A smart loudspeaker based on positioning beacon

Abstract

The present invention provides an intelligent loudspeaker based on a positioning beacon, which relates to the field of a loudspeaker system and comprises: a following positioning module, comprising a positioning beacon arranged on an object to be followed, a main base station and a plurality of slave base stations arranged on the loudspeaker, and a positioning analysis unit; an information acquisition module, which is used to acquire real-time environmental information; a loudspeaker following module, which is used to determine a following path and following parameters according to a real-time relative position relationship between a positioning beacon and the main base station, real-time environmental information, and a historical relative position relationship between the positioning beacon and the main base station, and control a walking component to drive the loudspeaker to move; a loudspeaker adjustment module, which is used to determine real-time loudspeaker parameters according to a real-time relative position relationship between a positioning beacon and the main base station, real-time environmental information, and a following path, and control a posture adjustment component to adjust the posture of the loudspeaker and adjust the output volume of the loudspeaker. The loudspeaker has the advantages of realizing intelligent following of the loudspeaker based on the positioning beacon and improving user experience.

Description

Technical Field

[0001] The present invention relates to the field of sound amplification systems, and in particular to an intelligent sound amplification system based on a positioning beacon. Background Art

[0002] A megaphone is an electronic device used to amplify sound, allowing it to travel farther. It is often used in teaching, tour guides, entertainment and other occasions to help people hear the sound more clearly.

[0003] Existing loudspeakers are usually fixed by users in places with high frequency of use. They are not easy to move and cannot meet the needs of users in certain scenarios. For example, electronic guides are installed in scenic tourist attractions, parks, museums, exhibition halls, visiting places, etc., which provide guide / explanatory clothes for individual tourists. Fixed electronic guides do not have a follow-up function and cannot bring tourists a convenient, interesting and cultural experience. For another example, a user connects to a loudspeaker via Bluetooth to play music, but the user may need to walk around the room for some reason. When the mobile terminal connected to the loudspeaker via Bluetooth is far away from the loudspeaker, the Bluetooth connection signal becomes weak or even disconnected, affecting people's experience of listening to music.

[0004] Therefore, it is necessary to provide a smart loudspeaker based on a positioning beacon, which is used to realize the smart following of the loudspeaker based on the positioning beacon and improve the user experience. Summary of the invention

[0005] The present invention provides an intelligent loudspeaker based on a positioning beacon, comprising: a following positioning module, comprising a positioning beacon arranged on an object to be followed, a main base station and a plurality of slave base stations arranged on the loudspeaker, and a positioning analysis unit, any two of the slave base stations are located at different heights, any one of the slave base stations and the main base station are located at different heights, the positioning analysis unit is used to determine the real-time relative position relationship between the positioning beacon and the main base station according to the interactive information between the positioning beacon and the main base station and the plurality of slave base stations; an information acquisition module is used to acquire real-time environmental information; a loudspeaker following module is used to determine the real-time relative position relationship between the positioning beacon and the main base station according to the interactive information between the positioning beacon and the main base station and the plurality of slave base stations; The following path and following parameters are determined based on the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, wherein the following parameters at least include a following speed, and according to the following path and the following parameters, the walking component is controlled to drive the loudspeaker to move; a loudspeaker adjustment module is used to determine real-time loudspeaker parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the following path, wherein the real-time loudspeaker parameters at least include a real-time volume and a real-time loudspeaker posture, and the posture adjustment component is controlled to adjust the posture of the loudspeaker according to the real-time loudspeaker posture, and the output volume of the loudspeaker is adjusted according to the real-time volume.

[0006] Furthermore, the follow-up positioning module sets a plurality of slave base stations on the loudspeaker, including: determining a plurality of first test positions on the loudspeaker, wherein any two of the first test positions are located at different heights, and any one of the first test positions is located at a different height from the main base station; obtaining first positioning test data of the plurality of first test positions respectively in a plurality of test scenarios; calculating the signal similarity between any two of the first test positions according to the first positioning test data of the plurality of first test positions; clustering the plurality of first test positions according to the signal similarity between any two of the first test positions by a clustering algorithm to obtain a clustering result; determining a plurality of second test positions according to the clustering result, wherein any two of the second test positions are located at different heights, and any one of the second test positions is located at a different height from the main base station; obtaining the second positioning test data of the main base station and the plurality of second test positions respectively in a plurality of test scenarios. third positioning test data; calculating the signal similarity between the main base station and the second test position according to the second positioning test data of the main base station and the third positioning test data of the second test position; screening the multiple second test positions according to the signal similarity between the main base station and the second test position to determine multiple third test positions; determining multiple position combinations according to the multiple third test positions, wherein each position combination includes at least two third test positions; obtaining fourth positioning test data for each position combination in multiple test scenarios, wherein the fourth positioning test data includes the test data of the main base station and the test data of each third test position included in the position combination; determining the optimal position combination according to the second positioning test data of the main base station, the third positioning test data of the multiple second test positions and the fourth positioning test data of each position combination, and setting multiple slave base stations on the loudspeaker according to the optimal position combination.

[0007] Further, the positioning analysis unit determines the real-time relative position relationship between the positioning beacon and the main base station based on the interaction information between the positioning beacon and the main base station and the multiple slave base stations, including: judging whether to follow according to the time delay between the main base station and the positioning beacon; if it is determined to follow, determining the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each of the slave base stations according to the time delay between the main base station and the positioning beacon and the time delay between each of the slave base stations and the positioning beacon; determining the real-time relative direction between the positioning beacon and the main base station according to the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each of the slave base stations through a multivariate regression model, wherein the real-time relative position relationship between the positioning beacon and the main base station includes the real-time distance and real-time relative direction between the positioning beacon and the main base station.

[0008] Furthermore, the information acquisition module includes an obstacle detection unit and a road surface detection unit, wherein the obstacle detection unit is used to obtain the relative position between the obstacle and the loudspeaker, and the road surface detection unit is used to obtain the roughness of the road surface.

[0009] Furthermore, the road surface detection unit includes a vibration detection component, an ultrasonic detection component and a roughness analysis component, wherein the vibration detection component is installed on the walking component and is used to collect vibration data of the walking component, the ultrasonic detection component is installed on the walking component and is used to obtain ultrasonic detection data of the road surface; the roughness analysis component determines the road surface roughness based on the vibration data of the walking component collected by the vibration detection component and the ultrasonic detection data of the road surface.

[0010] Furthermore, the roughness analysis component determines the road surface roughness based on the vibration data of the walking component collected by the vibration detection component and the ultrasonic detection data of the road surface, including: extracting the characteristics of the reflected echo from the ultrasonic detection data of the road surface, including at least the amplitude and the frequency; extracting the speed characteristics from the speed information of the walking component at multiple consecutive time points, including at least the speed mean and the speed standard deviation; performing variational modal decomposition on the vibration data of the walking component collected by the vibration detection component at multiple consecutive time points according to the speed characteristics, generating multiple vibration modal components, and extracting component characteristics of the vibration modal components; determining the road surface roughness through a roughness determination model according to the characteristics of multiple reflected echoes and the component characteristics of the vibration modal components whose center frequencies are within the center frequency range corresponding to the speed characteristics.

[0011] Furthermore, the loudspeaker following module determines a following path according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, including: analyzing user movement characteristics according to the historical relative position relationship between the positioning beacon and the main base station, wherein the user movement characteristics include the user's relative direction change range and the user's speed change characteristics; determining the target following position according to the real-time relative position relationship between the positioning beacon and the main base station and the relative direction change range; and determining the following path according to the target following position and the relative position between the obstacle and the loudspeaker using a path search algorithm.

[0012] Furthermore, the amplification following module analyzes the user movement characteristics according to the historical relative position relationship between the positioning beacon and the main base station, including: extracting the user speed change characteristics based on the historical relative position relationship between the positioning beacon and the main base station through a feature analysis model.

[0013] Furthermore, the amplification and following module determines the following parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, including: determining the following speed according to the following path, the user speed change characteristics and the road roughness.

[0014] Furthermore, the sound amplification adjustment module determines real-time sound amplification parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the following path, including: determining the real-time sound amplification posture according to the following path and the real-time relative position relationship between the positioning beacon and the main base station; determining the real-time volume according to the following path, the real-time relative position relationship between the positioning beacon and the main base station, and the relative position between the obstacle and the loudspeaker.

[0015] Compared with the prior art, the smart loudspeaker based on positioning beacons provided by the present invention has at least the following beneficial effects:

[0016] 1. Through the interactive information between the positioning beacon and the main base station and multiple slave base stations, the system can determine the relative position relationship between the object being followed (such as a speaker, performer, etc.) and the loudspeaker in real time. Multiple slave base stations are located at different heights, allowing the system to more accurately perceive position changes in three-dimensional space. The loudspeaker following module can determine the optimal following path and following parameters (such as following speed) based on the real-time relative position relationship, historical relative position relationship and real-time environmental information. This ensures that the loudspeaker can closely follow the object being followed while avoiding collisions and interference. The information acquisition module can perceive environmental changes in real time, such as crowd density, obstacle location, etc. Dynamically adjust the following path and following parameters based on this information to ensure that the loudspeaker can still follow stably in a complex environment. The loudspeaker adjustment module can dynamically adjust the output volume of the loudspeaker based on the real-time relative position relationship and real-time environmental information. This ensures that listeners can obtain clear and uniform sound quality in different positions and environments. The posture adjustment component can be controlled to adjust the posture of the loudspeaker based on real-time amplification parameters (such as real-time amplification posture). This helps to optimize the amplification effect and reduce attenuation and interference during sound propagation. The system realizes automatic operation, and can achieve accurate tracking of the loudspeaker and optimization of the sound amplification effect without manual intervention, which reduces the difficulty of operation and labor costs, and improves work efficiency.

[0017] 2. By determining multiple first test positions on the loudspeaker and obtaining the first positioning test data of these positions respectively, and clustering the first test positions using a clustering algorithm, the best distribution of test positions can be found according to signal similarity, thereby optimizing the layout of the slave base stations. By further screening and combining the third test positions, the optimal position combination can be found to ensure that the slave base station can accurately receive the signal of the positioning beacon and improve the positioning accuracy. Obtaining positioning test data in a variety of test scenarios can ensure that positioning can adapt to different environments and conditions. By optimizing the layout and number of slave base stations, signal interference and attenuation can be better dealt with, improving the robustness of the system.

[0018] 3. The signal strength of the signal sent by the positioning beacon received by the main base station at multiple consecutive time points can be used to determine whether the positioning beacon needs to be followed. This judgment method based on signal strength can avoid the situation of false following or missing following, and improve the accuracy of following decisions. The signal strength received by the main base station and multiple slave base stations is corrected to eliminate the influence of environmental noise, signal attenuation and other factors on the signal strength. This correction can ensure that the calculated distance and direction are more accurate. According to the corrected signal strength, the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each slave base station can be determined. At the same time, through the multivariate regression model, the system can also determine the real-time relative direction between the positioning beacon and the main base station. This real-time distance and direction information provides strong support for the precise following of the loudspeaker. By continuously monitoring the signal strength at multiple time points, the relative position relationship between the positioning beacon and the base station can be more accurately reflected. This continuous monitoring method can reduce errors caused by accidental factors and improve the stability of the system. It can adapt to different environmental conditions and noise levels, and ensure that the distance and direction can still be accurately calculated in complex environments through signal strength correction and multivariate regression models. This adaptability makes the system more robust.

[0019] 4. It can detect the relative position between obstacles and the loudspeaker in real time, provide obstacle avoidance information for the movement of the loudspeaker, and ensure that the loudspeaker can move safely and smoothly in complex environments. Through the vibration detection component and the ultrasonic detection component, the roughness information of the road surface can be accurately obtained, providing a basis for the mobile path planning and following speed adjustment of the loudspeaker. According to the historical relative position relationship between the positioning beacon and the main base station, the user's movement characteristics can be analyzed, including the direction change range and speed change characteristics, so as to more accurately predict the user's movement trend. Combined with the real-time relative position relationship and user movement characteristics, the target following position can be determined to ensure that the loudspeaker can always follow the user and maintain an appropriate distance and direction. Using the obstacle detection information, the path search algorithm is used to determine the optimal following path to avoid collisions with obstacles and improve the following efficiency and safety. According to the following path, the user's speed change characteristics and the roughness of the road surface, the following speed of the loudspeaker is dynamically adjusted to ensure that a stable following effect can be maintained under different road conditions and user movement speeds. According to the following path, the real-time relative position relationship and the obstacle information, the system can dynamically adjust the position and volume of the loudspeaker to ensure that the sound can always cover the user's area and reduce unnecessary noise interference. Dynamically adjust the sound amplification parameters based on real-time environmental information and user movement characteristics to ensure clear and uniform sound and enhance the user's auditory experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0021] Figure 1 is a module schematic diagram of a smart loudspeaker based on a positioning beacon according to some embodiments of this specification;

[0022] Figure 2 is a schematic diagram of a process of setting multiple slave base stations on a loudspeaker according to some embodiments of this specification;

[0023] Figure 3 It is a schematic diagram of a process for determining the real-time relative position relationship between a positioning beacon and a main base station according to some embodiments of this specification. DETAILED DESCRIPTION

[0024] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0025] Figure 1 is a schematic diagram of a module of a smart loudspeaker based on a positioning beacon according to some embodiments of this specification, such as Figure 1 As shown, a smart loudspeaker based on a positioning beacon may include a following positioning module, an information acquisition module, a loudspeaker following module and a loudspeaker adjusting module.

[0026] The following positioning module may include a positioning beacon set on the object to be followed, a main base station and multiple slave base stations set on a loudspeaker, and a positioning analysis unit. Any two slave base stations are located at different heights, and any slave base station is located at a different height from the main base station. The positioning analysis unit is used to determine the real-time relative position relationship between the positioning beacon and the main base station based on the interactive information between the positioning beacon and the main base station and the multiple slave base stations.

[0027] Figure 2 is a flow chart of setting multiple slave base stations on a loudspeaker according to some embodiments of this specification, such as Figure 2 As shown, as a preferred embodiment, the follow-up positioning module sets a plurality of slave base stations on the loudspeaker, including:

[0028] Determine a plurality of first test positions at the loudspeaker, wherein any two of the first test positions are located at different heights, and any one of the first test positions is located at a different height from the main base station;

[0029] Under multiple test scenarios, respectively obtain first positioning test data of multiple first test positions, wherein the first positioning test data may include strength data of a signal received under each test scenario;

[0030] Calculating the signal similarity between any two first test positions according to the first positioning test data of the plurality of first test positions;

[0031] Clustering the plurality of first test positions according to the signal similarity between any two first test positions by using a clustering algorithm (for example, a K-means clustering algorithm, a hierarchical clustering algorithm, etc.) to obtain a clustering result;

[0032] Determine a plurality of second test positions according to the clustering result, wherein any two second test positions are located at different heights, and any second test position is located at a different height from the main base station;

[0033] Under various test scenarios, respectively obtain the second positioning test data of the primary base station and the third positioning test data of multiple second test locations;

[0034] Calculating the signal similarity between the main base station and the second test position according to the second positioning test data of the main base station and the third positioning test data of the second test position;

[0035] Screening the plurality of second test locations according to the signal similarity between the primary base station and the second test location to determine a plurality of third test locations;

[0036] Determine a plurality of position combinations according to the plurality of third test positions, wherein each position combination includes at least two third test positions;

[0037] In a variety of test scenarios, fourth positioning test data of each position combination is obtained, wherein the fourth positioning test data includes test data of the primary base station and test data of each third test position included in the position combination;

[0038] The optimal position combination is determined based on the second positioning test data of the main base station, the third positioning test data of multiple second test positions, and the fourth positioning test data of each position combination, and multiple slave base stations are set on the loudspeaker based on the optimal position combination.

[0039] Specifically, in different test scenarios, the relative position relationship between the beacon and the first test position is different. In each test scenario, the beacon can be controlled to send a signal, and a test base station can be installed at the first test position to obtain the strength data of the signal received by the base station in the current test scenario. In order to avoid mutual interference, in the process of obtaining the first positioning test data, data is collected from multiple first test positions in sequence rather than simultaneously.

[0040] The signal similarity between the two first test positions can be calculated according to the following formula:

[0041]

[0042] in, is the signal similarity between the i-th first test position and the j-th first test position, is the total number of test scenarios, is the mean value of the signal strength received at the i-th first test position in the n-th test scenario, is the average value of the signal strength received by the j-th first test position in the n-th test scenario.

[0043] For each cluster, a first test position having the shortest distance to the cluster center of the cluster may be selected as the second test position.

[0044] The method of obtaining the second positioning test data of the main base station and the third positioning test data of multiple second test positions is similar to the method of obtaining the first positioning test data of multiple first test positions, which will not be repeated here.

[0045] The method of calculating the signal similarity between the main base station and the second test location is similar to the method of calculating the signal similarity between the two first test locations, and will not be repeated here.

[0046] The second test position whose signal similarity with the main base station is greater than the signal similarity threshold may be screened out, and the second test position whose signal similarity with the main base station is less than or equal to the signal similarity threshold may be used as the third test position.

[0047] For each location combination, the main base station and the slave base station are first installed according to the location combination, and then the beacon is controlled to send signals in various test scenarios to obtain the strength data of the signals received by the main base station and the slave base station in various test scenarios.

[0048] A combined evaluation system is established, wherein the combined evaluation system may include multiple combined evaluation indicators, such as a global interference indicator, a positioning accuracy indicator, a positioning efficiency indicator, etc.

[0049] For each position combination, the scores of the position combination in multiple combination evaluation indicators are calculated. The combination optimization model performs combination optimization based on the scores of each position combination in multiple combination evaluation indicators to generate the optimal position combination, wherein the combination optimization model can be a Generative Adversarial Networks (GAN) model.

[0050] For example, the scores of the position combination in the global interference index, positioning accuracy index, and positioning efficiency index can be calculated according to the following formula:

[0051]

[0052] in, is the score of the position combination in the global interference index, is the interference degree of the main base station corresponding to the position combination, is the interference degree received from the base station corresponding to the position combination, and is the preset weight, and are greater than 0, , is the average value of the strength of the signal received in the nth test scenario in the second positioning test data of the primary base station, is the average value of the strength of the signal received by the primary base station in the nth test scenario in the fourth positioning test data, is the average value of the strength of the signal received in the nth test scenario in the third positioning test data of the mth slave base station corresponding to the position combination, is the average value of the strength of the signal received by the mth slave base station corresponding to the position combination in the fourth positioning test data in the nth test scenario, is the total number of slave base stations corresponding to the position combination, is the score of the position combination in the positioning accuracy index, is the positioning coordinates of the beacon in the nth test scenario of the position combination, is the preset coordinate of the beacon in the nth test scenario, is the score of the position combination in the positioning efficiency index, The time it takes to determine the location coordinates of the beacon for the position combination in the nth test scenario.

[0053] Figure 3 is a flow chart of determining the real-time relative position relationship between a positioning beacon and a primary base station according to some embodiments of this specification, such as Figure 3 As shown, the positioning analysis unit determines the real-time relative position relationship between the positioning beacon and the main base station according to the interactive information between the positioning beacon and the main base station and multiple slave base stations, including:

[0054] According to the time delay between the main base station and the positioning beacon, determine whether to follow. For example, if the time delay between the main base station and the positioning beacon is greater than the time delay threshold, it is determined to follow.

[0055] If it is determined to follow, the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each slave base station are determined according to the time delay between the main base station and the positioning beacon and the time delay between each slave base station and the positioning beacon;

[0056] The real-time relative direction between the positioning beacon and the main base station is determined through a multivariate regression model based on the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each slave base station, wherein the real-time relative position relationship between the positioning beacon and the main base station includes the real-time distance and real-time relative direction between the positioning beacon and the main base station.

[0057] Specifically, the master base station and the slave base station will send UWB signals to the positioning beacon. After receiving the signal, the positioning beacon will reflect or forward it back to the base station. The base station will measure the time delay from sending the signal to receiving the reflected signal (also known as flight time).

[0058] Preferably, the positioning analysis unit determines the real-time relative position relationship between the positioning beacon and the main base station according to the interactive information between the positioning beacon and the main base station and the multiple slave base stations, including:

[0059] Obtaining the signal strength of the signal sent by the positioning beacon at multiple consecutive time points and received by the primary base station;

[0060] According to the signal strength of the signal sent by the positioning beacon received by the main base station at multiple consecutive time points, it is determined whether to follow. For example, if the average signal strength of the signal sent by the positioning beacon received by the main base station at multiple consecutive time points is less than the average strength threshold, it is determined to follow;

[0061] If it is determined to follow, the signal strength of the signal sent by the positioning beacons received by the master base station and the multiple slave base stations at multiple consecutive time points;

[0062] Correcting the signal strength of signals sent by positioning beacons received by the master base station and multiple slave base stations at multiple consecutive time points;

[0063] Determine the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each slave base station according to the signal strength of the signal sent by the positioning beacon at multiple consecutive time points received by the corrected main base station and multiple slave base stations;

[0064] The real-time relative direction between the positioning beacon and the main base station is determined through a multivariate regression model based on the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each slave base station, wherein the real-time relative position relationship between the positioning beacon and the main base station includes the real-time distance and real-time relative direction between the positioning beacon and the main base station.

[0065] Specifically, the dependent variable of the multiple regression model includes the real-time relative direction between the positioning beacon and the main base station, and the independent variables of the multiple regression model include the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each slave base station.

[0066] Preferably, the positioning analysis unit corrects the signal strength of the signals sent by the positioning beacons received by the master base station and the multiple slave base stations at multiple consecutive time points, including:

[0067] Performing variational mode decomposition on the signal strength of the signal sent by the positioning beacon received by the primary base station at multiple consecutive time points to generate multiple first mode components, and extracting component features of each first mode component, such as center frequency, bandwidth, energy, time domain features (such as amplitude, phase, etc.), etc.;

[0068] For each slave base station, performing variational mode decomposition on the signal strength of the signal sent by the positioning beacon received from the slave base station at multiple consecutive time points to generate multiple second mode components, and extracting component features of each second mode component;

[0069] The signal strength of the signal sent by the positioning beacons received by the main base station and multiple slave base stations at multiple consecutive time points is corrected according to the component characteristics of each first modal component and the component characteristics of each second modal component through the strength correction model, wherein the strength correction model can be a convolutional neural network (CNN) model.

[0070] The information acquisition module can be used to obtain real-time environmental information.

[0071] Preferably, the information acquisition module includes an obstacle detection unit and a road surface detection unit, wherein the obstacle detection unit is used to obtain the relative position between the obstacle and the loudspeaker, and the road surface detection unit is used to obtain the roughness of the road surface.

[0072] The road surface detection unit includes a vibration detection component, an ultrasonic detection component and a roughness analysis component, wherein the vibration detection component is installed on the walking component and is used to collect vibration data of the walking component, and the ultrasonic detection component is installed on the walking component and is used to obtain ultrasonic detection data of the road surface;

[0073] The roughness analysis component determines the road surface roughness based on the vibration data of the traveling component collected by the vibration detection component and the ultrasonic detection data of the road surface.

[0074] Specifically, the road surface detection unit transmits ultrasonic waves to the road surface, reflects echo signals, and extracts features of the reflected echoes, such as parameters such as amplitude and frequency.

[0075] Obtain the speed information of the walking component at multiple consecutive time points and extract speed features, such as speed mean, speed standard deviation, etc.

[0076] According to the speed characteristics, the vibration data of the walking component collected by the vibration detection component at multiple consecutive time points is subjected to variational modal decomposition to generate multiple vibration modal components, and the component characteristics of the vibration modal components are extracted, which specifically includes the following processes:

[0077] S11, determining a plurality of groups of speed features for testing, wherein any two groups of speed features for testing have a difference in at least one of a speed mean value, a speed standard deviation, etc.;

[0078] S12. For each group of test speed characteristics, obtain the vibration data of the walking component on the road surface with different roughness with the test speed characteristics. For each road surface with each roughness, perform variational modal decomposition on the vibration data of the walking component on the road surface with the test speed characteristics with the test speed characteristics to obtain multiple test vibration modal components, extract the center frequency of each test vibration modal component, and determine the initial center frequency range corresponding to the test speed characteristics according to the center frequency of each test vibration modal component corresponding to each road surface roughness of the test speed characteristics, wherein the two endpoints of the initial center frequency range are the maximum value and the minimum value of the center frequency of all the test vibration modal components corresponding to the test speed characteristics, divide the initial center frequency range into multiple segments, calculate the importance parameter of each segment, take the segment with the importance parameter greater than the importance parameter threshold as the target segment, and determine the center frequency range corresponding to the test speed characteristics according to the target segment, wherein the two endpoints of the center frequency range are the maximum value and the minimum value of the center frequency in the target segment, and the importance parameter can be calculated according to the following formula:

[0079]

[0080] in, is the importance parameter of the g-th segment, is a binary variable. When the central frequency of at least one test vibration modal component among the multiple test vibration modal components corresponding to the fth road surface roughness of the test speed characteristic is located in the gth segment, then ,otherwise, , is the total number of roughness tested, is the number of groups of speed characteristics for testing, is a binary variable. When the central frequency of at least one test vibration modal component among the multiple test vibration modal components corresponding to the fth road surface roughness of the test speed characteristic is located in the eth segment, then ,otherwise, .

[0081] S13, establishing a first mapping model according to the central frequency range corresponding to each group of test speed features, wherein the independent variable of the first mapping model is the central frequency range, and the dependent variable of the mapping model is the speed feature;

[0082] S14, obtaining current speed characteristics;

[0083] S15. Determine a center frequency range corresponding to the current speed feature according to the current speed feature through the first mapping model;

[0084] S16. Perform variational modal decomposition on the vibration data of the walking component collected by the vibration detection component at multiple consecutive time points to generate multiple vibration modal components, and extract component characteristics of the vibration modal components whose center frequencies are within the center frequency range corresponding to the current speed characteristics.

[0085] The road surface roughness is determined by a roughness determination model based on the characteristics of multiple reflected echoes and the component characteristics of the vibration modal components whose center frequencies are within the center frequency range corresponding to the current speed characteristics. The roughness determination model may be a convolutional neural network model.

[0086] The loudspeaker following module can be used to determine the following path and following parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, wherein the following parameters include at least the following speed, and according to the following path and the following parameters, the walking component is controlled to drive the loudspeaker to move.

[0087] Preferably, the amplification and following module determines the following path according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, including:

[0088] Analyze the user's mobility characteristics based on the historical relative position relationship between the positioning beacon and the main base station, where the user's mobility characteristics include the user's relative direction change range and the user's speed change characteristics;

[0089] Determine the target following position according to the real-time relative position relationship and relative direction change range between the positioning beacon and the main base station;

[0090] A path search algorithm (eg, A* algorithm, Dijkstra algorithm, Bellman-Ford algorithm, etc.) is used to determine a following path according to the target following position and the relative position between the obstacle and the loudspeaker.

[0091] Specifically, the user movement characteristics can be analyzed by the feature analysis model according to the historical relative position relationship between the positioning beacon and the main base station. The target following position can be determined by the position determination model according to the real-time relative position relationship and relative direction change range between the positioning beacon and the main base station, wherein the feature analysis model and the position determination model can both be convolutional neural network models.

[0092] Preferably, the amplification following module determines the following parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, including:

[0093] The following speed is determined according to the following path, the user's speed change characteristics and the road roughness.

[0094] Specifically, a second mapping model may be established, wherein the dependent variable of the second mapping model may include the following speed, and the independent variables of the second mapping model may include path characteristics (for example, the length of the following path, the number of turns in the following path, etc.), user speed change characteristics, and road roughness.

[0095] The following speed may be determined by the second mapping model according to path characteristics (eg, the length of the following path, the number of turns in the following path, etc.), user speed variation characteristics, and road roughness.

[0096] The sound amplification adjustment module can be used to determine the real-time sound amplification parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the following path, wherein the real-time sound amplification parameters include at least the real-time volume and the real-time sound amplification posture, and the posture adjustment component is controlled according to the real-time sound amplification posture to adjust the posture of the loudspeaker, and the output volume of the loudspeaker is adjusted according to the real-time volume.

[0097] Preferably, the sound amplification adjustment module determines the real-time sound amplification parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the following path, including:

[0098] Determine the real-time amplification position based on the following path and the real-time relative position relationship between the positioning beacon and the main base station;

[0099] The real-time volume is determined based on the following path, the real-time relative position relationship between the positioning beacon and the main base station, and the relative position between the obstacle and the loudspeaker.

[0100] Specifically, the real-time amplification posture can be determined by the posture determination model according to the following path and the real-time relative position relationship between the positioning beacon and the main base station, and the real-time volume can be determined by the volume determination model according to the following path, the real-time relative position relationship between the positioning beacon and the main base station, and the relative position between the obstacle and the loudspeaker. Among them, the posture determination model and the volume determination model can both be convolutional neural network models.

[0101] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. A smart loudspeaker based on a positioning beacon, characterized in that: include: A following positioning module, comprising a positioning beacon arranged on the object to be followed, a main base station and a plurality of slave base stations arranged on a loudspeaker, and a positioning analysis unit, wherein any two of the slave base stations are located at different heights, and any one of the slave base stations and the main base station are located at different heights, and the positioning analysis unit is used to determine the real-time relative position relationship between the positioning beacon and the main base station according to the interactive information between the positioning beacon and the main base station and the plurality of slave base stations; Information acquisition module, used to obtain real-time environmental information; A loudspeaker following module, configured to determine a following path and following parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, wherein the following parameters at least include a following speed, and control the walking component to drive the loudspeaker to move according to the following path and the following parameters; A sound amplification adjustment module, configured to determine real-time sound amplification parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the following path, wherein the real-time sound amplification parameters at least include real-time volume and real-time sound amplification posture, control the posture adjustment component to adjust the posture of the loudspeaker according to the real-time sound amplification posture, and adjust the output volume of the loudspeaker according to the real-time volume; The following positioning module sets a plurality of slave base stations on the loudspeaker, including: Determine a plurality of first test positions at the loudspeaker, wherein any two of the first test positions are located at different heights, and any one of the first test positions is located at a different height from the primary base station; Under multiple test scenarios, respectively obtain first positioning test data of multiple first test positions; Calculating the signal similarity between any two of the first test positions according to the first positioning test data of the plurality of first test positions; Clustering the plurality of first test positions according to the signal similarity between any two of the first test positions by using a clustering algorithm to obtain a clustering result; Determine a plurality of second test positions according to the clustering result, wherein any two of the second test positions are located at different heights, and any one of the second test positions is located at a different height from the primary base station; Under various test scenarios, respectively obtain the second positioning test data of the primary base station and the third positioning test data of multiple second test locations; Calculating the signal similarity between the main base station and the second test position according to the second positioning test data of the main base station and the third positioning test data of the second test position; Screening the plurality of second test positions according to the signal similarity between the primary base station and the second test position to determine a plurality of third test positions; Determine a plurality of position combinations according to the plurality of third test positions, wherein each of the position combinations includes at least two third test positions; In a plurality of test scenarios, fourth positioning test data of each position combination is obtained, wherein the fourth positioning test data includes test data of the primary base station and test data of each third test position included in the position combination; The optimal position combination is determined based on the second positioning test data of the main base station, the third positioning test data of multiple second test positions, and the fourth positioning test data of each position combination, and multiple slave base stations are set on the loudspeaker based on the optimal position combination.

2. The smart loudspeaker based on positioning beacon according to claim 1, characterized in that: The positioning analysis unit determines the real-time relative position relationship between the positioning beacon and the primary base station according to the interaction information between the positioning beacon and the primary base station and the plurality of secondary base stations, including: Determining whether to follow according to the time delay between the main base station and the positioning beacon; If it is determined to follow, the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each of the slave base stations are determined according to the time delay between the main base station and the positioning beacon and the time delay between each of the slave base stations and the positioning beacon; The real-time relative direction between the positioning beacon and the main base station is determined by a multivariate regression model according to the real-time distance between the positioning beacon and the main base station and the real-time distance between the positioning beacon and each of the slave base stations, wherein the real-time relative position relationship between the positioning beacon and the main base station includes the real-time distance and real-time relative direction between the positioning beacon and the main base station.

3. The smart loudspeaker based on positioning beacon according to claim 2, characterized in that: The information acquisition module includes an obstacle detection unit and a road surface detection unit, wherein the obstacle detection unit is used to obtain the relative position between the obstacle and the loudspeaker, and the road surface detection unit is used to obtain the roughness of the road surface.

4. The smart loudspeaker based on positioning beacon according to claim 3, characterized in that: The road surface detection unit includes a vibration detection component, an ultrasonic detection component and a roughness analysis component, wherein the vibration detection component is installed on the walking component and is used to collect vibration data of the walking component, and the ultrasonic detection component is installed on the walking component and is used to obtain ultrasonic detection data of the road surface; The roughness analysis component determines the road surface roughness based on the vibration data of the traveling component and the ultrasonic detection data of the road surface collected by the vibration detection component.

5. The smart loudspeaker based on positioning beacon according to claim 4, characterized in that: The roughness analysis component determines the road surface roughness according to the vibration data of the traveling component and the ultrasonic detection data of the road surface collected by the vibration detection component, including: Extracting the characteristics of the reflected echo from the ultrasonic detection data of the road surface, including at least the amplitude and the frequency; Extracting speed features from the speed information of the walking component at multiple consecutive time points, including at least a speed mean and a speed standard deviation; According to the speed characteristics, the vibration data of the walking component collected by the vibration detection component at multiple consecutive time points are subjected to variational modal decomposition to generate multiple vibration modal components, and the component characteristics of the vibration modal components are extracted; The road surface roughness is determined by the roughness determination model based on the characteristics of multiple reflected echoes and the component characteristics of the vibration mode components whose center frequencies are within the center frequency range corresponding to the speed characteristics.

6. The smart loudspeaker based on positioning beacon according to claim 5, characterized in that: The amplification and following module determines a following path according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information, and the historical relative position relationship between the positioning beacon and the main base station, including: Analyze user mobility characteristics according to the historical relative position relationship between the positioning beacon and the primary base station, wherein the user mobility characteristics include the user relative direction change range and the user speed change characteristics; Determine the target following position according to the real-time relative position relationship between the positioning beacon and the main base station and the relative direction change range; The following path is determined using a path search algorithm according to the target following position and the relative position between the obstacle and the loudspeaker.

7. The smart loudspeaker based on positioning beacon according to claim 6, characterized in that: The amplification following module analyzes the user movement characteristics according to the historical relative position relationship between the positioning beacon and the main base station, including: The user speed change feature is extracted based on the historical relative position relationship between the positioning beacon and the main base station through a feature analysis model.

8. The smart loudspeaker based on positioning beacon according to claim 7, characterized in that: The amplification following module determines the following parameters according to the real-time relative position relationship between the positioning beacon and the main base station, the real-time environmental information and the historical relative position relationship between the positioning beacon and the main base station, including: The following speed is determined according to the following path, a user speed change characteristic, and a road surface roughness.

9. The smart loudspeaker based on positioning beacon according to claim 8, characterized in that: The sound amplification adjustment module determines the real-time sound amplification parameters according to the real-time relative position relationship between the positioning beacon and the primary base station, the real-time environmental information and the following path, including: Determine a real-time amplification posture according to the following path and the real-time relative position relationship between the positioning beacon and the main base station; The real-time volume is determined according to the following path, the real-time relative position relationship between the positioning beacon and the main base station, and the relative position between the obstacle and the loudspeaker.

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