28 results about "Mission time" patented technology

The invention discloses a multi-unmanned aerial vehicle distribution and bus charging combined path optimization method, which aims at minimizing task total time, constructs a mixed integer programming model based on a space-time network, and comprehensively considers unmanned aerial vehicle electric quantity constraint, demand point full coverage, bus time window and charging pile number limitation. An original model is decoupled to limit a main problem and a sub-problem by adopting branch pricing and a Dantzigzag-Wolfe decomposition theory, the main problem deals with demand coverage and charging resource allocation, and modeling is a set coverage problem; for single-machine path generation, the latter is modeled as a resource-constrained and replenishable shortest path problem with a time window dependent feature. A multi-unmanned aerial vehicle initial solution is constructed through a random generation method, a dual variable is iteratively solved after a main problem is initialized, a sub-problem is solved based on a multi-label algorithm, and global optimal solution search is realized in combination with a column generation mechanism and a branch strategy. According to the invention, through joint optimization of the departure time and path planning of the unmanned aerial vehicle, the collaborative optimization problem of distribution and charging is accurately solved.

The present invention discloses a method for optimizing the trajectory and beamforming of multi-UAV communication and sensing integration based on MATD3, including: constructing a communication and sensing integration system supported by multi-UAVs; in terms of communication, calculating the communication link gain and signal-to-interference-plus-noise ratio (SINR), and therefrom deriving the communication sum rate; in terms of sensing, calculating the beam pattern gain; establishing an optimization problem with the objective of maximizing the total data rate of all communication users within the mission time period; using a hierarchical user association algorithm based on K-means to associate communication users, sensing users with UAVs; using the MATD3 algorithm with centralized training and distributed execution (CTDE) to train the UAVs, and completing the optimization of the trajectory and beamforming of multi-UAV communication and sensing integration. The present invention considers a more practical scenario of roaming users and the three-dimensional deployment of UAVs, and achieves a relatively high communication sum rate while meeting the sensing requirements.

The invention discloses a method and a system for planning an orbital task of a maneuvering satellite, and belongs to the field of spaceflight simulation analysis. The method comprises the following steps: creating a planning task and setting basic parameters of a maneuvering satellite; setting basic parameters of a target satellite and a general control center position point; maneuvering analysis is carried out with maneuvering satellite parameters, target satellite parameters and the position point of the master control center as constraints, and a task time window meeting the constraints is obtained; after the task time window is determined, an orbital maneuvering multi-strategy algorithm is called for calculation to obtain a maneuvering mode and a maneuvering parameter list of the maneuvering satellite arriving at the task point; and finally, entering a planning event processing module, sorting events according to time, judging whether impact events exist or not, and outputting a planning task success / failure state. The general control center evaluates the fuel remaining amount in real time based on a fuel formula and supports a user to dynamically formulate and issue an orbital transfer scheme, and integrated planning of maneuvering satellite task window calculation, maneuvering strategy selection and safety check is achieved.

The present application relates to the technical field of computer, in particular to a kind of experience-based field technician scheduling method and system, method includes: obtaining scheduling input data, including the directed graph of node and task node, travel time, available technician set, skill domain information, proficiency level, skill domain demand and demand proficiency level, income, task time window, work time window, service duration mapping relationship;According to proficiency level and demand proficiency level, compatible relationship is generated and experience-related service duration is calculated;Under the feasibility constraint, scheduling scheme is constructed, task node unique allocation is satisfied, job route is started from node and returns node, service starting time is determined according to travel time and experience-related service duration to satisfy time window;Heuristic insertion generates initial scheduling scheme;Iterative local search generates neighborhood, temperature parameter probability acceptance, disturbance and cooling;The optimal scheduling scheme is output to maximize the income.The present application can solve the problem of inaccurate time consumption estimation and insufficient plan robustness caused by the fact that the experience / proficiency of technicians is not explicitly reflected in the existing field technician scheduling.

The invention discloses a space debris removal task planning method based on a dynamic clustering and reachable graph network, which comprises the following steps: acquiring initial positions of all candidate debris, and calculating six orbit elements of all candidate debris on each time step of a task time window to form a dynamic ephemeris database; clustering all candidate fragments corresponding to each time step by adopting a DBSCAN clustering method, and taking each obtained cluster as a candidate path; eliminating a candidate path of which the spacecraft speed meets the relative speed constraint of all candidate fragments in all candidate paths to obtain a feasible path set; taking candidate paths in the feasible path set as nodes, and generating all possible node pairs; carrying out feasibility verification on the node pairs, and forming a reachable graph network by adopting the node pairs passing the feasibility verification; and according to the reachable graph network, performing path optimization by adopting a genetic algorithm, and generating a globally optimal candidate fragment removal task path for removing the most candidate fragments.

This invention discloses a dynamic aerial wireless mission network planning method and system based on multi-agent reinforcement learning. It addresses the problems of low planning efficiency, insufficient collaborative optimization capabilities, poor training stability, and difficulty in providing real-time, reliable, and globally efficient planning schemes in existing technologies. It achieves a reproducible, verifiable, and deployable software implementation to improve engineering usability. The method includes: configuring a corresponding agent for each service subnet; wherein the agent pre-loads a trained policy network; at each decision moment, each agent collects local observation states and inputs them into the corresponding policy network to obtain the optimal pairwise link switching action; each agent, based on the action, controls the connection and disconnection of communication links between UAVs within the corresponding service subnet, updating the network topology of the corresponding service subnet; until the mission ends, the network planning result in the mission time domain is obtained.

The embodiment of the invention provides a multi-platform multi-target dynamic task allocation method, system and device and a medium, and belongs to the field of multi-platform collaborative confrontation. The method comprises the following steps: performing time window segmentation on an action period of a target by using a platform; constructing a task allocation model; judging whether all targets in a model solving result are completely killed, and if so, taking the minimum total cost of consumed platform load as a first optimization target; and if not, taking the minimum target remaining overall threat as a second optimization target, and solving the first optimization target or the second optimization target by adopting a solve solver to obtain a target allocation scheme confronted by each platform channel in each action period. The task time window is segmented by adopting the action period, the problems of conflict of the platform to the target task time and waste of strike time are effectively solved, and according to whether the target is completely killed or not, the minimum platform load total cost or the minimum target residual overall threat is selected as an optimization index, so that the interception cost is minimum while the interception effect is ensured.

An autonomous ship AV mission planning and monitoring system (500) generates an AV mission and determines a ship configuration of a ship to autonomously execute a mission plan. A task planning and monitoring system (500) generates a task plan (1102) including at least a mobilization phase, a sailing phase, and a reviewing phase. The mission planning and monitoring system may also generate an emergency fallback plan for the vessel for compliance in unexpected events where the vessel cannot complete the assigned mission. Each stage of the AV task is assigned one or more activities or jobs for execution by the vessel according to the task timeline (1104). Each of the one or more activities is associated with one or more primitive commands by the task plan (1106). A candidate autonomous vessel is identified for autonomously performing a task (1108), and then capability information of the candidate vessel for performing a task plan is obtained (1110) by a task plan and monitoring system. Based on the capability information, a vessel configuration is generated (1114) for the vessel to employ to autonomously execute the task plan. The vessel configuration associates one or more automation and / or navigation primitive commands with each activity that the vessel will perform according to the task timeline.

A method and system for optimizing on-board orbit mission sequences based on real-time windward area is disclosed. The system includes a data configuration module, an area mapping module, a high-precision prediction module, and an autonomous feedback optimization module. The data configuration module receives mission sequences and space environment characteristic parameters, and synchronizes the satellite's real-time orbit vector. The area mapping module analyzes the target attitude based on the attitude parameters in the mission sequence and calculates the equivalent windward area corresponding to each mission time period in real time by combining the velocity vector. The high-precision prediction module executes the attitude-coupled variable area HPOP algorithm, incorporating the dynamically calculated equivalent windward area as a key perturbation term into the atmospheric drag calculation, and outputs orbit prediction results reflecting the attitude adjustment impact. The autonomous feedback optimization module performs consistency judgment on the difference between two adjacent recursive results. If the difference does not meet the preset requirements, it autonomously adjusts the mission execution time and mission execution parameters in the mission sequence and feeds them back to the area mapping module for iterative calculation.

A six-degree-of-freedom finite-time space rendezvous control method under multiple constraints belongs to the field of space technology. The implementation method of the present invention is as follows: a six-degree-of-freedom dynamic model is established based on the Lie group SE (3) framework, so that the spacecraft rendezvous process can satisfy the position end constraint while also satisfying the attitude end constraint, fully considering the attitude-orbit coupling problem caused by the thruster installation error in actual engineering, improving the spacecraft rendezvous accuracy, and avoiding the unwinding problem caused by the traditional six-degree-of-freedom dual quaternion representation method. A finite-time sliding mode control strategy is designed so that the rendezvous process can satisfy the mission time window constraint and improve the error convergence speed. In order to solve the potential collision risk in the rendezvous process and meet the safety constraints of the rendezvous mission, an artificial potential function is introduced to achieve collision avoidance in the rendezvous process and improve the safety of the spacecraft rendezvous process. The present invention can shorten the rendezvous time, improve the spacecraft space rendezvous accuracy, and improve the safety of the spacecraft rendezvous process.

The invention relates to a satellite task scheduling solution space expansion method based on double-layer granularity optimization. The method comprises the following steps: acquiring an initial task scheduling scheme; preprocessing the initial task scheduling scheme to obtain a potential selectable arc segment set, an uncompleted task set and a completed task set of each task; dynamically adjusting the uncompleted task set based on a double-layer granularity optimization method, and generating a new scheduling solution; and obtaining a task scheduling result based on the new scheduling solution, and evaluating the task scheduling result. Through a double-layer granularity replacement strategy, on the basis of an original scheduling solution, through layer-by-layer replacement optimization, on the premise that resources are not increased or task time is not prolonged, a solution space is effectively expanded, so that an appropriate scheduling time period is found for more tasks, and the task completion rate is improved.

The invention relates to the technical field of spaceflight orbit control, and provides a method and system for autonomously generating a satellite orbit control instruction and orbit control activity supervision table in order to solve the problems that a traditional satellite orbit control process depends on manual operation and is low in efficiency and prone to errors. According to the method, non-orbit-control-period orbit data are obtained, an apogee moment sequence is automatically calculated according to set parameters such as task time, thruster working duration and an orbit transfer mode, intelligent grouping is carried out according to a continuous or intermittent orbit transfer strategy, and the orbital transfer efficiency is improved. A complete orbit control plan including a specific ignition time sequence, an orbit lifting instruction, a hexadecimal source code capable of being directly injected and related physical parameters is generated, finally, a reported ephemeris file and an orbit control activity supervision record table which meet the specification are output in a one-key mode, and automation and standardization of the whole process from task planning to instruction generation and document compiling are achieved. The method is especially suitable for a task scene in which a low-orbit satellite climbs an orbit by using a thruster after satellite-rocket separation.

The present application relates to a method for designing a transfer orbit for a HALO orbiter to fly over a given ground point. The method includes: finding the moment when the lunar declination value is equal to the latitude value of the given ground point within the given mission time range, and selecting the time point closest to the initial moment as the initial value of the iteration for the orbit transfer moment; calculating the flight duration of the orbit transfer point relative to the starting point using the starting time and the initial value of the iteration for the orbit transfer moment; calculating the normalized time by dividing the flight duration by the HALO orbit period; calculating the magnitude of the orbit transfer velocity increment based on the normalized time using the polynomial fitting coefficients; establishing a mapping relationship between the magnitude of the orbit transfer velocity increment and the initial value of the iteration for the orbit transfer moment through numerical integration based on a high-precision force model; and completing the solution of the parameter to be solved using the Newton iteration method based on the mapping relationship. The method adopted has a short response time, high calculation result accuracy, and fast iteration convergence.

This invention discloses a highly reliable parachute deployment control method for ballistic reentry spacecraft. During the 0g overload period before reentry, software collects and filters information from overload sensors in each channel to obtain the overload zero-point value, which is then stored in a register. When the zero-point output voltage of the overload sensor exceeds the normal range of zero-point drift, external power-on is prompted to restore the fault. This method solves the problem of overload sensor circuit failure due to single-event effects before reentry. During the operation of the recovery control system, the difference between the measured overload value and the zero-point value is used for judgment. Utilizing the characteristic that the sensitivity of the overload sensor does not change over time, the influence of zero drift of the overload sensor on the parachute deployment timing accuracy is eliminated when the probe mission is long. This invention employs a multi-mode combined control method, combining overload time-based parachute deployment control and pure time-based parachute deployment control methods.

This invention discloses a method and system for joint planning of tasks and trajectories in heterogeneous UAV swarms based on feasibility feedback. The method includes: acquiring task set information, UAV swarm status information, and task environment information; constructing a multi-dimensional matching degree matrix between UAVs and tasks; generating an initial planning population based on the matrix, including task allocation codes and trajectory key point codes; performing feasibility closed-loop verification on individual planning entities, calculating the estimated flight energy consumption and task completion time based on the generated three-dimensional flight trajectory, and filtering based on remaining battery power constraints and task time window constraints; modulating pheromone concentration using the feasibility verification results to guide the search direction; and outputting a joint planning scheme for task allocation and three-dimensional trajectory that satisfies the flight constraints. This invention effectively solves the problem of infeasibility caused by the separation of task allocation and trajectory planning, improving the actual executability and optimization efficiency of the planning scheme.

A method for generating a predictive navigation system includes defining, based on a mission tasking, a mission route, identifying multiple mission planning images that correspond to a predetermined mission route, identifying geospatial data corresponding to the mission planning images, providing to a model, a mission plan, the mission planning images, and the geospatial data. The model is operated to generate predicted time sequenced and geo-sequenced images that are, provided to a platform control system. The predicted time sequenced and geo-sequenced images are presented during the mission to a pilot in real mission time. The mission plan includes multiple location markers that correspond to locations along the mission route. The time sequenced and geo-sequenced images depict landscapes along the mission plan corresponding to the mission plan. The predicted time sequenced and geo-sequenced images are provided to the platform control system before a mission.

The application discloses a kind of spacecraft near approach maneuver data set construction method, belong to spacecraft orbit design and optimization technical field, including the following steps: step 1, determine the maneuver type of maneuvering satellite and set the input of machine generation algorithm;Step 2, calculate the maximum flight circle number of target satellite and mission time;Step 3, based on the current circle number, calculate mission time, and solve initial guess;Step 4, construct the nonlinear equation representing the successful execution of maneuver of maneuvering satellite, and solve convergent solution using the derivative-free local optimal algorithm Sbplx based on Nlopt;Step 5, according to the solution, judge whether the optimal solution needs to be updated;Step 6, according to the current circle number, judge whether the iteration reaches the termination condition;Step 7, according to the maneuver type of maneuvering satellite, judge whether the algorithm reaches the termination condition, and whether additional maneuver is needed;The method provided by the application can satisfy the rapid construction of multiple near approach maneuver data sets.

This application relates to a method and system for obtaining joint maneuver parameters for geostationary orbit transfer and rendezvous. The method first obtains the initial parameters of the geostationary orbit transfer and rendezvous mission and determines the total number of orbital maneuvers, the total mission duration, and the rendezvous terminal aiming parameters. Then, it sequentially calls pre-constructed GTO transfer maneuver parameter acquisition problem models and GSO rendezvous maneuver parameter acquisition problem models for calculation. Next, it calls a pre-constructed joint maneuver parameter acquisition model for geostationary orbit transfer and rendezvous, considering the GTO transfer maneuver and the GSO rendezvous maneuver together. Finally, it uses a sequential quadratic programming algorithm to optimize and solve the joint maneuver parameter acquisition model for geostationary orbit transfer and rendezvous, obtaining the joint maneuver parameters. This allows for rapid rendezvous with the target spacecraft using the tracker's own thrust-limited orbital control engine, effectively shortening the orbital rendezvous mission time.

The present invention relates to a method for evaluating the resilience of an airport group system based on regional control capabilities. The aim is to address the problems existing in the research on the combat support effectiveness of airports. Taking the airport group system as the research object, a network model is established. Further considering the main factors such as the maximum sortie rate of the airport group system, the mission execution time, and the importance of the mission area, and combining with the resource-limited recovery strategy, a method and process for evaluating the resilience of the airport group system based on regional control capabilities are established. A case study is carried out on the airport group system in a certain region to analyze the dynamic impact of different recovery strategies on the resilience of the airport group system, providing support for the planning, design, and combat application of the resilient airport group system.

The invention relates to a transfer orbit design method for a HALO orbital vehicle to fly to a given ground point. The method comprises the following steps: finding a moment when a lunar declination value is equal to a given ground point latitude value according to the lunar declination value in a given task time range, and selecting a time point closest to an initial moment as an orbit transfer moment iteration initial value; calculating the flight duration of the orbital transfer point relative to the starting point by using the starting point time and the iteration initial value of the orbital transfer time; calculating normalization time according to the quotient of the flight duration and the HALO orbital period; according to a polynomial fitting coefficient, calculating the increment of the orbital transfer speed for the normalization time; based on a high-precision force model, establishing a mapping relation between the increment of the orbital transfer speed and the iteration initial value at the orbital transfer time through numerical integration; and solving the to-be-solved parameters by adopting a Newton iteration method based on the mapping relation. The method is short in response time, high in calculation result precision and fast in iteration convergence.

The present invention relates to the technical field of on-orbit servicing of spacecraft, and specifically to a method for mission planning of cooperative on-orbit refueling for multiple GEO spacecraft. The key points of its technical solution include: 1. Establish an orbit transfer model based on the method of attitude and phase adjustment maneuvers to reveal the relationship between the velocity increment and time of spacecraft orbit transfer; 2. Establish a two-layer optimization model for cooperative on-orbit refueling mission planning to determine the mission time range on the basis of minimizing fuel consumption; 3. Use a two-layer optimization algorithm to efficiently solve the optimization model, and the branch and bound algorithm and the fast elitist multi-objective genetic algorithm are respectively adopted for the inner and outer layers. The method of the present invention breaks through the limitations of the traditional many-to-many on-orbit refueling strategy, allows multiple service spacecraft to cooperate to complete the same refueling mission, reduces the fuel consumption and time cost of the on-orbit refueling mission, and the result is close to the Pareto optimal state. The present invention fully considers various constraints such as dynamic scheduling and payload limitations, and is closer to the actual engineering requirements.

The embodiment of the present invention provides a multi-platform multi-target dynamic task allocation method, system, device and medium, which belongs to the field of multi-platform collaborative confrontation. The method includes: using the platform to divide the target action cycle into time windows; constructing a task allocation model; judging whether all targets are completely killed according to the model solution result, if so, taking the minimum total cost of consuming the platform load as the first optimization goal; if not, taking the minimum overall threat remaining to the target as the second optimization goal, using the solve solver to solve the first or second optimization goal, and obtaining the target allocation scheme for each platform channel to confront in each action cycle. Using the action cycle to divide the task time window effectively solves the problem of conflict in the platform's task time on the target and the waste of attack time. According to whether the target is completely killed, the total cost of consuming the platform load or the minimum overall threat remaining to the target is selected as the optimization indicator to ensure the interception effect while minimizing the interception cost.

The invention provides a multi-mode observation-oriented satellite autonomous task planning method and system. The method comprises the steps of S1, setting task planning input parameters; s2, refining a task time window; s3, tracking mode point target planning; s4, pre-planning a search mode region target; s5, planning an imaging mode point target; and S6, outputting a planning result. The invention designs an autonomous task planning method suitable for an on-satellite processing system, so that a satellite can independently execute a task planning function, and the dependence on ground operation is reduced; autonomous task planning is carried out according to the target priority and the overhead moment, flexible adjustment can be carried out according to real-time requirements, and the flexibility of an on-satellite processing system is improved.

The present invention discloses a rendezvous mission planning method for rapid response of multi-target spacecraft on the same orbit, which belongs to the field of aerospace technology. According to the target orbit altitude and the total mission time constraint, the present invention uses phase difference to characterize the relative position of the mission spacecraft and the target on the same orbit, establishes and solves the Lambert problem of the rendezvous between the mission spacecraft and the target on the same orbit for all discretized phase difference situations, and obtains a database of speed increments required for the rendezvous between the mission spacecraft and the target on the same orbit. The positions of all targets that need to be rendezvoused are obtained, and the time required for the mission spacecraft to transfer between adjacent targets is used as the optimization variable, and the minimum total speed increment of each transfer is used as the optimization goal to establish a mission time allocation optimization problem. The mission time allocation problem is solved using a gradient-based solution algorithm. If the speed increment of the mission spacecraft exceeds the constraint, the number of targets to be rendezvoused is reduced until the total speed increment required for each transfer meets the constraint, thereby realizing the rendezvous mission planning.

The application relates to a DRO orbit aircraft orbit design method for falling on the moon at a given angle and coordinates. The method comprises the following steps: DRO initial position and speed value integration, output of L2 coordinate system positions of the moon at different moments in a period, and mapping of the moon falling speed and transfer orbit and white plane intersection position. The mapping and DRO period position are combined to reversely coarsely calculate the moon falling moment, initial speed and transfer time length. The three are taken as iteration initial values and constraints are set to reversely accurately calculate the integral end moment, speed and orbit flight time length. The end moment is taken as the orbit transfer moment initial value, the end speed and the DRO speed difference value are taken as the orbit transfer speed increment initial value, the orbit flight time length is taken as the transfer time length initial value, the forward accurate calculation is carried out by setting the terminal constraint and the integral termination condition, and finally the transfer orbit transfer moment and speed increment projection are obtained. The method can be suitable for different task times and different DRO orbit sizes, the calculation result is high in precision, and the iteration is fast and reliable.

The present invention discloses a method and system for estimating the probability distribution of equipment fault repair time, belonging to the field of equipment fault indicator quantification. The method comprises: integrating the gamma distribution density function of the lifespan of each component within the mission time, combined with the cumulative working time of each component, to obtain the probability of each component failing; calculating the repair weight coefficient of each component according to the probability of each component failing within the mission time in the inspection order; calculating the repair completion time array according to the inspection order, based on the time consumed for inspecting the status of each component and the time consumed for repairing each failed component; arranging each element in the repair completion time array in ascending order to obtain the sorted component number and the corresponding repair completion time; and cumulatively calculating the repair weight coefficient of each component in the sorted order to obtain the probability distribution of the equipment fault repair time. The present invention predicts the probability distribution of equipment fault repair time and can more specifically and comprehensively describe the equipment maintainability performance.

The invention relates to an orbital design method for a DRO orbital aircraft falling into the moon according to a given angle and coordinates. The method comprises the following steps: outputting earth-moon L2 coordinate system positions at different moments in one period according to DRO initial position speed numerical integration, and constructing mapping between the moon falling speed and the intersection point position of a transfer orbit and a white track plane; and performing reverse rough calculation by combining the mapping with the DRO periodic position to obtain the falling month moment, the initial speed and the transfer duration. Taking the three as iteration initial values and setting constraints, and performing reverse actuarial calculation to obtain integral end point time, speed and orbit flight duration. And by taking the end point moment as an orbit transfer moment initial value, the difference value between the end point speed and the DRO speed as an orbit transfer speed increment initial value and the orbit flight duration as a transfer duration initial value, forward actuarial calculation is carried out by setting a terminal constraint and an integral termination condition, and the transfer orbit transfer moment and speed increment projection is finally obtained. The method can adapt to different task time and different DRO orbit sizes, the calculation result is high in precision, and iteration convergence is rapid and reliable.

The present application relates to the technical field of deep space exploration flight control, and particularly relates to a task heuristic planetary rover flight program design method, comprising: dividing the planetary rover task into a moving module, a sensing module, a detection module and a standby charging module according to the principle of effectively connecting the in-orbit single task of the planetary rover and the inter-module; under the constraints of the target point position, the target task and the longest task allowed time, performing flight program design based on the "target task-target point" to obtain a preliminary flight program design; introducing energy constraints to update the preliminary flight program design to obtain a final flight program design according to the principle of satisfying the energy balance of the planetary rover. The present application realizes the rapid design of the flight program under the multi-constraints of task, time, position and energy.