Unmanned aerial vehicle control system and control method based on wearable device

Abstract

The invention provides an unmanned aerial vehicle control system and control method based on wearable equipment, the control system comprises an acquisition module, an analysis module, a processing module and a control module, the acquisition module is used for acquiring human body action data through a plurality of sensors; the analysis module is used for analyzing the human body action data to obtain human body action characteristics corresponding to the human body action data; the processing module is used for converting the human body action characteristics into a control instruction of the unmanned aerial vehicle; the control module is used for driving the unmanned aerial vehicle to execute a corresponding flight action according to a control instruction of the unmanned aerial vehicle, a natural interaction mode is provided, and a user can control the unmanned aerial vehicle through a visual action; high-precision unmanned aerial vehicle control is realized, and the control flexibility is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle control, and in particular relates to a wearable device-based unmanned aerial vehicle control system and a control method. Background Art

[0002] Current motion capture technology is mainly used in virtual reality, motion analysis, and film and television production, usually using optical, inertial, or electromagnetic sensors. These methods have problems such as expensive equipment, large delays, and environmental interference. In terms of drone control, traditional methods mostly rely on remote controls, mobile phone applications, or voice control, which have limitations in control accuracy and interactive experience. In recent years, with the development of smart wearable devices, the technology of controlling devices through human body movements has gradually emerged. However, there is a lack of an effective solution on the market that uses human intelligent wearable devices to achieve direct control of the flight posture of drones. Therefore, how to provide a method that can effectively directly control the flight posture of drones has become a technical problem that needs to be solved in this field. Summary of the invention

[0003] The purpose of the present invention is to provide a wearable device-based drone control system and a control method.

[0004] According to a first aspect of the present invention, a wearable device-based drone control system is provided, comprising: a collection module, a parsing module, a processing module and a control module, wherein:

[0005] The acquisition module is used to collect human motion data through multiple sensors;

[0006] The analysis module is used to analyze the human motion data to obtain human motion features corresponding to the human motion data;

[0007] The processing module is used to convert the human body motion characteristics into control instructions for the drone;

[0008] The control module is used to drive the drone to perform corresponding flight actions according to the control instructions of the drone.

[0009] Optionally, the acquisition module includes at least a plurality of sensors, and the sensors include at least an acceleration sensor, a gyroscope and a pressure sensor.

[0010] Optionally, the acquisition module is used to acquire the acceleration, rotation angle and joint motion range of the human body in real time according to a preset data acquisition frequency.

[0011] Optionally, the parsing module is used to:

[0012] The human motion data is processed according to a pre-trained feature extraction model to obtain human motion features in the human motion data, wherein the pre-trained feature extraction model is obtained by training a neural network model using sample human body data.

[0013] Optionally, the parsing module is further used for:

[0014] Using a preset fusion algorithm to perform fusion processing on the human motion data to obtain fused data;

[0015] The fused data is processed according to a pre-trained feature extraction model to extract human motion features from the human motion data.

[0016] Optionally, the processing module is used to:

[0017] According to the user's action state, a control instruction of the drone is determined, and the control instruction at least includes a pitch control instruction, a yaw control instruction and a roll control instruction.

[0018] Optionally, the processing module is used to adjust the response sensitivity of the drone according to the amplitude and direction of the user's action.

[0019] Optionally, the drone control system further includes a communication module, and the communication module is used to send control instructions of the drone to the drone.

[0020] Optionally, the drone control system further includes a protection module, and the protection module is used to:

[0021] When it is detected that the user's movements are beyond the preset range, it will enter safety mode to limit the flight attitude changes of the drone.

[0022] According to a second aspect of the present invention, a method for controlling a drone is provided, comprising the drone control system based on a wearable device according to any one of the first aspects of the present invention, the method comprising:

[0023] Collect human motion data through multiple sensors;

[0024] Parsing the human motion data to obtain human motion features corresponding to the human motion data;

[0025] Converting the human motion characteristics into control instructions for the drone;

[0026] According to the control instructions of the drone, the drone is driven to perform corresponding flight actions.

[0027] The beneficial effects brought by the present invention are as follows:

[0028] It can be seen from the above scheme that the embodiments of the present invention provide a drone control system and a control method based on wearable devices, which have the following beneficial effects: the control system includes: an acquisition module, an analysis module, a processing module and a control module, wherein: the acquisition module is used to collect human motion data through multiple sensors; the analysis module is used to analyze the human motion data to obtain human motion characteristics corresponding to the human motion data; the processing module is used to convert the human motion characteristics into control instructions for the drone; the control module is used to drive the drone to perform corresponding flight actions according to the control instructions of the drone, providing a natural interaction method, and the user can control the drone through intuitive actions; high-precision drone control is achieved and control flexibility is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A structural block diagram of a wearable device-based drone control system provided according to an embodiment;

[0030] Figure 2 A structural block diagram of another wearable device-based drone control system provided according to an embodiment;

[0031] Figure 3 The present invention is a flowchart of a method for controlling a drone based on a wearable device according to an embodiment. DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] Reference Figure 1 , shows a structural block diagram of a wearable device-based drone control system of the present application, the control system includes: a collection module 101, a parsing module 102, a processing module 103 and a control module 104, wherein:

[0034] The acquisition module 101 is used to collect human motion data through multiple sensors;

[0035] The parsing module 102 is used to parse the human motion data to obtain human motion features corresponding to the human motion data;

[0036] The processing module 103 is used to convert the human body motion characteristics into the control instructions of the drone;

[0037] The control module 104 is used to drive the drone to perform corresponding flight actions according to the control instructions of the drone.

[0038] like Figure 2 As shown, the present invention proposes a motion capture system based on human intelligent wearable devices, which is used to control the flight posture of a drone. The system includes the following modules:

[0039] (1) Smart wearable devices: built-in multiple sensors (such as accelerometers, gyroscopes, pressure sensors, etc.) to capture human motion data.

[0040] (2) Motion capture module: Analyze sensor data and extract human motion features.

[0041] (3) Data processing module: converts motion features into control instructions for the drone, such as pitch, yaw, roll, etc.

[0042] (4) UAV control module: receives control instructions and drives the UAV to perform corresponding flight actions.

[0043] Another embodiment of the present application further supplements the wearable device-based drone control system provided in the above embodiment.

[0044] Optionally, the acquisition module 101 includes at least a plurality of sensors, and the sensors include at least an acceleration sensor, a gyroscope and a pressure sensor. The acquisition module 101 is used to acquire the acceleration, rotation angle and joint range of motion of the human body in real time according to a preset data acquisition frequency.

[0045] The sensors of smart wearable devices are installed in key parts of the human body, including arms, legs, torso and head. These sensors collect data such as human acceleration, rotation angle, range of motion of joints, etc. in real time. The data collection frequency of each sensor can be set from 100Hz to 1000Hz to ensure high accuracy of motion capture.

[0046] For example:

[0047] When the user raises his right hand, the accelerometer and gyroscope of the smart wearable device detect the motion data of the right arm, including acceleration changes and rotation angles.

[0048] If the user's body leans to the left, the data from the leg and torso sensors will show the change in the direction and angle of the lean.

[0049] Optionally, the parsing module 102 is used to:

[0050] The human motion data is processed according to a pre-trained feature extraction model to obtain human motion features in the human motion data, wherein the pre-trained feature extraction model is obtained by training a neural network model using sample human data.

[0051] Optionally, the parsing module 102 is further configured to:

[0052] Using a preset fusion algorithm, the human motion data is fused and processed to obtain fused data;

[0053] According to the pre-trained feature extraction model, the fused data is processed to extract the human motion features in the human motion data.

[0054] After the motion capture module receives sensor data from the smart wearable device, it analyzes the data through a data fusion algorithm. The data fusion algorithm integrates different types of data (such as acceleration and angular velocity) from multiple sensors, removes noise and extracts accurate motion features.

[0055] For example, when the user makes a dive, the motion capture module detects sensor data from the waist and arms, and combines the acceleration and angular velocity changes to determine the direction and strength of the action. Based on the different action characteristics, the system will extract the control parameters of pitch, yaw and roll.

[0056] Optionally, the processing module 103 is used to:

[0057] According to the user's action state, the control command of the drone is determined, and the control command at least includes a pitch control command, a yaw control command and a roll control command.

[0058] Optionally, the processing module 103 is used to adjust the response sensitivity of the drone according to the amplitude and direction of the user's action.

[0059] The data processing module converts the motion feature parameters analyzed by the motion capture module into the flight control instructions of the drone. The specific process is as follows:

[0060] Pitch control: When the user tilts forward, the data processing module generates a corresponding pitch command to make the drone fly forward. The tilt angle determines the speed of the drone.

[0061] Yaw control: When the user turns around, the system generates yaw commands to control the direction and speed of the drone's rotation around the vertical axis.

[0062] Roll control: When the user raises one arm, the system will generate a roll command to make the drone tilt in the corresponding direction.

[0063] The system can automatically adjust the drone's response sensitivity based on the amplitude and direction of the user's movements. For example, larger movements correspond to larger flight attitude adjustments, while smaller movements are used to fine-tune the flight attitude.

[0064] Optionally, the drone control system further includes a communication module, and the communication module is used to send control instructions of the drone to the drone.

[0065] After receiving the flight command, the drone control module will send the command to the drone's flight controller through the wireless communication module. The flight controller drives the various actuators (such as motors and servos) according to the command to adjust the drone's pitch, yaw and roll angles.

[0066] In order to improve flight stability, the system also integrates a feedback control mechanism. The attitude sensor on the drone monitors the current flight status in real time and feeds the attitude data back to the data processing module. The system compares the target attitude with the current attitude and adjusts the flight instructions in real time to ensure that the drone flies according to the expected trajectory.

[0067] Optionally, the drone control system further includes a protection module, which is used to:

[0068] When it is detected that the user's movements are beyond the preset range, it will enter safety mode to limit the flight attitude changes of the drone.

[0069] The system also supports multi-user control mode. For example, in a multi-user interactive scenario, two users can control different functions of the drone, one user controls the flight direction, and the other user controls the camera's shooting angle. In addition, the system can integrate voice command recognition function, and control the drone through a combination of voice and action in certain scenarios.

[0070] The system has designed a variety of safety protection measures to prevent the drone from losing control or colliding:

[0071] Action over-limit protection: When the user's action is detected to be beyond the preset range, the system will automatically enter safety mode to limit the flight attitude changes of the drone.

[0072] Automatic hovering: When the signal is lost or the data is abnormal, the drone will automatically hover and maintain the current position to ensure safety.

[0073] Abnormal attitude alarm: If the UAV's flight attitude deviates abnormally, the system will issue an alarm to remind the user and automatically adjust the flight attitude.

[0074] Through the above detailed implementation steps and protection mechanisms, the system can achieve precise motion capture and UAV flight control, improving the naturalness and flexibility of control.

[0075] The system allows users to adjust control parameters according to different usage scenarios. For example, the sensitivity of the sensor can be set to adjust the speed and strength of the drone's response to actions. In addition, the system supports users to customize the mapping relationship between gestures or actions and flight commands to meet personalized control needs.

[0076] Example:

[0077] Users can define "raising hands upward" as the command for the drone to rise, and "pressing hands downward" as the command for the drone to descend. Users can set "quickly swinging arms" as the command for the drone to stop in an emergency. It provides a natural interaction method, allowing users to control the drone through intuitive movements; achieves high-precision drone control and improves control flexibility; is suitable for a variety of scenarios, such as entertainment, competition and rescue; and has low system latency to ensure real-time flight control.

[0078] It should be noted that each implementable method in this embodiment may be implemented separately, or may be implemented in combination in any combination without conflict, and this application is not limited thereto.

[0079] Another embodiment of the present application provides a drone control method, which is used to execute the wearable device-based drone control system provided in the above embodiment.

[0080] like Figure 3 As shown, another embodiment of the present application provides a drone control method, comprising:

[0081] Collect human motion data through multiple sensors;

[0082] Parsing the human motion data to obtain human motion features corresponding to the human motion data;

[0083] Convert human motion characteristics into control instructions for drones;

[0084] According to the control instructions of the drone, the drone is driven to perform corresponding flight actions.

[0085] Specifically, human body movements are captured by sensors of smart wearable devices and transmitted to the motion capture module for analysis. The data processing module then converts the movements into control instructions for the drone, and finally the drone control module executes these instructions.

[0086] It can be seen from the above scheme that the embodiments of the present invention provide a drone control system and a control method based on wearable devices, which have the following beneficial effects: the control system includes: an acquisition module, an analysis module, a processing module and a control module, wherein: the acquisition module is used to collect human motion data through multiple sensors; the analysis module is used to analyze the human motion data to obtain human motion features corresponding to the human motion data; the processing module is used to convert the human motion features into control instructions for the drone; the control module is used to drive the drone to perform corresponding flight actions according to the control instructions of the drone, providing a natural interaction method, and the user can control the drone through intuitive actions; high-precision drone control is achieved and control flexibility is improved.

[0087] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0088] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0089] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0090] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0091] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0092] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0094] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0095] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard drives, ROM, RAM, magnetic disks, or optical disks.

[0096] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0097] The above are preferred embodiments 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 principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A wearable device-based drone control system, characterized in that: The control system includes: an acquisition module, an analysis module, a processing module and a control module, wherein: The acquisition module is used to collect human motion data through multiple sensors; The analysis module is used to analyze the human motion data to obtain human motion features corresponding to the human motion data; The processing module is used to convert the human body motion characteristics into control instructions for the drone; The control module is used to drive the drone to perform corresponding flight actions according to the control instructions of the drone.

2. The wearable device-based drone control system according to claim 1, characterized in that: The acquisition module includes at least a plurality of sensors, and the sensors include at least an acceleration sensor, a gyroscope and a pressure sensor.

3. The wearable device-based drone control system according to claim 2, characterized in that: The acquisition module is used to acquire the acceleration, rotation angle and joint range of motion of the human body in real time according to a preset data acquisition frequency.

4. The wearable device-based drone control system according to claim 1, characterized in that: The parsing module is used to: The human motion data is processed according to a pre-trained feature extraction model to obtain human motion features in the human motion data, wherein the pre-trained feature extraction model is obtained by training a neural network model using sample human body data.

5. The wearable device-based drone control system according to claim 4, characterized in that: The parsing module is also used for: Using a preset fusion algorithm to perform fusion processing on the human motion data to obtain fused data; The fused data is processed according to a pre-trained feature extraction model to extract human motion features from the human motion data.

6. The wearable device-based drone control system according to claim 5, characterized in that: The processing module is used for: According to the user's action state, a control instruction of the drone is determined, and the control instruction at least includes a pitch control instruction, a yaw control instruction and a roll control instruction.

7. The wearable device-based drone control system according to claim 6, characterized in that: The processing module is used to adjust the response sensitivity of the drone according to the amplitude and direction of the user's action.

8. The wearable device-based drone control system according to claim 1, characterized in that: The drone control system also includes a communication module, which is used to send control instructions of the drone to the drone.

9. The wearable device-based drone control system according to claim 8, characterized in that: The drone control system further includes a protection module, which is used to: When it is detected that the user's movements are beyond the preset range, it will enter safety mode to limit the flight attitude changes of the drone.

10. A method for controlling a drone, characterized in that: Applied to the wearable device-based drone control system according to any one of claims 1 to 9, the method comprising: Collect human motion data through multiple sensors; Parsing the human motion data to obtain human motion features corresponding to the human motion data; Converting the human motion characteristics into control instructions for the drone; According to the control instructions of the drone, the drone is driven to perform corresponding flight actions.

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