Multi-mode intelligent mobile system and method based on UWB-Beidou fusion

Abstract

The invention relates to a multi-mode intelligent mobile system and method based on UWB-Beidou fusion, and aims to solve the problems of poor indoor positioning quality and multipath effect of Beidou in an indoor or sheltered environment by utilizing accurate position information provided by a Beidou positioning system in an outdoor open scene and utilizing a UWB and Beidou fusion positioning algorithm. Furthermore, a UWB / Beidou positioning technology integrated positioning system is built on a mobile device, and a voice control module is adopted to realize recognition and response of voice instructions and complete functions of mode switching, information output and the like. In the path planning and control algorithm design, the system can obtain the attitude and position of the equipment in real time by fusing the angle sensor and position data, and high-precision execution of path planning and fixed-point driving is ensured. In addition, the method is integrated with accurate positioning of a Beidou module, and a designed path planning algorithm can dynamically generate an optimal path according to a starting point and a target point, so that different environment and task requirements are met, and the flexibility and adaptability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent transportation, and particularly to a multi-modal intelligent mobile system and method based on UWB-Beidou fusion. Background Art

[0002] In the current positioning and control technology system, relatively mature technical ecosystems have been formed for high-precision positioning in outdoor environments. The Global Navigation Satellite System (GNSS) is used as the core technology to achieve all-weather coverage through multi-constellation collaboration. Among them, the Beidou-3 system, through the hybrid constellation design of 24 medium Earth orbit satellites, 3 geostationary orbit satellites, and 3 inclined geosynchronous orbit satellites, enables the positioning accuracy to reach the centimeter level. The GPS system uses L1 (1575.42 MHz) and L5 (1176.45 MHz) dual-frequency signals, combined with the carrier phase differential technology (RTK), to achieve real-time kinematic positioning of 2-5 cm in open areas. This technical advantage has promoted breakthrough developments in fields such as intelligent transportation and unmanned aerial vehicle inspection.

[0003] However, in indoor or occluded environments, traditional satellite positioning faces significant technical bottlenecks. The attenuation of L-band satellite signals by buildings can reach more than 30 dB, resulting in the received signal strength being lower than the capture threshold. More severely, the positioning error caused by multipath effects. After the electromagnetic wave is reflected multiple times by metal curtain walls and concrete structures, the signal propagation path is extended, resulting in pseudorange measurement deviation. In typical scenarios, the positioning drift can reach 50-100 meters. Therefore, in view of the technical problems such as weak signals and poor positioning quality caused by multipath effects faced by the traditional Beidou positioning system, the present application proposes a system that integrates UWB (Ultra Wide Band) technology and Beidou positioning technology, aiming to provide high-precision positioning services indoors and outdoors, and combining with other modules to achieve intelligent control of mobile devices. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the deficiencies in the prior art and provide a multi-modal intelligent mobile system and method based on UWB-Beidou fusion.

[0005] The present invention is realized through the following technical solutions:

[0006] A multi-modal intelligent mobile system based on UWB-Beidou fusion, comprising:

[0007] A positioning unit, including a UWB module and a Beidou / GPS dual-mode positioning module. In outdoor scenarios, the Beidou / GPS dual-mode positioning module is used to obtain outdoor positioning data. In indoor or occluded environments, the position information of the UWB module and the Beidou / GPS dual-mode positioning module is fused to obtain indoor positioning data;

[0008] The path planning and control unit includes an infrared sensing module, an ultrasonic module, an angle sensor module, and a PID controller. In an outdoor scenario, according to the outdoor positioning data and the destination positioning data, path navigation is achieved through the angle sensor module, the PID controller, and the ultrasonic module. In an indoor or occluded environment, according to the indoor positioning data, path navigation is achieved through the infrared sensing module and the ultrasonic module.

[0009] According to the above technical solution, preferably, when the position information of the UWB module is fused with the Beidou / GPS dual-mode positioning module, Kalman filtering is used to fuse multi-source positioning information, and its expression is:

[0010] K = PH T (HPH T +R) ―1

[0011] Where, the set target position is X = [x, y, z] T , the UWB measurement value is Z UWB , the Beidou measurement value is Z BD , the state transition matrix is F, the observation matrix is H, the process noise covariance matrix is Q, the observation noise covariance matrix is R, P is the prediction error covariance matrix, and K represents the Kalman gain;

[0012] The calculation formula for the fusion result is:

[0013] X fused = w UWB X UWB + w BD X BD

[0014] Where, the set positioning result after fusion is X fused , the positioning result of UWB is X UWB , the Beidou positioning result is w BD , the weight coefficient is w UWB and w BD , satisfying w UWB + w BD = 1.

[0015] According to the above technical solution, preferably, the multi-modal intelligent mobile system disclosed in this application further includes:

[0016] A voice control module, which is used for the recognition and response of voice commands, and completes functions such as switching working modes, system wake-up, operation, stop, information command reception and execution;

[0017] An environment detection module, which collects image or video data through a camera and transmits it to a remote server or a control center to realize real-time monitoring of the current environment.

[0018] This application also discloses a multi-modal intelligent mobile method based on UWB-Beidou integration. Based on the above multi-modal intelligent mobile system, it includes an indoor operation mode and an outdoor operation mode.

[0019] The indoor operation mode includes the following steps:

[0020] S11. When running on the black track built according to user requirements, multiple infrared sensing modules emit infrared rays. If the sensor does not receive the returned infrared rays, it outputs 1; if it receives the returned infrared rays, it outputs 0. Through programming, ensure that the mobile device always stays on the predetermined track.

[0021] S12. Real-time detect obstacles ahead through the ultrasonic module, enabling the mobile device to avoid obstacles autonomously.

[0022] The outdoor operation mode includes the following steps:

[0023] S21. The Beidou / GPS dual-mode positioning module cooperates with the main control single-chip microcomputer to obtain the positioning data of the mobile device in real time.

[0024] S22. Input the location information of the destination. The Beidou / GPS dual-mode positioning module cooperates with the angle sensor module to calculate the difference between the current azimuth and the target longitude and latitude. Through the PID controller, adjust the control parameters to make the mobile device run towards the input destination.

[0025] S23. Real-time detect obstacles ahead through the ultrasonic module, enabling the mobile device to avoid obstacles autonomously.

[0026] According to the above technical solution, preferably, the ultrasonic module includes an HC-SR04 ultrasonic sensor. By emitting ultrasonic pulses, measure the time difference from emission to reception, calculate the distance to the obstacle ahead. When the distance to the obstacle ahead is less than the set threshold, trigger the obstacle avoidance strategy, including stopping, detouring or backing up.

[0027] According to the above technical solution, preferably, in step S12, the HC-SR04 ultrasonic sensor is combined with a servo motor to drive the servo motor and drive the ultrasonic module to rotate.

[0028] According to the above technical solution, preferably, in step S22, the PID controller is used to calculate the control output according to the deviation between the current position and the target position, so that the mobile device moves towards the target point.

[0029] According to the above technical solution, preferably, the output calculation formula of the PID controller is:

[0030]

[0031] Among them, u(t) is the control output, and e(t) is the deviation between the current position and the target position.

[0032] Proportional term P: Calculate the control output according to the deviation between the current position and the target position. The proportional coefficient K p Determines the influence degree of the deviation on the control output.

[0033] Integral term I: Accumulate historical errors to eliminate steady-state errors. The integral coefficient K i Determines the influence degree of the integral term on the control output.

[0034] Differential term D: Predict future errors to suppress system overshoot. The differential coefficient K d Determines the influence degree of the differential term on the control output.

[0035] According to the above technical solution, preferably, it further includes: constructing a dynamic energy consumption perception-performance regulation coupling system to achieve the Pareto optimal balance between energy consumption and performance. Specifically, establish a power consumption feature library for the positioning unit, path planning and control unit, voice control module, and environment detection module, and implant an INA219 current sensor at the hardware layer to construct a distributed energy consumption monitoring network to achieve millisecond-level longitude power consumption sampling. According to the formulated operation mode dynamic switching strategy, maximize energy savings and improve the system's battery life while ensuring the normal operation of the mobile system.

[0036] The beneficial effects of the present invention are:

[0037] (1) The UWB and Beidou fusion positioning algorithm used in this application realizes high-precision positioning with seamless indoor and outdoor switching by combining the high-precision positioning, anti-interference ability, and flexible deployment method of UWB, as well as the outdoor positioning advantage of the Beidou system, overcoming the problems of insufficient positioning accuracy, difficult indoor positioning, and weak anti-interference ability in the prior art in complex environments.

[0038] (2) This application uses the SU-03T voice module to realize the recognition and response of voice commands, and complete functions such as mode switching and information output. It greatly improves the convenience and flexibility of use, and broadens the user market of mobile devices including the disabled.

[0039] (3) In the design of the path planning and control algorithm, by fusing the ATK-IMU901 angle sensor and position data, the system can obtain the attitude and position of the device in real time to ensure the high-precision execution of path planning and fixed-point driving.

[0040] (4) By integrating the path planning with the precise positioning of the Beidou module, the designed path planning algorithm can dynamically generate the optimal path according to the starting point and the target point, adapt to different environmental and task requirements, and improve the flexibility and adaptability of the system.

[0041] (5) A PID controller is adopted to calculate the position error in real time by adjusting the proportional (P), integral (I), and derivative (D) coefficients, and correct it through the control input to reduce the deviation and improve the stability and reliability of the system.

[0042] (6) Through the combination of the Wi-Fi video transmission module and the servo drive module in this application, an efficient and flexible environmental monitoring system is realized, overcoming the problems of complex wiring and inconvenient installation of traditional wired monitoring systems, and having significant technical advantages.

[0043] (7) By building a dynamic energy consumption perception - performance regulation coupling system, the Pareto optimal balance between energy consumption and performance is achieved, and the triple coupling of hardware characteristics - software strategies - environmental factors is realized, upgrading the traditional sensor fusion mechanism from functional fusion to efficiency collaborative fusion. Brief Description of the Drawings

[0044] Figure 1 It is the technical flow chart of the multi-modal intelligent mobile method disclosed by the present invention.

[0045] Figure 2 It is the schematic diagram of the UWB (Ultra Wide Band) positioning principle in the present invention. Detailed Embodiments

[0046] In order to enable those skilled in the art of the present technology to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the drawings and the best embodiments. Based on the embodiments of the invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the scope of protection of the invention.

[0047] Embodiment 1: A multi-modal intelligent mobile system based on UWB - Beidou fusion, comprising:

[0048] A positioning unit, including a UWB module and a Beidou / GPS dual-mode positioning module. In an outdoor scenario, the Beidou / GPS dual-mode positioning module is used to obtain outdoor positioning data. In an indoor or occluded environment, the position information of the UWB module and the Beidou / GPS dual-mode positioning module is fused to obtain indoor positioning data;

[0049] A path planning and control unit, including an infrared sensing module, an ultrasonic module, an angle sensor module, and a PID controller. In an outdoor scenario, according to the outdoor positioning data and the destination positioning data, path navigation is realized through the angle sensor module, the PID controller, and the ultrasonic module. In an indoor or occluded environment, path navigation is realized through the infrared sensing module and the ultrasonic module according to the indoor positioning data.

[0050] Among them, the positioning unit is composed of a UWB and an ATGM332D-5N-31 (Beidou / GPS dual-mode positioning module), including an outdoor positioning mode (OPM) and an indoor positioning mode (IPM), specifically including:

[0051] OPM mode: This mode is used in outdoor open scenarios. This mode mainly uses the ATGM332D-5N-31 module to provide high-precision position data of the system in the outdoor environment. The data output by the module (information such as longitude, latitude, time, etc.) is received and parsed through serial communication to provide accurate and effective position data for the movement method of the mobile system outdoors;

[0052] IPM mode: This mode is used in indoor or occluded environments. This mode adopts a positioning algorithm that combines UWB and Beidou. Develop a positioning algorithm that combines UWB and Beidou, and use methods such as Kalman filtering to fuse multi-source positioning information. Specifically, the position point of the target (mobile device) is obtained through the positioning algorithm that combines UWB and Beidou proposed in this patent, that is, the position information obtained by UWB and the position information obtained by Beidou are weighted and calculated, and then the two positioning information is fused through Kalman filtering to improve the positioning accuracy.

[0053] Among them, UWB ranging usually adopts the Time Difference of Arrival (TDOA) principle, and UWB positioning usually adopts the Time Difference of Arrival (TDOA) principle. The time difference of radio signal propagation between the positioning tag and multiple positioning modules is measured using UWB technology, so as to obtain the distance difference of the positioning tag, and the distance calculation formula is:

[0054]

[0055] In the above formula, (x,y) is the coordinate of the positioning tag, (x i , y i ) and (x j , y j ) are the coordinates of two positioning modules, and Δd ij is the distance difference between the two modules. By solving multiple such equations, the exact position of the positioning tag can be determined.

[0056] The above process mainly introduced the ranging calculation principle of UWB, and the specific principle of UWB positioning is as follows: The UWB system emits electromagnetic pulses with high frequency and extremely short duration, and calculates the distance by measuring the time difference of signal propagation. Based on these distances, three-point positioning is adopted. That is, in a two-dimensional plane, the coordinates (latitude and longitude) of three positioning base stations are known, denoted as A(x1, y1), B(x2, y2), and C(x3, y3) respectively. If the distances between these three base stations and the positioning target X(x, y) are d1, d2, and d3 respectively. Their corresponding relationship is: draw three circles A, B, and C with the base station coordinates as the center and d1, d2, and d3 as the radii so that they intersect at a point, and the coordinates of this point are the position of the positioning target. Continuously carry out this process, that is, draw the movement trajectory of the mobile device in the two-dimensional plane, and realize the real-time positioning of the mobile device at the same time.

[0057] The ranging principle of the BeiDou Navigation Satellite System (BDS) is as follows: The BeiDou satellite positioning adopts a three-dimensional positioning principle. By receiving the signals of at least four satellites, the position of the receiver is determined by using the three-sphere intersection positioning method. By solving the following equations, the three-dimensional position (x, y, z) of the receiver and the clock deviation t can be obtained:

[0058]

[0059] In the above formula, the position of the receiver is set as (x, y, z), the known position of satellite i is (x i , y i , z i ), the pseudorange between the receiver and satellite i is ρ i , and c is the speed of light.

[0060] Develop a positioning algorithm that fuses UWB and BeiDou, and use methods such as Kalman filtering to fuse multi-source positioning information. Its expression is:

[0061] K = PH T (HPH T + R) ―1

[0062] Among them, the target position is set as X = [x, y, z] T , the UWB measurement value is Z UWB , the BeiDou measurement value is Z BD , the state transition matrix is F, the observation matrix is H, the process noise covariance matrix is Q, the observation noise covariance matrix is R, P is the prediction error covariance matrix, and K represents the Kalman gain;

[0063] Realize the fusion of UWB and BeiDou positioning data to improve the positioning accuracy. The calculation formula for the fusion result is:

[0064] X fused = w UWB X UWB + w BD X BD

[0065] Wherein, the set positioning result after fusion is X fused , the positioning result of UWB is X UWB , the Beidou positioning result is w BD , and the weight coefficients are w UWB and w BD , satisfying w UWB + w BD = 1.

[0066] In addition, the multi-modal intelligent mobile system disclosed in this application further includes:

[0067] A voice control module, which is used for the recognition and response of voice commands, and completes functions such as switching working modes, system wake-up, operation, stop, information command reception and execution;

[0068] An environment detection module, which collects image or video data through a camera and transmits it to a remote server or a control center to realize real-time monitoring of the current environment.

[0069] In this example, the voice control module adopts the SU-03T voice module to realize the recognition and response of voice commands, including but not limited to: accepting and executing commands such as switching working modes, system wake-up, operation, stop and customized interesting communication. The SU-03T module supports custom wake-up words and command words, and can be configured through the Smart AD platform. The specific configuration steps are as follows: log in to the Smart AD platform, create a product and configure wake-up words and command words; download the generated SDK, and burn the firmware to the SU-03T module through a burning tool; in the STM32 main control single-chip microcomputer, communicate with the SU-03T module through a serial port to realize the recognition and response of voice commands. In addition, through the configuration of the SU-03T voice module, it can output the current position coordinates, and the user can also input the destination coordinates through voice, which is combined with path planning to realize the function of fixed-point driving.

[0070] In this example, the environmental detection module is the WIFI visual real-time video transmission module. Through wireless transmission technology, this module transmits the visual information around the device to the remote receiving end (remote server or control center) in real time, realizing remote monitoring and analysis of the environment. In this example, video coding standards such as H.264 or H.265 are adopted to compress the data volume and improve the transmission efficiency. At the receiving end, the image or video is decoded and displayed to realize real-time monitoring of the environment. In some application scenarios, the remote receiving end can control the device, such as adjusting the camera angle, starting or stopping image acquisition, etc. Combined with the servo, it drives the servo to drive the above-mentioned WiFi video transmission module to rotate at different angles. Common rotation methods include 0 - 90°, 0 - 180°, 0 - 360°. The specific servo model and angle rotation method can be determined according to user requirements.

[0071] This application proposes a system that integrates UWB (Ultra Wideband) technology and Beidou positioning technology, aiming to provide high-precision positioning services indoors and outdoors, and combined with other modules to achieve intelligent control of mobile devices. Specifically, the system realizes a series of instruction functions such as mode switching, information output, wake-up, operation, stop, and customized interesting communication through the linkage between the STM32 main control single-chip microcomputer (including but not limited to) and the SU-03T voice module. At the same time, the system is integrated with the HC-SR04 ultrasonic obstacle avoidance module to respond to sudden obstacles. Through the cooperation of the Wi-Fi video transmission module and the intelligent cloud platform, real-time monitoring of the environment around the mobile device is achieved.

[0072] Through the technical solution of this patent, it can effectively solve the problems of insufficient positioning accuracy, difficult indoor positioning, lack of intelligent interaction and environmental perception in the prior art in complex environments, and provide a multi-mode intelligent mobile system method with high-precision indoor and outdoor positioning functions.

[0073] Embodiment 2: This application also discloses a multi-modal intelligent mobile method based on UWB-Beidou integration. Based on the above multi-modal intelligent mobile system, hardware components such as the UWB module, Beidou / GPS dual-mode positioning module, STM32 main control single-chip microcomputer, SU-03T voice module, HC-SR04 ultrasonic obstacle avoidance module, and Wi-Fi video transmission module are integrated into the mobile device. Different mobile devices (such as ferry vehicles, drones, robots, etc.) may have different hardware platforms, but all need to integrate the above key modules. It should be noted that all modules need to communicate through a unified interface standard. Common interfaces include:

[0074] I2C (Inter-Integrated Circuit): Suitable for the communication of low-speed devices and is suitable for sensors, display modules, etc.

[0075] SPI (Serial Peripheral Interface): Suitable for high-speed data transmission and is often used in Wi-Fi video transmission modules or large-capacity sensors.

[0076] UART (Universal Asynchronous Receiver / Transmitter): Suitable for devices that transmit less data, such as voice modules (SU-03T) and ATK-IMU901 angle sensor modules.

[0077] GPIO (General Purpose Input / Output): Used for basic control and switching operations, such as controlling the trigger signal of the HC-SR04 ultrasonic module.

[0078] Each hardware module and component needs to physically adapt to the actual structure of the mobile device. Considering the physical forms of different devices (e.g., shuttle vehicles, drones, or other types of robots), the integration process needs to ensure a compact layout and shock-proof protection design for all modules. To ensure the stability of each module in complex environments, all electronic components need to be waterproofed, dustproofed, etc., especially for applications in outdoor or harsh weather conditions. For modules such as UWB positioning modules, Beidou positioning modules, and HC-SR04 ultrasonic modules, appropriate positions need to be selected to ensure good signal reception.

[0079] The method proposed in this application can be used in different mobile devices according to actual uses. To ensure the unified integration of different devices, users need to design a standardized interface and communication protocol according to the actual situation of the mobile device, so that regardless of the device form (shuttle vehicle, drone, mobile detector, etc.), the hardware modules can be integrated and work together in a unified manner. Specifically, it includes:

[0080] Interface standardization: Ensure that each module can communicate and exchange data through standardized interfaces (I2C, SPI, UART);

[0081] Software modularization: Design different software modules according to the different functions of the device to ensure that the same control platform can flexibly control different types of hardware devices.

[0082] The multi-modal intelligent mobile method disclosed in this application includes an indoor operation mode (IM) and an outdoor operation mode (OM), and the indoor operation mode includes the following steps:

[0083] S11. When running on the black track built according to the user's requirements, multiple infrared sensing modules (TCRT5000 infrared sensors) emit infrared rays. If the sensor does not receive the returned infrared rays, it outputs 1 (the sensor is above the track). If it receives the returned infrared rays, it outputs 0 (the sensor is not above the track). By programming, ensure that the mobile device is always on the predetermined track, that is, continuously adjust the movement direction of the mobile device.

[0084] S12. Detect the obstacles ahead in real time through the ultrasonic module, enabling the mobile device to avoid obstacles autonomously. The ultrasonic module includes an HC-SR04 ultrasonic sensor. By emitting ultrasonic pulses, measure the time difference from emission to reception, and calculate the distance to the obstacle ahead. When the distance to the obstacle ahead is less than the set threshold, trigger the obstacle avoidance strategy, including stopping, detouring, or reversing.

[0085] Specifically, use the ultrasonic module HC-SR04. Give Trig at least 10 us of high level. When jumping from low level to high level, it indicates the start of sending the Echo signal. When jumping back to low level from high level, it indicates that the wave returns and is received. Let the distance to the obstacle be S, start the timer to calculate the wave duration as T, and calculate the distance S. Its expression is:

[0086]

[0087] Program according to the user's requirements. When S is less than a certain value, execute the corresponding movement instruction.

[0088] Combine the HC-SR04 with the servo motor to drive the servo motor and drive the above ultrasonic module to rotate at different angles. Common rotation methods are 0 - 90°, 0 - 180°, 0 - 360°. The specific servo motor model and angle rotation method can be determined according to the user's requirements.

[0089] When the positioning system is in the IPM mode, the position and driving track of the mobile device are displayed in real time on the mobile device or a small program on the computer, realizing intelligent management and control of the mobile device. Functions such as real-time positioning management of devices or personnel, long-time stationary warning, quick search, and track tracing can be further designed according to actual needs.

[0090] In addition, when in the outdoor operation mode, install the ATGM332D-5N-31 module on the mobile device. This module supports global navigation satellite systems such as Beidou, GPS, GLONASS, and Galileo. By demodulating and processing these signals through the built-in receiver, the arrival time and position data of the satellite signals are extracted. This module can output information including position coordinates (longitude, latitude, altitude), speed, time, etc. Send these positioning information to the slave main control microcontroller (such as STM32) through communication interfaces such as serial port (UART), I2C, or SPI for subsequent navigation control or other positioning applications. By cooperating the ATGM332D-5N-31 module with the main control microcontroller, the system can calculate the current coordinates of the device in real time and can be fed back to the user through the voice module SU-03T. The user can interact with the system through voice commands for operations such as fixed-point navigation and path planning.

[0091] Among them, the outdoor operation mode includes the following steps:

[0092] S21. The Beidou / GPS dual-mode positioning module cooperates with the main control microcontroller to obtain the positioning data of the mobile device in real time, which can be fed back to the user through the voice module SU-03T. The user can interact with the system through voice commands for operations such as fixed-point navigation and path planning.

[0093] S22. The user can input the location information of the destination through the SU-03T voice module. The ATGM332D-5N-31 module can obtain the current location information, cooperate with the ATK-IMU901 angle sensor module, calculate the difference between the current azimuth angle and the target longitude and latitude, and adjust the control parameters through the PID controller to make the mobile device run towards the input destination.

[0094] S23. Detect obstacles ahead in real time through the ultrasonic module so that the mobile device can avoid obstacles autonomously.

[0095] Among them, it is worth noting that based on the ATK-IMU901 angle sensor data and the position data obtained through the ATGM332D-5N-31 module, path planning and fixed-point driving algorithms are designed to ensure that the device travels along the predetermined path.

[0096] Design a path planning algorithm to generate the optimal path from the starting point to the end point. Let the starting point be P start =[x start ,y start T , and the target path point be P target =[x target ,y targett T , and the control input be u = [v, w] T ​​, where v is the linear velocity and w is the angular velocity. The control algorithm calculates the control input according to the position error ∈ = ||P target ―P current || to ensure that the device travels along the path.

[0097] The control algorithm can adopt a PID controller. By adjusting the proportional (P), integral (I), and derivative (D) coefficients, precise control of the device can be achieved. The PID controller is used to calculate the control output according to the deviation between the current position and the target position, so that the mobile device moves towards the target point. The output calculation formula of the PID controller is:

[0098]

[0099] where u(t) is the control output, e(t) is the deviation between the current position and the target position,

[0100] Proportional term P: Calculate the control output according to the deviation between the current position and the target position. The proportional coefficient K p determines the influence degree of the deviation on the control output,

[0101] Integral term I: Accumulate historical errors to eliminate steady-state errors. The integral coefficient K i determines the influence degree of the integral term on the control output,

[0102] Derivative term D: Predict future errors and suppress system overshoot. The derivative coefficient K d determines the influence degree of the derivative term on the control output.

[0103] In addition, the multi-modal intelligent mobile method based on UWB-Beidou fusion disclosed in this application further includes: constructing a dynamic energy consumption perception-performance regulation coupling system to achieve the Pareto optimal balance between energy consumption and performance. Specifically, establish the power consumption characteristic libraries of the positioning unit, path planning and control unit, voice control module, and environment detection module, and implant an INA219 current sensor at the hardware layer to construct a distributed energy consumption monitoring network to achieve millisecond-level longitude power consumption sampling. According to the formulated operation mode dynamic switching strategy, maximize energy savings and improve the system's endurance while ensuring the normal operation of the mobile system.

[0104] An INA219 current sensor is implanted at the hardware layer to monitor the distributed power consumption of each module. The example monitoring code is as follows:

[0105]

[0106] Formulate rules for the fusion of data confidence, such as: high confidence when the UWB error is within 0.3 ms, and the higher the number of satellites, the higher the confidence, etc.

[0107] Based on this, an energy consumption prediction model can be established, and the example code is as follows:

[0108]

[0109] On this basis, for such multiple conflicting objectives (energy consumption VS performance), the NSGA-II algorithm is used to solve the Pareto optimal solution set, so that any two solutions in the solution set do not dominate each other, and the solution set is evenly and widely distributed in the objective space. The specific implementation steps are as follows:

[0110] (1) Stratify the solutions in the population according to the dominance relationship (frontier level). The solutions in the first front (Front1) are not dominated by any other solutions, and the solutions in the second front (Front 2) are only dominated by the first front, and so on.

[0111] (2) After sorting each objective function (dynamic energy consumption prediction of different modules) separately according to the above steps, calculate the local density of the solutions to ensure parameter diversity:

[0112]

[0113] In the above formula, M is the number of objective functions, is the right value of the adjacent solution in the m-th objective function, is the left value of the adjacent solution.

[0114] (3) Select the top N individuals according to the frontier level and local density, and continuously replace them with new parent data to achieve the simultaneous retention of the data of the offspring and the parent.

[0115] According to the optimal solution set obtained above, specify the dynamic mode switching state machine, and the example code is as follows:

[0116]

[0117] According to the above multi-objective optimization algorithm, dynamically adjust the working mode of the module to enable the mobile system to take into account both performance and energy consumption during operation, and maximize the battery life of the mobile system on the basis of ensuring performance.

[0118] For the adaptive power consumption strategy mode of each module, taking the adaptive video transmission strategy as an example:

[0119]

[0120] The remaining modules can be analogized accordingly.

[0121] The method provided in this application can be combined with actual usage scenarios, and the main control microcontroller (such as STM32) and the voice module (SU-03T module) can be flexibly linked through programming to realize the preset of the mobile route, the call and linkage of each module, and through SU-03T, the user can realize the mode (indoor / outdoor, route a / b / c / ...) switching, information output, basic wake-up, operation, stop, customized fun communication and other commands of the mobile system by voice input. At the same time, it is integrated with the HC-SR04 (Ultrasonic Sensor Module) ultrasonic obstacle avoidance module to respond to sudden obstacles (the specific response method can be designed in combination with the actual scene, such as detour, reverse, etc.). And through the cooperation of the WIFI (Wireless Fidelity) image transmission module and the intelligent gimbal, the monitoring of the surrounding environment of the mobile device can be realized.

[0122] For example, in large indoor / indoor / outdoor mixed places such as airport terminals, large shopping malls, and tourist attractions, the routes are relatively simple / easy to plan and the amount of movement is large. Such a mobile system that takes into account autonomous positioning, path planning, and intelligent interaction can appear in the form of a shuttle bus / small sightseeing car; in the field of search and rescue, in some difficult-to-reach areas, the system can be used in the form of an autonomous mobile detector, and the voice interaction and image transmission modules realize the connection between the monitored area or personnel and the monitoring party or the search and rescue party.

[0123] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A multi-modal intelligent mobile system based on UWB-Beidou fusion, characterized in that: include: The positioning unit includes a UWB module and a Beidou / GPS dual-mode positioning module. In outdoor scenarios, the Beidou / GPS dual-mode positioning module is used to obtain outdoor positioning data. In indoor or shielded environments, the UWB module is integrated with the position information of the Beidou / GPS dual-mode positioning module to obtain indoor positioning data. The path planning and control unit includes an infrared sensor module, an ultrasonic module, an angle sensor module, and a PID controller. In outdoor scenes, path navigation is achieved through the angle sensor module, PID controller, and ultrasonic module according to the outdoor positioning data and the destination positioning data. In indoor or shielded environments, path navigation is achieved through the infrared sensor module and ultrasonic module according to the indoor positioning data.

2. According to claim 1, a multi-modal intelligent mobile system based on UWB-Beidou fusion is characterized in that: When the position information of the UWB module and the Beidou / GPS dual-mode positioning module is integrated, Kalman filtering is used to integrate the multi-source positioning information, and the expression is: K=PH T (HPH T +R) ―1 Among them, the target position is set to X = [x, y, z] T , UWB measurement value is Z UWB , Beidou measurement value is Z BD , the state transfer matrix is ​​F, the observation matrix is ​​H, the process noise covariance matrix is ​​Q, the observation noise covariance matrix is ​​R, P is the prediction error covariance matrix, and K represents the Kalman gain; The calculation formula of the fusion result is: X fused =w UWB X UWB +w BD X BD Among them, the positioning result after fusion is set to X fused , the positioning result of UWB is X UWB , Beidou positioning result is w BD , the weight coefficient is w UWB and w BD , satisfying w UWB +w BD =1.

3. The multi-modal intelligent mobile system based on UWB-Beidou fusion according to claim 1, characterized in that: Also includes: The voice control module is used to recognize and respond to voice commands, and complete the functions of switching working modes, system wake-up, running, stopping, and receiving and executing information commands.

4. The multi-modal intelligent mobile system based on UWB-Beidou fusion according to claim 1, characterized in that: Also includes: The environment detection module collects images or video data through the camera and transmits it to the remote server or control center to achieve real-time monitoring of the current environment.

5. A multi-modal intelligent mobility method based on UWB-Beidou fusion, based on a multi-modal intelligent mobility system based on UWB-Beidou fusion as described in claims 1-4, characterized in that: Including indoor operation mode and outdoor operation mode, The indoor operation mode comprises the following steps: S11. When running on the black track built according to user requirements, multiple infrared sensor modules emit infrared rays. If the sensor does not receive the returned infrared rays, it outputs 1. If it receives the returned infrared rays, it outputs 0. The mobile device is always on the predetermined track through programming; S12. The ultrasonic module detects obstacles in front in real time, so that the mobile device can autonomously avoid obstacles; The outdoor operation mode comprises the following steps: S21. The Beidou / GPS dual-mode positioning module cooperates with the main control microcontroller to obtain real-time positioning data of the mobile device; S22. Input the location information of the destination. The Beidou / GPS dual-mode positioning module cooperates with the angle sensor module to calculate the difference between the current azimuth and the target longitude and latitude. Through the PID controller, adjust the control parameters to allow the mobile device to run to the input destination; S23. The ultrasonic module is used to detect obstacles ahead in real time, so that the mobile device can avoid obstacles autonomously.

6. The multi-modal intelligent mobility method based on UWB-Beidou fusion according to claim 5, characterized in that: The ultrasonic module includes an HC-SR04 ultrasonic sensor, which transmits ultrasonic pulses, measures the time difference from transmission to reception, and calculates the distance of the obstacle in front. When the distance of the obstacle in front is less than a set threshold, an obstacle avoidance strategy is triggered, including stopping, detouring or reversing.

7. The multi-modal intelligent mobility method based on UWB-Beidou fusion according to claim 6, characterized in that: In step S12, the HC-SR04 ultrasonic sensor is combined with a steering gear to drive the steering gear to drive the ultrasonic module to rotate.

8. The multi-modal intelligent mobility method based on UWB-Beidou fusion according to claim 5, characterized in that: In step S22, the PID controller is used to calculate a control output according to a deviation between the current position and the target position, so as to move the mobile device toward the target point.

9. The multi-modal intelligent mobility method based on UWB-Beidou fusion according to claim 8, characterized in that: The output calculation formula of the PID controller is: Among them, u(t) is the control output, e(t) is the deviation between the current position and the target position, Proportional term P: Calculate the control output based on the deviation between the current position and the target position, proportional coefficient K p Determines the degree of influence of the deviation on the control output. Integral term I: accumulated historical error, elimination of steady-state error, integral coefficient K i Determines the degree of influence of the integral term on the control output. Differential term D: predict future errors, suppress system overshoot, differential coefficient K d Determines the influence of the differential term on the control output.

10. The multi-modal intelligent mobility method based on UWB-Beidou fusion according to claim 5, characterized in that: Also includes: Build a dynamic energy consumption perception-performance regulation coupling system to achieve the Pareto optimal balance between energy consumption and performance. Specifically, A power consumption feature library of the positioning unit, path planning and control unit, voice control module, and environmental detection module is established, and an INA219 current sensor is implanted at the hardware layer to build a distributed energy consumption monitoring network, achieve millisecond-level longitude power consumption sampling, and dynamically switch strategies based on the established operating modes. This maximizes energy savings and improves system endurance while ensuring the normal operation of the mobile system.

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