A high-precision space GNC full-physical simulation test platform and experimental method

Abstract

The application belongs to the technical field of spacecraft ground simulation test, and discloses a high-precision space GNC full-physical simulation test platform, which is composed of a three-dimensional motion execution system, a distributed real-time control system, a capture interaction simulation system, a safety protection system and a three-dimensional motion simulation and path planning system, and through integration of a three-dimensional orbital large-range motion execution system and a double-grating scale closed-loop detection structure, the simulation motion range is significantly expanded, the technical bottleneck of the existing platform limited to a single shaft, a two-dimensional slide rail and a limited motion amplitude is broken through, the platform realizes high-precision cooperation of a motion control system and an orbit system, can satisfy space high-dynamic motion simulation of a large-size, high-inertia complex target, through integrated design of the capture interaction simulation system, supports autonomous tracking of a target flight path, flexible capture of a flying claw and verification of small multi-degree-of-freedom control, and can effectively simulate complex tasks such as space rendezvous and docking, target capture and micro-force control.

Description

Technical Field

[0001] This invention belongs to the field of spacecraft ground simulation and testing technology, specifically a high-precision space GNC full physical simulation test platform and experimental method. Background Technology

[0002] Existing space GNC simulation verification technologies mainly rely on single-dimensional motion platforms or distributed simulation architectures. Due to limitations in equipment structure and control capabilities, they generally suffer from narrow motion range, lag in dynamic response, and insufficient system synchronization accuracy. In particular, when facing scenarios such as space rendezvous and docking and high-speed motion capture of large-sized, high-inertia complex targets, existing simulation platforms struggle to achieve continuous, large-scale, and highly dynamic physical closed-loop verification in three-dimensional space, severely restricting the authenticity and effectiveness of ground simulation experiments.

[0003] While the currently widely used single-axis air-bearing platforms, two-dimensional sliding rail systems, and six-degree-of-freedom platforms can complete local motion simulations, the control logic between each system is dispersed and the motion range is limited. They cannot meet the requirements of large-stroke, high-synchronization, and high-precision motion simulation in real space environments, resulting in a large deviation between experimental results and actual on-orbit operations.

[0004] In addition, existing simulation platforms lack an integrated design for motion and target capture interaction, and cannot effectively support dynamic capture of complex paths, micro-force manipulation, and high-precision interactive verification. Summary of the Invention

[0005] The purpose of this invention is to provide a high-precision spatial GNC full physical simulation test platform and experimental method to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a high-precision spatial GNC full physical simulation test platform, which consists of a three-dimensional motion execution system, a distributed real-time control system, a capture and interactive simulation system, a safety protection system, and a three-dimensional motion simulation and path planning system;

[0007] Three-dimensional motion execution system: Based on a steel rail track, P43 steel rails with hydraulic buffer limiters are used in the X and Y directions, driven by gear rack and screw, with closed-loop detection by dual grating rulers and a gravity unloading mechanism to provide basic motion support for the simulation platform;

[0008] Distributed real-time control system: including ground control console, dual redundant servo controller (FPGA+DSP architecture, cycle <1ms), EtherCAT bus node (synchronization error <500μs) and motion monitoring unit, driving three-axis synchronous motion;

[0009] Capture and Interactive Simulation System: Includes a grappling capture device (flexible claws, travel ≥3 meters), a multi-degree-of-freedom control device, and a situational awareness and multi-dimensional measurement simulator, used for space target capture and micro-force control verification;

[0010] Safety protection system: Equipped with dual redundant emergency stop circuit, dynamic interference detection module, hydraulic buffer limit (stroke ≥50mm) and anti-tipping structure, real-time monitoring of movement to ensure safety;

[0011] 3D motion simulation and path planning system: includes 3D modeling (supports .STP and other formats), path planning, interference detection modules, and motion backtracking optimization function to realize modeling, planning and data backtracking;

[0012] Preferably, the three-dimensional motion execution system includes:

[0013] (1) Track structure and drive mechanism: Based on the rail type track structure, rigid heavy P43 steel rails are used in the X and Y directions. The hydraulic buffer limiter at the end ensures the safety of operation. In the gear rack and screw drive mechanism, the servo motor is connected by a rigid coupling and the planetary reducer drives the track. Its motion follows the track drive kinematic model that combines the relationship between speed, displacement and time. The screw is responsible for vertical motion and provides stable basic motion support for the system.

[0014] The formula for the orbital-driven kinematic model is as follows:

[0015]

[0016] In the formula, S: displacement (unit: m), v: initial velocity (unit: m / s), a: acceleration (unit: m / s2), t: motion time (unit: s), which guides the real-time track motion control;

[0017] It can ensure accurate displacement calculation during three-axis motion, support position prediction during high-speed motion, and improve the real-time response capability of overall motion control; three-dimensional orbital motion is driven by a rigid structure, and the motion displacement can be quickly calculated using basic kinematic formulas, which helps to plan the motion trajectory in advance and carry out safety protection, especially suitable for motion platforms with long stroke and large inertia.

[0018] (2) Detection and unloading mechanism: The dual grating ruler closed-loop detection device collects X, Y and Z axis position and speed signals in real time through dual channels and feeds them back to the motion control system for precise control. The gravity unloading wire rope mechanism uses pulley blocks to reduce the vertical load according to the force and motion relationship in the track drive kinematic model. It works in two sections to effectively reduce the vertical motion load and improve the system's operating efficiency and stability.

[0019] Preferably, the distributed real-time control system includes:

[0020] (1) Control core architecture: The ground control console serves as the central hub, integrating a high-performance industrial computer, fiber optic reflective memory card interface and real-time operating system. The dual redundant servo motion controller adopts an FPGA+DSP architecture, with a motion control cycle of less than 1ms. Its regulation follows the correlation logic between feedback and command in the servo motor speed closed-loop control model, providing a precise drive core for three-axis synchronous motion.

[0021] The formula for the closed-loop speed control model of a servo motor is as follows:

[0022]

[0023] In the formula, v out (t): Controller output speed command (unit: m / s), v ref (t): Reference velocity (unit: m / s), v meas (t): Actual measured velocity (unit: m / s), K p Speed ​​loop proportional coefficient, K i The velocity loop integral coefficient ensures motion tracking accuracy.

[0024] Real-time closed-loop control of servo motor speed in a 3D motion platform is achieved, effectively reducing motion deviation and improving path following accuracy. Speed ​​loop proportional-integral control is the general control basis of servo systems. Combined with feedback speed, it can achieve low-latency, high-precision real-time motion control, which is suitable for the multi-axis synchronous motion requirements of distributed motion platforms.

[0025] (2) Distributed synchronization and monitoring: EtherCAT bus nodes realize distributed synchronous control, with node clock synchronization error less than 500μs, ensuring coordination accuracy. The motion monitoring unit collects multiple parameters of the motor through the servo driver, and combines the parameter association logic in the speed closed-loop control model to provide data support for real-time system adjustment, ensuring efficient synchronization of three-axis motion.

[0026] Preferably, the capture interaction simulation system includes:

[0027] (1) Capture execution device: The flexible claw is driven by three ropes and synchronous belts, with a nitrile rubber buffer layer on the surface and a telescopic stroke of more than 3 meters. Its capture follows the correlation logic between force and contact state in the grappling capture mechanics model. It is a small multi-degree-of-freedom control device, with a six-degree-of-freedom servo motor driving the robotic arm. It is equipped with a joint torque sensor, and the clamping force and stroke range are clearly defined, which can accurately perform the control.

[0028] The gripping force of the grappling hook is adjusted in real time based on the target mass and relative acceleration to ensure stable gripping and no damage to the target during dynamic capture.

[0029] When capturing a moving target, the grappling hook needs to calculate the clamping force in real time to prevent insufficient clamping that would cause the target to slip out, and also to prevent excessive clamping that would cause the target to be damaged. The coupling of clamping force and motion state is an important safety control parameter of the dynamic capture system.

[0030] (2) Perception and Measurement System: The situational awareness simulator integrates a 64-line lidar and vision unit to capture the position and attitude of the flying target in real time. The six-axis force sensor of the multi-dimensional measurement simulator collects contact data and updates at a frequency of no less than 1000Hz, providing data support for capture and control verification.

[0031] Preferably, the security protection system includes:

[0032] (1) Core safety control mechanism: Dual redundant emergency stop circuit independently controls dual-loop servo power supply to ensure reliable shutdown in emergency situations. The dynamic interference detection module is based on bounding box algorithm, calculates the safe distance between the path and surrounding equipment according to the correlation between distance and motion parameters in the real-time minimum safe distance model, monitors the motion status in real time and dynamically adjusts the path.

[0033] The formula for the real-time minimum safe distance model is:

[0034]

[0035] In the formula, d min : Current minimum safe distance (unit: m), (x1, y1, z1): Current center point coordinates of the motion platform (unit: m), (x2, y2, z2): Coordinates of the nearest point of the surrounding equipment (unit: m);

[0036] Real-time monitoring of the minimum safe distance between the motion platform and surrounding equipment, timely triggering obstacle avoidance or stopping to prevent mechanical collisions during motion;

[0037] Real-time 3D safety distance detection is crucial for the protection of motion platforms. By using the bounding box distance formula, safety judgments can be made quickly during high-speed movement, making it particularly suitable for obstacle avoidance control in complex paths and dynamic environments.

[0038] (2) Protective structure guarantee: The hydraulic buffer limit structure has a buffer stroke of not less than 50mm, which can effectively absorb impact energy. The anti-overturning guide structure includes double wheel side guide and side wheel limit frame. Combined with the spatial constraint logic of the real-time minimum safety distance model, it provides multiple safety guarantees for the system and ensures stable and safe movement.

[0039] Preferably, the three-dimensional motion simulation and path planning system includes:

[0040] (1) Modeling and Path Planning Module: The 3D modeling module supports the import of 3D models in various formats, providing basic model support for the system. The path planning module adopts the priority path search algorithm and the inverse motion constraint solution method. Its calculation follows the multi-factor trade-off logic in the priority cost function of path planning, and can accurately calculate the real-time motion path to meet the system's motion planning requirements.

[0041] The principle of the path planning priority cost function is expressed by the following formula:

[0042] C total =w d ·d p +w v ·v p +w a ·a p

[0043] In the formula, C total : The current path value, d p Path length (in meters), v p Path velocity change (unit: m / s), a p Path acceleration change (unit: m / s²), w d ,w v ,w a These are the weighting coefficients for distance, velocity, and acceleration, respectively.

[0044] During path planning, path length, speed changes, and acceleration changes are dynamically and comprehensively considered. The optimal path is calculated by weighting priorities to improve path smoothness and motion efficiency.

[0045] Multi-objective path planning meets the engineering requirements of complex motion control systems. By adjusting the weights, it can adapt to different motion conditions and is particularly suitable for high dynamic capture and simulation platforms.

[0046] (2) Interference detection and data backtracking module: The interference detection module calculates the safety distance through the bounding box real-time collision detection algorithm to ensure motion safety. The motion backtracking and parameter optimization module can record historical paths and adjust parameters. Combined with the optimization idea of ​​path planning priority cost function, motion data backtracking and parameter optimization are realized to improve system performance.

[0047] This invention also provides the following technical solution: a high-precision spatial GNC full-physics simulation experimental method, which is based on the above-mentioned system, and the specific steps of the method are as follows:

[0048] S1: Platform initialization, start the three-dimensional motion execution system, the motion control system completes the zero point calibration of the X, Y and Z axes in sequence through the dual grating rulers, collects the current and position signals of the servo motor in real time, the three-dimensional motion simulation system imports the flight path data, and completes time synchronization with the control system through the fiber optic reflection memory card;

[0049] S2: Path loading and motion execution. The ground control console loads the target flight path. The motion control system generates servo motor motion commands based on the simulated path and drives the three-axis synchronous motion through the EtherCAT bus. The capture and interactive simulation system follows the motion path in real time to execute the extension and retraction of the grappling hook and the trajectory of the robotic arm. The safety protection system monitors the motion status and interference distance in real time. The motion control system dynamically adjusts the servo input through the model predictive control algorithm to achieve dynamic load synchronous compensation.

[0050] S3: Target Acquisition and Interactive Simulation. The situational awareness simulator tracks the flying target in real time based on LiDAR point cloud data and visual recognition images. The grappling hook acquisition device autonomously acquires the target according to the trajectory feedback from the motion control system. The small multi-degree-of-freedom control device performs micro-force control in real time. The three-dimensional motion simulation system calculates the path safety distance in real time and performs motion data backtracking. If the minimum safety distance is detected to be insufficient, the safety protection system issues path adjustment or stop commands through the motion control system.

[0051] Preferably, in the platform initialization phase of S1, the three-dimensional motion execution system is first started. The motion control system uses a dual-grating ruler closed-loop detection device to sequentially complete the zero-point calibration of the X, Y, and Z axes to ensure the accuracy of the motion reference. At the same time, the system collects key signals such as the current and position of the servo motor in real time to achieve dynamic monitoring. The three-dimensional motion simulation system synchronously imports the flight path data and achieves time synchronization with the motion control system through the fiber optic reflection memory card interface of the ground control console. This lays a unified timing foundation for subsequent motion modeling, path planning, and real-time interference detection, ensuring the consistency and accuracy of the entire platform's collaborative operation.

[0052] Preferably, the specific steps of path loading and motion execution in S2 are as follows:

[0053] S21, Path Loading and Driving: The ground control console loads the target flight path, the motion control system generates servo motor motion commands according to the simulated path, drives the three-axis synchronous motion via EtherCAT bus, captures the interactive simulation system to follow in real time, and executes the extension and retraction of the grappling hook and the trajectory of the robotic arm. Its regulation incorporates the dynamic adjustment logic of the model predictive control motion correction model.

[0054] The formula for the model predictive control motion correction model is as follows:

[0055]

[0056] In the formula, u(t): current control input (servo command), y(t+k|t): predicted future motion trajectory, r(t+k): desired reference trajectory, N p Prediction step size; Q, R: State weight matrix and control weight matrix;

[0057] During motion execution, servo commands are dynamically adjusted based on predictions of future motion trajectories to compensate for path deviations in advance and achieve high-precision following.

[0058] S22, Motion Control and Protection: The safety protection system monitors the motion status and interference distance in real time. The motion control system adopts a model predictive control algorithm, dynamically adjusting the servo input according to the correlation between the error and the adjustment amount in the motion correction model, realizing synchronous compensation of dynamic load, ensuring accurate and safe motion, and ensuring stable and reliable execution process.

[0059] Preferably, in S3, target acquisition and interactive simulation refers to the use of a situational awareness simulator to track the flying target in real time with the help of lidar point cloud data and visual recognition images. The grappling hook acquisition device autonomously completes target acquisition based on the trajectory fed back by the motion control system. The small multi-degree-of-freedom control device synchronously performs micro-force control. The three-dimensional motion simulation system calculates the path safety distance in real time and backtracks the motion data. Once the minimum safety distance is detected to be insufficient, the safety protection system immediately issues path adjustment or stop commands through the motion control system to ensure that the entire acquisition and control process is safe and controllable.

[0060] The formula for representing point cloud data is:

[0061]

[0062] In the formula, T: target current attitude transformation matrix, p i : Point cloud coordinates measured by the sensor, q i : Coordinates of the reference point of the target model, n: Number of point cloud data.

[0063] The beneficial effects of this invention are as follows:

[0064] 1. This invention significantly expands the simulation motion range by integrating a three-dimensional track-type large-range motion execution system with a dual-grating ruler closed-loop detection structure. It breaks through the technical bottleneck of existing platforms that are limited by single-axis, two-dimensional slide rails and limited motion amplitude. The platform achieves high-precision coordination between the motion control system and the track system, and can meet the spatial high-dynamic motion simulation of large-size, high-inertia complex targets. The overall motion simulation capability is significantly better than the existing technology.

[0065] 2. This invention, through the integrated design of a capture-interactive simulation system, supports autonomous tracking of target flight paths, flexible capture by grappling hooks, and verification of small-scale multi-degree-of-freedom manipulation. It can effectively simulate complex tasks such as space rendezvous and docking, target capture, and micro-force manipulation. The platform supports target recognition based on point cloud data and visual fusion, dynamic path adjustment, and multi-dimensional force control interaction, solving the problem that existing simulation platforms cannot complete high-dynamic target capture and real-time interactive verification, and significantly improving the ground verification capability and simulation realism of complex space tasks.

[0066] 3. The present invention adopts a fully physical closed-loop design through the simulation platform provided. It achieves highly synchronous and real-time closed-loop control of motion path planning, target acquisition, interactive control and safety protection through bidirectional coupling of distributed real-time control system and motion simulation system, coupled with dual redundant safety protection system. The control cycle is less than 1ms. The system has a high safety redundancy design, monitors motion status and safety distance in real time, and has the ability to avoid obstacles and correct paths in case of sudden working conditions. It provides a stable, safe and reliable simulation experimental environment for high-risk space missions. Attached Figure Description

[0067] Figure 1 This is a flowchart of the high-precision spatial GNC full-physics simulation test platform of the present invention;

[0068] Figure 2 This is a flowchart of the high-precision spatial GNC full physical simulation test method of the present invention. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] like Figures 1 to 2 As shown, this embodiment of the invention provides a high-precision spatial GNC full-physics simulation test platform, which consists of a three-dimensional motion execution system, a distributed real-time control system, a capture and interactive simulation system, a safety protection system, and a three-dimensional motion simulation and path planning system;

[0071] Example of a 3D motion execution system: The 3D motion execution system adopts an industrial-grade track structure. The X and Y direction tracks use P43 heavy-duty steel rails, with each track being 20 meters and 15 meters long respectively. Hydraulic buffer limiters with a stroke greater than 50mm are installed at the ends of the tracks. The servo motor is a Panasonic MSMF042L1 U2M model, which, together with a planetary reducer, drives the gear rack through a rigid coupling, with a transmission backlash of less than 0.02mm. The Z-axis vertical motion is supported by a ball screw and a double-guide rail slider. The ball screw drive motor has a power of 1.5kW. The position detection uses a Heidenhain brand dual-channel absolute grating ruler with a resolution of 0.01mm, which collects motion position signals in real time and feeds them back to the control system. The gravity unloading mechanism uses a Ф3mm steel wire rope pulley block, and the vertical motion unloading is achieved through a pre-tensioned counterweight design.

[0072] Distributed Real-Time Control System Example: The ground control console uses an ADLINK industrial control computer equipped with an RTX real-time operating system and a fiber optic reflective memory card for high-speed data exchange; the motion controller uses a Beckhoff C6670 dual-redundant servo motion controller with a control cycle of less than 1ms; the control nodes form a global synchronization network via an EtherCAT bus with a node synchronization error better than 500μs; the motion monitoring unit collects motor current, voltage, speed, and acceleration information in real time through sensors integrated into the servo driver, and transmits the monitoring data back to the motion controller in real time for motion status feedback and closed-loop adjustment;

[0073] Example of a capture-interactive simulation system: The grappling hook capture device uses a flexible gripper driven by three synchronous belts. The gripper surface is covered with a 2mm thick nitrile rubber buffer pad. The gripper's extension stroke is designed to be 3.5 meters. The entire grappling hook is connected to the motion platform through a slider structure. The situational awareness simulator uses a RoboSense 64-line LiDAR and a Basler industrial camera. The LiDAR refresh rate is 20Hz, and it collects target path information in real time. The multi-dimensional measurement simulator uses an ATI brand six-axis force sensor with a force measurement range of ±600N and a torque measurement range of ±15Nm. The data sampling frequency is 1000Hz.

[0074] Safety protection system implementation example: The safety protection system establishes a dual-redundant emergency stop circuit through Beckhoff safety control modules. The servo power supply independently controls the dual-circuit emergency power-off channels. The dynamic interference detection module communicates in real time with the motion controller through the embedded bounding box real-time collision detection software. The safety distance warning threshold is set to 100mm. If it is lower than the threshold, a path adjustment or emergency stop command is immediately issued. The hydraulic buffer limit structure adopts FESTO hydraulic buffers with a buffer stroke of 50mm. The buffer load can withstand the impact at the platform's highest operating speed. The anti-tipping guide structure prevents lateral instability of the motion platform through dual-wheel side guides and slide rail limit frames.

[0075] Example of a 3D motion simulation and path planning system: The 3D motion simulation system is built on MATLAB / Simulink, supporting the import of CATIA and UGNX models in .STP and .OBJ formats; the path planning module adopts a priority path search algorithm and inverse kinematics method, and the path planning software supports real-time calculation of path velocity and acceleration constraints; the interference detection module integrates a fast bounding box collision detection algorithm with a collision detection refresh rate of less than 20ms; the motion data backtracking module supports full-process path recording and parameter playback, supports exporting path optimization and adjustment results, and provides real-time feedback to the motion control system.

[0076] The three-dimensional motion execution system includes:

[0077] (1) Track structure and drive mechanism: Based on the rail type track structure, rigid heavy P43 steel rails are used in the X and Y directions. The hydraulic buffer limiter at the end ensures the safety of operation. In the gear rack and screw drive mechanism, the servo motor is connected by a rigid coupling and the planetary reducer drives the track. Its motion follows the track drive kinematic model that combines the relationship between speed, displacement and time. The screw is responsible for vertical motion and provides stable basic motion support for the system.

[0078] The formula for the orbital-driven kinematic model is as follows:

[0079]

[0080] In the formula, S: displacement (unit: m), v: initial velocity (unit: m / s), a: acceleration (unit: m / s2), t: motion time (unit: s), which guides the real-time track motion control;

[0081] (2) Detection and unloading mechanism: The dual grating ruler closed-loop detection device collects X, Y and Z axis position and speed signals in real time through dual channels and feeds them back to the motion control system for precise control. The gravity unloading wire rope mechanism uses pulley blocks to reduce the vertical load according to the force and motion relationship in the track drive kinematic model. It works in two sections to effectively reduce the vertical motion load and improve the system's operating efficiency and stability.

[0082] The distributed real-time control system includes:

[0083] (1) Control core architecture: The ground control console serves as the central hub, integrating a high-performance industrial computer, fiber optic reflective memory card interface and real-time operating system. The dual redundant servo motion controller adopts an FPGA+DSP architecture, with a motion control cycle of less than 1ms. Its regulation follows the correlation logic between feedback and command in the servo motor speed closed-loop control model, providing a precise drive core for three-axis synchronous motion.

[0084] The formula for the closed-loop speed control model of a servo motor is as follows:

[0085]

[0086] In the formula, v out (t): Controller output speed command (unit: m / s), v ref (t): Reference velocity (unit: m / s), v meas (t): Actual measured velocity (unit: m / s), K p Speed ​​loop proportional coefficient, K i The velocity loop integral coefficient ensures motion tracking accuracy.

[0087] (2) Distributed synchronization and monitoring: EtherCAT bus nodes realize distributed synchronous control, with node clock synchronization error less than 500μs, ensuring coordination accuracy. The motion monitoring unit collects multiple parameters of the motor through the servo driver, and combines the parameter association logic in the speed closed-loop control model to provide data support for real-time system adjustment, ensuring efficient synchronization of three-axis motion.

[0088] The capture-interactive simulation system includes:

[0089] (1) Capture execution device: The flexible claw is driven by three ropes and synchronous belts, with a nitrile rubber buffer layer on the surface and a telescopic stroke of more than 3 meters. Its capture follows the correlation logic between force and contact state in the grappling capture mechanics model. It is a small multi-degree-of-freedom control device, with a six-degree-of-freedom servo motor driving the robotic arm. It is equipped with a joint torque sensor, and the clamping force and stroke range are clearly defined, which can accurately perform the control.

[0090] (2) Perception and Measurement System: The situational awareness simulator integrates a 64-line lidar and vision unit to capture the position and attitude of the flying target in real time. The six-axis force sensor of the multi-dimensional measurement simulator collects contact data and updates at a frequency of no less than 1000Hz, providing data support for capture and control verification.

[0091] Among them, the security protection system includes

[0092] (1) Core safety control mechanism: Dual redundant emergency stop circuit independently controls dual-loop servo power supply to ensure reliable shutdown in emergency situations. The dynamic interference detection module is based on bounding box algorithm, calculates the safe distance between the path and surrounding equipment according to the correlation between distance and motion parameters in the real-time minimum safe distance model, monitors the motion status in real time and dynamically adjusts the path.

[0093] The formula for the real-time minimum safe distance model is:

[0094]

[0095] In the formula, dmin : Current minimum safe distance (unit: m), (x1, y1, z1): Current center point coordinates of the motion platform (unit: m), (x2, y2, z2): Coordinates of the nearest point of the surrounding equipment (unit: m);

[0096] (2) Protective structure guarantee: The hydraulic buffer limit structure has a buffer stroke of not less than 50mm, which can effectively absorb impact energy. The anti-overturning guide structure includes double wheel side guide and side wheel limit frame. Combined with the spatial constraint logic of the real-time minimum safety distance model, it provides multiple safety guarantees for the system and ensures stable and safe movement.

[0097] The 3D motion simulation and path planning system includes:

[0098] (1) Modeling and Path Planning Module: The 3D modeling module supports the import of 3D models in various formats, providing basic model support for the system. The path planning module adopts the priority path search algorithm and the inverse motion constraint solution method. Its calculation follows the multi-factor trade-off logic in the priority cost function of path planning, and can accurately calculate the real-time motion path to meet the system's motion planning requirements.

[0099] The principle of the path planning priority cost function is expressed by the following formula:

[0100] C total =w d ·d p +w v ·v p +w a ·a p

[0101] In the formula, C total : The current path value, d p Path length (in meters), v p Path velocity change (unit: m / s), a p Path acceleration change (unit: m / s²), w d ,w v ,w a These are the weighting coefficients for distance, velocity, and acceleration, respectively.

[0102] (2) Interference detection and data backtracking module: The interference detection module calculates the safety distance through the bounding box real-time collision detection algorithm to ensure motion safety. The motion backtracking and parameter optimization module can record historical paths and adjust parameters. Combined with the optimization idea of ​​path planning priority cost function, motion data backtracking and parameter optimization are realized to improve system performance.

[0103] This invention also provides a high-precision spatial GNC full-physics simulation experimental method, based on the aforementioned high-precision spatial GNC full-physics simulation experimental platform, and the specific steps of the method are as follows:

[0104] S1: Platform initialization, start the three-dimensional motion execution system, the motion control system completes the zero point calibration of the X, Y and Z axes in sequence through the dual grating rulers, collects the current and position signals of the servo motor in real time, the three-dimensional motion simulation system imports the flight path data, and completes time synchronization with the control system through the fiber optic reflection memory card;

[0105] S2: Path loading and motion execution. The ground control console loads the target flight path. The motion control system generates servo motor motion commands based on the simulated path and drives the three-axis synchronous motion through the EtherCAT bus. The capture and interactive simulation system follows the motion path in real time to execute the extension and retraction of the grappling hook and the trajectory of the robotic arm. The safety protection system monitors the motion status and interference distance in real time. The motion control system dynamically adjusts the servo input through the model predictive control algorithm to achieve dynamic load synchronous compensation.

[0106] S3: Target Acquisition and Interactive Simulation. The situational awareness simulator tracks the flying target in real time based on LiDAR point cloud data and visual recognition images. The grappling hook acquisition device autonomously acquires the target according to the trajectory feedback from the motion control system. The small multi-degree-of-freedom control device performs micro-force control in real time. The three-dimensional motion simulation system calculates the path safety distance in real time and performs motion data backtracking. If the minimum safety distance is detected to be insufficient, the safety protection system issues path adjustment or stop commands through the motion control system.

[0107] In the S1 platform initialization phase, the three-dimensional motion execution system is first started. The motion control system uses a dual-grating ruler closed-loop detection device to complete the zero-point calibration of the X, Y, and Z axes in sequence to ensure the accuracy of the motion reference. At the same time, the system collects key signals such as the current and position of the servo motors in real time to achieve dynamic monitoring. The three-dimensional motion simulation system synchronously imports the flight path data and achieves time synchronization with the motion control system through the fiber optic reflection memory card interface of the ground control console. This lays a unified timing foundation for subsequent motion modeling, path planning, and real-time interference detection, ensuring the consistency and accuracy of the entire platform's collaborative operation.

[0108] The specific steps for path loading and motion execution in S2 are as follows:

[0109] S21, Path Loading and Driving: The ground control console loads the target flight path, the motion control system generates servo motor motion commands according to the simulated path, drives the three-axis synchronous motion via EtherCAT bus, captures the interactive simulation system to follow in real time, and executes the extension and retraction of the grappling hook and the trajectory of the robotic arm. Its regulation incorporates the dynamic adjustment logic of the model predictive control motion correction model.

[0110] The formula for the model predictive control motion correction model is as follows:

[0111]

[0112] In the formula, u(t): current control input (servo command), y(t+k|t): predicted future motion trajectory, r(t+k): desired reference trajectory, N p Prediction step size; Q, R: State weight matrix and control weight matrix;

[0113] S22, Motion Control and Protection: The safety protection system monitors the motion status and interference distance in real time. The motion control system adopts a model predictive control algorithm, dynamically adjusting the servo input according to the correlation between the error and the adjustment amount in the motion correction model, realizing synchronous compensation of dynamic load, ensuring accurate and safe motion, and ensuring stable and reliable execution process.

[0114] Among them, the target acquisition and interactive simulation in S3 refers to the real-time tracking of flying targets by using LiDAR point cloud data and visual recognition images through a situational awareness simulator. The grappling hook acquisition device autonomously completes target acquisition based on the trajectory fed back by the motion control system. The small multi-degree-of-freedom control device synchronously performs micro-force control. The three-dimensional motion simulation system calculates the path safety distance in real time and backtracks the motion data. Once the minimum safety distance is detected to be insufficient, the safety protection system immediately issues path adjustment or stop commands through the motion control system to ensure that the entire acquisition and control process is safe and controllable.

[0115] The formula for representing point cloud data is:

[0116]

[0117] In the formula, T: target current attitude transformation matrix, p i : Point cloud coordinates measured by the sensor, q i : Coordinates of the reference point of the target model, n: Number of point cloud data.

[0118] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0119] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A high-precision spatial GNC full-physics simulation experimental method, characterized in that: The specific steps of this high-precision spatial GNC full-physics simulation experimental method are as follows: S1: Platform initialization, start the three-dimensional motion execution system, the motion control system completes the zero point calibration of the X, Y and Z axes in sequence through the dual grating rulers, collects the current and position signals of the servo motor in real time, the three-dimensional motion simulation system imports the flight path data, and completes time synchronization with the control system through the fiber optic reflection memory card; S2: Path loading and motion execution. The ground control console loads the target flight path. The motion control system generates servo motor motion commands based on the simulated path and drives the three-axis synchronous motion through the EtherCAT bus. The capture and interactive simulation system follows the motion path in real time to execute the extension and retraction of the grappling hook and the trajectory of the robotic arm. The safety protection system monitors the motion status and interference distance in real time. The motion control system dynamically adjusts the servo input through the model predictive control algorithm to achieve dynamic load synchronous compensation. S3: Target Acquisition and Interactive Simulation. The situational awareness simulator tracks the flying target in real time based on LiDAR point cloud data and visual recognition images. The grappling hook acquisition device autonomously acquires the target according to the trajectory feedback from the motion control system. The small multi-degree-of-freedom control device performs micro-force control in real time. The three-dimensional motion simulation system calculates the path safety distance in real time and performs motion data backtracking. If the minimum safety distance is detected to be insufficient, the safety protection system issues path adjustment or stop commands through the motion control system.

2. The high-precision spatial GNC full-physics simulation experimental method according to claim 1, characterized in that: In the platform initialization phase of S1, the three-dimensional motion execution system is first started. The motion control system uses a dual-grating ruler closed-loop detection device to complete the zero-point calibration of the X, Y, and Z axes in sequence to ensure the accuracy of the motion reference. At the same time, the system collects the current and position key signals of the servo motor in real time to achieve dynamic monitoring. The three-dimensional motion simulation system synchronously imports the flight path data and achieves time synchronization with the motion control system through the fiber optic reflection memory card interface of the ground control console.

3. The high-precision spatial GNC full-physics simulation experimental method according to claim 2, characterized in that: The specific steps for path loading and motion execution in S2 are as follows: S21, Path Loading and Driving: The ground control console loads the target flight path, the motion control system generates servo motor motion commands according to the simulated path, drives the three-axis synchronous motion via EtherCAT bus, captures the interactive simulation system to follow in real time, and executes the extension and retraction of the grappling hook and the trajectory of the robotic arm. Its regulation incorporates the dynamic adjustment logic of the model predictive control motion correction model. The formula for the model predictive control motion correction model is as follows: ； In the formula, Current control input, servo command, Predicted future trajectory Expected reference trajectory Predict step size, State weight matrix and control weight matrix; S22, Motion Control and Protection: The safety protection system monitors the motion status and interference distance in real time. The motion control system adopts a model predictive control algorithm, dynamically adjusting the servo input according to the correlation between the error and the adjustment amount in the motion correction model, realizing synchronous compensation of dynamic load, and ensuring accurate and safe motion.

4. The high-precision spatial GNC full-physics simulation experimental method according to claim 3, characterized in that: The target acquisition and interactive simulation in S3 refers to the use of a situational awareness simulator to track flying targets in real time with the help of lidar point cloud data and visual recognition images. The grappling hook acquisition device autonomously completes target acquisition based on the trajectory fed back by the motion control system. The small multi-degree-of-freedom control device synchronously performs micro-force control. The three-dimensional motion simulation system calculates the path safety distance in real time and backtracks the motion data. Once the minimum safety distance is detected to be insufficient, the safety protection system immediately issues path adjustment or stop commands through the motion control system to ensure that the entire acquisition and control process is safe and controllable. The formula for representing point cloud data is: ； In the formula, The target's current attitude transformation matrix, Point cloud coordinates measured by the sensor, Target model reference point coordinates Number of point cloud data.

5. A high-precision spatial GNC full-physics simulation test platform, characterized in that: The high-precision spatial GNC full-physics simulation experimental platform is based on the method described in any one of claims 1-4. The platform consists of a three-dimensional motion execution system, a distributed real-time control system, a capture and interactive simulation system, a safety protection system, and a three-dimensional motion simulation and path planning system. Three-dimensional motion execution system: Based on the steel rail type track, P43 steel rails with hydraulic buffer limiters are used in the X and Y directions. It is equipped with a gear rack and screw drive mechanism, a dual grating ruler closed-loop detection device and a gravity unloading mechanism to provide basic motion support for the simulation test platform. Distributed real-time control system: including ground control console, dual redundant servo controllers, EtherCAT bus nodes and motion monitoring units, driving three-axis synchronous motion; Capture and Interactive Simulation System: Equipped with a grappling hook capture device, a multi-degree-of-freedom control device, and a situational awareness and multi-dimensional measurement simulator, it is used for space target capture and micro-force control verification. Safety protection system: Equipped with dual redundant emergency stop circuits, dynamic interference detection module, hydraulic buffer limit and anti-tipping structure, real-time monitoring of movement to ensure safety; 3D Motion Simulation and Path Planning System: Includes 3D modeling, path planning, interference detection modules, and motion backtracking optimization functions to achieve modeling, planning, and data backtracking.

6. The high-precision spatial GNC full-physics simulation test platform according to claim 5, characterized in that: The three-dimensional motion execution system includes: (1) Track structure and drive mechanism: Based on the rail type track structure, rigid heavy P43 steel rails are used in the X and Y directions. The hydraulic buffer limiter at the end ensures the safety of operation. In the gear rack and screw drive mechanism, the servo motor is connected to the planetary reducer via a rigid coupling to drive the track. Its motion follows the track drive kinematic model that combines the relationship between speed, displacement and time. The screw is responsible for vertical motion. The formula for the orbital-driven kinematic model is as follows: ； In the formula, Motion displacement, Initial velocity, acceleration of motion, Exercise time; (2) Detection and unloading mechanism: The dual grating ruler closed-loop detection device collects X, Y and Z axis position and speed signals in real time through dual channels and feeds them back to the motion control system. The gravity unloading wire rope mechanism reduces the vertical load by means of pulley blocks according to the relationship between force and motion in the track drive kinematic model. It works in two sections in coordination.

7. The high-precision spatial GNC full-physics simulation test platform according to claim 6, characterized in that: The distributed real-time control system includes: (1) Control core architecture: The ground control console integrates a high-performance industrial computer, fiber optic reflective memory card interface and real-time operating system. The dual redundant servo motion controller adopts FPGA+DSP architecture, and the motion control cycle is less than 1ms. Its regulation follows the correlation logic of feedback and command in the servo motor speed closed-loop control model, providing a precise drive core for three-axis synchronous motion. The formula for the closed-loop speed control model of a servo motor is as follows: ； In the formula, The controller outputs speed commands. Reference speed, Actual measured speed, Speed ​​loop proportional coefficient, Velocity loop integral coefficient; (2) Distributed synchronization and monitoring: EtherCAT bus nodes realize distributed synchronization control, with node clock synchronization error less than 500μs, ensuring coordination accuracy. The motion monitoring unit collects multiple parameters of the motor through the servo driver and combines them with the parameter association logic in the speed closed-loop control model.

8. The high-precision spatial GNC full-physics simulation test platform according to claim 7, characterized in that: The capture-interaction simulation system includes: (1) Capture execution device: The flexible claw is driven by three ropes and synchronous belts. The surface is equipped with a nitrile rubber buffer layer. The telescopic stroke exceeds 3 meters. Its capture follows the correlation logic between force and contact state in the claw capture mechanics model. It is a small multi-degree-of-freedom control device. The robotic arm is driven by a six-degree-of-freedom servo motor and equipped with a joint torque sensor. The clamping force and stroke range are clear, and the control can be executed precisely. (2) Perception and measurement system: The situational awareness simulator integrates a 64-line lidar and vision unit to capture the position and attitude of the flying target in real time. The six-axis force sensor of the multi-dimensional measurement simulator collects contact data and updates at a frequency of no less than 1000Hz.

9. A high-precision spatial GNC full-physics simulation test platform according to claim 8, characterized in that: The security protection system includes: (1) Core mechanism of safety control: The dual redundant emergency stop circuit independently controls the dual-loop servo power supply to ensure reliable shutdown in emergency situations. The dynamic interference detection module is based on the bounding box algorithm, calculates the safe distance between the path and the surrounding equipment according to the correlation between distance and motion parameters in the real-time minimum safe distance model, monitors the motion status in real time and dynamically adjusts the path. The formula for the real-time minimum safe distance model is: ； In the formula, Current minimum safe distance The current center point coordinates of the motion platform Coordinates of the nearest point to surrounding equipment; (2) Protective structure guarantee: The hydraulic buffer limit structure has a buffer stroke of not less than 50mm, and the anti-overturning guide structure includes double wheel side guide and side wheel limit frame, combined with the spatial constraint logic of the real-time minimum safety distance model.

10. A high-precision spatial GNC full-physics simulation test platform according to claim 9, characterized in that: The three-dimensional motion simulation and path planning system includes: (1) 3D modeling and path planning module: The 3D modeling module supports importing 3D models in various formats. The path planning module adopts the priority path search algorithm and the inverse kinematics method. Its calculation follows the multi-factor trade-off logic in the priority cost function of path planning, and can accurately calculate the real-time motion path to meet the system's motion planning requirements. The principle of the path planning priority cost function is expressed by the following formula: ； In the formula, The value of the current path Path length, Path velocity change Path acceleration change These are the weighting coefficients for distance, velocity, and acceleration, respectively. (2) Interference detection and data backtracking module: The interference detection module calculates the safety distance in real time through the bounding box algorithm and the collision detection algorithm to ensure motion safety. The motion backtracking and parameter optimization module can record historical paths and adjust parameters. Combined with the optimization idea of ​​the path planning priority cost function, motion data backtracking and parameter optimization can be realized.

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