CN-121980583-A - Meta-universe digital asset source right determining method and equipment for robot cluster monitoring

CN121980583ACN 121980583 ACN121980583 ACN 121980583ACN-121980583-A

Abstract

The invention discloses a meta-universe digital asset source right-determining method and equipment for robot cluster monitoring, comprising the steps of supervising and observing the state of a target physical asset through a local sensor of each robot to obtain real-time supervision data, uploading the real-time supervision data to a blockchain network for distributed storage, enabling the real-time supervision data to comprise self-collected data and associated verification data of other robots in a cluster, enabling message transmission communication of the real-time supervision data among the robots by adopting an asymmetric encryption mechanism, further executing three-stage authenticity verification by adopting an intelligent contract to obtain a reputation value of each data collection source, and finally determining a source right-determining result based on the reputation value. The invention improves the robustness, expandability and active fraud prevention capability of the source rights process of the metauniverse digital asset.

Inventors

LUO JIE
ZHANG XINYU
CAO WENZHI
ZHANG WEIWEI
TAN HUI

Assignees

湖南红普创新科技发展有限公司

Dates

Publication Date: 20260505
Application Date: 20260108

Claims (10)

1. The meta-universe digital asset source right-determining method for robot cluster monitoring is characterized by comprising the following steps: S1, constructing a hybrid monitoring architecture, namely supervising and observing the state of a target physical asset through a local sensor of each robot to obtain real-time supervision data, and uploading the real-time supervision data to a blockchain network for distributed storage, wherein the supervision data comprises self-collected data and associated verification data of other robots in a cluster; S2, establishing an encryption communication channel, namely realizing message transmission communication of real-time supervision data among robots by adopting an asymmetric encryption mechanism, generating a public key/private key pair by each robot, encrypting a message load by using a public key of a receiver during message transmission communication, and generating a digital signature by using a private key of a sender; s3, performing three-stage authenticity verification of intelligent contract driving: Firstly, extracting supervision data of all robots from a block chain distributed storage to generate an asset state data frame set; step two, performing multi-view inconsistency analysis based on the asset state data frame set stored by the block chain to obtain an analysis result; Step three, dynamically adjusting the reputation value of the data acquisition source according to the analysis result, and storing the reputation value into a blockchain; And S4, determining a source right-confirming result based on the reputation value, wherein the right-confirming result is used for casting and judicial evidence storage of the metauniverse digital asset.
2. The method according to claim 1, wherein in the step S1: the block chain network is formed by HASHGRAPH programs of each robot node to form a decentralised storage architecture; real-time supervision data in the robot cluster are transmitted through an encrypted communication channel and written into the blockchain; the communication range of each robot is the same as the monitoring observation distance, so that an overlapped monitoring network is formed for the target asset, cross verification is realized, and the monitoring coverage rate needs to be satisfied that each physical asset is monitored by at least 3 or more robots simultaneously.
3. The method of claim 2, wherein the robot performs asset status supervision and observation through data fusion of a vision sensor and a laser radar, wherein the communication range is less than or equal to 10m, the supervision and observation distance is matched with the communication range so as to enable real-time supervision and coverage of observation and verification, the vision sensor adopts YOLOv algorithm to identify asset characteristic points and detect environment abnormal interferents, and the laser radar monitors asset position deviation through point cloud clustering.
4. The method of claim 1, wherein each data frame in the set of asset state data frames comprises { robot ID, timestamp, target asset identifier, self-supervision data, list of other robot supervision verification data in the cluster, supervision confidence score }, wherein performing a multi-view inconsistency analysis based on the set of asset state data frames stored in the blockchain to obtain the analysis result comprises: traversing an observation record of a neighbor robot of a target robot i aiming at the target robot i; For any one supervision robot j, calculating posterior probability of the object asset state and the consensus state in the cluster which are supervised and observed by the supervision robot j by adopting a dynamic Bayesian consensus algorithm, if the posterior probability is larger than a preset threshold value, marking the supervision robot j as a trusted node, otherwise marking the supervision robot j as an abnormal node; and determining an analysis result based on the number of the trusted nodes and the number of the abnormal nodes.
5. The method of claim 4, wherein determining the analysis result based on the number of trusted nodes and the number of abnormal nodes comprises: if the number of the abnormal nodes exceeds the number of the trusted nodes or the supervision confidence score is lower than the judicial evidence standard, judging that the analysis result is that the batch of supervision data is not trusted, triggering a source fraud alarm and stopping the digital asset casting process.
6. The method of claim 5, wherein dynamically adjusting the reputation value based on the analysis result comprises: if the analysis result of a certain robot node is judged to provide abnormal data, reducing the credit value of the node by delta by using a punishment coefficient alpha, otherwise, increasing the credit value by delta by using a rewarding coefficient beta, wherein delta is a preset adjustment parameter, and alpha > beta >0; If the reputation value is lower than the preset threshold value, the corresponding node is actively isolated, the supervision failure behavior of the corresponding node is recorded to the blockchain certificate, and the node is listed in a supervision blacklist.
7. The method of claim 6, wherein the method further comprises: the credit values of all robots are initialized to the same reference value; The preset threshold is a dynamic adjustable parameter; the isolated node enters the observation period and can participate in the supervision task again after system audit or manual rechecking, and the reputation value is reset according to the attenuation coefficient gamma when re-enqueuing.
8. A metauniverse digital asset source rights apparatus for robot cluster monitoring, characterized by performing the metauniverse digital asset source rights method for robot cluster monitoring as claimed in any one of claims 1 to 7, the apparatus comprising: The robot cluster monitoring module consists of a mobile robot carrying a vision sensor, a laser radar and HASHGRAPH nodes and is used for performing asset state supervision and observation and block chain data storage, and a judicial timestamp service is built in the module The encryption communication module is used for realizing asymmetric encryption and digital signature verification based on the ROS framework and executing encryption communication of the step S2; And the intelligent contract checking and verifying module is deployed in the blockchain network and is used for executing three-stage authenticity verification and reputation value management in the step S3, so that automatic combination rule checking of source data and digital asset casting authority control are realized.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements a method of meta-cosmic digital asset source validation for robot cluster monitoring as claimed in any of claims 1 to 7 when the computer program is executed by the processor.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the method of meta-cosmic digital asset source validation for robot cluster monitoring according to any of claims 1 to 7.

Description

Meta-universe digital asset source right determining method and equipment for robot cluster monitoring Technical Field The invention relates to the crossing field of intelligent robot technology and blockchain technology, in particular to a meta-universe digital asset source rights-determining method and equipment for robot cluster monitoring. Background With the deep development of metauniverse digital economy, ensuring that digital mapping of physical assets in metauniverse has judicial trusted sources becomes a core requirement. In the digital asset creation process, if part of data acquisition nodes generate a Bayesian behavior (such as uploading tampered data and lying asset states) due to hardware faults or malicious attacks, the trust basis of a digital asset system is directly destroyed, and the on-chain asset rights are disputed. The existing solution mainly relies on centralized institution authentication or fixed sensor data acquisition, and has the following technical problems: The scale of the trusted node needs to be preset, and the dynamic supervision capability and the self-adaptive fault tolerance mechanism are lacked; The source has weak anti-counterfeiting capability, and cannot realize real-time fraud detection and active defense linkage; the supervision dimension is single, and the multidimensional credible mapping and judicial traceability requirement of the meta-universe high-value asset are difficult to support; security vulnerabilities lack active defense mechanisms and source data integrity judicial evidence capabilities. Therefore, a scheme capable of automatically, decentralizing and actively performing authenticity verification and judicial curing on source data is needed to improve the robustness, expandability and judicial credibility of the source rights process of the metauniverse digital asset. Disclosure of Invention The embodiment of the invention provides a method, a device, computer equipment and a storage medium for determining the source of a metauniverse digital asset monitored by a robot cluster, so as to improve the robustness, the expandability and the judicial evidence effectiveness of the source of the metauniverse digital asset. In order to solve the technical problems, an embodiment of the present application provides a meta-universe digital asset source rights determining method for robot cluster monitoring, including: S1, constructing a hybrid monitoring architecture, namely supervising and observing the state of a target physical asset through a local sensor of each robot to obtain real-time supervision data, and uploading the real-time supervision data to a blockchain network for distributed storage, wherein the supervision data comprises self-collected data and associated verification data of other robots in a cluster; S2, establishing an encryption communication channel, namely realizing message transmission communication of real-time supervision data among robots by adopting an asymmetric encryption mechanism, wherein each robot generates a public key/private key pair, encrypting a message load by using a public key of a receiving party and generating a digital signature by using a private key of a transmitting party during message transmission communication, and S3, executing intelligent contract-driven three-stage fault detection: Firstly, extracting supervision data of all robots from a block chain distributed storage to generate an asset state data frame set; step two, performing multi-view inconsistency analysis based on the asset state data frame set stored by the block chain to obtain an analysis result; Step three, dynamically adjusting the reputation value of the data acquisition source according to the analysis result, and storing the reputation value into a blockchain; And S4, determining a source right determining result based on the reputation value, wherein the source right determining result is used as a judicial basis for casting the metauniverse digital asset. Optionally, in the step S1: the block chain network is formed by HASHGRAPH programs of each robot node to form a decentralised storage architecture; real-time supervision data in the robot cluster are transmitted through an encrypted communication channel and written into the blockchain; the communication range of each robot is the same as the monitoring observation distance, so that an overlapped monitoring network is formed for the target asset, cross verification is realized, and the monitoring coverage rate needs to be satisfied that each physical asset is monitored by at least 3 or more robots simultaneously. The method comprises the steps of enabling a robot to realize asset state supervision and observation through data fusion of a vision sensor and a laser radar, enabling a communication range to be less than or equal to 10m, enabling supervision and observation distance to be matched with the communication range, enabling each asset to be located in a common supervision s