continuous trigger threshold, generate 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.

[0064] In a feasible implementation, when updating the lighting configuration, the iteration module 17 synchronously performs a fitness comparison between the position update result and the original configuration. Specifically, for each newly generated configuration, the 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, it indicates that this position update does not bring performance improvement, but leads to fitness attenuation. In view of this situation, the iteration module 17 establishes a fitness attenuation penalty factor to quantify the negative impact of the update effect. The attenuation penalty factor is a value between 0 and 1. The more severe the attenuation, the greater the penalty factor. After generating the attenuation penalty factor, the iteration module 17 further determines whether it meets the preset continuous trigger threshold. The so-called continuous trigger threshold refers to the upper limit of the number of fitness attenuation in multiple consecutive updates. If within a certain number of iterations, the cumulative value or number of the attenuation penalty factor exceeds the threshold, it indicates that the current update strategy has fallen into a local bad area and needs to adjust the strategy. At this time, the iteration module 17 generates a backtracking instruction, starts the parameter backtracking mechanism, and self-corrects the search process.

[0065] Afterwards, the iteration module 17 will backtrack the parameters that cause fitness decay to the previous state according to the backtracking instruction. Specifically, the iteration module 17 finds the configuration that did not trigger the decay penalty the last time, uses it as the new search starting point, and replaces the current decay configuration. Through such parameter backtracking, the iteration 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 iteration 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 iteration module 17 will end the current search process and return the optimal configuration currently found as the final result.

[0066] The adaptive optimization update strategy can cope with the adaptive ability of complex and changing search environments, and can promptly detect the bad state in the search process, so that the search direction can get rid of local traps and move towards more promising areas. Compared with the fixed search scheme, the strategy can be dynamically adjusted according to real-time feedback, thus significantly improving the optimization efficiency and success rate.

[0067] Furthermore, the embodiment of the present application also includes: The multi-source feedback module is used to construct a monitoring data set by monitoring the target area through integrated sensors, perform consistency authentication of control through the monitoring data set and the optimization parameters, and generate abnormal feedback according to the consistency authentication result.

[0068] In a preferred embodiment, a multi-source feedback module is added to achieve real-time monitoring and control quality assessment of the target area, and to generate abnormal feedback based on the assessment results to guide the shadowless lamp control to perform self-correction.

[0069] First, the multi-source feedback module monitors the target area through integrated sensors to build a monitoring data set. The so-called integrated sensors refer to various types of sensing equipment arranged in the target area, such as light intensity sensors, infrared thermal imagers, visible light cameras, etc. These sensors collect the status data of the surgical site in real time from different physical quantity angles to form a comprehensive and three-dimensional monitoring data set. For example, the light intensity sensor detects the actual illumination distribution in the target area, the thermal imager perceives the temperature field changes in the surgical field, and the visible light camera captures the video image of the surgical scene. Through the data fusion of multiple sensors, the monitoring data set can reflect the actual effect of surgical lighting in a multi-dimensional and high-fidelity manner.

[0070] Secondly, the multi-source feedback module uses the monitoring data set to evaluate the actual control effect of the shadowless lamp. Specifically, the multi-source feedback module compares the monitoring data with the optimization parameters output by the iteration module and performs consistency certification. The so-called consistency certification is to check the degree of consistency between the actual lighting effect and the expected optimization effect. For example, the multi-source feedback module calculates the difference between the actual illuminance distribution monitored and the target illuminance distribution corresponding to the optimization parameters, and obtains the illuminance deviation value as the consistency certification result. Subsequently, the multi-source feedback module generates corresponding abnormal feedback based on the consistency certification result. If the consistency certification result shows that the actual lighting effect deviates greatly from the expected one, the multi-source feedback module generates a deviation alarm, indicating that the current control performance does not meet the standard. The alarm information includes the deviation amount, deviation type (such as uneven illumination, abnormal temperature, poor lighting effect, etc.), deviation position, etc., which provides a basis for the correction of the control of the shadowless lamp. After receiving the abnormal feedback, the iteration module responds quickly, restarts the optimization, and makes targeted adjustments to the control parameters until the deviation is eliminated and the quality requirements are met. Through the closed-loop control of real-time monitoring and feedback correction, it can continuously improve itself and continuously maintain the best lighting performance of the shadowless lamp.

[0071] In summary, the shadowless lamp remote control system based on multi-source fusion provided by the embodiment of the present application has the following technical effects: The taboo area creation module is used to establish a regional data set for the target area, and to construct the spatial coordinates of the obstruction based on the regional data set, to establish a taboo area, to provide spatial constraints for the shadowless lamp irradiation, and to 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, and important regional identification is established to express the lighting requirements in a refined manner, providing 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 the brightness limit value, the position limit value, and the adjustment angle limit value. 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 problem solving. The fitness function construction module is used to establish the light 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 according to the light intensity fitting and the regional importance identification, and the lighting requirements are mathematically transformed 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 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, and establish fitness analysis results to estimate the pros and cons of the current solution and guide the subsequent iterative search direction. 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 according to 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, so as to realize intelligent and precise remote control of the shadowless lamp in a complex environment.

[0072] Embodiment 2 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, the embodiment of 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 the target area, constructing the spatial coordinates of the obstruction based on the regional data set, and establishing a taboo area; Obtain the user's input information, parse the input information, divide the target area into regions based on the parsed results of the input information, and establish important regional identifiers; Reading shadowless lamp information, wherein the shadowless lamp information includes 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 of 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 identification; 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 through the illumination constraint, performing fitness analysis of multiple groups of lighting configurations and establishing fitness analysis results; According to the fitness analysis results, multiple groups of lighting configurations are optimized and updated, and update iterations are performed, and optimization parameters are established according to the update iteration results; The shadowless lamp is remotely controlled by using the optimized parameters.

[0073] Furthermore, the embodiment of the present application also includes: The formula for constructing light intensity fitting is as follows: ; in, Characterization point The light intensity, is the total number of shadowless lamps, Indicates A shadowless lamp, For the The brightness of a shadowless lamp, Characterization The position of the 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; The illumination uniformity index, the impact minimization index and the lighting efficiency index are configured, and the fitness of the illumination point is constructed by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the light intensity. The fitness of the illumination point is optimized by the regional importance identification, and a fitness function is constructed.

[0074] Furthermore, the embodiment of the present application also includes: The calculation formulas for the illumination uniformity index, the impact minimization index, and the lighting efficiency index are established as follows: ; ; ; in, is the illumination uniformity index, Characterize the area under consideration The light intensity at all points in The minimum value of Characterize the area under consideration The light intensity at all points in 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 lighting points is configured according to the weights.

[0075] Furthermore, the embodiment of the present application also includes: Creating a search space based on the parameter limit value, wherein the search space is a search space for multiple groups 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 groups of lighting configurations are created according to the initial preset solution and the initial random solution.

[0076] Furthermore, the embodiment of the present application also includes: Get the lighting configuration corresponding to the maximum fitness in the fitness analysis results; Taking the lighting configuration as an optimization target, executing position updates of multiple sets of lighting configurations at preset step sizes; Update multiple sets of lighting configurations based on the position update results to complete a round of optimization update.

[0077] Furthermore, the embodiment of the present application also includes: Compare the fitness of the updated position with that of the original position, and establish a fitness attenuation penalty factor; Determine whether the fitness decay penalty factor meets the continuous trigger threshold, and if the fitness decay penalty factor meets the continuous trigger threshold, generate 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.

[0078] Furthermore, the embodiment of the present application also includes: 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 abnormal feedback is generated according to the consistency authentication result.

[0079] 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.

[0080] 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 equivalent technologies, 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 occluder based on the regional data set to establish the taboo area; The identification segmentation module is used to obtain the user's 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 identification; An irradiation constraint reconstruction module is used to read the 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 building 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 identification; An initialization module, used for setting parameter limits of the shadowless lamp according to the shadowless lamp information, and creating multiple groups of lighting configurations within the parameter limits; An evaluation module, configured to perform fitness analysis of multiple groups of lighting configurations after optimizing the fitness function through the illumination constraint, and establish fitness analysis results; Iteration module, used to optimize and update multiple lighting configurations according to the fitness analysis results, perform update iterations, and establish optimization parameters according to the update iteration results; A 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 as claimed in claim 1, characterized in that: The fitness function building module is also used to: The formula for constructing light intensity fitting is as follows: ； in, Characterization point The light intensity, is the total number of shadowless lamps, Indicates A shadowless lamp, For the The brightness of a shadowless lamp, Characterization The position of the 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; The illumination uniformity index, the impact minimization index and the lighting efficiency index are configured, and the fitness of the illumination point is constructed by fitting the illumination uniformity index, the impact minimization index, the lighting efficiency index and the light intensity. The fitness of the illumination point is optimized by the regional importance identification, and a fitness function is constructed.

3. The shadowless lamp remote control system based on multi-source fusion as claimed in 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, the impact minimization index, and the lighting efficiency index are established as follows: ； ； ； in, is the illumination uniformity index, Characterize the area under consideration The light intensity at all points in The minimum value of Characterize the area under consideration The light intensity at all points in 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 lighting points is configured according to the weights.

4. The remote control system for shadowless lamp based on multi-source fusion as claimed in claim 3, characterized in that: The initialization module is also used for: Creating a search space based on the parameter limit value, wherein the search space is a search space for multiple groups 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 groups of lighting configurations are created according to the initial preset solution and the initial random solution.

5. The shadowless lamp remote control system based on multi-source fusion as claimed in 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, executing position updates of multiple sets of lighting configurations at preset step sizes; Update multiple sets of 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 as claimed in claim 5, characterized in that: The method of updating multiple groups of lighting configurations according to the position update results to complete a round of optimization update also includes: Compare the fitness of the updated position with that of the original position, and establish a fitness attenuation penalty factor; Determine whether the fitness decay penalty factor meets the continuous trigger threshold, and if the fitness decay penalty factor meets the continuous trigger threshold, generate 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 shadowless lamp remote control system based on multi-source fusion as claimed in claim 1, characterized in that: The system further comprises: The multi-source feedback module is used to construct a monitoring data set by monitoring the target area through integrated sensors, perform consistency authentication of 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 the user's input information, parse the input information, divide the target area into regions based on the parsed results of the input information, and establish important regional identifiers; Reading shadowless lamp information, wherein the shadowless lamp information includes 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 of 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 identification; 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 through the illumination constraint, performing fitness analysis of multiple groups of lighting configurations and establishing fitness analysis results; According to the fitness analysis results, multiple groups of lighting configurations are optimized and updated, and update iterations are performed, and optimization parameters are established according to the update iteration results; The shadowless lamp is remotely controlled by using the optimized parameters.

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