12 results about "Mission time" patented technology

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.

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.

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.

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.

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 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.