Unmanned aerial vehicle take-off and landing space-time resource scheduling system and method based on beidou grid code

Abstract

This invention relates to airspace resource scheduling, specifically to a UAV takeoff and landing spatiotemporal resource scheduling system and method based on BeiDou grid codes. The system includes a resource segmentation module that combines each time slice with the physical location of the parking space to generate spatiotemporal resource units and maps them to BeiDou grid codes; a prediction and reservation module that constructs a fish catch prediction model and reserves grid resources for future time periods with the system scheduling center based on the prediction results; a dynamic scheduling and conflict resolution module that maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests; and an automatic loading and unloading triggering module that, after the UAV lands at the parking space and undergoes spatiotemporal resource verification, loads the refrigerated crates containing the cargo into the UAV's cargo hold. The technical solution provided by this invention effectively overcomes the shortcomings of existing technologies, such as the lack of refined management of parking spaces as spatiotemporal resources and low utilization rate of parking space resources.

Description

Technical Field

[0001] This invention relates to airspace resource scheduling, specifically to a UAV take-off and landing time and space resource scheduling system and method based on BeiDou grid codes. Background Technology

[0002] Existing drone take-off and landing site management mostly adopts a centralized, single-point management approach similar to airports, relying on manual or simple queuing systems for scheduling. For multi-point take-off and landing scenarios on islands (where multiple fishing boats arrive at the island-based take-off and landing platform individually or simultaneously, and the island-based take-off and landing platform serves as the parking space), the following problems exist:

[0003] 1) Severe resource conflict: Multiple fishing boats arrive at the same time, and the drone landing space (usually only 1-2 landing spaces) becomes a bottleneck, causing cargo to wait and affecting the core goal of "seafood from capture to market within 2 hours";

[0004] 2) Disconnected from natural conditions: Resource allocation is not coordinated with tides and peak fishing seasons, resulting in idle or overloaded resources;

[0005] 3) Lack of transparency: There is a lack of digital management of the "time and space resources" of the parking space, a key node.

[0006] The root cause of these problems lies in treating island-based drone take-off and landing sites as a single, unified resource, rather than as spatiotemporal resources that can be subdivided into parking spaces. Furthermore, the discrete nature of sea fishing and the regularity of tides were not incorporated into the scheduling algorithm, resulting in low resource utilization. Summary of the Invention

[0007] (a) Technical problems to be solved

[0008] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a UAV take-off and landing spatiotemporal resource scheduling system and method based on Beidou grid code, which can effectively overcome the defects of the existing technology, such as the lack of refined management of parking spaces as spatiotemporal resources and the low utilization rate of parking space resources.

[0009] (II) Technical Solution

[0010] To achieve the above objectives, the present invention provides the following technical solution:

[0011] The UAV take-off and landing spatiotemporal resource scheduling system based on Beidou grid code includes a resource segmentation module, a prediction and reservation module, a dynamic scheduling and conflict resolution module, and an automatic loading and unloading triggering module.

[0012] The resource segmentation module combines each time slice with the physical location of the parking position to generate spatiotemporal resource units and maps them to BeiDou grid codes.

[0013] The prediction and reservation module constructs a fish catch prediction model and reserves grid resources for future time periods from the system scheduling center based on the prediction results.

[0014] The dynamic scheduling and conflict resolution module maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests.

[0015] The automatic loading and unloading trigger module loads the chilled crates containing the goods into the drone's cargo compartment after the drone lands at its parking position and performs spatiotemporal resource verification.

[0016] Preferably, the resource segmentation module combines each time slice with the physical location of the parking position to generate a spatiotemporal resource unit, and maps it to a BeiDou grid code, including:

[0017] Divide the i-th stop position into a set of time slices according to the smallest slice granularity of the time axis, Δt. , t m This refers to the m-th time slice, where m is the number of time slices.

[0018] The j-th time slice t j Physical position P of the stop position i Combined, spatiotemporal resource units are generated and mapped to BeiDou grid codes R. i,j : ; Among them, R i,j For the i-th stop position in the j-th time slice t j The BeiDou grid code is encode(·), which is the BeiDou grid encoding function.

[0019] Preferably, the prediction and reservation module constructs a catch prediction model and, based on the prediction results, reserves grid resources for future time periods with the system scheduling center, including: By integrating tidal data and historical catch data from sea fishing vessels, a catch prediction model conforming to a Poisson distribution is constructed, and the capture time t is output based on the catch prediction model. hook ; The expected arrival time (ETA) for fishing boats is: ; Among them, t preprocess For the pre-processing time on board, t boat The sailing time for sea fishing boats is a fixed value. Based on the expected arrival time of the fishing boat, the ETA reserves one or more BeiDou grid codes for future time periods with the system dispatch center.

[0020] Preferably, the dynamic scheduling and conflict resolution module maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests, including: Maintain a global spatiotemporal resource occupancy table. When the system scheduling center receives multiple reservation requests, it performs priority-based conflict resolution. The priority is calculated using the following formula: ; Among them, V value For the estimated value of the goods, △T fresh C is the time elapsed since capture. customer For each customer level, all parameters are normalized. w1, w2, and w3 are weighting coefficients, and w1+w2+w3=1. If multiple reservation requests compete for the same BeiDou grid code, the reservation requests will be automatically sorted according to priority, and the lower priority reservation requests will be scheduled to the BeiDou grid code of the adjacent time slot.

[0021] Preferably, after the drone lands at its parking position and performs a spatiotemporal resource verification, the automatic loading and unloading triggering module loads the refrigerated crate containing the goods into the drone's cargo hold, including: Once the fishing boat arrives and the cargo is placed in the refrigerated box, the system automatically generates a QR code containing the BeiDou grid code based on the assigned BeiDou grid code. After the drone arrives at its designated parking position based on the assigned BeiDou grid code, it performs a spatiotemporal resource verification by scanning a QR code. Once the verification is successful, the automatic loading and unloading trigger module is unlocked, and the chilled crates containing the goods are loaded into the drone's cargo bay.

[0022] The method for scheduling UAV takeoff and landing spatiotemporal resources based on BeiDou grid codes includes the following steps: S1. Combine each time slice with the physical location of the parking position to generate a spatiotemporal resource unit and map it as a Beidou grid code; S2. Construct a fish catch prediction model and reserve grid resources for future time periods from the system scheduling center based on the prediction results; S3. By maintaining a global spatiotemporal resource occupancy table, priority-based conflict resolution is performed on reservation requests; S4. After the drone lands at its parking position and undergoes time and space resource verification, load the chilled crate containing the goods into the drone's cargo hold.

[0023] Preferably, in S1, each time slice is combined with the physical location of the parking position to generate a spatiotemporal resource unit, which is then mapped to a BeiDou grid code, including: Divide the i-th stop position into a set of time slices according to the smallest slice granularity of the time axis, Δt. , t m This refers to the m-th time slice, where m is the number of time slices. The j-th time slice t j Physical position P of the stop position iCombined, spatiotemporal resource units are generated and mapped to BeiDou grid codes R. i,j : ; Among them, R i,j For the i-th stop position in the j-th time slice t j The BeiDou grid code is encode(·), which is the BeiDou grid encoding function.

[0024] Preferably, in S2, a fish catch prediction model is constructed, and based on the prediction results, grid resources for future time periods are reserved from the system scheduling center, including: By integrating tidal data and historical catch data from sea fishing vessels, a catch prediction model conforming to a Poisson distribution is constructed, and the capture time t is output based on the catch prediction model. hook ; The expected arrival time (ETA) for fishing boats is: ; Among them, t preprocess For the pre-processing time on board, t boat The sailing time for sea fishing boats is a fixed value. Based on the expected arrival time of the fishing boat, the ETA reserves one or more BeiDou grid codes for future time periods with the system dispatch center.

[0025] Preferably, in S3, a global spatiotemporal resource occupancy table is maintained, and priority-based conflict resolution is performed on reservation requests, including: Maintain a global spatiotemporal resource occupancy table. When the system scheduling center receives multiple reservation requests, it performs priority-based conflict resolution. The priority is calculated using the following formula: ; Among them, V value For the estimated value of the goods, △T fresh C is the time elapsed since capture. customer For each customer level, all parameters are normalized. w1, w2, and w3 are weighting coefficients, and w1+w2+w3=1. If multiple reservation requests compete for the same BeiDou grid code, the reservation requests will be automatically sorted according to priority, and the lower priority reservation requests will be scheduled to the BeiDou grid code of the adjacent time slot.

[0026] Preferably, in step S4, after the drone lands at the parking position and undergoes spatiotemporal resource verification, the refrigerated crate containing the goods is loaded into the drone's cargo hold, including: Once the fishing boat arrives and the cargo is placed in the refrigerated box, the system automatically generates a QR code containing the BeiDou grid code based on the assigned BeiDou grid code. After the drone arrives at its designated parking position based on the assigned BeiDou grid code, it performs a spatiotemporal resource verification by scanning a QR code. Once the verification is successful, the automatic loading and unloading trigger module is unlocked, and the chilled crates containing the goods are loaded into the drone's cargo bay.

[0027] (III) Beneficial Effects Compared with existing technologies, the UAV take-off and landing spatiotemporal resource scheduling system and method based on BeiDou grid codes provided by this invention have the following beneficial effects: 1) Increased throughput: By dividing the parking positions into spatiotemporal resource units and carrying out refined spatiotemporal resource scheduling, the number of flights handled per day at a single landing site can be increased by more than 30%, effectively coping with peak fishing seasons. 2) Freshness Guarantee: Time management is precise to the 10-minute level to minimize the waiting time of goods on the island; 3) High degree of automation: The spatiotemporal resource verification based on Beidou grid code provides reliable technical support for realizing fully automated unmanned loading and unloading. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0029] Figure 1 This is a schematic diagram of the system of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0031] The following describes the specific functional modules of the UAV takeoff and landing spatiotemporal resource scheduling system based on BeiDou grid codes provided by this invention, using concrete examples (such as...). Figure 1 (As shown) and its technical effects. The system's functional modules include: resource partitioning module, prediction and reservation module, dynamic scheduling and conflict resolution module, and automatic loading / unloading triggering module; The resource segmentation module combines each time slice with the physical location of the parking position to generate spatiotemporal resource units and maps them to BeiDou grid codes. The prediction and reservation module constructs a fish catch prediction model and reserves grid resources for future time periods from the system scheduling center based on the prediction results. The dynamic scheduling and conflict resolution module maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests. The automatic loading and unloading trigger module loads the chilled crates containing the goods into the drone's cargo compartment after the drone lands at its parking position and performs spatiotemporal resource verification.

[0032] I. Resource Partitioning Module The resource segmentation module combines each time slice with the physical location of the parking position to generate spatiotemporal resource units, which are then mapped to BeiDou grid codes, including: Divide the i-th stop position into a set of time slices according to the smallest slice granularity of the time axis, Δt (Δt = 10 min). , t m This refers to the m-th time slice, where m is the number of time slices. The j-th time slice t j Physical position P of the stop position i Combined, spatiotemporal resource units are generated and mapped to BeiDou grid codes R. i,j : ; Among them, R i,j For the i-th stop position in the j-th time slice t j The BeiDou grid code is encode(·), which is the BeiDou grid encoding function.

[0033] II. Prediction and Reservation Module The forecasting and reservation module constructs a catch prediction model and, based on the prediction results, reserves grid resources for future time periods with the system scheduling center, including: By integrating tidal data and historical catch data from sea fishing vessels, a catch prediction model conforming to a Poisson distribution is constructed, and the capture time t is output based on the catch prediction model. hook ; The expected arrival time (ETA) for fishing boats is: ; Among them, t preprocess The pretreatment time on board (fixed at 30 minutes), t boat The sailing time for the sea fishing boat is fixed at 10 minutes. Based on the expected arrival time of the fishing boat, the ETA reserves one or more BeiDou grid codes for future time periods with the system dispatch center.

[0034] III. Dynamic Scheduling and Conflict Resolution Module The dynamic scheduling and conflict resolution module maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests, including: Maintain a global spatiotemporal resource occupancy table. When the system scheduling center receives multiple reservation requests, it performs priority-based conflict resolution. The priority is calculated using the following formula: ; Among them, V value For the estimated value of goods (e.g., tuna > large yellow croaker), △T fresh C is the time elapsed since capture. customer For each customer level, all parameters are normalized. w1, w2, and w3 are weighting coefficients, and w1+w2+w3=1. If multiple reservation requests compete for the same BeiDou grid code, the reservation requests will be automatically sorted according to priority, and the lower priority reservation requests will be scheduled to the BeiDou grid code of the adjacent time slot.

[0035] In the technical solution of this application, more factors can be introduced into the priority calculation function, such as the remaining battery power of the drone and the weather window. Meanwhile, conflict resolution can employ an "auction mechanism," allowing high-value goods to obtain higher priority by paying a fee.

[0036] IV. Automatic Loading / Unloading Trigger Module After the drone lands at its parking position and undergoes a spatiotemporal resource verification, the automatic loading and unloading trigger module loads the refrigerated crates containing the goods into the drone's cargo bay, including: Once the fishing boat arrives and the cargo is placed in the refrigerated box, the system automatically generates a QR code containing the BeiDou grid code based on the assigned BeiDou grid code. After the drone arrives at its designated parking position based on the assigned BeiDou grid code, it performs a spatiotemporal resource verification by scanning a QR code. Once the verification is successful, the automatic loading and unloading trigger module is unlocked, and the chilled crates containing the goods are loaded into the drone's cargo bay.

[0037] Based on the aforementioned disclosure of a UAV takeoff and landing spatiotemporal resource scheduling system based on BeiDou grid codes, this invention also discloses a UAV takeoff and landing spatiotemporal resource scheduling method based on BeiDou grid codes, comprising the following steps: S1. Combine each time slice with the physical location of the parking position to generate a spatiotemporal resource unit and map it as a Beidou grid code; S2. Construct a fish catch prediction model and reserve grid resources for future time periods from the system scheduling center based on the prediction results; S3. By maintaining a global spatiotemporal resource occupancy table, priority-based conflict resolution is performed on reservation requests; S4. After the drone lands at its parking position and undergoes time and space resource verification, load the chilled crate containing the goods into the drone's cargo hold.

[0038] Specifically, S1 combines each time slice with the physical location of the parking position to generate spatiotemporal resource units, which are then mapped to BeiDou grid codes, including: Divide the i-th stop position into a set of time slices according to the smallest slice granularity of the time axis, Δt. , t m This refers to the m-th time slice, where m is the number of time slices. The j-th time slice t j Physical position P of the stop position i Combined, spatiotemporal resource units are generated and mapped to BeiDou grid codes R. i,j : ; Among them, R i,j For the i-th stop position in the j-th time slice t j The BeiDou grid code is encode(·), which is the BeiDou grid encoding function.

[0039] Specifically, S2 constructs a fish catch prediction model and, based on the prediction results, reserves grid resources for future time periods with the system scheduling center, including: By integrating tidal data and historical catch data from sea fishing vessels, a catch prediction model conforming to a Poisson distribution is constructed, and the capture time t is output based on the catch prediction model. hook ; The expected arrival time (ETA) for fishing boats is: ; Among them, t preprocess For the pre-processing time on board, t boat The sailing time for sea fishing boats is a fixed value. Based on the expected arrival time of the fishing boat, the ETA reserves one or more BeiDou grid codes for future time periods with the system dispatch center.

[0040] Specifically, S3 maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests, including: Maintain a global spatiotemporal resource occupancy table. When the system scheduling center receives multiple reservation requests, it performs priority-based conflict resolution. The priority is calculated using the following formula: ; Among them, V value For the estimated value of the goods, △T fresh C is the time elapsed since capture. customerFor each customer level, all parameters are normalized. w1, w2, and w3 are weighting coefficients, and w1+w2+w3=1. If multiple reservation requests compete for the same BeiDou grid code, the reservation requests will be automatically sorted according to priority, and the lower priority reservation requests will be scheduled to the BeiDou grid code of the adjacent time slot.

[0041] Specifically, in S4, after the drone lands at its parking position and undergoes spatiotemporal resource verification, the refrigerated crates containing the goods are loaded into the drone's cargo bay, including: Once the fishing boat arrives and the cargo is placed in the refrigerated box, the system automatically generates a QR code containing the BeiDou grid code based on the assigned BeiDou grid code. After the drone arrives at its designated parking position based on the assigned BeiDou grid code, it performs a spatiotemporal resource verification by scanning a QR code. Once the verification is successful, the automatic loading and unloading trigger module is unlocked, and the chilled crates containing the goods are loaded into the drone's cargo bay.

[0042] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. 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 of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A UAV take-off and landing spatiotemporal resource scheduling system based on BeiDou grid codes, characterized in that: It includes a resource partitioning module, a prediction and reservation module, a dynamic scheduling and conflict resolution module, and an automatic loading and unloading triggering module; The resource segmentation module combines each time slice with the physical location of the parking position to generate spatiotemporal resource units and maps them to BeiDou grid codes. The prediction and reservation module constructs a fish catch prediction model and reserves grid resources for future time periods from the system scheduling center based on the prediction results. The dynamic scheduling and conflict resolution module maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests. The automatic loading and unloading trigger module loads the chilled crates containing the goods into the drone's cargo compartment after the drone lands at its parking position and performs spatiotemporal resource verification.

2. The UAV takeoff and landing spatiotemporal resource scheduling system based on BeiDou grid code according to claim 1, characterized in that: The resource segmentation module combines each time slice with the physical location of the parking position to generate spatiotemporal resource units, which are then mapped to BeiDou grid codes, including: Divide the i-th stop position into a set of time slices according to the smallest slice granularity of the time axis, Δt. , t m This refers to the m-th time slice, where m is the number of time slices. The j-th time slice t j Physical position P of the stop position i Combined, spatiotemporal resource units are generated and mapped to BeiDou grid codes R. i,j : ； Among them, R i,j For the i-th stop position in the j-th time slice t j The BeiDou grid code is encode(·), which is the BeiDou grid encoding function.

3. The UAV takeoff and landing spatiotemporal resource scheduling system based on BeiDou grid code according to claim 2, characterized in that: The prediction and reservation module constructs a catch prediction model and, based on the prediction results, reserves grid resources for future time periods with the system scheduling center, including: By integrating tidal data and historical catch data from sea fishing vessels, a catch prediction model conforming to a Poisson distribution is constructed, and the capture time t is output based on the catch prediction model. hook ; The expected arrival time (ETA) for fishing boats is: ； Among them, t preprocess For the pre-processing time on board, t boat The sailing time for sea fishing boats is a fixed value. Based on the expected arrival time of the fishing boat, the ETA reserves one or more BeiDou grid codes for future time periods with the system dispatch center.

4. The UAV takeoff and landing spatiotemporal resource scheduling system based on BeiDou grid code according to claim 3, characterized in that: The dynamic scheduling and conflict resolution module maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests, including: Maintain a global spatiotemporal resource occupancy table. When the system scheduling center receives multiple reservation requests, it performs priority-based conflict resolution. The priority is calculated using the following formula: ； Among them, V value For the estimated value of the goods, △T fresh C is the time elapsed since capture. customer For each customer level, all parameters are normalized. w1, w2, and w3 are weighting coefficients, and w1+w2+w3=1. If multiple reservation requests compete for the same BeiDou grid code, the reservation requests will be automatically sorted according to priority, and the lower priority reservation requests will be scheduled to the BeiDou grid code of the adjacent time slot.

5. The UAV takeoff and landing spatiotemporal resource scheduling system based on BeiDou grid code according to claim 4, characterized in that: The automatic loading and unloading triggering module loads the refrigerated crates containing the goods into the drone's cargo hold after the drone lands at its parking position and performs a spatiotemporal resource verification. This includes: Once the fishing boat arrives and the cargo is placed in the refrigerated box, the system automatically generates a QR code containing the BeiDou grid code based on the assigned BeiDou grid code. After the drone arrives at its designated parking position based on the assigned BeiDou grid code, it performs a spatiotemporal resource verification by scanning a QR code. Once the verification is successful, the automatic loading and unloading trigger module is unlocked, and the chilled crates containing the goods are loaded into the drone's cargo bay.

6. A method for scheduling UAV takeoff and landing spatiotemporal resources based on BeiDou grid codes, applicable to the UAV takeoff and landing spatiotemporal resource scheduling system based on BeiDou grid codes as described in claim 1, characterized in that: Includes the following steps: S1. Combine each time slice with the physical location of the parking position to generate a spatiotemporal resource unit and map it as a Beidou grid code; S2. Construct a fish catch prediction model and reserve grid resources for future time periods from the system scheduling center based on the prediction results; S3. By maintaining a global spatiotemporal resource occupancy table, priority-based conflict resolution is performed on reservation requests; S4. After the drone lands at its parking position and undergoes time and space resource verification, load the chilled crate containing the goods into the drone's cargo hold.

7. The method for scheduling UAV takeoff and landing spatiotemporal resources based on BeiDou grid codes according to claim 6, characterized in that: S1 combines each time slice with the physical location of the parking position to generate a spatiotemporal resource unit, which is then mapped to a BeiDou grid code, including: Divide the i-th stop position into a set of time slices according to the smallest slice granularity of the time axis, Δt. , t m This refers to the m-th time slice, where m is the number of time slices. The j-th time slice t j Physical position P of the stop position i Combined, spatiotemporal resource units are generated and mapped to BeiDou grid codes R. i,j : ； Among them, R i,j For the i-th stop position in the j-th time slice t j The BeiDou grid code is encode(·), which is the BeiDou grid encoding function.

8. The method for scheduling UAV takeoff and landing spatiotemporal resources based on BeiDou grid codes according to claim 7, characterized in that: In S2, a fish catch prediction model is constructed, and based on the prediction results, grid resources for future time periods are reserved from the system scheduling center, including: By integrating tidal data and historical catch data from sea fishing vessels, a catch prediction model conforming to a Poisson distribution is constructed, and the capture time t is output based on the catch prediction model. hook ; The expected arrival time (ETA) for fishing boats is: ； Among them, t preprocess For the pre-processing time on board, t boat The sailing time for sea fishing boats is a fixed value. Based on the expected arrival time of the fishing boat, the ETA reserves one or more BeiDou grid codes for future time periods with the system dispatch center.

9. The method for scheduling UAV takeoff and landing spatiotemporal resources based on BeiDou grid codes according to claim 8, characterized in that: S3 maintains a global spatiotemporal resource occupancy table and performs priority-based conflict resolution for reservation requests, including: Maintain a global spatiotemporal resource occupancy table. When the system scheduling center receives multiple reservation requests, it performs priority-based conflict resolution. The priority is calculated using the following formula: ； Among them, V value For the estimated value of the goods, △T fresh C is the time elapsed since capture. customer For each customer level, all parameters are normalized. w1, w2, and w3 are weighting coefficients, and w1+w2+w3=1. If multiple reservation requests compete for the same BeiDou grid code, the reservation requests will be automatically sorted according to priority, and the lower priority reservation requests will be scheduled to the BeiDou grid code of the adjacent time slot.

10. The method for scheduling UAV takeoff and landing spatiotemporal resources based on BeiDou grid codes according to claim 9, characterized in that: In S4, after the drone lands at its parking position and undergoes spatiotemporal resource verification, the refrigerated crates containing the goods are loaded into the drone's cargo bay, including: Once the fishing boat arrives and the cargo is placed in the refrigerated box, the system automatically generates a QR code containing the BeiDou grid code based on the assigned BeiDou grid code. After the drone arrives at its designated parking position based on the assigned BeiDou grid code, it performs a spatiotemporal resource verification by scanning a QR code. Once the verification is successful, the automatic loading and unloading trigger module is unlocked, and the chilled crates containing the goods are loaded into the drone's cargo bay.

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