Control methods for model aircraft remote controllers

Abstract

This invention proposes a control method for a model aircraft remote controller. First, the parameters of all model aircraft are acquired. Then, when a returning model aircraft returns, the parameters of the target model aircraft for takeoff at the next moment are automatically acquired. During the return journey of the returning model aircraft, the system establishes a stable signal channel with the target model aircraft in advance based on its communication signal frequency band, ensuring that the target model aircraft can quickly respond to the remote controller's commands upon takeoff. This allows for automatic model aircraft switching and signal configuration without manual intervention, thereby improving operational efficiency. It not only avoids the tedious process of manual frequency band adjustment but also enables the model aircraft to complete takeoff quickly and respond rapidly to remote controller commands by configuring the signal frequency band and establishing a signal channel in advance. Especially when the model aircraft needs to take off urgently or capture images, it can avoid missing the optimal opportunity, improving flight flexibility and efficiency.

Description

Technical Field

[0001] This invention relates to the field of model aircraft remote control technology, and in particular to a control method for model aircraft remote control. Background Technology

[0002] Model aircraft enthusiasts typically own multiple types of model aircraft to suit different usage needs and shooting scenarios. For example, they might own model aircraft with varying image resolution, battery life, and size to meet the requirements of different situations. These model aircraft can be interchanged for different environments and mission requirements, thereby improving flight flexibility and practicality.

[0003] However, existing model aircraft remote controllers typically require a significant amount of time for signal matching and debugging when pairing signals between different model aircraft. This matching process is often cumbersome and requires individual debugging and configuration for each model aircraft, making it impossible to achieve rapid and automatic matching between the model aircraft and the remote controller. This time delay, especially when the model aircraft needs to take off quickly or capture urgent photos, often results in missed opportunities, thus affecting the efficiency and user experience of using the model aircraft. Summary of the Invention

[0004] Therefore, it is necessary to propose a control method for model aircraft remote controllers to address the aforementioned technical problems.

[0005] This invention proposes a control method for a model aircraft remote controller, the control method comprising:

[0006] Obtain all model aircraft parameters;

[0007] When the returning model returns, obtain the model parameters of the target model that will take off at the next moment;

[0008] Configure the target communication signal frequency band for the target model aircraft based on the communication signal frequency band of the returning model aircraft;

[0009] During the return journey of the returning model aircraft, a signal channel is established with the target model aircraft based on the target communication signal frequency band.

[0010] In at least one embodiment of this application, the specific steps of configuring the target communication signal frequency band for the target model based on the communication signal frequency band of the returning model aircraft include:

[0011] The frequency band of the communication signal used to acquire the returning model aircraft is denoted as the used signal frequency band;

[0012] Collect all signal frequency bands around the remote control and record them as the interference signal frequency band set;

[0013] All signal frequency bands acquired by the remote control are denoted as the communication signal frequency band set;

[0014] The set of usable signal frequency bands is generated by removing the used signal frequency band and the set of interference signal frequency bands from the set of communication signal frequency bands.

[0015] The target communication signal frequency band is generated based on the set of available signal frequency bands.

[0016] In at least one embodiment of this application, the step of generating a target communication signal frequency band based on the set of available signal frequency bands further includes:

[0017] Determine whether a signal frequency band exists in the set of available signal frequency bands;

[0018] If it exists, the target communication signal frequency band is generated based on the set of available signal frequency bands.

[0019] In at least one embodiment of this application, the step of determining whether a signal frequency band exists in the set of available signal frequency bands further includes:

[0020] If it does not exist, then select the signal frequency band with the least interference with the used signal frequency band and the least interference with other communication signals within the remote control range from the set of interference signal frequency bands, and generate the target communication signal frequency band.

[0021] In at least one embodiment of this application, the control method for the model aircraft remote controller further includes:

[0022] Acquire video images captured during the return of the model aircraft and generate a return video;

[0023] Based on the return video and the target model aircraft, a takeoff debugging path and debugging commands are generated;

[0024] When the target model aircraft executes the debugging command and flies according to the takeoff debugging path, it establishes communication between the remote controller and the target model aircraft through the target communication signal frequency band.

[0025] In at least one embodiment of this application, the specific steps of generating the takeoff debugging path and debugging command based on the return video and the target model aircraft further include:

[0026] Obtain the landing coordinates of the target model aircraft and the returning model aircraft, and generate the target coordinates and the returning coordinates.

[0027] Obtain the return path of the returning model aircraft;

[0028] The target coordinate point and the return coordinate point are mapped onto the return video, and the takeoff test path is calculated from the return video based on the return path.

[0029] In at least one embodiment of this application, the step of mapping the target coordinate point and the return coordinate point to the return video, and calculating the takeoff test path in the return video based on the return path, further includes:

[0030] Analyze the data of the first obstacle near the target coordinate point in the return video;

[0031] The takeoff test path is adjusted based on the first obstacle data to generate a calibrated takeoff test path.

[0032] In at least one embodiment of this application, the specific steps of acquiring video images taken during the return of the model aircraft and generating the return video further include:

[0033] Obtain the coordinates of surrounding model aircraft and generate nearby coordinate data;

[0034] When the returning model returns, real-time video of the model corresponding to the nearby coordinate data is obtained;

[0035] The calibrated takeoff test path is recalibrated based on the real-time video.

[0036] In at least one embodiment of this application, the specific steps of obtaining the coordinates of the target model aircraft around it, generating nearby coordinate data, and obtaining the real-time video of the model aircraft corresponding to the nearby coordinate data when the returning model aircraft returns include:

[0037] From the nearby coordinate data, select the coordinate points that are closest to the target model aircraft and are located in at least two different directions, and generate auxiliary coordinate point pairs;

[0038] When the returning model returns, real-time video is obtained for the corresponding model based on the auxiliary coordinate points;

[0039] Obstacles that are different from the first obstacle data are parsed from the real-time video, and second obstacle data is generated;

[0040] The calibrated takeoff test path is recalibrated based on the second obstacle data.

[0041] In at least one embodiment of this application, the specific steps for obtaining the model aircraft parameters for takeoff at the next moment include:

[0042] Obtain the coordinates of the returning model aircraft and the return coordinates, generate an automatic return route, and send the automatic return route to the returning model aircraft to execute the automatic return;

[0043] After the target model aircraft completes takeoff and testing and the returning model aircraft returns to the return coordinate point, the used signal frequency band is replaced with the target communication signal frequency band to establish a communication channel between the target model aircraft and the remote controller.

[0044] The control method for the model aircraft remote controller implemented in this embodiment will have at least the following beneficial effects:

[0045] The control method for the model aircraft remote controller described above first acquires the parameters of all model aircraft. Then, when the returning model aircraft returns, it automatically acquires the parameters of the target model aircraft to take off at the next moment. During the return journey of the returning model aircraft, the system establishes a stable signal channel with the target model aircraft in advance based on the target model aircraft's communication signal frequency band, ensuring that the target model aircraft can quickly respond to the remote controller's commands upon takeoff. This allows for automatic model aircraft switching and signal configuration without manual intervention, thereby improving operational efficiency.

[0046] This not only avoids the tedious process of manual frequency band adjustment, but also enables the model aircraft to take off quickly and respond rapidly to remote control commands by pre-configuring the signal frequency band and establishing a signal channel. Especially when the model aircraft needs to take off urgently or capture images, it can avoid missing the optimal opportunity, improving flight flexibility and efficiency. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] in:

[0049] Figure 1 This is a flowchart of a control method for a model aircraft remote controller in one embodiment;

[0050] Figure 2 for Figure 1 A detailed flowchart of the control method for a Chinese-made model aircraft remote controller;

[0051] Figure 3 A flowchart illustrating another embodiment of the control method for a model aircraft remote controller;

[0052] Figure 4 Flowchart of another embodiment of the control method for a model aircraft remote controller. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] This invention proposes a control method for a model aircraft remote controller, the control method comprising:

[0055] S101. Obtain all model aircraft parameters.

[0056] S102. When the returning model returns, obtain the model parameters of the target model that will take off at the next moment.

[0057] S103. Configure the target communication signal frequency band for the target model based on the communication signal frequency band of the returning model.

[0058] S104. During the return journey of the returning model aircraft, a signal channel is established with the target model aircraft based on the target communication signal frequency band.

[0059] Please refer to Figures 1-2 In this embodiment, firstly, the parameters of all model aircraft are acquired, including key data such as model aircraft type, communication signal frequency band, and flight status.

[0060] Then, when the returning model returns, the system automatically acquires the model parameters of the target model taking off at the next moment. These parameters will be used to configure the communication signal frequency band of the target model, thereby ensuring signal matching between the target model and the remote controller.

[0061] During the return journey of the returning model aircraft, the system establishes a stable signal channel with the target model aircraft in advance based on its communication signal frequency band, ensuring that the target model aircraft can quickly respond to the remote control commands upon takeoff. This allows for automatic model aircraft switching and signal configuration without manual intervention, thereby improving operational efficiency.

[0062] This not only avoids the tedious process of manual frequency band adjustment, but also enables the model aircraft to take off quickly and respond rapidly to remote control commands by pre-configuring the signal frequency band and establishing a signal channel. Especially when the model aircraft needs to take off urgently or capture images, it can avoid missing the optimal opportunity, improving flight flexibility and efficiency.

[0063] In at least one embodiment of this application, the specific steps of configuring the target communication signal frequency band for the target model based on the communication signal frequency band of the returning model aircraft include:

[0064] S1031. The communication signal frequency band of the returning model aircraft is denoted as the used signal frequency band.

[0065] S1032. Obtain all signal frequency bands around the remote control and record them as the interference signal frequency band set.

[0066] S1033. Obtain all signal frequency bands of the remote control and record them as the communication signal frequency band set.

[0067] S1034. Remove the used signal frequency band and the interference signal frequency band set from the communication signal frequency band set to generate an available signal frequency band set.

[0068] S1035. Generate a target communication signal frequency band based on the set of available signal frequency bands.

[0069] Please refer to Figures 1-2 In this embodiment, the communication signal frequency band of the returning model aircraft is acquired and recorded as the used signal frequency band. Next, the remote controller detects all surrounding signal frequency bands and records them as a set of interfering signal frequency bands. Then, all communication signal frequency bands supported by the remote controller itself are acquired and recorded as a set of communication signal frequency bands.

[0070] Based on this, frequency bands in the sets of used and interfering signal bands are removed to generate a set of available signal bands. Finally, according to this set of available signal bands, the system configures a suitable communication signal band for the target model aircraft to ensure a stable and reliable communication channel between the model aircraft and the remote controller.

[0071] The system can automatically configure the optimal signal frequency band according to the real-time environment, avoiding signal conflicts and interference, thereby achieving automated and accurate frequency band allocation.

[0072] First, by automatically eliminating both active and interfering frequency bands, signal conflicts between model aircraft are avoided, ensuring signal independence when multiple model aircraft are operated simultaneously. Second, by identifying and eliminating interfering frequency bands, the communication channel between the target model aircraft and the remote controller is ensured to be stable, greatly improving stability and reliability during flight.

[0073] In addition, automatic configuration of signal frequency bands greatly reduces the time spent on manual adjustments. Especially when model aircraft need to take off quickly or perform emergency tasks, it can ensure the rapid establishment of communication channels, avoid operational delays, and significantly improve flight efficiency.

[0074] It should be noted that the communication signal frequency band of the returning model aircraft is denoted as the used signal frequency band. The returning model aircraft maintains communication with the remote controller during flight, therefore its communication signal frequency band is crucial for subsequent frequency band allocation. Obtaining the communication signal frequency band of the returning model aircraft clarifies the currently used frequency band, avoiding frequency band conflicts with the target model aircraft.

[0075] Acquire all signal frequency bands around the remote control and denote them as the interference signal frequency band set. The remote control may be interfered with by other signal frequency bands from the surrounding environment, which may affect the normal operation of the remote control. Therefore, it is necessary to detect and identify all interference signal frequency bands.

[0076] Acquire all signal frequency bands of the remote controller, denoted as the communication signal frequency band set. This includes all available communication frequency bands for the remote controller, including bands that may be used to control model aircraft and other less commonly used bands.

[0077] In at least one embodiment of this application, the step of generating a target communication signal frequency band based on the set of available signal frequency bands further includes:

[0078] S201. Determine whether there is a signal frequency band in the set of available signal frequency bands.

[0079] If it exists, the target communication signal frequency band is generated based on the set of available signal frequency bands.

[0080] In at least one embodiment of this application, the step of determining whether a signal frequency band exists in the set of available signal frequency bands further includes:

[0081] S203. If it does not exist, then select the signal frequency band with the least interference with the used signal frequency band and the least interference with other communication signals within the remote control range from the set of interference signal frequency bands, and generate the target communication signal frequency band.

[0082] Please refer to Figures 1-2 In this embodiment, the system first determines whether there is a valid frequency band available in the set of available signal frequency bands. If a signal frequency band exists, a suitable frequency band is directly selected from the set as the target communication signal frequency band, ensuring that the target model aircraft can establish a stable communication channel with the remote controller.

[0083] If the set of available signal frequency bands is empty, that is, there are no available frequency bands, the system will select the signal frequency band with the least interference with the currently used frequency band and the least interference with other signals within the remote control range from the set of interfering signal frequency bands, and use it as the backup target communication signal frequency band.

[0084] By reducing the impact of interference on communication signals, the target model aircraft can continue to operate normally even in suboptimal signal environments.

[0085] This ensures the system can flexibly select the optimal signal frequency band in different environments, preventing model aircraft from going out of control or communication interruptions due to insufficient frequency bands or excessive interference. By dynamically adjusting the target communication signal frequency band, it can effectively cope with complex signal environments and guarantee the smooth operation of the model aircraft.

[0086] By automatically filtering available signal frequency bands or selecting the least interfering frequency band from interfering signal frequency bands, frequency band conflicts and interference are avoided, ensuring the stability and reliability of communication.

[0087] When no available frequency bands are available, the system can intelligently select the least interfering frequency band from among the interfering signal bands. This enhances the system's adaptability to complex environments, enabling it to cope with signal problems that may occur in different flight missions and operational environments, thereby improving the operational stability and success rate of the model aircraft.

[0088] By automatically selecting the signal frequency band, manual intervention is reduced, simplifying the operation process. This not only improves operational efficiency but also reduces the flight failure rate caused by frequency band mismatch or signal interference. Especially when model aircraft need to take off quickly or perform tasks, it can rapidly establish a communication channel, ensuring stable flight and optimizing the user's operating experience.

[0089] In environments where multiple aircraft need to fly, multiple model aircraft may need to operate on the same frequency band, which can lead to severe signal interference and conflicts.

[0090] The system can intelligently allocate different communication signal frequency bands to each target model aircraft, effectively avoiding signal interference between models, enabling multiple models to fly simultaneously in the same scenario, greatly improving the application range and flexibility of model aircraft. For example, during the performance phase, multiple models can fly simultaneously in the same scenario.

[0091] By dynamically selecting and configuring the target communication signal frequency band, problems such as frequency band conflict and signal interference in existing technologies are avoided, significantly improving the communication stability and operational efficiency of model aircraft. In particular, it has stronger adaptability and reliability in complex environments and multi-aircraft flight scenarios.

[0092] In at least one embodiment of this application, the control method for the model aircraft remote controller further includes:

[0093] S301. Acquire video images taken during the return of the model aircraft and generate a return video.

[0094] Based on the return video and the target model aircraft, a takeoff debugging path and debugging commands are generated.

[0095] S303. When the target model aircraft executes the debugging command and flies according to the takeoff debugging path, it establishes communication between the remote controller and the target model aircraft through the target communication signal frequency band.

[0096] Please refer to Figures 1-3In this embodiment, when the returning model begins its return journey, the remote controller acquires real-time video images of the model via its camera or other sensors and generates a return-home video. This video includes perspective images from the model's flight path, which helps in planning the subsequent test path and preparing for takeoff.

[0097] After acquiring the return flight video, the system intelligently generates a takeoff and test path based on the video information and the current state of the target model aircraft. Simultaneously, based on the flight trajectory of the returning model aircraft and the flight characteristics of the target model aircraft, test commands are generated to guide the target model aircraft to fly along the predetermined path.

[0098] After receiving the debugging command, the target model aircraft will fly according to the generated takeoff debugging path. At the same time, the communication frequency band between the target aircraft and the remote controller will be optimized and stabilized through the configured target communication signal frequency band, thereby ensuring uninterrupted communication throughout the debugging process.

[0099] Intelligent debugging commands and path generation eliminate the need for manual intervention, improving the automation level of takeoff and flight debugging. Return-to-home video provides precise flight data, reflecting the model aircraft's flight status in real time, making debugging path planning more accurate.

[0100] Meanwhile, automated signal frequency band configuration ensures stable communication between the model aircraft and the remote controller, further improving the efficiency and reliability of flight debugging.

[0101] By automatically generating takeoff and debugging paths and commands, manual operations are reduced, and the efficiency and accuracy of debugging are improved.

[0102] By combining the return flight video with the real-time information of the target model aircraft to generate a test path, the system can intelligently plan the takeoff test path based on the flight trajectory of the return flight model aircraft, environmental factors, and the specific status of the target model aircraft, thereby ensuring that the takeoff process of the target model aircraft is smooth and flies along the expected path.

[0103] By acquiring return-to-home videos of the model aircraft in advance and planning takeoff and adjustment paths within the videos, the system can complete the flight preparation of the target model aircraft in a short time, avoiding delays caused by manual adjustments and signal matching during emergency missions or rapid takeoffs. This improves flight response speed and ensures that the model aircraft can be ready to execute missions in the shortest possible time.

[0104] In at least one embodiment of this application, the specific steps of generating the takeoff debugging path and debugging command based on the return video and the target model aircraft further include:

[0105] S3021. Obtain the landing coordinates of the target model and the returning model, and generate the target coordinates and the returning coordinates.

[0106] S3022, Obtain the return path of the returning model aircraft.

[0107] S3023. Map the target coordinate point and the return coordinate point to the return video, and calculate the takeoff test path in the return video based on the return path.

[0108] Please refer to Figures 1-3 In this embodiment, the system first obtains the landing coordinates of the target model and the returning model, records the landing position of the target model as the target coordinate point, and records the landing position of the returning model as the returning coordinate point. These coordinates can be reported in real time by the ground positioning system, RTK, or the navigation module of the model itself, so as to accurately determine the spatial position of the two models in the geographic coordinate system.

[0109] Subsequently, the system extracts the return path from the flight control data of the returning model aircraft. This return path reflects the actual flight trajectory and attitude changes of the returning model aircraft as it returns from the flight airspace to the return coordinate point.

[0110] With the return-to-home video available, the system maps the target coordinates and return-to-home coordinates to the corresponding image coordinates or pixel positions in the return-to-home video, establishing a one-to-one correspondence between geographical coordinates and video footage. Combined with the return-to-home path of the model aircraft, the system reproduces the flight trajectory of the model aircraft in the return-to-home video. Using this trajectory as a reference, the system calculates a takeoff and debugging path suitable for the target model aircraft. For example, it generates an optimal takeoff route that starts from the target coordinates, avoids the area already flown by the model aircraft and ground obstacles, and is within the camera's coverage area. Finally, the system generates a debugging command that matches the takeoff and debugging path and issues it to the target model aircraft for execution.

[0111] By using a joint processing method that maps coordinates to paths and then to video, the actual flight information of the returning model aircraft is transformed into a takeoff reference template for the target model aircraft. This allows path calculation to no longer rely on manual visual inspection or repeated test flights, but to be automatically planned based on the actual return trajectory and video footage.

[0112] By acquiring the landing coordinates of the target model and the returning model and mapping them onto the return video, the takeoff and test path of the target model can be calculated directly within the video frame using the return path of the returning model. This makes the takeoff path generation more accurate and more in line with the current flight environment. The path planning is based on the real airspace and field of view that the returning model has just experienced, eliminating the need for the operator to estimate distance and altitude, and significantly reducing the risk of collisions with obstacles such as buildings and trees during the takeoff phase.

[0113] The path planning is linked to the return video, which makes it easy to check and fine-tune the data in the video. This is helpful in quickly finding the best takeoff direction and altitude in complex shooting scenarios (such as follow-up shooting, reshooting, and secondary takeoff for background filling).

[0114] The path adjustment process, which originally required manual judgment and multiple test flights, was moved forward to the return stage and automated. The takeoff path calculation of the target model was completed while the returning model was still on its return journey, which greatly reduced the time window from standby to safe takeoff of the target model and avoided missing key shooting opportunities due to long adjustment periods.

[0115] In multi-aircraft collaborative scenarios, the return path and takeoff path refer to each other, which can naturally form staggered airspace, reduce potential aerial conflicts between model aircraft, and improve overall flight safety and mission execution efficiency.

[0116] In at least one embodiment of this application, the step of mapping the target coordinate point and the return coordinate point to the return video, and calculating the takeoff test path in the return video based on the return path, further includes:

[0117] S3024. Analyze the data of the first obstacle near the target coordinate point in the return video.

[0118] S3025. Adjust the takeoff test path based on the first obstacle data to generate a calibrated takeoff test path.

[0119] Please refer to Figures 1-3 In this embodiment, the image processing module built into the processing terminal or remote controller analyzes the image area located near the target coordinate point in the return video to obtain the first obstacle data.

[0120] The first obstacle data may include information such as the distance, orientation, height range, outline boundary, and obstacle type of the obstacle relative to the target coordinate point, which is used to characterize the spatial distribution of fixed or semi-fixed obstacles such as buildings, trees, and utility poles within the takeoff area.

[0121] Specifically, the system can determine a preset detection area centered on the target coordinate point in the return video, analyze the brightness changes, edge contours and depth information in the detection area, thereby extracting the geometric features of at least one obstacle and organizing them into first obstacle data.

[0122] After acquiring the first obstacle data, the system determines whether the safe distance between the path and the obstacle in three-dimensional space meets the preset threshold based on the initially generated takeoff test path. If it is found that the trajectory segment of the takeoff test path has a potential collision risk or insufficient safe distance to the obstacle corresponding to the first obstacle data, the takeoff test path is dynamically corrected by adjusting the path's height, yaw angle, or horizontal offset to generate a calibrated takeoff test path. The control command that matches the calibrated takeoff test path is then used as the test command to be executed by the subsequent target model aircraft.

[0123] By using the above method, the takeoff test path is not only geometrically planned based on the return path and coordinate points, but also undergoes secondary calibration by combining the real obstacle information identified in the return video. This makes the generated path more closely match the actual takeoff environment, achieving integrated processing of path planning and environmental perception.

[0124] After generating the initial takeoff test path, the path is then calibrated by combining the first obstacle data parsed from the return video. This can significantly improve the adaptability of the takeoff path to the actual environment, avoid the takeoff trajectory from being too close to or passing through obstacles such as buildings and trees, thereby reducing the risk of the target model aircraft scraping or losing control during the takeoff acceleration phase and improving flight safety.

[0125] Since obstacle data comes directly from the return-to-home video just acquired by the model aircraft, it is real-time in time and consistent in space, eliminating the need for operators to repeatedly observe on-site or rely on experience to judge the presence of obstacles. Especially in scenarios requiring rapid takeoff and capturing fleeting moments, obstacle environment analysis and path calibration can be completed during the return-to-home phase, allowing the target model aircraft to safely take off along the calibrated takeoff test path after receiving the takeoff command, avoiding takeoff delays caused by temporary observation or on-site test flights.

[0126] In at least one embodiment of this application, the specific steps of acquiring video images taken during the return of the model aircraft and generating the return video further include:

[0127] S3026. Obtain the coordinates of the model aircraft around the target model aircraft and generate nearby coordinate data.

[0128] S3027. When the returning model returns, obtain the real-time video of the model corresponding to the nearby coordinate data.

[0129] S3028. The calibrated takeoff test path is recalibrated based on the real-time video.

[0130] Please refer to Figures 1-3 In this embodiment, the system first acquires the coordinate information of the model aircraft around the target model aircraft. The model aircraft can be other model aircraft in the current airspace that are hovering, cruising or in standby state. Through the ground station, remote controller or unified flight control management system, the positions of these model aircraft in a unified coordinate system are collected and organized into nearby coordinate data, which is used to identify the observation nodes that are adjacent to the spatial position of the target model aircraft.

[0131] When the returning model begins to return, the system selects one or more models whose relative position, azimuth, and altitude distribution are more favorable for observing the takeoff area based on nearby coordinate data, controls their cameras to collect real-time video, and transmits the real-time video back to the remote controller or ground processing terminal.

[0132] The processing terminal uses these real-time videos together with the return-to-home videos generated by the returning model aircraft for path verification. Based on the calibrated takeoff test path obtained from the return-to-home videos and the first obstacle data, the terminal further checks the passage of the path in the area around the target model aircraft in the real-time videos from the auxiliary perspective. For example, it determines whether there are any obstructions, dynamic objects, or blind spots along the path that are not covered in the return-to-home videos. Based on the scene changes parsed from these real-time videos, the terminal fine-tunes the local altitude, heading, or horizontal offset of the calibrated takeoff test path and generates a recalibrated takeoff test path.

[0133] This ensures that the takeoff and debugging path not only matches the historical flight environment of the returning model aircraft, but also aligns with the real-time environment of the target model aircraft's current surrounding airspace, thereby providing a more refined and safer path reference for subsequent takeoff and debugging commands issued to the target model aircraft.

[0134] First, by introducing the coordinates of the target model aircraft and nearby coordinates, the nearby model aircraft can be used as temporary distributed observation nodes. This allows for supplementary observation of the airspace around the target model aircraft from multiple directions and altitudes. Compared with the existing scheme that relies solely on the single perspective of the returning model aircraft, this significantly reduces the problem of incomplete environmental perception caused by perspective obstruction and blind spots, making the takeoff and test path safer in space.

[0135] By generating and calibrating the takeoff test path during the return phase, and then recalibrating the path using real-time video from nearby model aircraft just before takeoff, temporary obstacles or environmental changes (such as temporary structures, mobile devices, etc.) that appear in the site can be reflected in the path planning in a timely manner, preventing the target model aircraft from taking off along the previously established path, thereby significantly reducing the risk of collisions caused by environmental changes.

[0136] Instead of deploying additional fixed monitoring equipment, other existing model aircraft in this scenario can be reused as mobile observation platforms, reducing system deployment costs and improving the scalability and flexibility of the solution in multi-aircraft cooperative flight scenarios.

[0137] Through a graded calibration mechanism that combines return flight video and real-time video of nearby model aircraft, the takeoff debugging path can be initially planned during the return flight of the model aircraft and final fine-tuned before the target model aircraft is ready to take off, thus greatly shortening the time interval between the return flight and the safe takeoff of the next model aircraft.

[0138] In at least one embodiment of this application, the specific steps of obtaining the coordinates of the target model aircraft around it, generating nearby coordinate data, and obtaining the real-time video of the model aircraft corresponding to the nearby coordinate data when the returning model aircraft returns include:

[0139] From the nearby coordinate data, select the coordinate points that are closest to the target model aircraft and are located in at least two different directions to generate auxiliary coordinate point pairs.

[0140] When the returning model returns, real-time video is obtained for the corresponding model based on the auxiliary coordinate points.

[0141] Obstacles that are different from the first obstacle data are parsed from the real-time video, and second obstacle data is generated.

[0142] The calibrated takeoff test path is recalibrated based on the second obstacle data.

[0143] Please refer to Figures 1-3 In this embodiment, the system selects multiple model aircraft positions closest to the target model aircraft based on the nearby coordinate data obtained when the returning model aircraft returns. These model aircraft should be located in different orientations to ensure that the takeoff path of the target model aircraft can be monitored from multiple directions. Through these auxiliary coordinate points, the system can obtain multiple perspectives, thereby providing a comprehensive view for subsequent video acquisition and obstacle detection.

[0144] As the returning model aircraft begins its return journey, the system selects the model aircraft best suited to the target model's takeoff path and acquires real-time video of these models based on their location indicated by their coordinates. This video data provides additional visual information, aiding in further analysis of obstacles in the surrounding environment before the target model takes off.

[0145] The system parses new obstacle data from real-time video, generating secondary obstacle data. These obstacles may have been missed in the return flight model's video or added after the return process. Real-time video can capture changes in the surrounding environment, such as other moving objects, temporary obstacles, or dynamically changing scenes. By extracting this obstacle data, the system can promptly identify any potential risks affecting the takeoff path.

[0146] Once the second obstacle data is acquired, the system will perform a secondary correction on the initially calibrated takeoff test path. Based on the second obstacle data, the system can adjust the altitude, yaw angle, or horizontal position of the takeoff path to ensure that the target model aircraft can safely avoid all obstacles. Ultimately, the generated takeoff test path can avoid obstacles to the greatest extent possible, ensuring the safe takeoff of the model aircraft.

[0147] By using auxiliary coordinate points in multiple directions, the system can acquire real-time video of the environment around the target model aircraft from different angles, avoiding blind spots and comprehensively improving the accuracy of path planning.

[0148] With real-time data updates, the takeoff path of the target model aircraft can be dynamically adjusted during flight based on new obstacle data, greatly reducing the risk of collisions or obstacle interference.

[0149] By analyzing real-time video and updating obstacle data, the system can promptly detect and adjust to newly appearing obstacles, avoiding dangers caused by failing to consider obstacle positions during flight. Especially in multi-aircraft parallel flight or complex environments, the target model's takeoff path can fully adapt to the surrounding environment, ensuring safe takeoff.

[0150] By identifying and avoiding obstacles in advance, takeoff failures and test flight delays caused by obstacles can be significantly reduced, thereby accelerating mission execution. This is especially true in scenarios requiring rapid takeoff or filming, ensuring the target model aircraft can take off in the shortest possible time.

[0151] In an environment where multiple model aircraft are flying simultaneously, the takeoff path is dynamically adjusted to avoid signal interference and collisions between the model aircraft, thereby improving the safety and efficiency of multi-aircraft flight.

[0152] In at least one embodiment of this application, the specific steps for obtaining the model aircraft parameters for takeoff at the next moment include:

[0153] S401. Obtain the coordinates of the returning model and the return coordinates, generate an automatic return route, and send the automatic return route to the returning model to execute the automatic return.

[0154] S402. After the target model aircraft has completed its takeoff and testing and the returning model aircraft has returned to the return coordinate point, the used signal frequency band is replaced with the target communication signal frequency band to establish a communication channel between the target model aircraft and the remote controller.

[0155] Please refer to Figure 4 In this embodiment, when the target model aircraft completes its flight mission and prepares for takeoff, the system first acquires the current coordinates of the returning model aircraft (i.e., its current position) and the return coordinates (i.e., the preset return destination). Based on these coordinates, the system automatically generates the return route for the returning model aircraft. This return route is intelligently calculated based on the model aircraft's current position, flight status, and environmental factors (such as wind speed and obstacles), ensuring that the returning model aircraft can safely and smoothly return to the predetermined location.

[0156] Once the return route is generated, the system sends the route information to the flight control system of the returning model aircraft, instructing it to perform the automatic return function. This ensures that the returning model aircraft can automatically return along the preset route after completing its mission, without manual intervention or frequent operations, thereby reducing operational difficulty and time.

[0157] When the target model aircraft completes takeoff testing and is ready to take off, the system will automatically replace the currently used signal frequency band with the target model aircraft's communication signal frequency band after the returning model aircraft successfully returns to the return coordinate point.

[0158] A communication channel can be established between the target model aircraft and the remote controller, ensuring that the target model aircraft is not interfered with by signals from other frequency bands during takeoff, and that communication is stable and error-free.

[0159] By synchronizing the automatic return of the returning model aircraft with the takeoff preparation process of the target model aircraft, seamless integration between missions is achieved. Automated return and signal frequency switching operations avoid problems such as debugging delays and frequency conflicts that may occur in traditional methods. At the same time, the system is simpler to operate, reducing the complexity of manual operation and improving the efficiency and reliability of flight missions.

[0160] By automatically generating return routes and instructing the model aircraft to return automatically, manual operation can be reduced, and the level of automation in flight operations can be improved. The signal frequency switching of the target model aircraft is also completed after the automatic return is completed, avoiding frequency conflict or debugging failures and reducing debugging and operation time.

[0161] By automatically switching to the target model's communication signal frequency band during takeoff, signal conflicts or interference that might occur due to using the return-to-home model's frequency band are avoided. This allows the target model to maintain stable and clear communication with the remote controller during takeoff, ensuring control accuracy and stability during flight. This significantly reduces the risk of communication interruptions, especially in complex environments with multiple aircraft flying together.

[0162] By synchronizing the return of the returning model aircraft with the takeoff and debugging process of the target model aircraft, mission scheduling becomes more flexible and smoother. When executing multi-model aircraft missions, it effectively reduces waiting time and ensures that flight operations between different models do not conflict, improving the efficiency and safety of multi-aircraft collaborative operations. Especially in scenarios requiring rapid switching between model aircraft for missions, it enables rapid scheduling and takeoff while ensuring the safety of the model aircraft.

[0163] The entire process, from the automatic return of the returning model aircraft to the takeoff and debugging of the target model aircraft's route and signal frequency band switching, can be completed automatically. This reduces the operator's workload, especially in multi-model aircraft collaborative tasks, simplifying the scheduling process and improving the user's operating experience.

[0164] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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.

[0165] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method of regulating a model airplane remote controller, characterized by, The method for controlling the model remote controller comprises the following steps: acquiring all model parameters; when the return model returns, acquiring model parameters of a target model taking off at the next time; configuring a target communication signal frequency band for the target model according to the communication signal frequency band of the return model; acquiring the communication signal frequency band of the return model, which is recorded as a used signal frequency band; acquiring all signal frequency bands around the remote controller, which is recorded as an interference signal frequency band set; acquiring all signal frequency bands of the remote controller, which is recorded as a communication signal frequency band set; eliminating the used signal frequency band and the interference signal frequency band set from the communication signal frequency band set to generate an available signal frequency band set; generating a target communication signal frequency band according to the available signal frequency band set; during the return process of the return model, establishing a signal channel between the remote controller and the target model according to the target communication signal frequency band; the method for controlling the model remote controller further comprises the following steps: acquiring video images taken when the return model returns to generate a return video; generating a take-off debugging path and a debugging command according to the return video and the target model; when the target model executes the debugging command and flies according to the take-off debugging path, the remote controller and the target model establish communication through the target communication signal frequency band.

2. The method of claim 1, wherein the model airplane remote controller is a radio controlled model airplane remote controller. the step of generating a target communication signal frequency band according to the available signal frequency band set further comprises the following steps: judging whether there is a signal frequency band in the available signal frequency band set; if yes, generating a target communication signal frequency band according to the available signal frequency band set.

3. The method of claim 2, wherein the model airplane remote controller is configured to transmit the control signal to the model airplane in response to the user input. the step of judging whether there is a signal frequency band in the available signal frequency band set further comprises the following steps: if no, selecting a signal frequency band with the least interference degree with the used signal frequency band and the least interference degree with other communication signals within the remote control range from the interference signal frequency band set to generate a target communication signal frequency band.

4. The method of claim 1, wherein the model airplane remote controller is a radio controlled model airplane remote controller. the specific steps of generating a take-off debugging path and a debugging command according to the return video and the target model further comprise the following steps: acquiring landing coordinate points of the target model and the return model to generate target coordinate points and return coordinate points; acquiring a return path of the return model; mapping the target coordinate points and the return coordinate points to the return video and calculating the take-off debugging path in the return video according to the return path.

5. The method of claim 4, wherein the model airplane remote controller is configured to transmit the control signal to the model airplane in response to the user input. the steps after mapping the target coordinate points and the return coordinate points to the return video and calculating the take-off debugging path in the return video according to the return path further comprise the following steps: analyzing first obstacle data about the target coordinate points in the return video; adjusting the take-off debugging path according to the first obstacle data to generate a calibrated take-off debugging path.

6. The method of claim 5, wherein the model airplane remote controller is configured to transmit the control signal to the model airplane in response to the user input. the specific steps of acquiring video images taken when the return model returns to generate a return video further comprise the following steps: acquiring model coordinates around the target model to generate nearby coordinate data; when the return model returns, acquiring real-time video of models corresponding to the nearby coordinate data; re-calibrating the calibrated take-off debugging path according to the real-time video.

7. The method of claim 6, wherein the model airplane remote controller is configured to transmit the control signal to the model airplane in response to the user input. The specific steps of acquiring the real-time video of the aerial vehicle corresponding to the nearby coordinate data when the return aerial vehicle returns include: Filtering out the coordinate points closest to the target aerial vehicle and at least two different directions from the nearby coordinate data to generate auxiliary coordinate point pairs; Acquiring real-time video from the aerial vehicle corresponding to the auxiliary coordinate point pairs when the return aerial vehicle returns; Analyzing the second obstacle data from the real-time video, which is different from the first obstacle data; Calibrating the take-off debugging path again according to the second obstacle data.

8. The method of claim 3, wherein the model airplane remote controller is a radio controlled model airplane remote controller. The specific steps of acquiring the aerial vehicle parameters of the target aerial vehicle taking off at the next time include: Acquiring the coordinate points of the return aerial vehicle and the return coordinate points, generating an automatic return route, and sending the automatic return route to the return aerial vehicle to execute automatic return; After the target aerial vehicle finishes take-off debugging and the return aerial vehicle returns to the return coordinate points, replacing the use signal frequency band with the target communication signal frequency band to establish a communication channel between the target aerial vehicle and the remote controller.

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