A UWB-based remote control method and system

Abstract

The embodiment of the present disclosure discloses a UWB-based remote control method and system, relates to the technical field of data transmission, and is used for solving the technical problem of poor control stability of the remote control system in the prior art. The UWB-based remote control system comprises a UWB module, an inertial detection module and a data processing module. The UWB module is used for interacting with a UWB base station to determine initial position information of the remote control system. The inertial detection module is used for acquiring current inertial parameters of the remote control system. The data processing module is used for determining an inertial offset according to the current inertial parameters, updating the initial position information according to the inertial offset to obtain target position information, and sending the target position information to a controlled device to control the controlled device. The control stability of the controlled device can be improved.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the technical field of data transmission, and in particular to a remote control method and system based on UWB. BACKGROUND

[0002] Smart remote control devices have deeply penetrated daily life scenarios. In the smart home field, users control the lighting system to adjust the color temperature through the remote control. In the business demonstration scenario, the presenter uses it to accurately mark the key content of the demonstration document. In the game interaction scenario, players rely on motion sensing to achieve immersive operation. These cross-field applications have put forward demands such as millimeter-level positioning accuracy, instantaneous response speed, and scene adaptability for remote control systems.

[0003] Current remote control systems face multiple technical bottlenecks in the field of intelligent interaction, which seriously restricts the improvement of user experience. Traditional infrared remote control technology is limited by the directional transmission mechanism, and the signal propagation range is limited and easily affected by physical shielding, resulting in frequent control interruptions. Although the radio frequency remote control scheme improves the transmission distance, the spatial positioning accuracy is insufficient, which produces obvious operation deviation in the smart TV channel selection or projection marking scenarios. Ultra-Wideband (UWB) positioning technology can achieve centimeter-level high-precision positioning and has strong anti-interference ability, but when used alone, it still faces the challenges of high power consumption and insufficient adaptability to dynamic environments, making it difficult to stably maintain millimeter-level precision requirements under low power consumption constraints. SUMMARY

[0004] Therefore, embodiments of the present disclosure aim to provide a remote control method and system based on UWB, which can solve the technical problem of poor control stability of the remote control system in the prior art.

[0005] The technical solution of the embodiments of the present disclosure is as follows:

[0006] In a first aspect, the embodiments of the present disclosure provide a remote control system based on UWB, comprising:

[0007] a UWB module configured to interact with a UWB base station to determine initial position information of the remote control system;

[0008] an inertial detection module configured to obtain current inertial parameters of the remote control system;

[0009] a data processing module configured to determine an inertial offset based on the current inertial parameters, update the initial position information based on the inertial offset to obtain target position information, and send the target position information to a controlled device to control the controlled device.

[0010] In some examples, the data processing module comprises:

[0011] a pose estimation unit configured to determine an inertial offset based on the initial position information, the current inertial parameter, and the historical inertial parameter;

[0012] In some examples, the data processing module further includes:

[0013] a lever arm compensation unit configured to determine a physical offset based on a relative position between the UWB module and the inertial detection module, and update the target position information based on the physical offset, and transmit the updated target position information to the controlled device to control the controlled device.

[0014] In some examples, the data processing module further includes:

[0015] a solving unit configured to determine an attitude angle of the remote control system based on the current inertial parameter;

[0016] the pose estimation unit is configured to determine a confidence of the current inertial parameter based on the attitude angle and a set threshold, and determine the inertial offset based on the confidence and the current inertial parameter.

[0017] In some examples, the data processing module further includes:

[0018] a trajectory assistance unit configured to perform motion compensation on an actual trajectory of the remote control system based on a current movement mode of the remote control system and the current inertial parameter, to improve a similarity between the compensated actual trajectory and a target trajectory corresponding to the current movement mode.

[0019] In some examples, the trajectory assistance unit includes:

[0020] a fluctuation determination module configured to determine a fluctuation value corresponding to the current movement mode based on historical data of the current movement mode;

[0021] a compensation determination module configured to determine a weight value of the fluctuation value based on angular velocity data in the current inertial parameter, and perform motion compensation on the actual trajectory based on the fluctuation value and the weight value corresponding to the fluctuation value.

[0022] In some examples, the remote control system further includes:

[0023] a signal transmission module configured to transmit the target position information and / or operation information of the remote control system to the controlled device.

[0024] In some examples, the remote control system further includes:

[0025] a mode switching module configured to switch the remote control system between a pointing mode and a normal mode in response to an operation instruction of a user;

[0026] wherein in the pointing mode, the signal transmission module transmits the target position information and / or operation information of the remote control system to the controlled device.

[0027] In normal mode, the signal transmission module transmits the operation information of the remote control system to the controlled device.

[0028] In some examples, in the normal mode, the UWB module and the inertial detection module are both in standby state.

[0029] In some examples, the remote control system further includes:

[0030] The power control module determines the sleep state of the remote control system according to the motion state of the remote control system.

[0031] In a second aspect, an embodiment of the present disclosure provides a remote control method based on UWB, comprising:

[0032] Interact with the UWB base station to determine the initial location information of the remote control system;

[0033] Get the current inertial parameters of the remote control system;

[0034] An inertia offset is determined according to the current inertia parameter, and initial position information is updated according to the inertia offset to obtain target position information, so as to send the target position information to the controlled device to control the controlled device.

[0035] The disclosed embodiments provide a remote control method and system based on UWB; the remote control system interacts with the UWB base station through the UWB module to obtain the initial position information of the remote control system. The UWB module uses ultra-wideband technology to achieve high-precision positioning, ensuring the basic accuracy of the initial position information of the device. The inertial detection module is responsible for obtaining the current inertial parameters of the remote control system and providing real-time input for subsequent processing. The data processing module calculates the inertial offset based on the current inertial parameters, and updates the initial position information accordingly to obtain the target position information. The target position information is sent to the controlled device to achieve precise control of the controlled device. This process eliminates external interference and improves operational stability. The inertial detection module detects displacements that the UWB module cannot collect to optimize the confirmation of the target position information, further improving the control stability of the controlled device. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A system framework diagram of a UWB-based remote control system provided in an embodiment of the present disclosure.

[0037] Figure 2 A system framework diagram of another UWB-based remote control system provided in an embodiment of the present disclosure.

[0038] Figure 3 A system framework diagram of another UWB-based remote control system provided in an embodiment of the present disclosure.

[0039] Figure 4A system framework diagram of a UWB-based remote control system with a trajectory assistance unit provided in an embodiment of the present disclosure.

[0040] Figure 5 A system framework diagram of a UWB-based remote control system with a signal transmission module provided in an embodiment of the present disclosure.

[0041] Figure 6 A system framework diagram of a UWB-based remote control system with a mode switching module provided in an embodiment of the present disclosure.

[0042] Figure 7 A system framework diagram of a UWB-based remote control system with a power management module provided in an embodiment of the present disclosure.

[0043] Figure 8 A data association diagram of a mode switching module provided in an embodiment of the present disclosure.

[0044] Figure 9 A data flow diagram of a UWB-based remote control system provided in an embodiment of the present disclosure.

[0045] Figure 10 A flowchart of a UWB-based remote control method provided in an embodiment of the present disclosure.

[0046] The above drawings illustrate specific embodiments of the present disclosure, which will be described in more detail below. These drawings and textual descriptions are not intended to limit the scope of the present disclosure in any way, but rather to illustrate the concepts of the present disclosure to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0047] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0048] In addition, the accompanying drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0049] In smart home scenarios, users need to control multiple device systems such as TVs, air conditioners, and lights at the same time, requiring the remote control to accurately locate on-screen menu items and quickly switch control objects; in business presentation scenarios, speakers need to use the remote control to mark key points on the projected image with millimeter-level precision, and the trajectory must be smooth and jitter-free; game interaction scenarios require the device to capture the wrist flip angle in real time to achieve zero-delay response of the crosshairs in shooting games.

[0050] Infrared remote controls fail when physically blocked, and radio frequency solutions produce positioning errors at long distances. While gyroscope-based motion-sensing remote controls offer freedom from directional constraints, sensor drift can cause cursor jitter. Devices experience random deviations in static environments, and trajectory deviations increase further during dynamic operation, causing visual fatigue and operational errors. Existing technologies struggle to balance positioning accuracy with power consumption. High refresh rate positioning solutions significantly shorten device battery life, while energy-saving modes significantly increase response latency, violating the principle of real-time human-computer interaction.

[0051] Mainstream products on the market generally lack scene-specific adaptability. Controlling multiple devices in a smart home requires frequent switching of remote control modes, but current systems rely on manual switching, which is time-consuming. Many users report the need to recalibrate positioning after switching. The specialized demands of interactive gaming scenarios expose the shortcomings of traditional solutions in motion compensation mechanisms, resulting in significant linear deviations in fast-moving trajectories, significantly reducing operational immersion.

[0052] These technical flaws can lead to operational failures due to lack of accuracy, power imbalances that limit usage, and rigid modes that hinder scenario migration. Therefore, there is an urgent need to develop a remote control system that integrates high-precision positioning, dynamic compensation, and intelligent decision-making, achieving a technical balance between centimeter-level positioning, long-term battery life, and instantaneous response.

[0053] Based on this, the present disclosure first provides a remote control system based on UWB, referring to Figure 1 The UWB-based remote control system may include a UWB module 11, an inertia detection module 12, and a data processing module 13, wherein the UWB module 11 is used to interact with the UWB base station 2 to determine the initial position information of the remote control system; the inertia detection module 12 is used to obtain the current inertia parameters of the remote control system; the data processing module 13 is used to determine the inertia offset according to the current inertia parameters, and update the initial position information according to the inertia offset to obtain the target position information, so as to send the target position information to the controlled device 3 to control the controlled device 3.

[0054] UWB module 11 refers to a wireless positioning component that utilizes ultra-wideband technology. Its core function is to exchange pulse signals with a UWB base station 2 deployed in space (based on the principle of two-way time-of-flight ranging). By calculating signal transmission delays, it determines the remote control system's initial position in three-dimensional space. In some examples, UWB base station 2 can be integrated with the aforementioned monitored device.

[0055] The inertial detection module 12 can be an inertial measurement unit (IMU) sensor combination, which may include a three-axis gyroscope and a three-axis accelerometer. Its function is to capture the current inertial parameters of the remote control system in real time during motion. The current inertial parameters can include acceleration, angular velocity, etc. The specific types of the current inertial parameters can be customized based on user needs and will not be detailed here.

[0056] Inertial offset refers to the instantaneous device displacement compensation value calculated by the data processing module 13 from the current inertial parameters. When a user moves the remote control system, UWB positioning cannot capture subtle movements due to signal refresh rate limitations. However, the high-frequency sampling of the inertial detection module 12 can detect millimeter-level jitter. The data processing module 13 converts the angular velocity / acceleration into a position offset vector, which is the inertial offset.

[0057] The controlled device 3 refers to a terminal device that receives remote control commands, such as a smart TV, a projector, etc. The type of the controlled device 3 can also be customized according to user needs, which will not be described in detail in this example implementation.

[0058] It should be noted that the above-mentioned initial position information can be obtained in real time or according to a preset sampling frequency. The sampling frequency can be customized according to device parameters and user needs, which will not be described in detail in this example implementation.

[0059] The UWB-based remote control system disclosed herein interacts with the UWB base station 2 via the UWB module 11 to obtain the initial position information of the remote control system. The UWB module 11 utilizes ultra-wideband technology to achieve high-precision positioning, ensuring the basic accuracy of the device's initial position information. The inertial detection module 12 is responsible for obtaining the current inertial parameters of the remote control system, providing real-time input for subsequent processing. The data processing module 13 calculates the inertial offset based on the current inertial parameters and updates the initial position information accordingly. The target position information is sent to the controlled device 3, enabling precise control of the controlled device 3. This process eliminates external interference and improves operational stability.

[0060] In some examples, reference Figure 2The data processing module 13 may include a pose estimation unit 131 and a lever arm compensation unit 132. The pose estimation unit 131 is configured to determine the inertial offset based on the initial position information, current inertial parameters, and historical inertial parameters. Specifically, an Error State Kalman Filter (ESKF) may be employed for real-time pose estimation. The ESKF utilizes the initial position information of the UWB module 11 as a reference, combined with the current inertial parameters of the inertial detection module 12 and referenced to historical inertial parameters (such as the attitude angle or error state at the previous moment) to predict the inertial offset.

[0061] The lever arm compensation unit 132 is used to determine the relative position of the UWB module and the inertial detection module, determine the physical offset, and update the target position information based on the physical offset, so as to send the updated target position information to the controlled device to control the controlled device.

[0062] Among them, the physical offset is due to the physical separation of the antenna of the UWB module 11 and the inertial detection module 12. The radii of their motion trajectories are different, resulting in the angular velocity / acceleration data measured by the inertial detection module 12 being unable to directly correspond to the actual spatial position of the UWB module 11, forming a basic offset.

[0063] In a specific implementation process, the lever arm compensation unit 132 maps the inertial parameters collected by the inertial detection module 12 to the actual spatial position of the UWB module 11 based on the above relative position to update the above target position.

[0064] Specifically, the data processing module 13 includes a posture estimation unit 131 and a lever arm compensation unit 132 that work together. The posture estimation unit 131 calculates the inertial offset using an Error State Kalman Filter (ESKF) algorithm based on the initial position information provided by the UWB module 11 and the current inertial parameters and historical inertial parameter datasets collected by the inertial detection module 12.

[0065] It should be noted that the calculation process of the inertia offset may also adopt other algorithms, which will not be described in detail in this example implementation.

[0066] During the specific implementation process, the ESKF can first be used to fuse the real-time data streams of the three-axis angular velocity and three-axis acceleration in the inertial parameters, and combined with the historical motion trajectory to establish a state prediction model; secondly, the fourth-order Runge-Kutta integration method is used to solve the device attitude angle (pitch angle / yaw angle / roll angle) to obtain the above-mentioned inertial offset.

[0067] In some examples, the lever arm compensation unit 132 is responsible for correcting the impact of the physical position deviation between the UWB module 11 and the inertial detection module 12 on the positioning accuracy. During the implementation process, the physical offset can be corrected first, and then the inertial offset can be corrected. Specifically, it can be divided into two stages. The first stage loads the preset lever arm parameters, that is, the above-mentioned relative position. For example, in the coordinate system where the remote control system is located, the UWB module 11 is offset by 2 cm in the X-axis direction and 1.5 cm in the Z-axis direction relative to the inertial detection module 12. The position coordinates of the original initial position information of the UWB module 11 are converted to the actual position reference point of the inertial detection module 12; the second stage injects the inertial offset output by the posture estimation unit 131, and generates the above-mentioned target position information by superposition of spatial vectors.

[0068] It should be noted that the establishment of the coordinate system of the remote control system can be customized based on user needs, which will not be described in detail here.

[0069] In some examples, reference Figure 3 The data processing module 13 may further include a solution unit 133. The solution unit 133 in the data processing module 13 works in conjunction with the posture estimation unit 131. The solution unit 133 is used to determine the attitude angle of the remote control system based on the current inertial parameters; the posture estimation unit 131 dynamically determines the confidence level of the current inertial parameters based on the attitude angle data output by the solution unit 133 and a preset threshold. This process follows a dynamic noise adjustment mechanism. The preset thresholds may include a maximum trust angle and a minimum trust angle. For example, when the attitude angle is less than the maximum trust angle, the maximum confidence level is assigned to the current inertial parameters, and the current inertial parameters are considered highly reliable. If the attitude angle exceeds the minimum trust angle, the minimum confidence level is enabled, and filtering is enhanced to suppress abnormal interference.

[0070] It should be noted that the values ​​of the maximum trust angle and the minimum trust angle can be set based on user needs, and the settings of the maximum confidence level and the maximum confidence level can also be set based on user needs and accuracy requirements, which will not be detailed in this example implementation.

[0071] Within the range of angles between the maximum and minimum trust angles, the system calculates the confidence coefficient through linear interpolation to achieve a smooth transition. This mechanism uses attitude angle as a trust evaluation metric. For example, when the device is held vertically (at low tilt angles), the motion data has low noise, so a high confidence level is assigned. However, as the tilt angle increases (such as when the user holds the device sideways), hand tremors increase, leading to increased data noise. The system automatically lowers the confidence level to filter out unreliable signals. The confidence calculation directly influences the weight of subsequent data processing, ensuring system stability in complex operating scenarios.

[0072] Based on the calculated confidence level, the pose estimation unit 131 further determines the inertial offset. This confidence level is weighted and applied to the fusion process of the current inertial parameters. Specifically, when the confidence level is high, the original current inertial parameters can be directly used to calculate the displacement compensation value. When the confidence level is low, a Kalman prediction is performed in combination with the historical inertial parameters to generate a noise-resistant inertial offset vector. This process not only suppresses coordinate mutations caused by hand shake but also maintains responsiveness for rapid motion. The confidence mechanism ensures that the offset calculation is suitable for both static fine-tuning scenarios and dynamic high-speed operations.

[0073] In some examples, reference Figure 4 The data processing module 13 may further include a trajectory assisting unit 134, which is configured to perform motion compensation on the actual trajectory of the remote control system according to the current movement mode and inertial parameters of the remote control system, so as to improve the similarity between the compensated actual trajectory and the target trajectory corresponding to the current movement mode.

[0074] Specifically, the above-mentioned trajectory assistance unit 134 may include a fluctuation determination module and a compensation determination module; wherein the fluctuation determination module is used to determine the fluctuation value corresponding to the current movement mode based on the historical data of the current movement mode; the compensation determination module determines the weight value of the fluctuation value based on the angular velocity data in the current inertia parameter, and performs operation compensation on the actual trajectory based on the fluctuation value and the weight value corresponding to the fluctuation value.

[0075] In some examples, the current movement mode is used to define intelligent recognition based on user operation intent. Optionally, the current movement mode can be divided into two categories: linear mode and non-linear mode, and the determination is based on linear regression analysis of historical trajectory data. For example, when the standard deviation of the direction angles of 10 consecutive coordinate points is less than 5°, the system determines that the movement mode is linear, such as dragging a presentation pen horizontally. Otherwise, it is considered a non-linear mode, such as freely drawing a curve. The pattern recognition result directly affects the processing logic of the fluctuation determination module.

[0076] The trajectory assistance unit 134 optimizes motion compensation through the synergy of the fluctuation determination module and the compensation determination module. The fluctuation determination module calculates a fluctuation value based on historical data of the current movement pattern. This value quantifies the magnitude of random perturbations in the motion trajectory. The specific implementation process involves establishing a multi-level time window analysis model, extracting the standard deviation of trajectory coordinates within a short window, and using a Markov chain to predict historical weight trends within a long window. Ultimately, the module outputs a fluctuation value parameter that describes the degree of path deviation.

[0077] For example, in a short time window, the fluctuation determination module calculates the standard deviation of the coordinate sequence of the historical data; in a long time window, the fluctuation trend is predicted by using a Markov chain update algorithm to generate a normalized fluctuation value in the interval [0, 1]. For example, when the user moves horizontally, if it is detected that the vertical direction fluctuation value is continuously greater than 0.8, it is determined that there is serious hand jitter interference.

[0078] In the trajectory assistance unit 134 of the remote control system, the time window refers to a specific time interval defined for analyzing the motion state, and its essence is an algorithm boundary for dynamically intercepting the data stream. This parameter directly determines the recognition accuracy and response speed of the motion characteristics, and is specifically divided into two levels of short time window and long time window:

[0079] It should be noted that the short time window can be in the order of 50 milliseconds to capture instantaneous jitter characteristics. The long time window can be extended to the order of 500 milliseconds, and the core goal is to identify macro motion trends. The two windows complement each other, with the short time window collecting transient jitter and the long time window classifying movement patterns.

[0080] In the implementation process, the compensation determination module dynamically calculates the weight value based on the angular velocity data in the current inertial parameter, and performs compensation by fusing the fluctuation value. Specifically, an angular velocity data weighting strategy can be used, wherein the angular velocity in the angular velocity data is positively correlated with the size of the weight value, that is, the greater the angular velocity, the greater the corresponding weight. In some examples, the value of the above angular velocity data can have a linear positive correlation with the weight value.

[0081] The fluctuation value and the weight value are multiplied to generate a compensation amount. For example, in the straight line assistance mode, if the X-axis displacement amount accounts for more than 80%, the system automatically applies a compensation amount to the Y-axis coordinates to suppress the actual trajectory and improve the similarity between the actual trajectory and the target trajectory (ideal straight line).

[0082] The UWB-based remote control system of the present disclosure uses angular velocity data to drive weight value adjustment, which not only ensures the hand-following nature of fast operation, but also enhances the stability of static fine-tuning. According to the current movement mode, the corresponding fluctuation value is determined to accurately match the user's operation intention.

[0083] In some examples, with reference to Figure 5 The above UWB-based remote control system can further include a signal transmission module 14, wherein the signal transmission module 14 can be used to transmit target position information and / or operation information of the remote control system to the controlled device 3 to achieve the purpose of wireless control. The signal transmission module 14 interacts with the above controlled device 3 to control the controlled device 3.

[0084] In some examples, the signal transmission module 14 can be a low-power wireless transceiver, such as a Bluetooth, ZigBee protocol, or wireless network. Its core function is to transmit the target location information and / or operation information generated by the data processing module 13 to the controlled device 3. The signal transmission module 14 adopts a low-power processing strategy, automatically switching to a sleep state during data transmission intervals and waking up only when a valid operation is detected, thereby improving the battery life of the remote control system.

[0085] In some examples, reference Figure 6 The UWB-based remote control system may further include a mode switching module 15, which is used to switch the remote control system between pointing mode and normal mode in response to the user's operation instructions; wherein, in the pointing mode, the signal transmission module 14 transmits the target position information and / or the operation information of the remote control system to the controlled device 3; in the normal mode, the signal transmission module 14 transmits the operation information of the remote control system to the controlled device 3.

[0086] In some examples, reference Figure 6 The data processing module 13 may also include a pointer coordinate mapping unit 135, which can be used to convert the device attitude angle output by the solution unit 133 into a cursor position in the screen coordinate system. The coordinate mapping unit can use a linear mapping algorithm to resolve operational inconsistencies caused by attitude changes in traditional solutions, such as cursor drift or response distortion caused by tilting a gyroscope device. Specifically, the data processing module 13 first calculates high-precision attitude angles using an ESKF (Error State Kalman Filter) and a fourth-order Runge-Kutta integral method. These angle data serve as the input source for the pointer coordinate mapping unit 135. The mapping process can linearly convert the attitude angles based on the screen size. The system pre-acquires the screen parameters of the controlled device 3 and establishes a linear relationship function between the attitude angles and screen coordinates, which is then converted into corresponding initial position information.

[0087] The signal transmission module 14 synchronously sends the target position information and the operation information. The operation information is reconstructed into a mouse event, such as the middle button triggering the left button action of the mouse, etc. The specific type of the operation information can also be such as pressing the left and right buttons, which is not detailed in this example embodiment.

[0088] In normal remote control mode, the signal transmission module 14 only transmits operation information, such as direction key instructions and volume adjustment codes, and the transmission channel of target location information is closed to save power. In this case, the remote control system functions the same as traditional infrared devices and is suitable for basic operations such as changing TV channels.

[0089] This dual-mode architecture dynamically allocates resources through the power consumption strategy formulation unit. The pointing mode enables the full-function modules (UWB module 11 + inertial detection module 12 + data processing module 13); the normal mode only maintains key scanning and basic communication, reducing power consumption.

[0090] It should be noted that the user instructions for switching modes mentioned above can be through button triggering, action recognition, protocol linkage, etc., among which button triggering can be long pressing the middle button for 3 seconds to trigger mode conversion; action recognition can include a shake gesture; protocol linkage can include receiving the TV standby protocol to automatically switch to normal mode. Specific user instructions can also be set based on needs, which will not be repeated in this example implementation.

[0091] In some examples, reference Figure 7 The remote control system may also include a power management module 16. The power management module 16 may also determine the sleep state of the remote control system based on its motion state. The sleep state may include running state, light sleep, and deep sleep. A sleep time threshold A may be pre-set to determine whether to enter the light sleep state. When the remote control system remains stationary for more than the sleep time threshold A, the system automatically enters the light sleep state. If the light sleep state lasts longer than another sleep time threshold B, the remote control system enters the deep sleep state.

[0092] The remote control system uses variance analysis of gyroscope and accelerometer data to determine motion. Specifically, it calculates the variance of acceleration and angular velocity. When these variances exceed the first wake-up threshold, C, the system determines motion and wakes the device. If the system is in deep sleep, the accumulated angular displacement must exceed the second wake-up threshold, D, for the system to successfully wake up. This design effectively prevents false wake-ups.

[0093] Optional, see Figure 8 , key switching depends on the key module 17 of the remote control system, action recognition depends on the inertia detection module 12 of the above remote control system, protocol linkage switching can be controlled by other modules 18, and the results of the mode can be linked with the power management module 16 to achieve low power consumption.

[0094] In some examples, reference Figure 9 As shown, the inertial detection module 12 and the UWB module 11 transmit data to the above-mentioned data processing module 13, which then passes through the solution unit 133, the posture estimation unit 131, the lever arm compensation unit 132, the pointer coordinate mapping unit 135 and the trajectory assistance unit 134 in the data processing module 13 to generate initial position information on the controlled device 3 to complete the control of the controlled device 3.

[0095] The UWB-based remote control system provided by the embodiment of the present disclosure achieves a generational breakthrough in spatial positioning accuracy through deep collaboration between the UWB module 11 and the IMU. The UWB module 11 provides initial position information, and the IMU module captures the three-axis acceleration and angular velocity with high-frequency sampling to form inertial parameters. The data processing module 13 adopts fusion correction: the data processing module 13 solves the device attitude angle based on ESKF attitude estimation and the fourth-order Runge-Kutta integral method to eliminate gyroscope drift; the arm compensation unit loads the preset offset parameters to correct the physical misalignment between the UWB module 11 and the IMU; the confidence mechanism dynamically adjusts the data weight according to the device inclination angle. The generated inertial offset is compensated in real time, and in conjunction with the dual-window analysis strategy of the trajectory auxiliary unit 134, a breakthrough improvement in trajectory similarity is achieved through cross-axis suppression in the straight line mode.

[0096] Secondly, the mode switching module 15 supports a triple mechanism of key triggering, motion recognition, and protocol linkage to achieve the transition between pointing mode and normal mode. The power management module 16 dynamically switches between three sleep levels based on motion state variance analysis. Full functionality is activated in the running state, the UWB module 11 high-frequency scanning is disabled in the light sleep state, and the IMU is frozen in the deep sleep state. The angular velocity data weighting strategy maintains responsiveness during rapid operation, enhances filtering during static fine-tuning, and cooperates with the angular displacement accumulation wake-up mechanism to effectively prevent false triggering. This design enables the device to maintain instantaneous responsiveness even in long-term battery life, resolving the conflict between control accuracy and energy consumption.

[0097] Furthermore, the present disclosure provides a remote control method based on UWB, referring to Figure 10 The UWB remote control method may include steps S1010 to S1030.

[0098] In step S1010 , interaction is performed with a UWB base station to determine initial location information of the remote control system.

[0099] In step S1020, the current inertia parameters of the remote control system are obtained.

[0100] In step S1030, an inertia offset is determined according to the current inertia parameter, and the initial position information is updated according to the inertia offset to obtain target position information, so as to send the target position information to the controlled device to control the controlled device.

[0101] It should be noted that the details of steps S1010 to S1030 can be found in the above description of the UWB-based remote control system, and are not described in detail here.

[0102] In the above embodiments, the description of each embodiment has its own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant description of other embodiments. The technical features of the above embodiments can be combined in any way. To keep the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0103] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention claimed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not claimed in this disclosure.

[0104] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A remote control system based on UWB, characterized in that: include: A UWB module, configured to interact with a UWB base station to determine initial position information of the remote control system; An inertia detection module, used to obtain current inertia parameters of the remote control system; a data processing module, configured to determine an inertia offset according to the current inertia parameter, and update the initial position information according to the inertia offset to obtain target position information, so as to send the target position information to a controlled device to control the controlled device; Wherein, the data processing module includes: a posture estimation unit, configured to determine the inertial offset according to the initial position information, the current inertial parameters, and historical inertial parameters; a trajectory assisting unit, configured to perform motion compensation on an actual trajectory of the remote control system according to a current movement mode of the remote control system and the current inertia parameters, so as to improve a similarity between the compensated actual trajectory and a target trajectory corresponding to the current movement mode; The trajectory assistance unit includes: a fluctuation determination module, configured to determine a fluctuation value corresponding to the current movement mode based on historical data of the current movement mode; a compensation determination module, configured to determine a weight value of the fluctuation value based on the angular velocity data in the current inertial parameters, and perform operation compensation on the actual trajectory based on the fluctuation value and the weight value corresponding to the fluctuation value, thereby using the angular velocity data to determine the adjustment of the weight value to ensure the hand tracking performance of fast operation while enhancing the stability of static fine-tuning; The angular velocity in the angular velocity data is positively correlated with the weight value.

2. The remote control system according to claim 1, characterized in that The data processing module also includes: The lever arm compensation unit is used to determine a physical offset according to the relative position of the UWB module and the inertial detection module, and update the target position information based on the physical offset, so as to send the updated target position information to the controlled device to control the controlled device.

3. The remote control system according to claim 1, characterized in that The data processing module also includes: a solving unit, configured to determine an attitude angle of the remote control system according to the current inertial parameters; The posture estimation unit is used to determine the confidence of the current inertial parameter according to the posture angle and a set threshold, and determine the inertial offset according to the confidence and the current inertial parameter.

4. The remote control system according to claim 1, wherein: The remote control system further comprises: A signal transmission module is used to transmit the target position information and / or the operation information of the remote control system to the controlled device.

5. The remote control system according to claim 4, characterized in that: The remote control system further comprises: a mode switching module, responsive to a user's operation instruction, to switch the remote control system between a pointing mode and a normal mode; Wherein, in the pointing mode, the signal transmission module transmits the target position information and / or the operation information of the remote control system to the controlled device; In the normal mode, the signal transmission module transmits the operation information of the remote control system to the controlled device.

6. The remote control system according to claim 5, characterized in that: In the normal mode, the UWB module and the inertia detection module are both in standby state.

7. The remote control system according to claim 1, characterized in that: The remote control system further comprises: The power control module determines the sleep state of the remote control system according to the motion state of the remote control system.

8. A remote control method based on UWB, characterized in that: Interact with the UWB base station to determine the initial location information of the remote control system; Obtaining current inertial parameters of the remote control system; determining an inertia offset according to the current inertia parameter, and updating the initial position information according to the inertia offset to obtain target position information, so as to send the target position information to the controlled device to control the controlled device; Wherein, determining the inertia offset according to the current inertia parameter includes: Determining the inertia offset according to the initial position information, the current inertia parameter, and the historical inertia parameter; The method further comprises: performing motion compensation on an actual trajectory of the remote control system according to a current movement mode of the remote control system and the current inertia parameters, so as to improve a similarity between the compensated actual trajectory and a target trajectory corresponding to the current movement mode; The performing motion compensation on the actual trajectory of the remote control system according to the current movement mode of the remote control system and the current inertia parameter includes: determining a fluctuation value corresponding to the current movement mode according to historical data of the current movement mode; Determining a weight value of the fluctuation value based on angular velocity data in the current inertial parameters, and performing operation compensation on the actual trajectory based on the fluctuation value and the weight value corresponding to the fluctuation value, thereby using the angular velocity data to determine the adjustment of the weight value to ensure the hand tracking performance of fast operation while enhancing the stability of static fine-tuning; The angular velocity in the angular velocity data is positively correlated with the weight value.

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