CN-121979263-A - Six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recovery system

CN121979263ACN 121979263 ACN121979263 ACN 121979263ACN-121979263-A

Abstract

The invention discloses a six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recovery system, which belongs to the technical field of ship-borne unmanned aerial vehicle recovery and comprises the steps of collecting multiple types of data by an information collecting and intelligent networking module, constructing a network and unifying formats, constructing a model prediction trend by a motion prediction and confidence assessment module, calculating confidence and parallel transmitting data, realizing information interaction by a consensus decision and link reconstruction module, reconstructing a framework, adjusting equipment calibration postures by a dynamic compensation and posture calibration module, completing recovery and circulation preparation by a flexible recovery and circulation preparation module, solving the problems of data isomerism and the like by constructing a decentralized navigation intelligent network, improving the accuracy and timeliness of data processing, accurately correcting posture deviation by a machine-ship linkage regulation instruction generation algorithm and the like, improving the control accuracy by the whole flow cooperative design, realizing high-efficiency connection of recovery and the like, enhancing the operation flexibility and continuity of the system, forming a closed loop and improving the overall efficiency.

Inventors

GUAN GUAN
SHI ZHEHAO
JIN CHAOGUANG
MA MINGJUN
WU DONGQI

Assignees

大连理工大学

Dates

Publication Date: 20260505
Application Date: 20260211

Claims (10)

1. Six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recovery system is characterized in that the system comprises: The information acquisition and intelligent agent networking module acquires six-degree-of-freedom motion data of a ship and original perception data from a plurality of heterogeneous navigation sensors, completes parameter calibration and state self-checking of each navigation intelligent agent, constructs a decentralised navigation intelligent agent network and unifies data formats; The motion prediction and confidence assessment module is used for constructing a ship-machine cooperative dynamics model based on acquired data, predicting a ship motion trend, outputting data of each intelligent body based on the model, calculating the fusion confidence of each navigation intelligent body through a multi-dimensional dynamic confidence fusion algorithm, and transmitting a motion prediction result, intelligent body pose data and fusion confidence data in a linkage way; The consensus decision and link reconstruction module is used for receiving a motion prediction result, intelligent body pose data and fusion confidence coefficient data, realizing independent information interaction of all intelligent bodies through a weighted voting consensus algorithm based on the confidence coefficient, judging and eliminating failure nodes, dynamically reconstructing a navigation fusion framework, generating a fusion navigation instruction and calculating the average fusion confidence coefficient of all effective intelligent bodies; the dynamic compensation and gesture calibration module is used for adjusting the telescopic state of the actuating column of the six-degree-of-freedom dynamic compensation platform through a machine-ship linkage adjustment instruction generation algorithm by combining the fusion navigation instruction, the motion prediction result and the average fusion confidence coefficient, driving the intelligent mechanical arm to adjust the gesture of each joint and calibrating the position of the sliding rail; and the flexible recovery and circulation preparation module is used for receiving the docking speed data of the unmanned aerial vehicle and the pitch angle data of the ship body, adjusting the state of the magnetorheological damping device to realize unmanned aerial vehicle recovery, fixing the unmanned aerial vehicle through the electric control locking mechanism, starting the current compensation process and the load quick-change operation, and updating the initial state of the intelligent network and the data acquisition standard.
2. The six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recycling system is characterized in that parameter calibration of the information acquisition and intelligent agent networking module comprises millimeter wave array ranging zero calibration, visual unit fractal mark coordinate calibration, camera internal reference calibration and double IMU zero bias calibration, the calibration process is completed by data comparison with a standard attitude reference table, calibration records are generated and stored after calibration, a decentralised navigation intelligent agent network is constructed through an Ethernet switch, equipment identification, communication address and data type are bound when each intelligent agent node is registered, and hardware connection state, data transmission link connectivity and power supply stability of each node are detected in a network self-checking process.
3. The six-degree-of-freedom cooperative control ship-based unmanned aerial vehicle dynamic deck recovery system is characterized in that in the motion prediction and confidence assessment module, a ship-machine cooperative dynamic model is constructed by integrating dynamic characteristics of a ship and an unmanned aerial vehicle and comprises a ship dynamic sub-model, an unmanned aerial vehicle dynamic sub-model and a ship-machine coupling mechanism, the ship dynamic sub-model is based on a ship motion equation, comprises sea wave disturbance action and ship structural characteristics, inputs ship six-degree-of-freedom original motion data, outputs motion gesture change trend in a short time of the ship, the unmanned aerial vehicle dynamic sub-model is combined with quality, rotational inertia and pneumatic characteristic parameters of the unmanned aerial vehicle, inputs real-time flight state data of the unmanned aerial vehicle, outputs inertial response characteristic data of the unmanned aerial vehicle, the ship-machine coupling mechanism fuses output of the ship dynamic sub-model and output of the unmanned aerial vehicle dynamic sub-model in real time through a data synchronization interface, and constructs a unified dynamic mapping relation, and the model output data is used for calculation of fusion confidence and generation of motion prediction results.
4. The six-degree-of-freedom cooperatively controlled ship-borne unmanned aerial vehicle dynamic deck recovery system of claim 1, wherein in the motion prediction and confidence assessment module, the mathematical expression of the multidimensional dynamic confidence fusion algorithm is: wherein Is the first The navigation intelligent agent is at the moment Is used for the dynamic fusion of the confidence coefficient, 、、 In order to dynamically adapt the weights to be used, Is the first The self-base confidence of the individual navigation agents, Is the first The self-base confidence of the individual navigation agents, Is the first The number of adjacent active agents of the individual navigation agents, Is the first A neighborhood agent set of individual navigation agents, Is the first The navigation intelligent agent is at the moment The pose solving result of the model (a), Is the first The navigation intelligent agent is at the moment The pose solving result of the model (a), At the level of the minimum value of the total number of the components, The adaptation coefficients are for the ship body disturbance.
5. The six-degree-of-freedom cooperatively controlled ship-based unmanned aerial vehicle dynamic deck recycling system according to claim 1 is characterized in that in the consensus decision and link reconstruction module, timestamp alignment processing is firstly carried out after data are received, a system base time axis is used as a unified reference, time sequence deviation of different navigation agent data is corrected by adopting a linear interpolation method, a fusion confidence threshold value is set to be 0.3, for navigation agents with fusion confidence lower than the threshold value, the navigation agents are marked as suspected failure nodes and trigger a secondary confirmation flow, 3 adjacent navigation agents designated by the system respectively check data continuity of the suspected nodes in a latest preset time period and consistency of pose data and data of the check nodes, when all 3 check nodes are failed in feedback check, the nodes are judged to be failure nodes and are eliminated, when the navigation fusion architecture is reconstructed, when only a single navigation agent fails, the rest navigation agent occupies a new allocation weight according to the respective fusion confidence, the weight allocation sum is kept to be 1, when a plurality of navigation agents are subjected to the fusion confidence, the navigation agents with the fusion confidence of front 3 are preferentially extracted, and the core navigation agents with the fusion confidence of the navigation level is ranked to be 2.0.
6. The six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recycling system is characterized in that in the consensus decision and link reconstruction module, a weighted voting consensus algorithm based on credibility is implemented by actively sending self pose data, fusion confidence coefficient data and a data acquisition timestamp to all navigation agents in an adjacent domain in an information interaction stage, normalizing processing is carried out on the basis of fusion confidence coefficient of each navigation agent after each navigation agent receives the adjacent domain data to obtain voting weights of the corresponding neighborhood navigation agents, the sum of the voting weights of all the neighborhood navigation agents is 1, each navigation agent carries out voting on target pose parameters based on self calculation results and the neighborhood data, the voting results are multiplied by the corresponding weights to obtain weighted voting values, an invalid voting with the weighted voting values lower than 0.05 is removed in a statistics stage, the pose parameter consensus results are obtained by combining the pose results of all the effective navigation agents, and the fusion confidence coefficient average ratio fusion confidence coefficient of the navigation agents is calculated at the same time by combining the fusion confidence coefficient with the fusion average value generated high-precision navigation instruction.
7. The six-degree-of-freedom cooperatively controlled ship-borne unmanned aerial vehicle dynamic deck recovery system of claim 1, wherein in the dynamic compensation and attitude calibration module, the mathematical expression of the machine-ship linkage adjustment instruction generation algorithm is: wherein For the moment of time Is provided with a linkage adjustment instruction set, As a result of the confidence weighting coefficients, At time for all active navigation agents Is used to determine the average fusion confidence of the (c) in the (c), The gain is adjusted for a six-degree-of-freedom dynamic compensation platform, For the moment of time Is characterized by that the attitude deviation of lifting reference plane, The gain is adjusted for the gesture of the intelligent mechanical arm, For the moment of time The alignment deviation of the center line of the slide rail and the flight vector of the unmanned plane, The correction factors are adapted to the sea conditions, For the moment of time Is used for controlling the docking speed deviation of the unmanned aerial vehicle, As the time-varying amount of the speed deviation, For the moment of time Is a real-time value of the ship pitch angle.
8. The six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recovery system is characterized in that in the dynamic compensation and posture calibration module, an improved parallel configuration is adopted by a six-degree-of-freedom dynamic compensation platform, an upper end plate and a lower end plate are of symmetrical rigid structures, an actuating column is connected with the upper end plate and the lower end plate through spherical joints, the actuating column is arranged in a pairwise crossed symmetrical mode to form a space triangle configuration, the actuating column is controlled to stretch out and draw back through a servo driving unit, an intelligent mechanical arm adopts a serial configuration and comprises a rotary joint, a front end stretching mechanism and an auxiliary fine tuning joint, the sliding rail posture is adjusted through multi-joint cooperative action, the sliding rail calibration process receives feedback data of a visual sensor in real time, when deviation between a sliding rail center line and an unmanned aerial vehicle flight vector is detected, fine tuning parameters are recalculated immediately based on a linkage adjustment instruction, and secondary posture correction is started, so that the sliding rail and an unmanned aerial vehicle flight path is kept matched.
9. The six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recycling system is characterized in that in the flexible recycling and circulating preparation module, a magnetorheological damping device is formed by a magnetorheological fluid cavity and a carbon fiber beam Duan Goucheng and is arranged in a specific section at the tail end of a sliding rail, the magnetorheological fluid viscosity is changed by adjusting the magnetic field strength, an electric control locking mechanism comprises an electromagnetic lock and a mechanical locating pin, the unmanned aerial vehicle is primarily fixed through the electromagnetic lock after being stationary, secondary limiting is carried out through the mechanical locating pin, and a locking state is detected through a sensor after locking.
10. The six-degree-of-freedom cooperatively controlled shipboard unmanned aerial vehicle dynamic deck recovery system of claim 1, wherein in the flexible recovery and circulation preparation module, a load quick-change interface adopts a modularized structure and comprises a power busbar, a data bus and a mechanical positioning structure, a load tray replacement functional module is pulled out during load replacement, and is automatically guided to align through the mechanical positioning structure after being pushed back, so that the power and the data interface are synchronously docked, and the whole replacement process does not need system outage.

Description

Six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recovery system Technical Field The invention belongs to the technical field of ship-borne unmanned aerial vehicle recovery, and particularly relates to a six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recovery system. Background The combination of the multi-agent cooperative control technology and the visual perception and multi-source navigation data fusion technology becomes an important development direction of the field of civil and military offshore operation, the cooperative operation of a ship and an unmanned aerial vehicle can greatly expand the coverage range and execution efficiency of offshore tasks, the multi-agent cooperative control technology plays a key role in tasks such as offshore reconnaissance, environment monitoring and communication relay, the offshore environment has complex and changeable disturbance characteristics, the ship can generate multi-degree-of-freedom motion, the flying posture of the unmanned aerial vehicle is easily influenced by sea wind and sea waves, strict requirements are provided for motion matching, navigation accuracy and recovery reliability between the ship and the unmanned aerial vehicle, various sensing devices such as millimeter wave arrays, visual units and navigation modules are required to be integrated to ensure the stability of cooperative operation, the data processing, decision generation and execution control are realized through cooperative interaction between the ship and the unmanned aerial vehicle, currently, the related technologies are evolving towards the direction of multi-source data integration and intelligent decision, but the problems such as disturbance adaptation, data synchronization and cooperative response speed brought by the complex working conditions at sea still need to meet the requirements of a more sophisticated technical scheme, and high-reliability cooperative operation requirements are solved. The traditional ship and unmanned aerial vehicle cooperative control system mostly adopts a centralized network architecture, decision and data transmission excessively depend on a core node, once the core node fails or a link is disturbed, the operation stability of the whole system can be seriously affected, even the cooperative operation is interrupted, in a data processing link, the original data of different sensing devices lack unified calibration standards and format specifications, the data consistency is difficult to ensure, the fusion mode of multi-source data is simpler, the dynamic change of the states and the environment disturbance of the devices cannot be fully considered, the accuracy of a navigation decision is insufficient, a confidence evaluation mechanism is insufficient, the data validity is judged only by a single dimension, the low-reliability data is difficult to effectively reject, the scientificity of the cooperative decision is further affected, dynamic compensation and attitude calibration link lack of deep linkage with the navigation data and the environment disturbance is realized, the response is delayed, the real-time motion change of the ship and the unmanned aerial vehicle cannot be quickly adapted, furthermore, the unmanned aerial vehicle recovery process lacks effective flexible buffer mechanism, the reliability of a fixed mode is insufficient, the load system operation is required to be interrupted, the continuity and the operation are seriously affected, and the whole system is difficult to adapt to the requirements of the cooperative operation under the complex sea environment. Disclosure of Invention The invention aims to make up the defects of the prior art, provides a six-degree-of-freedom cooperative control ship-borne unmanned aerial vehicle dynamic deck recovery system, integrates multisource perception data to construct a decentralization network, realizes motion prediction and reliability assessment through a ship-machine cooperative dynamics model and a multidimensional confidence fusion algorithm, completes decision and link dynamic reconstruction by means of a weighted voting consensus algorithm, realizes accurate dynamic compensation and attitude calibration by combining a machine-ship linkage adjustment mechanism, and combines flexible recovery, locking fixation and load quick change functions, so that the system can dynamically adapt to complex disturbance at sea, solves the problems of data isomerism, response lag, insufficient operation continuity and the like in the traditional cooperative control, realizes high-precision and high-reliability cooperation in offshore tasks, and remarkably improves the operation efficiency and environmental adaptability. The invention provides a six-degree-of-freedom cooperatively controlled ship-borne unmanned aerial vehicle dynamic deck recovery system for solving the technical problems, which comprises the follow