Multi-unmanned aerial vehicle synchronous positioning and mapping method based on block chain information security enhancement

Abstract

The invention belongs to the technical field of unmanned aerial vehicles, and particularly relates to a multi-unmanned aerial vehicle synchronous positioning and mapping method based on block chain information security enhancement. According to the invention, the data uploaded by the unmanned aerial vehicle can be stored in a non-tampering manner at the server side by combining the block chain technology, and the function of the group key is dynamically adjusted according to the state of the unmanned aerial vehicle, so that the unmanned aerial vehicle can be ensured to flexibly and safely join or exit from the network in different states; therefore, the flexibility and fault tolerance of an unmanned aerial vehicle network are improved, a plurality of unmanned aerial vehicles collect and upload local map data at the same time, the server can integrate the data to form a larger regional map, the precision and efficiency of environmental perception are improved, the redundancy is reduced, the reliability is improved, and the unmanned aerial vehicles can realize high-precision map construction. Meanwhile, the chain structure of the block chain ensures the historical traceability of each data block, and ensures that the source of map data is clear and the process is transparent.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to a multi-unmanned aerial vehicle synchronous positioning and mapping method based on blockchain information security enhancement. Background Art

[0002] UAVs are unmanned aerial vehicles that are controlled by radio remote control or autonomous control devices to complete specific mission requirements. Due to their low cost, high maneuverability and safety, stealth performance and strong battlefield survivability, they are widely used in military, civilian and commercial fields.

[0003] Simultaneous Localization and Mapping (SLAM) technology mainly refers to the mobile robot relying on various sensors to obtain environmental information when moving in an unknown environment, thereby simultaneously building an environmental map and estimating position information. Due to the advantages of low cost, high positioning accuracy, portability and strong scalability, this technology has been widely used in the field of drones. According to the difference in the number of drones in the SLAM system, its implementation methods can be divided into single-drone SLAM and multi-drone SLAM.

[0004] Blockchain technology is a data system that reassembles blocks of stored data in a chain in chronological order. It has the characteristics of security, reliability, simple storage, and convenient data self-verification. Blockchain technology introduces decentralized architecture, redundant storage protocols, programmable frameworks, etc., making it a core technical solution to enhance the security of drone swarm networks and their constituent systems. In addition, the distributed ledger technology in the blockchain can reach a consensus on network communication data by updating and verifying the data collected by drones, thereby improving the security of drone communication data storage and transmission.

[0005] Limited by the number of onboard equipment and perception viewpoints, a single drone cannot meet the needs of complex environments and diverse tasks. In addition, if a single drone fails during the execution of a task, it may cause the interruption of the task and even affect the execution of the entire task. For this reason, when drones in a multi-drone system perform tasks and communicate in real time, a continuous control strategy is usually adopted to obtain system status information. However, the continuous data exchange between nodes, frequent sensor sampling and controller updates lead to a large waste of storage and transmission resources. In particular, when the number of network nodes increases, the data processing capabilities and network transmission requirements of drones are greatly increased. However, due to the limitations of node computing power and storage capacity of multi-drone clusters, traditional encryption methods cannot handle the massive keyframes and map key point data in collaborative mapping tasks. In addition, drone nodes are also vulnerable to data access and secret surveillance by unauthorized nodes, which may damage user privacy or maliciously tamper with data, resulting in the failure of mapping tasks. Summary of the invention

[0006] The purpose of the present invention is to provide a multi-UAV synchronous positioning and mapping method based on blockchain information security enhancement, which can enhance the security of map information data and the ability to resist external intrusion, and improve the system's defense against potential malicious tampering.

[0007] The technical solution adopted by the present invention is as follows: A multi-UAV synchronous positioning and mapping method based on blockchain information security enhancement, comprising: Get the ID of each drone, get the corresponding encryption key according to each drone ID, verify whether the encryption key is correct, and if correct, add the drone ID corresponding to the correct encryption key to the network; Get the number of drones, and get the group key of the corresponding drone ID according to the number of drones, get the current state of the drone, and determine whether the current state of the drone meets the preset conditions. If not, get the new group key of the corresponding drone ID according to the current state of the drone, and verify whether the new group key is correct. If correct, add the drone ID corresponding to the correct new group key to the network; Obtain video data collected by drones in the network, and obtain corresponding multiple key frames and multiple map points based on the video data; Obtain a local local map, link multiple key frames and multiple map points with the local local map, construct regional local map data near the drone, and send the regional local map data to the server; The server receives the regional local map data, initializes the map stack of the server, and stores the regional local map data in the initialized map stack of the server; According to the hash function, the regional local map data in the map stack is encapsulated into multiple data blocks, and the corresponding hash value is obtained according to the data block. According to the blockchain, the multiple data blocks are formed into a chain data structure and stored.

[0008] In a preferred solution, the steps of obtaining each drone ID, obtaining a corresponding encryption key according to each drone ID, verifying whether the encryption key is correct, and if correct, adding the drone ID corresponding to the correct encryption key to the network include: Get each drone ID; Obtain the corresponding encryption key according to each drone ID, where the encryption key includes a public key and a private key; Each drone encrypts the identity information and timestamp according to the private key to obtain encrypted data, and sends the encrypted data to the server; The server decrypts and verifies the identity information is correct based on the public key corresponding to each drone ID, and verifies whether the timestamp of the encrypted data is within the validity period; If the verification is successful, the server will return an identifier, and the drone will be considered to have passed the verification and successfully joined the network, and the drone ID will be added to the legal node list; If the verification fails, the server will reject the drone's access request and prompt you to reapply for verification.

[0009] In a preferred solution, the failure of verification includes any one of the following: the time stamp is out of validity period and the public key decryption identity information is wrong.

[0010] In a preferred solution, the steps of obtaining the number of drones, obtaining the group key corresponding to the drone ID according to the number of drones, obtaining the current state of the drone, and judging whether the current state of the drone meets the preset conditions, if not, obtaining a new group key corresponding to the drone ID according to the current state of the drone, and verifying whether the new group key is correct, and if correct, adding the drone ID corresponding to the correct new group key to the network, include: Get the number of drones, and get the group key of the corresponding drone ID according to the number of drones; Get the current status of the drone, where the current status of the drone includes whether the number of drones has changed and whether the drone group key has reached the update cycle; Determine whether the number of drones has changed or whether the drone group key has reached the update cycle; If the number of drones changes or the drone group key reaches the update cycle, the corresponding new group key is obtained based on the drone ID; Verify that the new group key of the drone ID matches; If the new group key is verified to match, the server will re-add the drone ID to the network; If the verification of the new group key does not match, the server will reject the drone ID from joining the network and issue a fault warning.

[0011] In a preferred embodiment, the step of obtaining video data collected by drones in the network and obtaining corresponding multiple key frames and multiple map points according to the video data includes: Obtain video data collected by each drone in the network; Acquire multiple image frames according to the video data; Obtain key frames from multiple image frames; Get the corresponding map point according to each key frame data.

[0012] In a preferred embodiment, the steps of obtaining a local local map, linking a plurality of key frames and a plurality of map points with the local local map, constructing regional local map data near the drone, and sending the regional local map data to the server include: Get local map; Obtain map data within the flight range of the drone from the local local map and mark it as a flight local map; Combine all keyframes and map points related to the local flight map to construct a local map of the area within the current flight range of the drone; Send the regional local map data to the server.

[0013] In a preferred embodiment, the server receives the regional local map data and initializes the map stack of the server, and the step of storing the regional local map data in the initialized map stack of the server includes: Create a corresponding map stack in the server according to the ID of each drone in the network; The server receives the regional local map data and initializes the server's map stack; The server stores the received regional local map data in the map stack corresponding to the drone ID.

[0014] In a preferred embodiment, the steps of encapsulating the regional local map data in the map stack into multiple data blocks according to the hash function, obtaining corresponding hash values ​​according to the data blocks, and forming a chain data structure and storing the multiple data blocks according to the blockchain include: Divide the local map data of the region in the map stack into multiple regions, and encapsulate each region into a data block; Generate a hash value for the encapsulated data block according to the hash function, and bind each data block to the corresponding hash value; According to the order of hash value generation, multiple data blocks are sorted, the hash value of each data is associated with the content of the next data block, and a chain data structure is constructed and stored.

[0015] In a preferred solution, if the drone group key reaches the update cycle, it returns to obtaining the number of drones, and obtains the group key corresponding to the drone ID based on the number of drones, obtains the current state of the drone, and determines whether the current state of the drone meets the preset conditions. If not, a new group key corresponding to the drone ID is obtained according to the current state of the drone, and it is verified whether the new group key is correct. If correct, the drone ID corresponding to the correct new group key is added to the networking step.

[0016] And, a multi-UAV synchronous positioning and mapping terminal based on blockchain information security enhancement, including: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-UAV synchronous positioning and mapping method based on blockchain information security enhancement.

[0017] The technical effects achieved by the present invention are: The present invention ensures that only legal drones can access the network through an encryption key verification mechanism, thereby ensuring the security of the network. At the same time, the application of blockchain technology enables the data uploaded by the drone to be stored in a tamper-proof form on the server side. Each data block has a unique hash value, and any tampering will be detected in real time. The function of dynamically adjusting the group key according to the state of the drone ensures that the drone can flexibly and safely join or exit the network in different states, thereby improving the flexibility and fault tolerance of the drone network. Multiple drones collect and upload local map data at the same time, and the server can integrate these data to form a larger regional map, thereby reducing data redundancy. Through the simultaneous positioning and mapping (SLAM) technology, drones can work together without interfering with each other, thereby improving the accuracy and efficiency of environmental perception. The distributed storage structure based on blockchain can store data on multiple nodes, thereby improving reliability. Even if a single node fails, other nodes can still provide complete map data. Through the key frame extraction of video data and the generation of map points, the drone can achieve high-precision map construction. At the same time, the chain structure of the blockchain ensures the historical traceability of each data block, and ensures that the source of the map data is clear and the process is transparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a flow chart of the method provided by the present invention; Figure 2 It is a system architecture diagram provided by the present invention; Figure 3 It is a local route map of each drone provided by the present invention; Figure 4 It is the global route map of each drone provided by the present invention; Figure 5 It is a graph of the accuracy of the simulated paths of each UAV provided by the present invention compared with the actual paths. DETAILED DESCRIPTION

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0020] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" that appears in different places in this specification does not refer to the same embodiment, nor is it a separate or selective embodiment that is mutually exclusive with other embodiments.

[0022] Secondly, the present invention is described in detail in conjunction with schematic diagrams. When describing the embodiments of the present invention in detail, for the convenience of explanation, the schematic diagrams are only examples and should not limit the scope of protection of the present invention.

[0023] Please see attached Figures 1 to 5 As shown, a multi-UAV synchronous positioning and mapping method based on blockchain information security enhancement is provided, including: S1. Obtain each drone ID, obtain the corresponding encryption key according to each drone ID, and verify whether the encryption key is correct. If correct, add the drone ID corresponding to the correct encryption key to the network; S2. Obtain the number of drones, and obtain the group key corresponding to the drone ID according to the number of drones, obtain the current state of the drone, and determine whether the current state of the drone meets the preset conditions. If not, obtain the new group key corresponding to the drone ID according to the current state of the drone, and verify whether the new group key is correct. If correct, add the drone ID corresponding to the correct new group key to the network; S3, obtaining video data collected by drones in the network, and obtaining corresponding multiple key frames and multiple map points according to the video data; S4, obtaining a local local map, linking multiple key frames and multiple map points with the local local map, constructing regional local map data near the drone, and sending the regional local map data to the server; S5. The server receives the regional local map data, initializes the map stack of the server, and stores the regional local map data in the initialized map stack of the server; S6. Encapsulate the regional local map data in the map stack into multiple data blocks according to the hash function, obtain the corresponding hash value according to the data block, and form a chain data structure with the multiple data blocks according to the blockchain and store them.

[0024] As in the above steps S1 to S6, each drone is identified by its unique ID and a corresponding encryption key is assigned to it. During the networking process, the encryption key is verified to be correct to ensure that only verified drones can join the network to avoid unauthorized device access. In response to the state changes of the drones (the number of drones changes, the drone group key reaches the update cycle), the group key is redistributed and verified according to the latest state to ensure the security and dynamics of the drone networking. After the networking is successful, the drone will start to collect video data. Through image processing technology, multiple key frames and map points are extracted from the video data to generate a local map of the drone's surrounding environment. The local map data constructed by the drone is transmitted to the server through the network. The server initializes the map stack and stores the regional local map data uploaded by the drone in the specified stack. The server will encapsulate the received regional local map data into multiple data blocks according to the hash function. Each data block is uniquely identified by a hash value. Then, these data blocks will be stored in the blockchain in a chain structure. The integrity and security of the data are ensured through the mutual dependence between blocks. The chain structure of the blockchain ensures that the data cannot be tampered with. Even if the local data is tampered with, the authenticity of the data can be detected by verifying the hash value. Authenticity, through the encryption key verification mechanism, it is ensured that only legal drones can access the network, ensuring the security of the network. At the same time, the application of blockchain technology enables the data uploaded by drones to be stored in an unalterable form on the server side. Each data block has a unique hash value, and any tampering will be detected in real time. The function of dynamically adjusting the group key according to the drone status ensures that the drone can flexibly and safely join or exit the network in different states, thereby improving the flexibility and fault tolerance of the drone network. Multiple drones collect and upload local map data at the same time, and the server can integrate these data to form a larger regional map, reducing data redundancy. Through the simultaneous positioning and mapping (SLAM) technology, drones can work together without interfering with each other, improving the accuracy and efficiency of environmental perception. The distributed storage structure based on blockchain can store data on multiple nodes, improving reliability. Even if a single node fails, other nodes can still provide complete map data. Through the key frame extraction of video data and the generation of map points, drones can achieve high-precision map construction. At the same time, the chain structure of blockchain ensures the historical traceability of each data block, ensuring that the source of map data is clear and the process is transparent.

[0025] In a specific embodiment, the steps of obtaining each drone ID, obtaining a corresponding encryption key according to each drone ID, verifying whether the encryption key is correct, and if correct, adding the drone ID corresponding to the correct encryption key to the network include: S101, obtain each drone ID; S102, obtaining a corresponding encryption key according to each drone ID, wherein the encryption key includes a public key and a private key; S103, each drone encrypts the identity information and timestamp according to the private key to obtain encrypted data, and sends the encrypted data to the server; S104, the server decrypts and verifies whether the identity information is correct according to the public key corresponding to each drone ID, and verifies whether the timestamp of the encrypted data is within the validity period; If the verification is successful, the server will return an identifier, and the drone will be considered to have passed the verification and successfully joined the network, and the drone ID will be added to the legal node list; If the verification fails, the server will reject the drone's access request and prompt you to reapply for verification.

[0026] The failure of verification includes any one of the following: the timestamp is out of validity period and the public key decryption identity information is wrong.

[0027] As in the above steps S101 to S104, a unique ID is assigned to each drone, and each drone has a pair of encryption keys: a public key and a private key. The private key is used for local encryption of the drone, and the public key is used for decryption on the server. Each drone encrypts the identity information and timestamp with its private key. The encrypted data contains the unique identity and timestamp of the drone to ensure the uniqueness and timeliness of the data. The drone sends the encrypted data to the server, and the server decrypts the encrypted data using the public key of the drone to verify whether the identity information matches the drone ID. The server not only verifies whether the decrypted identity information is correct, but also checks whether the timestamp is within the validity period to ensure that the encrypted data sent by the drone is the latest and prevent expired data packets that may be used by attackers. If the verification is successful, the server returns an identifier, indicating that the drone's identity has been confirmed, and adds the drone's ID to the list of legal nodes, allowing it to access the network. If the verification fails, the server will reject the drone's access request and inform the drone to retry. For new application verification, the reasons for failure include public key decryption failure (identity information error) or timestamp expiration. Using the public key and private key encryption mechanism, each drone can only be encrypted by its private key, and the server decrypts by the public key. This mechanism ensures the uniqueness of the drone's identity and prevents the possibility of tampering with data midway. By encrypting the identity information with the private key, the server can directly verify the legitimacy of the drone by decryption. For any decryption failure or timestamp expiration, the server will automatically reject the access request to ensure that only legal and latest drones can successfully access the network. It has the ability of real-time identity authentication and status update. Whether it is a newly connected drone or a drone with a changed status, it can be dynamically managed and verified through encryption keys and timestamps, making the management of the entire network more flexible and efficient. The public key, private key encryption and timestamp mechanism ensures the security of drone access and effectively prevents threats such as identity fraud, data tampering and replay attacks. Only verified drones can join the network, enhancing the overall security and stability of the networking system.

[0028] In a specific embodiment, the steps of obtaining the number of drones, obtaining a group key corresponding to the drone ID according to the number of drones, obtaining the current state of the drone, and determining whether the current state of the drone meets a preset condition, if not, obtaining a new group key corresponding to the drone ID according to the current state of the drone, and verifying whether the new group key is correct, and if correct, adding the drone ID corresponding to the correct new group key to the network, include: S201, obtaining the number of drones, and obtaining the group key corresponding to the drone ID according to the number of drones; S202, obtaining the current state of the drone, wherein the current state of the drone includes whether the number of drones has changed and whether the drone group key has reached the update cycle; S203, determining whether the number of drones has changed or whether the drone group key has reached an update cycle; If the number of drones changes or the drone group key reaches the update cycle, the corresponding new group key is obtained based on the drone ID; S204, verify whether the new group key of the drone ID matches; If the new group key is verified to match, the server will re-add the drone ID to the network; If the verification of the new group key does not match, the server will reject the drone ID from joining the network and issue a fault warning.

[0029] As in the above steps S201 to S204, the number of drones currently connected to the network is counted, and a corresponding group key is assigned to each drone. The group key is used for encrypted communication between the drone and the server. The current status of the drone mainly includes two aspects: whether the number of drones has changed (i.e., drones have joined or left) and whether the group key has reached the preset update cycle. Regularly updating the group key helps to enhance security and prevent potential risks caused by long-term use of the same key. If the number of drones changes, or the group key has reached the update cycle, a new group key needs to be obtained, and the update of the group key is triggered to ensure that new devices can successfully join the network. In the process of updating the group key, the old key is prevented from being used by attackers. A new group key is generated according to the ID of each drone, and these new keys are distributed to each drone. The server will verify the new key sent by each drone. Ensure that the new key is consistent with the corresponding key stored in the server. If the verification is successful, the server will re-add the drone's ID to the network, indicating that the drone can continue to communicate securely. If the verification fails (that is, the new key does not match), the server will refuse the drone to join the network and trigger a fault warning, prompting the operator to conduct further inspection and repair, ensuring that drones in the network can flexibly join or exit without restarting the entire system. It can dynamically manage group keys according to real-time changes (such as changes in the number of drones), improve the flexibility and adaptability of the network, and regularly update the group key to reduce the security risks brought by long-term use of the same key. Even if an attacker obtains the old group key, he cannot attack the new group key, thereby improving the security of the drone network. By verifying the validity of the new group key, it can ensure that only drones with legitimate keys can join the network, eliminating the risk of access by illegal devices.

[0030] In a specific embodiment, the step of obtaining video data collected by a drone in the network and obtaining corresponding multiple key frames and multiple map points according to the video data includes: S301, obtaining video data collected by each drone in the network; S302, acquiring multiple image frames according to the video data; S303, obtaining key frames from multiple image frames; S304: Obtain corresponding map points according to each key frame data.

[0031] As in the above steps S301 to S304, each drone will continuously collect video data during flight. These video data contain real-time environmental information from the drone's perspective. All drones connected to the network will send their collected video data to the central server or processing node, and extract multiple static image frames from the received video data, which can be processed through ORB (Oriented FAST and Rotated Image Processing). The SLAM visual odometer of BRIEF) processes the image frames of the video data. These image frames represent the pictures at different time points in the video. In the image frames, key frames are identified by image processing technology. Key frames usually contain significant environmental features or change information. Compared with other image frames, key frames can more effectively represent the characteristic information of the environment. The information extracted from the key frames is used to generate map points. Map points are feature points representing specific geographical locations. These points are used to build maps or perform navigation positioning. Image feature matching technology is usually used to compare the significant features in the key frames with known map points to obtain new map point data, which can efficiently model the environment. The selection of key frames ensures that only important image information is used for map construction, thereby improving the accuracy and reliability of the model. Image frames and key frames are extracted from the video data of the drone in real time, and the map can be updated dynamically. This processing method supports real-time environmental monitoring and map updates, and improves the real-time response capability of the drone system. The use of key frames ensures high accuracy in the map construction process and reduces redundant and unnecessary data. Through precise key frame extraction, the generation of map points is more accurate, which improves the accuracy and reliability of the map.

[0032] In a specific embodiment, the steps of obtaining a local local map, linking a plurality of key frames and a plurality of map points with the local local map, constructing regional local map data near the drone, and sending the regional local map data to the server include: S401, obtaining a local partial map; S402, obtaining map data within the flight range of the UAV from the local local map, and marking it as a flight local map; S403, combining all key frames and map points related to the local flight map to construct a local map of the area within the current flight range of the UAV; S404: Send the regional local map data to the server.

[0033] As in the above steps S401 to S404, the drone will generate and update the local local map in real time during the flight. This map data is the environmental information within the current field of view of the drone, including terrain, obstacles and other relevant features. The map data within the current flight range of the drone is extracted from the local local map. This data set is marked as a flight local map, which is specifically used to represent the environmental features of the drone in the current flight area, ensuring that only the map information within the actual flight area of ​​the drone is focused on, avoiding processing of irrelevant data, and using the extracted flight local map data, combined with relevant key frames and map point information, to construct a local map of the area within the current flight range of the drone. The frames and map points are integrated to generate a complete and detailed regional map to accurately reflect the flight environment of the drone. After the regional local map is built, the map data is sent to the central server. The server is responsible for receiving, storing and further processing the map data for subsequent analysis, sharing or integration. It can accurately build regional local maps. This precise map information helps to improve the drone's navigation and obstacle avoidance capabilities and ensure the safety and reliability of flight. Combining the information of key frames and map points to build regional local maps can more comprehensively and accurately describe the drone's flight area, help improve the accuracy of the map, and provide a reliable basis for subsequent map analysis and mission planning.

[0034] In a specific embodiment, the server receives the regional local map data and initializes the map stack of the server, and the step of storing the regional local map data in the initialized map stack of the server includes: S501, creating a corresponding map stack in the server according to each drone ID in the network; S502, the server receives the regional local map data and initializes the map stack of the server; S503: The server stores the received regional local map data in the map stack corresponding to the drone ID.

[0035] As in the above steps S501 to S503, the server creates a unique map stack for each drone to store the map data uploaded by the drone. These map stacks are containers for organizing and managing the map data generated by the drone, ensuring that the data of each drone can be tracked and managed separately. The server receives the regional local map data from the drone and initializes the corresponding map stack. The initialization process includes setting the data storage format and structure to ensure that the map data can be correctly stored and retrieved. The server stores the received regional local map data in the corresponding map stack according to the drone ID. By creating a separate map stack for each drone, the server can effectively organize and manage the map data of different drones, which helps to keep the data neat and consistent, making data management more efficient. The map data of each drone is stored in an independent map stack. This isolation measure improves data security, ensures that data between drones will not be confused or leaked, and protects sensitive map data generated by each drone.

[0036] In a specific embodiment, the steps of encapsulating the regional local map data in the map stack into multiple data blocks according to the hash function, obtaining corresponding hash values ​​according to the data blocks, and forming a chain data structure and storing the multiple data blocks according to the blockchain include: S601, dividing the regional local map data in the map stack into a plurality of regions, and encapsulating each region into a data block; S602, generating a hash value for the encapsulated data block according to a hash function, and binding each data block to the corresponding hash value; S603, sorting multiple data blocks according to the hash value generation order, associating the hash value of each data with the content of the next data block, constructing a chain data structure and storing it.

[0037] As in the above steps S601 to S603, the regional local map data in the map stack is logically divided into several smaller data blocks, each data block contains a part of the map data or metadata. This division method can facilitate the management and processing of large-scale data sets. The encapsulated data blocks provide basic units for subsequent hash processing and chain storage. A hash function is used to perform a hash operation on each data block to generate a unique hash value. The hash value is a digital fingerprint that can uniquely identify the content of the data block. By binding the hash value to the data block, the integrity of the data block can be ensured, and whether the data has been tampered with during storage or transmission can be detected. The data blocks are sorted according to the hash value generation order to form a chain structure. Each data block contains a hash value reference to the previous data block, thus forming a chain. In this way, any modification to the data block in the chain will cause the hash value of the subsequent data block to change, thereby easily detecting data tampering. The data blocks are stored in a chain structure to form a blockchain to ensure data security and consistency.

[0038] It should be noted that in any of steps S3 to S6, if the drone group key reaches the update cycle, the process returns to obtaining the number of drones, and obtains the group key corresponding to the drone ID based on the number of drones, obtains the current state of the drone, and determines whether the current state of the drone meets the preset conditions. If not, a new group key corresponding to the drone ID is obtained based on the current state of the drone, and it is verified whether the new group key is correct. If correct, the drone ID corresponding to the correct new group key is added to the networking step.

[0039] In the above, during the execution of any of steps S3 to S6, if it is found that the group key has reached the update cycle, the key update process is triggered, and the process returns to step S2 to re-acquire the number of drones and the corresponding group key, ensuring that the group key is regularly updated to prevent key leakage or cracking, reduce potential security risks, and ensure the security of drone communications and data transmission.

[0040] And, a multi-UAV synchronous positioning and mapping terminal based on blockchain information security enhancement, including: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-UAV synchronous positioning and mapping method based on blockchain information security enhancement.

[0041] The above is only a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention shall be implemented according to the conventional means in the art unless otherwise specified and limited.

Claims

1. A multi-UAV synchronous positioning and mapping method based on blockchain information security enhancement, characterized in that: include: Get the ID of each drone, get the corresponding encryption key according to each drone ID, verify whether the encryption key is correct, and if correct, add the drone ID corresponding to the correct encryption key to the network; Get the number of drones, and get the group key of the corresponding drone ID according to the number of drones, get the current state of the drone, and determine whether the current state of the drone meets the preset conditions. If not, get the new group key of the corresponding drone ID according to the current state of the drone, and verify whether the new group key is correct. If correct, add the drone ID corresponding to the correct new group key to the network; Obtain video data collected by drones in the network, and obtain corresponding multiple key frames and multiple map points based on the video data; Obtain a local local map, link multiple key frames and multiple map points with the local local map, construct regional local map data near the drone, and send the regional local map data to the server; The server receives the regional local map data, initializes the map stack of the server, and stores the regional local map data in the initialized map stack of the server; According to the hash function, the regional local map data in the map stack is encapsulated into multiple data blocks, and the corresponding hash value is obtained according to the data block. According to the blockchain, the multiple data blocks are formed into a chain data structure and stored.

2. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to claim 1 is characterized in that: The steps of obtaining each drone ID, obtaining a corresponding encryption key according to each drone ID, verifying whether the encryption key is correct, and if correct, adding the drone ID corresponding to the correct encryption key to the network include: Get each drone ID; Obtain the corresponding encryption key according to each drone ID, where the encryption key includes a public key and a private key; Each drone encrypts the identity information and timestamp according to the private key to obtain encrypted data, and sends the encrypted data to the server; The server decrypts and verifies the identity information is correct based on the public key corresponding to each drone ID, and verifies whether the timestamp of the encrypted data is within the validity period; If the verification is successful, the server will return an identifier, and the drone will be considered to have passed the verification and successfully joined the network, and the drone ID will be added to the legal node list; If the verification fails, the server will reject the drone's access request and prompt you to reapply for verification.

3. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to claim 2 is characterized in that: The verification failure includes any one of the following: the timestamp is out of validity period and the public key decryption identity information is wrong.

4. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to claim 1 is characterized in that: The steps of obtaining the number of drones, obtaining the group key corresponding to the drone ID according to the number of drones, obtaining the current state of the drone, and judging whether the current state of the drone meets the preset conditions, if not, obtaining the new group key corresponding to the drone ID according to the current state of the drone, and verifying whether the new group key is correct, and if correct, adding the drone ID corresponding to the correct new group key to the network, include: Get the number of drones, and get the group key of the corresponding drone ID according to the number of drones; Get the current status of the drone, where the current status of the drone includes whether the number of drones has changed and whether the drone group key has reached the update cycle; Determine whether the number of drones has changed or whether the drone group key has reached the update cycle; If the number of drones changes or the drone group key reaches the update cycle, the corresponding new group key is obtained based on the drone ID; Verify that the new group key of the drone ID matches; If the new group key is verified to match, the server will re-add the drone ID to the network; If the verification of the new group key does not match, the server will reject the drone ID from joining the network and issue a fault warning.

5. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to claim 1 is characterized in that: The step of obtaining video data collected by drones in the network and obtaining corresponding multiple key frames and multiple map points according to the video data includes: Obtain video data collected by each drone in the network; Acquire multiple image frames according to the video data; Obtain key frames from multiple image frames; Get the corresponding map point according to each key frame data.

6. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to claim 1 is characterized in that: The steps of obtaining a local local map, linking a plurality of key frames and a plurality of map points with the local local map, constructing regional local map data near the drone, and sending the regional local map data to the server include: Get local map; Obtain map data within the flight range of the drone from the local local map and mark it as a flight local map; Combine all keyframes and map points related to the local flight map to construct a local map of the area within the current flight range of the drone; Send the regional local map data to the server.

7. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to claim 1 is characterized in that: The server receives the regional local map data, initializes the map stack of the server, and stores the regional local map data in the initialized map stack of the server, including: Create a corresponding map stack in the server according to the ID of each drone in the network; The server receives the regional local map data and initializes the server's map stack; The server stores the received regional local map data in the map stack corresponding to the drone ID.

8. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to claim 1 is characterized in that: The steps of encapsulating the regional local map data in the map stack into multiple data blocks according to the hash function, obtaining corresponding hash values ​​according to the data blocks, and forming a chain data structure and storing the multiple data blocks according to the blockchain include: Divide the local map data of the region in the map stack into multiple regions, and encapsulate each region into a data block; Generate a hash value for the encapsulated data block according to the hash function, and bind each data block to the corresponding hash value; According to the order of hash value generation, multiple data blocks are sorted, the hash value of each data is associated with the content of the next data block, and a chain data structure is constructed and stored.

9. The method for synchronous positioning and mapping of multiple UAVs based on blockchain information security enhancement according to any one of claims 5 to 8, characterized in that: If the drone group key reaches the update cycle, it returns to the step of obtaining the number of drones, and obtains the group key of the corresponding drone ID according to the number of drones, obtains the current state of the drone, and determines whether the current state of the drone meets the preset conditions. If not, it obtains the new group key corresponding to the drone ID according to the current state of the drone, and verifies whether the new group key is correct. If correct, the drone ID corresponding to the correct new group key is added to the networking step.

10. A multi-UAV synchronous positioning and mapping terminal based on blockchain information security enhancement, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the multi-UAV synchronous positioning and mapping method based on blockchain information security enhancement as described in any one of claims 1 to 9.

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