Low-altitude intelligent operation method and device for dynamic take-off and landing and flight path planning and medium

Abstract

This invention provides a method, apparatus, equipment, and medium for low-altitude intelligent operation with dynamic takeoff and landing and trajectory planning, comprising: receiving a flexible flight request submitted by a user; calculating the available energy limit based on the current remaining energy and safety backup energy, and selecting stealth takeoff and landing platforms that meet the available energy limit as a candidate platform set; generating candidate four-dimensional trajectories based on the candidate platform set, performing four-dimensional conflict detection with existing trajectories, and if a conflict exists, implementing a layered resolution strategy to adjust the trajectory until an optimal solution containing conflict-free trajectories is generated; after the user confirms the optimal solution is pushed, sending a deployment command to the target stealth takeoff and landing platform to lock the four-dimensional airspace resources occupied by the conflict-free trajectories; after the aircraft executes the conflict-free trajectory mission, releasing the four-dimensional airspace resources and sending a retrieval command to the target stealth takeoff and landing platform, thereby solving the problems of inflexible infrastructure deployment, rigid flight plan management, and lack of energy security and conflict prevention in low-altitude operation systems.

Description

Technical Field

[0001] This invention relates to the field of urban air traffic management and intelligent infrastructure technology, and in particular to a low-altitude intelligent operation method, device, equipment and medium for dynamic take-off and landing and trajectory planning. Background Technology

[0002] With the rapid development of the low-altitude economy, the large-scale operation of drones and electric vertical takeoff and landing (eVTOL) aircraft in urban environments has become an important trend. However, low-altitude operations currently face three major bottlenecks: infrastructure deployment, airspace management, and operational safety.

[0003] First, regarding infrastructure, existing take-off and landing sites are mostly fixed ground or rooftop platforms, which presents problems such as difficulty in site selection, long construction periods, permanent occupation of urban space, and damage to the landscape, limiting the deployment density and flexibility of the low-altitude transportation network. Second, in terms of airspace management, current flight plan applications are based on the traditional fixed flight plan model. Operators must submit flight plans containing fixed take-off and landing points and fixed routes to the control department in advance, and can only execute them after a complex approval process. This model has a long response time and poor flexibility, making it difficult to adapt to the high-frequency and real-time operational needs of future urban air traffic. In addition, in terms of operational safety, when take-off and landing points or routes change dynamically, the uncertainty of flight paths will significantly increase the risk of mid-air collisions, and the existing scheduling system lacks a systematic pre-assessment of the energy status of aircraft, making it difficult to effectively prevent energy depletion accidents.

[0004] To address the aforementioned issues, some technical solutions have proposed partial improvements. For example, patent document CN202410609482.4 discloses a modular, quick-release vertical takeoff and landing (VTOL) UAV, primarily focusing on optimizing the physical structure of the takeoff and landing platform. The academic community has also proposed various UAV path planning algorithms for generating flight paths in static environments. However, these existing solutions address specific problems in isolation, failing to organically combine dynamically deployable intelligent infrastructure, novel management protocols supporting dynamic intentions, and global optimization algorithms ensuring energy security. Specifically, existing technologies still suffer from the following shortcomings: takeoff and landing sites cannot achieve seamless, integrated deployment with urban buildings; flight plan application modes are rigid, unable to support dynamic intentions without specifying fixed takeoff and landing points and routes; in dynamic scheduling scenarios, there is a lack of a planning mechanism that uses the aircraft's energy state as a core constraint and iteratively coordinates with conflict detection; and the subsystems are isolated from each other, failing to form a complete technical solution for closed-loop collaborative operation.

[0005] Therefore, there is an urgent need to provide a low-altitude intelligent operation method with dynamic take-off and landing and trajectory planning to solve the technical problems of inflexible infrastructure deployment, rigid flight plan management and lack of collaborative guarantee mechanisms for energy safety and conflict avoidance in low-altitude operation systems. Summary of the Invention

[0006] To overcome the problems existing in related technologies, this disclosure provides a method, apparatus, equipment and medium for low-altitude intelligent operation with dynamic take-off and landing and trajectory planning, so as to solve the technical problems of inflexible infrastructure deployment, rigid flight plan management and lack of energy safety and conflict avoidance coordination guarantee mechanism in low-altitude operation systems.

[0007] This specification provides one or more embodiments of a low-altitude intelligent operation method with dynamic takeoff and landing and trajectory planning, including the following steps: Receive a flexible flight request submitted by a user, the flexible flight request including starting point information, ending point area information and the remaining energy reported by the aircraft in real time; The available energy limit is calculated based on the current remaining energy and the preset safety backup energy. Stealth take-off and landing platforms that meet the available energy limit are selected from the endpoint area information as a candidate platform set. Based on the candidate platform set, candidate four-dimensional tracks containing timestamps are generated. The candidate four-dimensional tracks are then compared with existing tracks for four-dimensional conflict detection. If a conflict exists, a hierarchical resolution strategy is executed to adjust the tracks until an optimal solution containing conflict-free tracks is generated and pushed to the user. After the user confirms the optimal solution is pushed, a deployment command is sent to the target stealth take-off and landing platform, and the four-dimensional airspace resources occupied by the conflict-free flight path are locked. The aircraft executes the conflict-free flight path mission, releases the four-dimensional airspace resources after the mission is completed, and sends a recovery command to the target stealth take-off and landing platform.

[0008] Preferably, the stealth take-off and landing platform specifically includes: Platform panel, drive mechanism, wireless charging module, and visual guidance system; The drive mechanism is used to drive the platform panel to switch between stealth mode and working mode; The wireless charging module is used to wirelessly charge the aircraft during takeoff and landing. The visual guidance system is used to provide landing guidance signals in the operating state.

[0009] Preferably, generating a four-dimensional track containing timestamps based on the candidate platform set specifically includes the following steps: The path search is performed using the energy-constrained A* algorithm. The cost function of the energy-constrained A* algorithm is based on the sum of the consumed energy and the estimated minimum required energy. The pruning condition is that the sum of the consumed energy and the estimated minimum required energy is greater than the upper limit of available energy.

[0010] Preferably, the step of performing four-dimensional conflict detection between the candidate four-dimensional track and the existing track, and if a conflict exists, executing a hierarchical resolution strategy to adjust the track, specifically includes the following steps: Based on the candidate four-dimensional tracks of the aircraft, the spatiotemporal occupancy window of each track is determined; When the spatial distance between any two aircraft within the same time window is less than the preset safe distance, it is determined that there is a conflict; The hierarchical decoupling strategy includes time adjustment, space adjustment, and priority scheduling.

[0011] Preferably, locking the four-dimensional airspace resources occupied by the conflict-free flight path specifically includes the following steps: The conflict-free flight path is discretized into spatial points with timestamps to form a spatiotemporal occupancy unit; In the airspace digital twin model, the spatiotemporal occupancy unit is marked as occupied, and constraints are provided for conflict detection of subsequent flight requests.

[0012] Preferably, the process of generating the optimal solution containing conflict-free flight paths and pushing it to the user specifically includes the following steps: Construct an optimization objective function, which includes the energy consumption cost of flying to the candidate platform, the flight time cost, and the congestion index around the platform; The comprehensive cost of each candidate solution is calculated by pre-set weighting coefficients, and the solution with the lowest comprehensive cost is selected as the optimal solution. The weighting coefficients are dynamically adjusted according to the application scenario.

[0013] This specification provides one or more embodiments of a low-altitude intelligent operation device for dynamic takeoff and landing and trajectory planning, including: The request receiving module is used to receive flexible flight requests submitted by users. The flexible flight requests include starting point information, ending point area information, and the remaining energy reported by the aircraft in real time. The filtering module is used to calculate the upper limit of available energy based on the current remaining energy and the preset safety backup energy, and to filter out stealth take-off and landing platforms that meet the upper limit of available energy from the endpoint area information as a candidate platform set; The conflict resolution module is used to generate candidate four-dimensional tracks containing timestamps based on the candidate platform set, and to perform four-dimensional conflict detection between the candidate four-dimensional tracks and existing tracks. If a conflict exists, a hierarchical resolution strategy is executed to adjust the tracks until an optimal solution containing conflict-free tracks is generated and pushed to the user. The resource locking module is used to send a deployment command to the target stealth take-off and landing platform after the user confirms the optimal solution push, and lock the four-dimensional airspace resources occupied by the conflict-free flight path. The mission execution module is used for the aircraft to execute the conflict-free flight path mission, release the four-dimensional airspace resources after the mission is completed, and send a recovery command to the target stealth take-off and landing platform.

[0014] Preferably, the stealth take-off and landing platform specifically includes: Platform panel, drive mechanism, wireless charging module, and visual guidance system; The drive mechanism is used to drive the platform panel to switch between stealth mode and working mode; The wireless charging module is used to wirelessly charge the aircraft during takeoff and landing. The visual guidance system is used to provide landing guidance signals in the operating state.

[0015] This specification provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the low-altitude intelligent operation method of dynamic take-off and landing and trajectory planning as described above.

[0016] This specification provides one or more embodiments of a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the low-altitude intelligent operation method for dynamic take-off and landing and trajectory planning described above.

[0017] This disclosure provides a low-altitude intelligent operation method, apparatus, equipment, and medium for dynamic takeoff and landing and trajectory planning. Its advantages lie in that by receiving flexible flight requests submitted by users, it accurately acquires diverse takeoff and landing needs and the real-time energy status of the aircraft, laying a data foundation for subsequent dynamic planning and feasibility assessment under energy constraints. It calculates the upper limit of available energy based on remaining energy and safety backup energy, and filters out stealth takeoff and landing platforms that meet the conditions, effectively eliminating destinations beyond the endurance range and ensuring the reachability of takeoff and landing platforms. Simultaneously, it generates a concise set of candidate platforms, reducing the computational complexity of subsequent trajectory planning. Based on the candidate platforms, it generates a timestamped four-dimensional trajectory, which conflicts with existing trajectories. Detection and retraction adjustments can identify and eliminate spatiotemporal conflicts in advance, ensuring that the generated conflict-free flight path satisfies both energy constraints and is executable in four-dimensional space, thus improving flight safety and airspace utilization efficiency. After user confirmation, a deployment command is sent to the target platform and the four-dimensional airspace resources occupied by the conflict-free flight path are locked, preventing subsequent requests for the same spatiotemporal resources from being repeatedly allocated, achieving exclusive reservation of resources, and ensuring the determinism of flight mission execution. After the aircraft completes its mission, it promptly releases the four-dimensional airspace resources and sends a retrieval command to the platform, enabling the rapid recovery of idle resources for use by other aircraft, while avoiding long-term exposure of stealth take-off and landing platforms, enhancing the system's dynamic scheduling capabilities and platform stealth. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a cloud-edge-device three-layer architecture provided in one or more embodiments of this specification; Figure 2 A flowchart illustrating a low-altitude intelligent operation method for dynamic takeoff and landing and trajectory planning provided in one or more embodiments of this specification; Figure 3 A flowchart of the dynamic flight intent declaration-real-time intelligent scheduling workflow provided for one or more embodiments of this specification; Figure 4 A schematic diagram of two core operating states of the stealth take-off and landing platform provided in one or more embodiments of this specification; Figure 5 A schematic diagram illustrating the overall architecture and workflow provided for one or more embodiments of this specification; Figure 6 A flowchart of the core algorithm of the central scheduling system provided in one or more embodiments of this specification; Figure 7 A schematic diagram of the structure of a low-altitude intelligent operation device for dynamic take-off and landing and trajectory planning provided for one or more embodiments of this specification; Figure 8 This is a schematic diagram of the structure of a computer device provided for one or more embodiments of this specification. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this invention.

[0021] The present invention will now be described in detail with reference to specific embodiments and accompanying drawings.

[0022] Method Implementation Examples like Figure 1The diagram shown is a schematic of the cloud-edge-device three-layer architecture provided in this embodiment. The present invention adopts a cloud-edge-device three-layer architecture, and its core components and workflow are as follows: (1) Intelligent stealth take-off and landing platform (end-physical layer): Deployed on the building facade or roof, including retractable platform panels and drive mechanism. It has a stealthy state when retracted and flush with the building surface and a working state when deployed to form a take-off and landing area, and integrates wireless charging, visual guidance, sensors, etc.

[0023] (2) Central Intelligent Dispatch System (Cloud-Decision Layer): The brain of the system, which includes four core engines.

[0024] Dynamic resource pool management engine: manages the status of all takeoff and landing fields.

[0025] Energy-constrained trajectory planning engine: Plans trajectories using the aircraft's real-time energy as a hard constraint.

[0026] Real-time 4D Conflict Detection and Resolution (4D-CDR) engine: ensures that all tracks are conflict-free in space and time.

[0027] Dynamic Flight Intent Processing Engine: Handles new types of flight requests that do not specify fixed landing points and routes.

[0028] (3) Aircraft adaptation module (end-mobile layer): The aircraft must have the ability to report energy status in real time and receive and execute four-dimensional tracks.

[0029] According to embodiments of the present invention, a low-altitude intelligent operation method with dynamic takeoff and landing and trajectory planning is provided, such as... Figure 2 The diagram shown is a flowchart illustrating the low-altitude intelligent operation method with dynamic takeoff and landing and trajectory planning provided in this embodiment. The low-altitude intelligent operation method with dynamic takeoff and landing and trajectory planning according to this embodiment includes the following steps: S210: Receive a flexible flight request submitted by the user, such as from point A to area B, without specifying a specific landing platform or flight path. Utilize the dynamic flight intent processing engine to transform the user's fuzzy intent into a calculable planning objective. The flexible flight request includes origin information, destination area information, and the aircraft's real-time reported remaining energy.

[0030] S220. Based on the flexible flight request, calculate the upper limit of available energy according to the current remaining energy and the preset safety backup energy, and select stealth take-off and landing platforms that meet the upper limit of available energy from the destination area information as a candidate platform set.

[0031] S230. Based on the candidate platform set, generate candidate four-dimensional tracks containing timestamps. Send the candidate four-dimensional tracks and existing tracks into the 4D-CDR engine for four-dimensional conflict detection. If a conflict exists, execute a layered resolution strategy to adjust the tracks until an optimal solution containing energy-safe and conflict-free tracks is generated and pushed to the user.

[0032] S240. After the user confirms the optimal solution is pushed, a deployment command is sent to the target stealth take-off and landing platform, and the four-dimensional airspace resources occupied by the conflict-free flight path in the system's digital twin airspace are locked. The four-dimensional airspace resources include space and time.

[0033] Specifically, the intent data structure is as follows: { “origin”: “point A or region A”, / / starting point: precise point or fuzzy region "destination": "Point B or region B", / / Destination point: precise point or ambiguous region "time_window": ["14:00", "14:30"], / / Expected execution time window "priority": "high / medium / low" / / Task priority } Processing flow: (1) Region resolution: The system first resolves the fuzzy region descriptions (such as administrative divisions, geofences, grid codes, custom polygons, etc.) submitted by the user into standard polygon geometric objects.

[0034] (2) Platform filtering: Filter the set of available hidden platforms from the destination region.

[0035] (3) Energy accessibility screening: Join the platform

[0036] (4) Multi-objective optimization to select the optimal solution:

[0037] Parameter explanation: Fly to the platform Energy consumption costs.

[0038] Flight time cost.

[0039] :platform The surrounding congestion index (reflecting the level of activity in the area).

[0040] Weighting coefficient (can be dynamically adjusted according to the scenario).

[0041] Output: Select the platform with the lowest cost and its corresponding trajectory plan and push it to the user for confirmation.

[0042] S250: The aircraft executes the conflict-free flight path mission. After the mission is completed, it releases the four-dimensional airspace resources, sends a recovery command to the target stealth take-off and landing platform, and monitors the entire process. In case of an anomaly, it triggers dynamic replanning.

[0043] like Figure 3 The diagram shown is a flowchart of the dynamic flight intent declaration-real-time intelligent scheduling workflow provided in this embodiment.

[0044] The method provided in this embodiment, by receiving flexible flight requests submitted by users, accurately acquires diverse takeoff and landing needs of users and the real-time energy status of the aircraft, laying a data foundation for subsequent dynamic planning and feasibility assessment under energy constraints. It calculates the upper limit of available energy based on remaining energy and safe backup energy, and filters out stealth takeoff and landing platforms that meet the conditions, effectively eliminating destinations beyond the range of flight, ensuring the reachability of takeoff and landing platforms, and generating a concise set of candidate platforms, reducing the computational complexity of subsequent trajectory planning. Based on the candidate platforms, it generates timestamped four-dimensional trajectories, performs conflict detection and reconciliation adjustments with existing trajectories, and can identify and eliminate conflicts in advance. In addition to addressing spatiotemporal conflicts, ensuring that the generated conflict-free flight paths satisfy both energy constraints and four-dimensional space executability improves flight safety and airspace utilization efficiency. After user confirmation, sending deployment instructions to the target platform and locking the four-dimensional airspace resources occupied by the conflict-free flight paths prevents subsequent requests for duplicate allocation of the same spatiotemporal resources, achieving exclusive resource reservation and ensuring the determinism of flight mission execution. After the aircraft completes its mission, it promptly releases the four-dimensional airspace resources and sends a retrieval instruction to the platform, enabling rapid recovery of idle resources for use by other aircraft, while avoiding long-term exposure of stealth take-off and landing platforms, enhancing the system's dynamic scheduling capabilities and platform stealth.

[0045] In one embodiment, such as Figure 4 The diagram shown illustrates two core operating states of the stealth takeoff and landing platform provided in this embodiment. The stealth takeoff and landing platform specifically includes: The platform panel 201 is flush with the building exterior wall 202. The platform panel 201 extends outward and is stably supported by the support structure 204. It is equipped with boundary indicator lights 205, a tethering device 206, a wireless charging module 207, a visual guidance system 208, and a drive mechanism 203.

[0046] The drive mechanism 203 is used to drive the platform panel to switch between stealth mode and working mode.

[0047] The wireless charging module 207 is used to wirelessly charge the aircraft during takeoff and landing.

[0048] The visual guidance system 208 is used to provide landing guidance signals in the operating state.

[0049] The method provided in this embodiment enables flexible switching between stealth and operational states through a drive mechanism, balancing platform concealment with on-demand deployment capabilities. A wireless charging module can replenish the aircraft's energy during takeoff and landing, extending mission endurance. The visual guidance system provides precise landing signals in operational state, improving takeoff and landing safety and automation. Overall, the platform integrates concealed deployment, energy replenishment, and autonomous guidance functions, effectively supporting the dynamic takeoff and landing requirements of low-altitude intelligent operations.

[0050] In one embodiment, generating a four-dimensional track containing timestamps based on the candidate platform set specifically includes the following steps: The path search is performed using the energy-constrained A* algorithm. The cost function of the energy-constrained A* algorithm is based on the sum of the consumed energy and the estimated minimum required energy. The pruning condition is that the sum of the consumed energy and the estimated minimum required energy is greater than the upper limit of available energy.

[0051] Specifically, under the premise of satisfying the energy constraints of the aircraft, a flyable four-dimensional trajectory from the starting point to the target area or candidate platform is planned for the flight mission.

[0052] Energy-constrained model: ; in, The aircraft followed its flight path Total energy required for flight The aircraft's current remaining energy is reported by the aircraft in real time. :Safe backup energy, such as 15% of the total power, to deal with emergencies.

[0053] Planning Algorithm: An improved energy-constrained A* algorithm is adopted. Cost function: ; in, Fly from the starting point to the current node Energy consumed. : Estimate from the current node The estimated minimum energy required to reach the destination, calculated based on the straight-line distance. : Indicates passing through a node The estimated total energy consumption of this path.

[0054] Pruning conditions: If the energy cannot be reached, then pruning is necessary.

[0055] This means that when searching for a path, if energy has already been consumed to reach the current node... In addition, it is estimated that it will take at least [time] to reach the destination. If the total exceeds the available energy limit, it means that this path is blocked. The system immediately abandons the search for this branch and performs pruning to avoid invalid calculations.

[0056] Output: The optimal four-dimensional trajectory that satisfies the energy constraint. That is, a series of spatial points with timestamps.

[0057] The method provided in this embodiment uses the energy-constrained A* algorithm for four-dimensional trajectory search. The cost function integrates the consumed energy and the estimated minimum remaining energy, and prunes in a timely manner when the available energy limit is exceeded. This ensures that the generated trajectory is strictly feasible and close to optimal in terms of energy, while significantly reducing invalid search nodes and improving planning efficiency and real-time performance.

[0058] In one embodiment, during the planning or operation phase, the candidate four-dimensional trajectory is compared with existing trajectories for four-dimensional conflict detection. If a conflict exists, a hierarchical resolution strategy is executed to adjust the trajectory in order to detect and eliminate spatiotemporal conflicts between multiple aircraft. Specifically, this includes the following steps: Based on the candidate four-dimensional tracks of the aircraft, the spatiotemporal occupancy window of each track is determined.

[0059] A conflict is determined when the spatial distance between any two aircraft within the same time window is less than a preset safety distance. Specifically, a conflict is determined when two aircraft i and j satisfy the following equation at time t:

[0060] ; The spatial position of spacecraft i at time t. Minimum safe distance, for example, 50 meters. The time window during which aircraft i occupies a certain segment of airspace is defined using a left-closed, right-open interval. Under this definition, Resources are constantly being occupied. Time resources are released immediately, allowing another aircraft to operate at the same time. Entering this airspace enables safe and seamless resource integration.

[0061] The layered decoupling strategy includes: Time adjustment: Adjust takeoff time or speed to avoid conflicting time periods.

[0062] Spatial adjustment: Horizontal / vertical offset around the target, offset Δd ≥ Dsafe.

[0063] Priority scheduling: High-priority routes are maintained, while low-priority routes are replanned or diverted.

[0064] The method provided in this embodiment accurately calculates the spatiotemporal occupancy window of each track and achieves rapid determination of four-dimensional conflicts based on a safe distance threshold. When a conflict occurs, a hierarchical resolution strategy combining time adjustment, spatial adjustment and priority scheduling is adopted to flexibly and efficiently resolve the spatiotemporal overlap between tracks, ensure the generation of conflict-free feasible tracks, and improve airspace operation safety and planning flexibility.

[0065] In one embodiment, locking the four-dimensional airspace resources occupied by the conflict-free flight path specifically includes the following steps: The conflict-free flight path is discretized into spatial points with timestamps to form a spatiotemporal occupancy unit.

[0066] In the airspace digital twin model, the spatiotemporal occupancy unit is marked as occupied, and constraints are provided for conflict detection of subsequent flight requests.

[0067] The method provided in this embodiment discretizes conflict-free flight paths into spatiotemporal occupancy units with timestamps and marks them as occupied in the airspace digital twin model, enabling refined and digital locking of four-dimensional airspace resources. At the same time, it provides clear constraint boundaries for conflict detection of subsequent flight requests, effectively preventing resource duplication and ensuring the exclusivity and security of flight mission execution.

[0068] In one embodiment, the optimal solution containing conflict-free flight paths is pushed to the user, specifically including the following steps: An optimization objective function is constructed, which includes the energy cost of flying to the candidate platform, the flight time cost, and the congestion index around the platform. The objective function is as follows:

[0069] in, Fly to the platform Energy consumption cost Flight time cost :platform The congestion index of the surrounding area reflects the level of activity in the region. Weighting coefficient, which can be dynamically adjusted according to the scenario.

[0070] The comprehensive cost of each candidate solution is calculated by pre-set weighting coefficients, and the solution with the lowest comprehensive cost is selected as the optimal solution. The weighting coefficients are dynamically adjusted according to the application scenario.

[0071] The method provided in this embodiment constructs a multi-objective optimization function that includes energy consumption, time, and congestion index, and uses dynamically adjustable weight coefficients for comprehensive cost evaluation. This allows the method to automatically select the optimal solution with the lowest overall cost from multiple candidate conflict-free paths. At the same time, the weight coefficients can be flexibly adjusted according to the application scenario, so that the solution has good adaptability and decision quality under different operational requirements.

[0072] The following specific implementation case further illustrates the solution: like Figure 5 The diagram shown illustrates the overall architecture and workflow of this embodiment. It clearly indicates the data and control flows between the "user terminal," "central intelligent scheduling system," "edge controller," "stealth takeoff and landing platform," and "aircraft," and highlights the five core steps from "intent submission" to "mission completion."

[0073] like Figure 6 The diagram shows the core algorithm flowchart of the central scheduling system provided in this embodiment. The diagram clearly expresses the logical judgment process of "receiving intent and energy data" → "energy reachability screening" → "conflict detection and resolution loop" → "scheme optimization and push" → "resource reservation and locking", especially the two key judgment nodes "Is the energy sufficient?" and "Is there a conflict?" and their corresponding processing branches ("return no solution" or "adjust the track and re-verify the energy").

[0074] Device Examples According to embodiments of the present invention, a low-altitude intelligent operation device with dynamic takeoff and landing and trajectory planning is provided, such as... Figure 7 The diagram shown is a structural schematic of the low-altitude intelligent operation device for dynamic takeoff and landing and trajectory planning provided in this embodiment. The low-altitude intelligent operation device for dynamic takeoff and landing and trajectory planning according to this embodiment of the invention includes: The request receiving module 71 is used to receive a flexible flight request submitted by a user. The flexible flight request includes starting point information, ending point area information, and the remaining energy reported by the aircraft in real time.

[0075] The filtering module 72 is used to calculate the upper limit of available energy based on the current remaining energy and the preset safety backup energy, and to filter out stealth take-off and landing platforms that meet the upper limit of available energy from the endpoint area information as a candidate platform set. The stealth take-off and landing platform specifically includes: Platform panel, drive mechanism, wireless charging module and visual guidance system.

[0076] The drive mechanism is used to drive the platform panel to switch between stealth mode and working mode.

[0077] The wireless charging module is used to wirelessly charge the aircraft during takeoff and landing.

[0078] The visual guidance system is used to provide landing guidance signals in the operating state.

[0079] The conflict resolution module 73 is used to generate candidate four-dimensional tracks containing timestamps based on the candidate platform set, and to perform four-dimensional conflict detection between the candidate four-dimensional tracks and existing tracks. If a conflict exists, a hierarchical resolution strategy is executed to adjust the tracks until an optimal solution containing conflict-free tracks is generated and pushed to the user.

[0080] The resource locking module 74 is used to send a deployment command to the target stealth take-off and landing platform after the user confirms the optimal solution push, and to lock the four-dimensional airspace resources occupied by the conflict-free flight path.

[0081] The mission execution module 75 is used for the aircraft to execute the conflict-free flight path mission, release the four-dimensional airspace resources after the mission is completed, and send a recovery command to the target stealth take-off and landing platform.

[0082] The device provided in this embodiment receives flexible flight requests submitted by users through the request receiving module 71, achieving accurate acquisition of diverse user takeoff and landing needs and the real-time energy status of the aircraft, laying a data foundation for subsequent dynamic planning and feasibility assessment under energy constraints. The filtering module 72 calculates the upper limit of available energy based on remaining energy and safe backup energy, and filters stealth takeoff and landing platforms that meet the conditions, effectively eliminating destinations beyond the range of flight, ensuring the reachability of takeoff and landing platforms, and generating a concise set of candidate platforms, reducing the computational complexity of subsequent trajectory planning. The conflict resolution module 73 generates a four-dimensional trajectory with timestamps based on the candidate platforms, performs conflict detection and resolution adjustments with existing trajectories, and can identify conflicts in advance. The system eliminates spatiotemporal conflicts, ensuring that the generated conflict-free flight path satisfies both energy constraints and four-dimensional space executability, thus improving flight safety and airspace utilization efficiency. After user confirmation in the resource locking module 74, a deployment command is sent to the target platform, locking the four-dimensional airspace resources occupied by the conflict-free flight path. This prevents subsequent requests for duplicate allocation of the same spatiotemporal resources, achieving exclusive resource reservation and ensuring the determinism of flight mission execution. After the aircraft completes its mission, the mission execution module 75 promptly releases the four-dimensional airspace resources and sends a retrieval command to the platform. This enables the rapid recovery of idle resources for use by other aircraft, while avoiding long-term exposure of the stealth take-off and landing platform, enhancing the system's dynamic scheduling capabilities and platform stealth.

[0083] The embodiments of the present invention are device embodiments corresponding to the above method embodiments. The specific operations of each module processing step can be understood with reference to the description of the method embodiments, and will not be repeated here.

[0084] like Figure 8As shown, the present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it implements the low-altitude intelligent operation method of dynamic take-off and landing and trajectory planning in the above embodiments, or when the computer program is executed by a processor, it implements the low-altitude intelligent operation method of dynamic take-off and landing and trajectory planning in the above embodiments.

[0085] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0086] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for apparatus or system embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The apparatus and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and the contents not described in detail in the specification of the present invention are known to those skilled in the art.

Claims

1. A method for dynamic take-off and landing and route planning for low altitude intelligent operation, characterized in that, Includes the following steps: Receive a flexible flight request submitted by a user, the flexible flight request including starting point information, ending point area information and the remaining energy reported by the aircraft in real time; The available energy limit is calculated based on the current remaining energy and the preset safety backup energy. Stealth take-off and landing platforms that meet the available energy limit are selected from the endpoint area information as a candidate platform set. Based on the candidate platform set, candidate four-dimensional tracks containing timestamps are generated. The candidate four-dimensional tracks are then compared with existing tracks for four-dimensional conflict detection. If a conflict exists, a hierarchical resolution strategy is executed to adjust the tracks until an optimal solution containing conflict-free tracks is generated and pushed to the user. After the user confirms the optimal solution is pushed, a deployment command is sent to the target stealth take-off and landing platform, and the four-dimensional airspace resources occupied by the conflict-free flight path are locked. The aircraft executes the conflict-free flight path mission, releases the four-dimensional airspace resources after the mission is completed, and sends a recovery command to the target stealth take-off and landing platform.

2. The dynamic VTOL and trajectory planning low altitude intelligent operation method of claim 1, wherein, The stealth take-off and landing platform specifically includes: Platform panel, drive mechanism, wireless charging module, and visual guidance system; The drive mechanism is used to drive the platform panel to switch between stealth mode and working mode; The wireless charging module is used to wirelessly charge the aircraft during takeoff and landing. The visual guidance system is used to provide landing guidance signals in the operating state.

3. The low-altitude intelligent operation method for dynamic takeoff and landing and trajectory planning as described in claim 1, characterized in that, The process of generating a four-dimensional track containing timestamps based on the candidate platform set specifically includes the following steps: The path search is performed using the energy-constrained A* algorithm. The cost function of the energy-constrained A* algorithm is based on the sum of the consumed energy and the estimated minimum required energy. The pruning condition is that the sum of the consumed energy and the estimated minimum required energy is greater than the upper limit of available energy.

4. The low-altitude intelligent operation method for dynamic takeoff and landing and trajectory planning as described in claim 1, characterized in that, The process of performing four-dimensional conflict detection between the candidate four-dimensional track and existing tracks, and if a conflict exists, implementing a hierarchical resolution strategy to adjust the track, specifically includes the following steps: Based on the candidate four-dimensional tracks of the aircraft, the spatiotemporal occupancy window of each track is determined; When the spatial distance between any two aircraft within the same time window is less than the preset safe distance, it is determined that there is a conflict; The hierarchical decoupling strategy includes time adjustment, space adjustment, and priority scheduling.

5. The low-altitude intelligent operation method for dynamic takeoff and landing and trajectory planning as described in claim 1, characterized in that, The process of locking the four-dimensional airspace resources occupied by the conflict-free flight path specifically includes the following steps: The conflict-free flight path is discretized into spatial points with timestamps to form a spatiotemporal occupancy unit; In the airspace digital twin model, the spatiotemporal occupancy unit is marked as occupied, and constraints are provided for conflict detection of subsequent flight requests.

6. The low-altitude intelligent operation method for dynamic takeoff and landing and trajectory planning as described in claim 1, characterized in that, The process of generating the optimal solution containing conflict-free flight paths and pushing it to the user includes the following steps: Construct an optimization objective function, which includes the energy consumption cost of flying to the candidate platform, the flight time cost, and the congestion index around the platform; The comprehensive cost of each candidate solution is calculated by pre-set weighting coefficients, and the solution with the lowest comprehensive cost is selected as the optimal solution. The weighting coefficients are dynamically adjusted according to the application scenario.

7. A low-altitude intelligent operation device for dynamic takeoff and landing and trajectory planning, characterized in that, include: The request receiving module is used to receive flexible flight requests submitted by users. The flexible flight requests include starting point information, ending point area information, and the remaining energy reported by the aircraft in real time. The filtering module is used to calculate the upper limit of available energy based on the current remaining energy and the preset safety backup energy, and to filter out stealth take-off and landing platforms that meet the upper limit of available energy from the endpoint area information as a candidate platform set; The conflict resolution module is used to generate candidate four-dimensional tracks containing timestamps based on the candidate platform set, and to perform four-dimensional conflict detection between the candidate four-dimensional tracks and existing tracks. If a conflict exists, a hierarchical resolution strategy is executed to adjust the tracks until an optimal solution containing conflict-free tracks is generated and pushed to the user. The resource locking module is used to send a deployment command to the target stealth take-off and landing platform after the user confirms the optimal solution push, and lock the four-dimensional airspace resources occupied by the conflict-free flight path. The mission execution module is used for the aircraft to execute the conflict-free flight path mission, release the four-dimensional airspace resources after the mission is completed, and send a recovery command to the target stealth take-off and landing platform.

8. The low-altitude intelligent operation device for dynamic takeoff and landing and trajectory planning as described in claim 7, characterized in that, The stealth take-off and landing platform specifically includes: Platform panel, drive mechanism, wireless charging module, and visual guidance system; The drive mechanism is used to drive the platform panel to switch between stealth mode and working mode; The wireless charging module is used to wirelessly charge the aircraft during takeoff and landing. The visual guidance system is used to provide landing guidance signals in the operating state.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the low-altitude intelligent operation method for dynamic take-off and landing and trajectory planning as described in any one of claims 1 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the low-altitude intelligent operation method for dynamic take-off and landing and trajectory planning as described in any one of claims 1 to 6.

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