Multi-load cooperative control system based on PSDK relay and interface adaptation method

Abstract

The invention relates to the technical field of unmanned aerial vehicle communication, and discloses a multi-load cooperative control system based on a PSDK relay and an interface adaptation method, the system comprises an unmanned aerial vehicle ePort interface, a plurality of load devices with heterogeneous load types and a PSDK relay device, and the PSDK relay device comprises an interface adaptation module and a private protocol cooperation module. The interface adaptation method is applied to the system. According to the multi-load cooperative control system based on the PSDK relay and the interface adaptation method, the load equipment end detects the hardware difference and generates the hardware difference identifier, the PSDK relay equipment end generates the adaptive communication protocol based on the identifier and establishes the private communication protocol, and finally unified control instruction issuing and multi-load cooperative control are achieved. And the adaptation problem of the heterogeneous interface and the protocol is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle communication, in particular to a multi-load cooperative control system based on PSDK relay and an interface adaptation method. BACKGROUND

[0002] With the wide application of unmanned aerial vehicles in industrial inspection, logistics transportation, emergency rescue and other fields, the demand for multi-task cooperative operation is increasing. However, in the prior art, the ePort interface of the unmanned aerial vehicle cannot be used universally due to the differences in hardware design, for example, the ePort interface of the same unmanned aerial vehicle may have voltage range mismatching, communication protocol incompatibility and other problems due to version iteration or manufacturer differences, forcing the load device to be customized and developed for a specific unmanned aerial vehicle model, significantly increasing the research and development cost and deployment difficulty. Secondly, there is a lack of unified protocol adaptation and task scheduling mechanism among multi-load devices. The existing scheme usually relies on a single communication protocol or hard-coded logic, which is difficult to dynamically adapt to the protocol differences of heterogeneous loads, resulting in problems such as data interaction delay and state synchronization failure during task execution, which limits the cooperative efficiency in complex scenarios.

[0003] Therefore, there is an urgent need for a multi-load cooperative control technology for unmanned aerial vehicles to improve the quality and efficiency of multi-load task execution of unmanned aerial vehicles. SUMMARY

[0004] The purpose of the present application is to provide a multi-load cooperative control system based on PSDK relay and an interface adaptation method to solve the technical problems raised in the background.

[0005] To achieve the above purpose, the present application discloses the following technical solutions:

[0006] In a first aspect, the present application discloses a multi-load cooperative control system based on PSDK relay, comprising:

[0007] an unmanned aerial vehicle ePort interface;

[0008] a plurality of load devices with heterogeneous load types, each of which is configured with a program module, the program module being used to generate a hardware difference identifier by detecting the hardware characteristics of the unmanned aerial vehicle ePort interface, and automatically loading a driver program matching the unmanned aerial vehicle ePort interface based on the hardware difference identifier, wherein the hardware characteristics include pin electrical characteristics and communication timing signals;

[0009] a PSDK relay device connecting the load devices and the unmanned aerial vehicle ePort interface as an intermediate layer, the PSDK relay device comprising:

[0010] an interface adaptation module for generating an adapted communication protocol based on the hardware difference identifier;

[0011] a private protocol coordination module, configured to establish a private communication protocol based on the adaptive communication protocol, and to issue a unified control instruction to a plurality of load devices through the private communication protocol, and to perform coordinated control on different load devices by shielding differences in underlying interfaces, the unified control instruction including task scheduling, data interaction, and state synchronization among the plurality of load devices.

[0012] Preferably, the program module includes:

[0013] a voltage detection unit, configured to collect a pin voltage range of the UAV ePort interface in real time, and compare the pin voltage range with a preset voltage range database to generate pin electrical characteristics;

[0014] a timing analysis unit, configured to capture a communication timing signal of the UAV ePort interface, and match a corresponding communication protocol template based on a timing feature classification algorithm;

[0015] a difference identification unit, configured to compare the pin electrical characteristics and the communication timing signal with a preset hardware characteristic database to generate a unique hardware difference identification;

[0016] a program matching unit, configured to dynamically load a driver based on a matching result of the hardware difference identification in a program database, the driver including a hardware abstraction layer and a communication protocol stack.

[0017] Preferably, the private protocol coordination module is further configured to, when establishing the private communication protocol, convert original protocols of different load devices into a unified private protocol, generate a protocol fingerprint through a protocol identifier generation algorithm, and dynamically adjust parameters of the communication protocol according to task urgency of the plurality of load devices.

[0018] Preferably, the dynamically adjusting parameters of the communication protocol according to task urgency of the plurality of load devices includes the following steps:

[0019] data collection: collecting communication traffic data of the plurality of load devices in real time, and generating a bandwidth utilization report based on a preset monitoring period;

[0020] threshold triggering: when bandwidth utilization of any load device continuously exceeds a preset high threshold, dynamically expanding a communication time slot of the load device or increasing a protocol baud rate of the load device; when bandwidth utilization of any load device is lower than a preset low threshold, releasing redundant communication resources of the load device and reallocating the redundant communication resources to a load device corresponding to a high-priority task;

[0021] Allocation optimization: fixed time slots and maximum bandwidth guarantee are allocated to the load devices corresponding to high-priority tasks; a dynamic time slot polling mechanism is used for the load devices corresponding to low-priority tasks, and the dynamic time slot polling mechanism includes allocating the remaining bandwidth only in the idle period;

[0022] Allocation analysis: analyze the future bandwidth demand of the load device according to its historical traffic data, and adjust the allocation strategy in advance based on the analysis result.

[0023] As preferred, the step of analyzing the future bandwidth demand of the load device according to its historical traffic data, and adjusting the allocation strategy in advance based on the analysis result, comprises the following steps:

[0024] According to the multiple load devices and the urgency of the tasks, the load devices are divided into high-priority devices, medium-priority devices or low-priority devices, and a priority queue is generated;

[0025] A bandwidth allocation weight is preset for each priority device, and the communication time slot allocation of each load device is adjusted in real time based on the weighted polling algorithm;

[0026] The bandwidth allocation strategy is optimized online through a deep reinforcement learning algorithm, wherein the state space of the deep reinforcement learning algorithm includes the bandwidth utilization, task priority and historical traffic pattern of each load device; the action space of the deep reinforcement learning algorithm includes adjusting the bandwidth allocation proportion of a specified load device; and the reward function of the deep reinforcement learning algorithm includes maximizing the throughput of key tasks and minimizing the delay fluctuation of low-priority tasks;

[0027] An optimal bandwidth allocation strategy is dynamically generated through real-time training of a model, and is fed back to the protocol priority queue.

[0028] As preferred, the step of dynamically adjusting the parameters of the communication protocol according to the urgency of the tasks of the multiple load devices further comprises the following steps:

[0029] When any load device has a communication exception, the communication of the load device is switched to a low-bandwidth mode through the PSDK relay device;

[0030] The data packets of the load device are automatically retransmitted through a sliding window algorithm, and a maximum number of retransmissions is set;

[0031] The error code and timestamp corresponding to the abnormal communication are recorded in a non-volatile memory.

[0032] As preferred, the PSDK relay device further comprises:

[0033] An encryption communication unit is configured to encrypt data between the plurality of load devices and the PSDK relay device based on an encryption algorithm, and to perform key exchange through an asymmetric encryption algorithm;

[0034] A device authentication unit is configured to verify the legitimacy of the accessed load device through a preset digital certificate.

[0035] Preferably, the UAV ePort interface is configured with a standardized protocol compatible mechanism for switching communication protocols through a hardware switch or software configuration.

[0036] Preferably, the UAV ePort interface is further configured with a protocol conflict detection mechanism for recovering communication through an arbitration algorithm when multiple load devices simultaneously send conflicting data packets.

[0037] In a second aspect, the application discloses an interface adaptation method of a PSDK relay-based multi-load cooperative control system, which is applied to the PSDK relay-based multi-load cooperative control system as described above and sequentially includes the following steps:

[0038] At the load device end, detect the hardware differences with the UAV ePort interface and generate a hardware difference identifier;

[0039] According to the hardware difference identifier, automatically load a driver matched with the UAV ePort interface;

[0040] At the PSDK relay device end, generate an adapted communication protocol based on the hardware difference identifier, and establish a private communication protocol based on the adapted communication protocol;

[0041] Through the private communication protocol, issue unified control instructions to the plurality of load devices, and cooperatively control different load devices by shielding the underlying interface differences.

[0042] Beneficial effects: the multi-load cooperative control system and interface adaptation method based on PSDK relay of the application avoid poor versatility of the load device due to heterogeneous hardware of the unmanned aerial vehicle ePort interface, improve interface compatibility, through the program module built-in the load device to detect hardware characteristics of the unmanned aerial vehicle ePort interface in real time, generate a unique hardware difference identifier, and dynamically load the matching driver; through the interface adaptation module of the PSDK relay device, generate an adaptive communication protocol based on the hardware difference identifier, establish a unified private communication protocol in combination with the private protocol cooperative module, realize task scheduling, data interaction and state synchronization among multiple load devices, and improve overall collaboration efficiency of the system; through the function of shielding the bottom interface difference of the PSDK relay device, different load devices do not need to be customized and developed for specific ePort interfaces, reduce the complexity of multi-load integration, and expand flexibility and adaptability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0044] Figure 1 The structure diagram of the multi-load cooperative control system based on PSDK relay provided by the embodiments of the present application is shown. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application will be described clearly and completely below. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0046] In this paper, the term "including" is intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or includes elements inherent to such process, method, article or device. Without more limitations, the elements defined by the statement "including" do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0047] The present embodiment discloses a multi-load cooperative control system based on PSDK relay in the first aspect, as shown in the figure. Figure 1 The multi-load cooperative control system based on PSDK relay comprises:

[0048] The UAV ePort interface is a standard physical interface on the UAV for connecting external load devices, with power pins (such as 3.3V / 5V / 12V power supply), data pins (such as SPI, I 2 C, UART, etc. communication protocol corresponding pins) and control pins (such as PWM signal output);

[0049] A number of load devices with heterogeneous load types (such as load device 1, load device 2, …, load device n), which can be cameras, laser radars, and environmental sensors, etc. Each of the load devices is configured with a program module, which is used to generate a hardware difference identifier by detecting the hardware characteristics of the UAV ePort interface, and automatically load the driver matching the UAV ePort interface based on the hardware difference identifier, wherein the hardware characteristics include pin electrical characteristics and communication timing signals;

[0050] PSDK relay device, as an intermediate layer connecting the load device and the UAV ePort interface, PSDK relay device is a development kit provided by DJI, which aims to help developers create load devices compatible with DJI UAV systems. The PSDK relay device includes:

[0051] Interface adaptation module, for generating an adapted communication protocol based on the hardware difference identifier, the generation of the adapted communication protocol is obtained by dynamically configuring the communication parameters (such as baud rate, data bits, and check mode) in the communication protocol template described below according to the hardware difference identifier, such as if the hardware difference identifier is TypeA_SPI (representing a hardware type (TypeA) and a communication protocol (SPI) of the UAV ePort interface), then the baud rate is configured to 1Mbps, the data bits are 8, and the check mode is no check;

[0052] Private protocol coordination module, for establishing a private communication protocol based on the adapted communication protocol, and issuing a unified control instruction to multiple load devices through the private communication protocol, and for coordinating control of different load devices by shielding the underlying interface differences, the unified control instruction includes task scheduling, data interaction, and state synchronization among multiple load devices.

[0053] By the above-mentioned multi-load cooperative control system based on PSDK relay, the hardware characteristics of the UAV ePort interface are detected in real time by the program module built-in the load device, the hardware difference identifier is generated, and the matching driver is dynamically loaded, solving the problem that different load devices cannot be used in common due to the heterogeneous ePort interface hardware, and improving the interface compatibility; the PSDK relay device generates an adaptive communication protocol through the interface adaptation module, and establishes a unified private communication protocol based on the private protocol cooperation module, shielding the differences in the underlying interface, realizing the task scheduling, data interaction and state synchronization among multiple load devices, and overcoming the problem of insufficient heterogeneous load cooperation capability; by shielding the differences in the underlying interface through the relay device, different load devices do not need to be customized for specific ePort interfaces, greatly reducing the complexity of multi-load integration, and expanding the flexibility and adaptability of the system.

[0054] In the present embodiment, the program module comprises:

[0055] The voltage detection unit adopts point-by-point sampling (such as a 100 Hz sampling rate) to collect the pin voltage range (such as 3.3V / 5V / 12V) of the UAV ePort interface in real time, and can eliminate noise through sliding window mean filtering (window size = 10), and compare the collected pin voltage range or filtered data with a preset voltage range database to generate pin electrical characteristics (such as {'Pin1':3.3V,'Pin2':5V});

[0056] The timing analysis unit is configured to capture the communication timing signal (such as the rising edge / falling edge time interval, the SCLK frequency of SPI, the I 2 C address bit length, etc.) of the UAV ePort interface through Fourier transform, and match the corresponding communication protocol template based on a timing feature classification algorithm (such as K-Nearest Neighbor algorithm or Decision Tree), and initialize the hardware abstraction layer and the communication protocol stack, wherein the communication protocol template is a pre-defined standardized protocol structure (such as the general template of UART, CAN), which provides a benchmark framework (such as data format, timing rules) for the protocol. An exemplary communication protocol template can be, for example, {'SPI':{'SCLK':400kHz},'I 2 C':{'Address':7bit}};

[0057] The difference identifier unit is configured to generate a unique hardware difference identifier based on the comparison of the pin electrical characteristics and the communication timing signal with a preset hardware characteristic database, such as {'Voltage':'TypeA','Protocol':'SPI'}, and map it to the driver program in the program database for driver program matching;

[0058] A program matching unit is configured to dynamically load a driver based on a matching result of the hardware difference identifier in a program database, the driver including a hardware abstraction layer and a communication protocol stack (such as a UART and a CAN). An example of dynamically loading a driver is that when it is detected that the ePort interface is Type A and the protocol is SPI, a driver 'Driver_SPI_TypeA' is loaded, and the baud rate of the SPI master device is configured to be 1 Mbps, the data bit is 8, and the check bit is None.

[0059] Based on the design of the above program module, the pin voltage range of the ePort interface is collected in real time by the voltage detection unit, and is compared with a preset voltage range database to generate a pin electrical characteristic. The timing analysis unit captures a communication timing signal and matches a communication protocol template, and the unique hardware difference identifier is generated in combination with the difference identification unit, thereby improving the automation level and accuracy of hardware difference identification. The program matching unit dynamically loads a matching driver (including a hardware abstraction layer and a communication protocol stack) from a program database based on the hardware difference identifier, thereby solving the problems of low efficiency and poor compatibility caused by traditional manual adaptation.

[0060] In the embodiment, the private protocol cooperation module is further configured to, when establishing the private communication protocol, convert original protocols (such as SPI, I 2 C, and UART) of different load devices into a unified private protocol, generate a protocol fingerprint through a protocol identifier generation algorithm to ensure protocol consistency, and dynamically adjust parameters of the communication protocol according to the task urgency of the load devices. The PSDK relay device also regularly synchronizes state information (such as battery power and task progress) of the load devices through the private protocol.

[0061] Specifically, the steps of establishing the private communication protocol based on the adapted communication protocol are as follows:

[0062] (1) Original protocol conversion

[0063] 1. Input: original communication protocols (such as SPI, I 2 C, and UART) of multiple load devices.

[0064] 2. Processing:

[0065] (1) Protocol standardization: map original protocol fields (such as the command field CMD in the SPI protocol and the address field Address in the I 2 C protocol) of different load devices into unified private protocol fields (for example, {'command': 'task A', 'data': {'X': 0x12, 'Y': 0x34}}).

[0066] (2) Protocol fingerprint generation: generate a unique protocol fingerprint (e.g. 'Protocol Fingerprint_SPI_TaskA') through a protocol identifier generation algorithm for fast matching of the capability characteristics of the load device.

[0067] (3) Output: generate a unified private communication protocol (e.g. {'command': 'TaskA', 'priority': 1}).

[0068] Based on the design of the above-mentioned private protocol collaboration module, the original protocols of different load devices are converted into a unified private protocol, and a protocol fingerprint is generated through a protocol identifier generation algorithm, solving the problem of heterogeneous protocol compatibility. Secondly, the private protocol collaboration module dynamically adjusts the communication protocol parameters according to the urgency of the load task, prioritizes the communication needs of high-priority tasks, and improves the overall communication efficiency of the system.

[0069] Further, the step of dynamically adjusting the parameters of the communication protocol according to the urgency of the tasks of the plurality of load devices comprises the following steps:

[0070] Data collection: real-time collection of communication traffic data of a plurality of load devices, and generation of a bandwidth utilization report based on a pre-set monitoring period;

[0071] Threshold triggering: when the bandwidth utilization of any load device continuously exceeds a pre-set high threshold, dynamically expanding the communication time slot of the load device or increasing the protocol baud rate of the load device; when the bandwidth utilization of any load device is lower than a pre-set low threshold, releasing the redundant communication resources of the load device and reallocating them to the load devices corresponding to high-priority tasks;

[0072] Allocation optimization: allocating fixed time slots and maximum bandwidth to load devices corresponding to high-priority tasks (such as cameras); for load devices corresponding to low-priority tasks (such as environmental sensors), a dynamic time slot polling mechanism is used, which includes allocating only the remaining bandwidth in idle periods;

[0073] Allocation analysis: analyzing the future bandwidth demand of the load device based on its historical traffic data, and adjusting the allocation strategy in advance based on the analysis results to avoid congestion caused by sudden traffic.

[0074] Based on the above-mentioned design of dynamically adjusting the parameters of the communication protocol, by real-time collection of communication traffic data of the load device and generation of a bandwidth utilization report, combined with the threshold triggering mechanism to dynamically expand or release communication resources, the problem of resource waste or bottleneck caused by traditional static allocation is solved. Secondly, fixed time slots and maximum bandwidth are allocated to high-priority tasks, and a dynamic time slot polling mechanism is used for low-priority tasks, ensuring the communication quality of critical tasks while taking into account the resource utilization of low-priority tasks.

[0075] It is feasible to analyze the future bandwidth demand of the load device according to its historical traffic data, and adjust the allocation strategy in advance based on the analysis results, including the following steps:

[0076] According to the multiple load devices (such as cameras, laser radars, and environmental sensors) and the task urgency (such as real-time demand and data size), the load devices are divided into high-priority devices (such as real-time video stream devices), medium-priority devices (such as laser radar point cloud data devices), or low-priority devices (such as environmental sensor data devices), and a priority queue is generated;

[0077] A bandwidth allocation weight is preset for each priority device (such as 60% for high-priority devices, 30% for medium-priority devices, and 10% for low-priority devices), and the communication time slot allocation of each load device is adjusted in real time based on the weighted round robin algorithm;

[0078] The bandwidth allocation strategy is optimized online through a deep reinforcement learning algorithm (such as DQN or PPO), wherein the state space of the deep reinforcement learning algorithm includes the current bandwidth utilization, task priority, and historical traffic pattern of each load device; the action space of the deep reinforcement learning algorithm includes adjusting the bandwidth allocation proportion of a specified load device (such as increasing / decreasing the bandwidth of a camera by 5%); and the reward function of the deep reinforcement learning algorithm includes maximizing the throughput of a key task (such as camera video stream) while minimizing the delay fluctuation of a low-priority task;

[0079] An optimal bandwidth allocation strategy is dynamically generated through real-time training of the model and fed back to the protocol priority queue.

[0080] Among them, the design of the deep reinforcement learning algorithm is as follows:

[0081] I. For the state space:

[0082] 1. Dimension:

[0083] Bandwidth utilization (range 0 to 1): indicates the usage ratio of the current communication link (0 indicates complete idle, 1 indicates full load), used to quantify the real-time load of the communication link;

[0084] Task priority (0, 1, 2, and 3): indicates the urgency of the load task (0 is the lowest priority, 3 is the highest priority), used to distinguish the urgency of the task by numerical value, for example: 0 represents background tasks (such as data log recording), 1 represents ordinary tasks (such as regular image transmission), 2 represents high-priority tasks (such as real-time video stream), and 3 represents key tasks (such as flight control instructions);

[0085] Historical traffic pattern (range 0 to 1): represents the fluctuation characteristics of communication traffic in the past period (0 represents stable, 1 represents high fluctuation), used for analyzing future demand;

[0086] For example: state = [0.85, 2, 0.7]: indicates that the current bandwidth utilization is 85%, the task priority is 2, and the historical traffic pattern is 0.7 (moderate fluctuation).

[0087] 2. For the action space, adjust the bandwidth allocation ratio:

[0088] Increase bandwidth allocation ratio by 10%: increase the communication resource allocation of the specified load device.

[0089] Reduce bandwidth allocation ratio by 10%: reduce the communication resource allocation of the specified load device.

[0090] Maintain the current allocation ratio: maintain the existing bandwidth allocation strategy unchanged.

[0091] 3. Reward function:

[0092] The formula is: R = α × throughput - β × delay fluctuation R = α × throughput - β × delay fluctuation

[0093] Where, throughput represents the communication efficiency of critical tasks (such as the amount of data transmitted per unit time, unit: MB / s); delay fluctuation represents the communication delay stability of low-priority tasks (such as the standard deviation of delay, unit: ms); α = 0.8 (prioritize optimizing throughput); β = 0.2 (moderately control the delay fluctuation of low-priority tasks).

[0094] 4. Model training

[0095] Use the Proximal Policy Optimization (Proximal Policy Optimization) algorithm, update the policy network every 1000 steps, discount factor γ = 0.99, and entropy coefficient 0.01. The training data is the bandwidth utilization curve (such as sine wave + noise) and task priority sequence generated by the simulation environment.

[0096] Based on the above allocation analysis design, the bandwidth allocation strategy is optimized online through deep reinforcement learning algorithm (state space includes bandwidth utilization, task priority, historical traffic pattern, action space includes adjusting bandwidth allocation ratio, reward function considers throughput and delay fluctuation), which improves the adaptive ability of the system in complex scenarios; secondly, through real-time training model and feedback to the protocol priority queue, the optimal bandwidth allocation strategy is generated, which solves the defect that traditional rule-based allocation is difficult to cope with dynamic load changes.

[0097] Further possible, the dynamic adjustment of the parameters of the communication protocol according to the task urgency of the plurality of load devices further comprises the following steps:

[0098] When any of the load devices has a communication exception (such as a CRC error rate > 1%), the communication of the load device is switched to a low-bandwidth mode (such as a baud rate from 2 Mbps to 100 kbps) by the PSDK relay device;

[0099] The data packet of the load device is automatically retransmitted by a sliding window algorithm (such as a sliding window algorithm with a back N frame protocol and a window size = 4), and the maximum number of retransmissions (such as 3 times) is set, and the timeout time is 100 ms;

[0100] The error code and timestamp corresponding to the abnormal communication are recorded to a non-volatile memory (such as a Flash) for subsequent fault analysis.

[0101] Based on the above design of dynamically adjusting the parameters of the communication protocol, when the load device has a communication exception, it is automatically switched to a low-bandwidth mode, and the data packet is retransmitted by a sliding window algorithm, which effectively reduces the impact of communication interruption on system stability, and the error code and timestamp of abnormal communication are recorded to a non-volatile memory, facilitating subsequent fault diagnosis and system optimization.

[0102] In the embodiment, the PSDK relay device further comprises:

[0103] The encryption communication unit is configured to encrypt data between the plurality of load devices and the PSDK relay device based on an encryption algorithm (such as an AES-256 algorithm), and perform key exchange by an asymmetric encryption algorithm (such as an RSA algorithm), with a public key length of 2048 bits and a padding mode of optimal asymmetric encryption padding.

[0104] The device authentication unit is configured to verify the legitimacy of the accessed load device by a preset digital certificate, such as checking the issuer and validity period of the load device certificate based on the X.509 standard, to prevent unauthorized devices from accessing.

[0105] Based on the further design of the PSDK relay device, the encryption communication unit encrypts data based on an encryption algorithm and performs key exchange by an asymmetric encryption algorithm, ensuring the confidentiality and integrity of data transmission, and at the same time, the device authentication unit verifies the legitimacy of the load device by a digital certificate, preventing illegal devices from accessing the system and enhancing the security protection capability of the system.

[0106] In the embodiment, the UAV ePort interface is configured with a standardized protocol compatible mechanism for switching communication protocols (such as CAN, UART, SPI protocol) through a hardware switch (selecting a protocol through a jumper) or a software configuration (sending a configuration command through the UAV ePort interface).

[0107] Based on the setting of the above-mentioned standardized protocol compatible mechanism, the adaptation problem caused by inconsistent ePort interface protocols is solved, and the versatility and deployment flexibility of the system are improved.

[0108] Further, the UAV ePort interface is also configured with a protocol conflict detection mechanism for restoring communication through an arbitration algorithm (such as priority polling) when multiple load devices simultaneously send conflicting data packets (such as multiple load devices simultaneously occupying a transmission channel). A feasible conflict handling method is to discard low-priority data packets and resend high-priority data packets when a conflict data packet is detected.

[0109] Based on the setting of the above-mentioned protocol conflict detection mechanism, when multiple load devices simultaneously send conflicting data packets, communication is quickly restored through an arbitration algorithm, avoiding the problem of data packet loss or system deadlock.

[0110] In the second aspect, the embodiment provides an interface adaptation method of a PSDK relay-based multi-load cooperative control system, which is applied to the PSDK relay-based multi-load cooperative control system as described above and sequentially includes the following steps:

[0111] At the load device end, detect the hardware differences with the UAV ePort interface and generate a hardware difference identifier;

[0112] According to the hardware difference identifier, automatically load a driver that matches the UAV ePort interface;

[0113] At the PSDK relay device end, generate an adapted communication protocol based on the hardware difference identifier, and establish a private communication protocol based on the adapted communication protocol;

[0114] Through the private communication protocol, issue a unified control instruction to multiple load devices, and perform cooperative control on different load devices by shielding the underlying interface differences.

[0115] The PSDK relay-based multi-load cooperative control system of the embodiment detects hardware differences at the load device end and generates a hardware difference identifier, and the PSDK relay device end generates an adapted communication protocol based on the identifier and establishes a private communication protocol, finally realizing unified control instruction issuance and multi-load cooperative control, solving the adaptation problem of heterogeneous interfaces and protocols, and forming a complete interface adaptation method closed loop.

[0116] It should be noted that the interface adaptation method of the PSDK relay-based multi-load cooperative control system of the embodiment corresponds to the PSDK relay-based multi-load cooperative control system described above, and therefore, the parts (including but not limited to refined technical solutions, further technical effects, etc.) not specifically disclosed in the interface adaptation method of the PSDK relay-based multi-load cooperative control system can be correspondingly referred to the related description in the PSDK relay-based multi-load cooperative control system described above, and this text will not be repeated here.

[0117] In the embodiments provided in the present application, it should be understood that the embodiments described herein can be realized in hardware, software, firmware, middleware, code, or any appropriate combination thereof. For hardware implementation, the processor can be realized in one or more of the following units: application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing device (DSPD), programmable logic device (PLD), field programmable gate array (FPGA), processor, controller, microcontroller, microprocessor, other electronic units designed to implement the functions described herein, or a combination thereof. For software implementation, part or all of the processes of the embodiments can be instructed by a computer program to relevant hardware. When implemented, the above program can be stored in a computer readable storage medium or transmitted as one or more instructions or codes on a computer readable storage medium. The computer readable storage medium includes computer storage medium and communication medium, wherein the communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a computer. The computer readable storage medium can include but is not limited to RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer.

[0118] Finally, it should be noted that: the above only describes the preferred embodiments of the present application and does not limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments or make equivalent replacements to some technical features, as long as they are within the spirit and principles of the present application. Any modification, equivalent replacement, improvement, etc. made shall be included in the protection scope of the present application.

Claims

1. A multi-load cooperative control system based on PSDK relay, characterized in that, The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type.

2. The PSDK relay based multi-load cooperative control system according to claim 1, wherein, The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type.

3. The PSDK relay based multi-load cooperative control system of claim 1, wherein, The application relates to a UAV ePort interface and a load device with a heterogeneous load type.

4. The PSDK relay based multi-load cooperative control system according to claim 3, wherein, The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. The application relates to a UAV ePort interface and a load device with a heterogeneous load type. 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The PSDK relay based multi-load cooperative control system according to claim 4, wherein, The method comprises the following steps: According to the historical traffic data of the load device, the future bandwidth demand of the load device is analyzed, and the allocation strategy is adjusted in advance based on the analysis result, including the following steps: According to the multiple load devices and the task urgency, the load devices are divided into high-priority devices, medium-priority devices or low-priority devices, and a priority queue is generated; A bandwidth allocation weight is preset for each priority device, and the communication time slot allocation of each load device is adjusted in real time based on the weighted round robin algorithm; The bandwidth allocation strategy is optimized online through a deep reinforcement learning algorithm, wherein the state space of the deep reinforcement learning algorithm includes the bandwidth utilization, task priority and historical traffic pattern of each load device; the action space of the deep reinforcement learning algorithm includes adjusting the bandwidth allocation proportion of a specified load device; and the reward function of the deep reinforcement learning algorithm includes maximizing the throughput of critical tasks and minimizing the delay fluctuation of low-priority tasks.

6. The PSDK relay based multi-load cooperative control system according to claim 4, wherein, An optimal bandwidth allocation strategy is dynamically generated through real-time training of the model, and is fed back to the protocol priority queue. The method further comprises the following steps: When any load device has communication abnormalities, the communication of the load device is switched to a low-bandwidth mode through the PSDK relay device; The data packets of the load device are automatically retransmitted through a sliding window algorithm, and the maximum number of retransmissions is set; 7. The PSDK relay based multi-load cooperative control system of claim 1, wherein, The error code and timestamp corresponding to the abnormal communication are recorded in the non-volatile memory. The PSDK relay device further comprises: An encrypted communication unit for encrypting data between the multiple load devices and the PSDK relay device based on an encryption algorithm, and performing key exchange through an asymmetric encryption algorithm; 8. The PSDK relay based multi-load cooperative control system of claim 1, wherein, A device authentication unit for verifying the legitimacy of the access load device through a preset digital certificate.

9. The PSDK relay based multi-load cooperative control system of claim 1, wherein, The UAV ePort interface is configured with a standardized protocol compatible mechanism for switching communication protocols through a hardware switch or software configuration.

10. An interface adaptation method of a PSDK relay based multi-load cooperative control system, applied to the PSDK relay based multi-load cooperative control system according to any one of claims 1-9, characterized in that, The UAV ePort interface is further configured with a protocol conflict detection mechanism for recovering communication through an arbitration algorithm when multiple load devices simultaneously send conflicting data packets. The method comprises the following steps in sequence: At the load device end, the hardware differences with the UAV ePort interface are detected, and a hardware difference identifier is generated; According to the hardware difference identifier, a driver program matched with the UAV ePort interface is automatically loaded; At the PSDK relay device end, an adaptive communication protocol is generated based on the hardware difference identifier, and a private communication protocol is established based on the adaptive communication protocol; Through the private communication protocol, a unified control instruction is issued to the multiple load devices, and different load devices are cooperatively controlled by shielding the underlying interface differences.

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