Dynamic take-off and landing accurate docking method for low-altitude aircraft and medium-heavy truck

Abstract

The invention provides a dynamic take-off and landing accurate docking method for a low-altitude aircraft and a medium-heavy truck. The method comprises the following sub-steps: S1, collecting data of a medium-heavy truck end and uploading the data to a cloud end; s2, the cloud end receives medium and heavy truck end data and generates a dynamic docking plan; s3, generating and issuing a dynamic docking plan; s4, dynamic take-off and landing accurate docking is executed; through the combination of a multi-source fusion positioning technology, an anti-bumping attitude control module and a high-precision differential positioning technology, the positioning precision is remarkably improved, the relative position and attitude of the aircraft and the truck can be monitored in real time in the driving process of the truck, the attitude of the aircraft is adjusted according to dynamic changes such as bumping of the truck, the deviation is prevented from being too large, and the positioning precision is improved. Therefore, high-precision dynamic butt joint is ensured; the low-altitude aircraft can be intelligently adjusted according to the real-time condition of the truck, cooperative scheduling between the aircraft and the truck is achieved, waiting time and no-load operation are reduced, and the use efficiency of resources is improved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of dynamic take-off and landing docking, and in particular to a dynamic take-off and landing precise docking method for a low-altitude aircraft and a medium / heavy truck. BACKGROUND

[0002] With the low-altitude economy being included in the strategic emerging industry, relevant policies continue to promote the construction of the "air-ground integration" system. The medium / heavy truck, as the core carrier of the trunk line logistics, and the low-altitude aircraft, as the "trunk line + terminal" connection, become the key link to break through the whole logistics chain. At present, the low-altitude aircraft needs to frequently complete dynamic take-off and landing docking with the medium / heavy truck in the running or parking state in the scenes of industrial logistics, emergency logistics, mine / port special operation and the like, but the existing docking method still has the following disadvantages: The positioning accuracy is insufficient and cannot match the dynamic docking demand: in the prior art, the GNSS positioning is mostly relied on, and the high-precision differential positioning and multi-source sensor correction are not fused. In the scene of truck jolting, the docking deviation rate of the aircraft and the truck cargo compartment is too high, and the static take-off and landing algorithm cannot dynamically adapt to the vehicle shaking, resulting in a low docking success rate. The vehicle-machine data is fragmented and the collaborative scheduling is rigid: the aircraft cannot obtain the truck state in real time, such as the load, the cargo compartment position and the like, and can only take off and land according to the pre-planned program, resulting in resource waste such as "truck early arrival waiting" and "aircraft empty round trip", and the task cannot be collaboratively scheduled, and the efficiency is low. SUMMARY

[0003] The application aims at solving the problems in the prior art and provides a dynamic take-off and landing precise docking method for a low-altitude aircraft and a medium / heavy truck.

[0004] To achieve the above-mentioned purpose, the application adopts the following technical scheme: The dynamic take-off and landing precise docking system for the low-altitude aircraft and the medium / heavy truck comprises a low-altitude aircraft end, a cloud end and a medium / heavy truck end. The low-altitude aircraft end takes a DBOX intelligent terminal as a core carrier and comprises a multi-source fusion positioning module, an anti-jolting attitude control module and a communication module. The medium / heavy truck end takes a TBOX as a core carrier and comprises a data acquisition module, a vehicle-machine data transmission module and a suspension collaborative control module. The cloud end takes a vehicle-air route cloud intelligence networking system as a core carrier and comprises a digital twin scene construction module, a dynamic scheduling algorithm module and a communication module. Specifically, the dynamic take-off and landing precise docking method for the low-altitude aircraft and the medium / heavy truck comprises the following sub-steps: S1: collect the medium / heavy truck end data and upload to the cloud end; The data acquisition module collects the medium and heavy truck end data through the TBOX, and the medium and heavy truck end data includes cargo carrying data, space-time scheduling data, driving state data, cargo compartment state data, and medium and heavy truck equipment parameters; The cargo carrying data includes cargo weight and cargo category (such as cold chain fresh food, precision parts, etc.); The driving state data includes real-time driving speed and driving jolt amplitude, etc. The space-time scheduling data includes real-time estimated arrival time of the target docking point, target docking point position coordinates, etc. The cargo compartment state data includes real-time position coordinates of the medium and heavy truck cargo compartment, real-time loading / unloading port state of the medium and heavy truck cargo compartment, etc. The medium and heavy truck equipment parameters include cargo compartment structure parameters, suspension system parameters, and loading / unloading port structure parameters, etc. The vehicle data transmission module uploads the collected medium and heavy truck end data and corresponding time stamp to the cloud.

[0005] S2: The cloud receives the medium and heavy truck end data and generates a dynamic docking plan; including the following sub-steps: S21: Verify the received medium and heavy truck end data; The cloud receives the medium and heavy truck end data and records the current time, and verifies the received medium and heavy truck end data, which includes integrity verification, accuracy verification, timeliness verification, etc. The cloud's vehicle-space-road cloud intelligent networking system has pre-set list fields to be collected, reasonable threshold ranges, and transmission delay thresholds; S211: Perform integrity verification; Compare the received medium and heavy truck end data with the list fields to be collected. If any one or more of the list fields to be collected is missing in the received medium and heavy truck end data, it is determined that the data is incomplete. The cloud generates a prompt message through the data interaction unit and transmits the prompt message to the vehicle data transmission module; The prompt message includes the determination result, the missing field list, and the operation instruction to require supplementing the missing fields and uploading them in priority; If the received medium and heavy truck end data contains all the list fields to be collected, the integrity verification is passed, and step S212 is entered; S212: Perform accuracy verification; Compare each item of the received medium and heavy truck end data with the corresponding reasonable threshold range. If it is not within the reasonable threshold range, it is determined that the data is inaccurate. The cloud generates a prompt message through the data interaction unit and transmits the prompt message to the vehicle data transmission module; The prompt information includes the judgment result, a list of inaccurate fields, and an operation instruction to re-collect the inaccurate fields and upload them first. If each item of the received medium and heavy truck terminal data is within the corresponding reasonable threshold range, the accuracy verification is passed, and the process proceeds to step S213. S213: Perform timeliness verification; The difference between the timestamp in the received data from the medium and heavy-duty truck terminal and the current time recorded in the cloud is calculated. This difference is the transmission delay. The transmission delay is compared with the set transmission delay threshold. If the transmission delay is greater than the transmission delay threshold, the data is determined to be expired. The cloud generates a prompt message through the data interaction unit and transmits the prompt message to the vehicle data transmission module. The prompt information includes the judgment result and an operation instruction requiring re-collection and uploading; If the transmission delay is less than or equal to the transmission delay threshold, the timeliness check passes.

[0006] S22: Build a 3D dynamic scene based on the verified data; S221: Real-time synchronization data from low-altitude aircraft; The real-time data from the low-altitude aircraft is uploaded to the cloud via DBOX synchronization. The low-altitude aircraft data includes basic flight data, equipment status data, environmental perception data, low-altitude aircraft physical parameters, and timestamps. The basic flight data includes the real-time position coordinates, flight speed, flight altitude, attitude angles, etc. of the low-altitude aircraft; The device status data includes remaining battery power, battery life, load weight, and load fixation status (including fixed, loose, etc.); The environmental sensing data includes real-time wind speed, visibility, etc. The physical parameters of the low-altitude aircraft include fuselage structural parameters, power interface parameters, load-related parameters, etc. S222: Cloud-based construction of 3D dynamic scenes; The cloud performs integrity, accuracy, and timeliness checks on the received low-altitude aircraft data. After the checks are completed, the cloud-based digital twin scene construction module aligns the medium and heavy truck data and the low-altitude aircraft data according to the timestamp. The aligned low-altitude aircraft data and medium and heavy truck data are then imported into the medium and heavy truck 3D model that is completely consistent with the equipment parameters of the medium and heavy truck and the low-altitude aircraft 3D model that is completely consistent with the physical parameters of the low-altitude aircraft. The digital twin scene construction module uses digital twin technology to import the three-dimensional models of medium and heavy trucks and low-altitude aircraft into a three-dimensional dynamic scene that is consistent with the physical space of the actual driving section of the low-altitude aircraft and medium and heavy trucks; S223: Receive data and update model status in real time; The cloud system imports the verified data from the low-altitude aircraft and the medium- and heavy-duty truck into the corresponding 3D models of the low-altitude aircraft and the medium- and heavy-duty truck in real time, updates the status of the 3D models of the low-altitude aircraft and the medium- and heavy-duty truck in real time, performs dynamic simulation, and generates the motion trajectories of the low-altitude aircraft and the medium- and heavy-duty truck. S3: Generate and distribute dynamic docking plans; The dynamic scheduling algorithm module extracts data from the low-altitude aircraft and the medium and heavy-duty truck. Based on the dynamic simulation of the three-dimensional models of the low-altitude aircraft and the medium and heavy-duty truck in the three-dimensional dynamic scene, it generates a dynamic docking plan. The dynamic docking plan includes the docking time window, docking position, attitude adjustment angle of the low-altitude aircraft, and suspension damping coefficient of the medium and heavy-duty truck. The digital twin scenario construction module simulates the generated dynamic docking plan until it is determined that there is no risk of collision or deviation, and the plan is deemed feasible; otherwise, the dynamic scheduling algorithm module regenerates the dynamic docking plan.

[0007] S4: Performs dynamic takeoff and landing with precise docking; S41: Low-altitude aircraft and medium- and heavy-duty trucks conduct dynamic coordination preparation; The cloud-based system uses a communication module to send the dynamic docking plan to the DBOX on the low-altitude aircraft and the TBOX on the medium and heavy-duty truck. The low-altitude aircraft adjusts its flight path and attitude angle based on a dynamic docking plan. The medium and heavy-duty truck side adjusts driving status data and prepares the cargo hold based on the dynamic docking plan; S42: Both parties coordinate and prepare for and confirm the docking window; The cloud-based system exchanges and schedules data in real time with both the low-altitude aircraft and the medium and heavy-duty truck via a communication module. After receiving feedback from both sides (such as the aircraft being successfully adjusted or the truck being ready), the cloud-based system will confirm whether to proceed to the docking phase. If there is any abnormal feedback or time misalignment, the cloud-based system will immediately readjust the docking plan and reissue it. The cloud platform monitors the actual movement of low-altitude aircraft and medium- and heavy-duty trucks in real time to confirm that the aircraft and truck reach the docking position within the set docking time window. S43: Conduct actual dynamic takeoff and landing docking; When the low-altitude aircraft approaches the medium and heavy-duty truck, the aircraft will continue to adjust its attitude and flight path according to real-time data to accurately dock with the cargo hold. The cargo hold of the medium and heavy-duty truck will adjust its position and status according to the dynamic docking plan to ensure that the docking position and angle of the cargo hold and the aircraft match. During the docking process, the low-altitude aircraft and the medium and heavy-duty truck will maintain dynamic coordination. After the low-altitude aircraft successfully docks with the medium- and heavy-duty truck, the system sends a success notification via the communication module; the cloud records the docking data and generates a docking report based on the status of the aircraft and the truck.

[0008] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention significantly improves positioning accuracy by combining multi-source fusion positioning technology, anti-bump attitude control module and high-precision differential positioning technology. During truck driving, it can monitor the relative position and attitude of the aircraft and the truck in real time, and adjust the attitude of the aircraft according to dynamic changes such as vehicle bumps to avoid excessive deviation, thereby ensuring high-precision dynamic docking. This invention introduces a two-way feedback mechanism based on a communication module. During the dynamic docking process, the low-altitude aircraft and the medium- and heavy-duty truck exchange data in real time, and the cloud adjusts the docking plan based on the feedback. Through this real-time dynamic adjustment, a rapid response can be made when problems occur, ensuring the smooth progress of the docking process. Attached Figure Description

[0009] Figure 1 This is a flowchart illustrating the steps of the dynamic take-off and landing precision docking method for low-altitude aircraft and medium-to-heavy-duty trucks based on the present invention. Detailed Implementation

[0010] To provide a further understanding of the purpose, structure, features, and functions of the present invention, detailed descriptions are provided below with reference to specific embodiments.

[0011] A dynamic take-off and landing precision docking system based on low-altitude aircraft and medium and heavy-duty trucks, the system including the low-altitude aircraft end, the cloud end, and the medium and heavy-duty truck end; The low-altitude aircraft terminal uses the DBOX smart terminal as its core carrier and includes a multi-source fusion positioning module, an anti-turbulence attitude control module, and a communication module. The medium and heavy-duty truck terminal uses TBOX as its core carrier and includes a data acquisition module, a vehicle-to-everything (V2X) data transmission module, and a suspension coordination control module. The cloud platform is based on the vehicle-air-road-cloud intelligent network system, which includes a digital twin scenario construction module, a dynamic scheduling algorithm module, and a communication module.

[0012] like Figure 1 As shown, a method for precise dynamic take-off and landing docking between a low-altitude aircraft and a medium-to-heavy-duty truck includes the following sub-steps: S1: Collect data from medium and heavy-duty trucks and upload it to the cloud; The data acquisition module collects medium and heavy-duty truck terminal data through TBOX, which includes cargo data, time and air conditioning scheduling data, driving status data, and cargo compartment status data. The cargo data includes cargo weight and cargo type (such as cold chain fresh food, precision parts, etc.). The time and temperature data includes the estimated time to reach the target transfer point and the coordinates of the target transfer point. The driving status data includes real-time driving speed, driving bump amplitude, etc. The cargo hold status data includes the real-time location coordinates of the medium and heavy-duty truck cargo hold and the real-time loading and unloading port status of the medium and heavy-duty truck cargo hold. The vehicle-mounted data transmission module uploads the collected data from medium and heavy-duty trucks to the cloud.

[0013] Specifically, the load weight is collected in real time by the weighing sensors on the medium and heavy trucks, and the type of goods is identified by RFID tags in the cargo compartment of the medium and heavy trucks. The TBOX uses its built-in GNSS positioning module to obtain the real-time estimated arrival time at the target docking point and the coordinates of the target docking point. The real-time driving speed of the medium and heavy truck's electronic control unit (ECU) is read via the CAN bus protocol, and the amplitude of driving bumps is collected via the MEMS gyroscope integrated in the TBOX. The real-time position coordinates of the cargo compartment are obtained by a laser rangefinder on the top of the cargo compartment of the medium and heavy truck, and the opening and closing status of the loading and unloading port is determined by a proximity sensor on the loading and unloading port of the cargo compartment. Preferably, the method for obtaining the real-time estimated time to reach the target connection point is as follows: Based on the location coordinates of the target docking point and the real-time location coordinates of the medium and heavy truck cargo compartment, the real-time distance between the medium and heavy truck cargo compartment and the target docking point is calculated using the Haversine distance formula; the base time is obtained by dividing the real-time distance by the real-time driving speed. By accessing the open data interface of the local management department through the wireless communication module of TBOX, the real-time traffic information released by the official authorities can be obtained and converted into traffic correction coefficients. For example, the coefficient for smooth traffic is 1.0 (no correction), slow traffic is 1.3 (time increases by 30%), and congested traffic is 2.0 (time doubles). The driving speed sequence of medium and heavy trucks within time period A is collected by TBOX, and the speed volatility (standard deviation of driving speed sequence / average speed of driving speed sequence) is calculated. A speed volatility threshold a is preset. If the calculated speed volatility is greater than the speed volatility threshold a, it is determined that the speed is unstable; otherwise, it is determined that the speed is stable. The determination result is converted into a stability coefficient, for example, 1.0 for stable and 1.2 for unstable. By pre-setting the weights of road condition correction coefficients and stability coefficients, the base time is corrected to obtain the real-time estimated time to reach the target connection point; Real-time estimated time to reach the target pick-up point = base time * (road condition correction factor * corresponding weight + stability factor * corresponding weight); TBOX recalculates the estimated time to reach the target connection point in real time at a set frequency and transmits it to the cloud.

[0014] S2: The cloud receives data from medium and heavy-duty trucks and generates a dynamic docking plan; Includes the following sub-steps: S21: Verify the received data from the medium and heavy-duty truck end; The cloud receives data from medium and heavy-duty truck terminals and records the current time, and verifies the received data, including integrity verification, accuracy verification, and timeliness verification. The cloud-based vehicle-air-road intelligent network system pre-sets the list of fields to be collected, reasonable threshold ranges, and transmission delay thresholds. S211: Perform integrity verification; The received data from the medium and heavy-duty truck terminal is compared with the list fields to be collected. If any one or more of the list fields to be collected are missing in the received data from the medium and heavy-duty truck terminal, the data is determined to be incomplete. The cloud generates a prompt message through the data interaction unit and transmits the prompt message to the vehicle data transmission module. The prompt information includes the judgment result, a list of missing fields, and an operation instruction to collect the missing fields and upload them first. If the received data from the medium and heavy truck end contains all the list fields that need to be collected, then the integrity check passes and proceeds to step S212. S212: Perform accuracy verification; The received data from medium and heavy-duty trucks is compared item by item with the corresponding reasonable threshold range. If the data is not within the reasonable threshold range, it is determined that the data is inaccurate. The cloud generates a prompt message through the data interaction unit and transmits the prompt message to the vehicle data transmission module. The prompt information includes the judgment result, a list of inaccurate fields, and an operation instruction to re-collect the inaccurate fields and upload them first. If each item of the received medium and heavy truck terminal data is within the corresponding reasonable threshold range, the accuracy verification is passed, and the process proceeds to step S213. S213: Perform timeliness verification; The difference between the timestamp in the received data from the medium and heavy-duty truck terminal and the current time recorded in the cloud is calculated. This difference is the transmission delay. The transmission delay is compared with the set transmission delay threshold. If the transmission delay is greater than the transmission delay threshold, the data is determined to be expired. The cloud generates a prompt message through the data interaction unit and transmits the prompt message to the vehicle data transmission module. The prompt information includes the judgment result and an operation instruction requiring re-collection and uploading; If the transmission delay is less than or equal to the transmission delay threshold, the timeliness check passes.

[0015] S22: Build a 3D dynamic scene based on the verified data; S221: Real-time synchronization data from low-altitude aircraft; The real-time data from the low-altitude aircraft is uploaded to the cloud via DBOX synchronization. The low-altitude aircraft data includes basic flight data, equipment status data, environmental perception data, low-altitude aircraft physical parameters, and timestamps. The basic flight data includes the real-time position coordinates, flight speed, flight altitude, attitude angles, etc. of the low-altitude aircraft; The device status data includes remaining battery power, battery life, load weight, and load fixation status (including fixed, loose, etc.); The environmental sensing data includes real-time wind speed, visibility, etc. The physical parameters of the low-altitude aircraft include fuselage structural parameters, power interface parameters, load-related parameters, etc. S222: Cloud-based construction of 3D dynamic scenes; The cloud performs integrity, accuracy, and timeliness checks on the received low-altitude aircraft data. After the checks are completed, the cloud-based digital twin scene construction module aligns the medium and heavy truck data and the low-altitude aircraft data according to the timestamp. The aligned low-altitude aircraft data and medium and heavy truck data are then imported into the medium and heavy truck 3D model that is completely consistent with the equipment parameters of the medium and heavy truck and the low-altitude aircraft 3D model that is completely consistent with the physical parameters of the low-altitude aircraft. The digital twin scene construction module uses digital twin technology to import the three-dimensional models of medium and heavy trucks and low-altitude aircraft into a three-dimensional dynamic scene that is consistent with the physical space of the actual driving section of the low-altitude aircraft and medium and heavy trucks; S223: Receive data and update model status in real time; The cloud system imports the verified data from the low-altitude aircraft and the medium- and heavy-duty truck into the corresponding 3D models of the low-altitude aircraft and the medium- and heavy-duty truck in real time, updates the status of the 3D models of the low-altitude aircraft and the medium- and heavy-duty truck in real time, performs dynamic simulation, and generates the motion trajectories of the low-altitude aircraft and the medium- and heavy-duty truck. S3: Generate and distribute dynamic docking plans; The dynamic scheduling algorithm module extracts data from the low-altitude aircraft and the medium and heavy-duty truck. Based on the dynamic simulation of the three-dimensional models of the low-altitude aircraft and the medium and heavy-duty truck in the three-dimensional dynamic scene, it generates a dynamic docking plan. The dynamic docking plan includes docking time window, docking position, attitude adjustment angle of low-altitude aircraft, suspension damping coefficient of medium and heavy-duty truck, etc. Specifically, the dynamic scheduling algorithm module extracts data from the low-altitude aircraft and the medium and heavy-duty truck, and maps the data from the low-altitude aircraft and the medium and heavy-duty truck to the three-dimensional models of the low-altitude aircraft and the medium and heavy-duty truck, respectively, to simultaneously simulate the motion state of the low-altitude aircraft and the medium and heavy-duty truck. The Kalman filter algorithm is used to predict the trajectory and interaction time of low-altitude aircraft and medium- and heavy-duty trucks. Based on the trajectory and interaction time, the docking time window is determined. The docking position is determined based on the real-time position coordinates of the cargo hold and the driving trajectory using a high-precision differential positioning algorithm. The attitude adjustment angle of the low-altitude aircraft is obtained by using the PID control algorithm based on the docking position, the current attitude angle of the low-altitude aircraft, and environmental perception data. The suspension damping coefficient of medium and heavy-duty trucks is obtained based on the current driving bump amplitude using a suspension dynamics model.

[0016] The digital twin scenario construction module simulates the generated dynamic docking plan until it is determined that there is no risk of collision or deviation, and the plan is deemed feasible; otherwise, the dynamic scheduling algorithm module regenerates the dynamic docking plan.

[0017] This invention integrates multi-source data from low-altitude aircraft and medium- and heavy-duty trucks through a cloud-based data acquisition and processing system. By utilizing dynamic scheduling algorithms and digital twin technology, it constructs a three-dimensional dynamic scene in real time, performs dynamic simulation, and accurately generates docking plans. This improves the accuracy and adaptability of docking plans, ensuring that low-altitude aircraft and medium- and heavy-duty trucks can efficiently and safely complete dynamic docking in actual operation.

[0018] S4: Performs dynamic takeoff and landing with precise docking; S41: Low-altitude aircraft and medium- and heavy-duty trucks conduct dynamic coordination preparation; The cloud-based system uses a communication module to send the dynamic docking plan to the DBOX on the low-altitude aircraft and the TBOX on the medium and heavy-duty truck. Preferably, after receiving the dynamic docking plan, a successful reception signal is returned within a set time. If the cloud does not receive feedback or the feedback content is "plan abnormal", the cloud immediately regenerates the dynamic docking plan and sends it out a second time. The low-altitude aircraft adjusts its flight path and attitude angle based on a dynamic docking plan. Specifically, the multi-source fusion positioning module combines environmental perception data, the docking position in the dynamic docking plan, and the docking time window to scan obstacles and adjust the flight path and speed pointing to the docking position based on the remaining battery power. The anti-turbulence attitude control module breaks down the attitude adjustment angle of the low-altitude aircraft in the dynamic docking plan into altitude compensation parameters and heading correction parameters, and adjusts the attitude angle of the low-altitude aircraft by combining altitude deviation and heading deviation. Specifically, the anti-turbulence attitude control module extracts the attitude adjustment angle of the low-altitude aircraft in the dynamic docking plan, and converts the vertical component of the attitude adjustment angle of the low-altitude aircraft into altitude compensation parameters (including altitude compensation amount, vertical adjustment rate, etc.) through parameter decomposition algorithm, and converts the horizontal component of the attitude adjustment angle of the low-altitude aircraft into heading correction parameters (including heading angle correction amount, roll angle compensation amount, etc.). The altitude deviation between the current altitude of the aircraft and the target docking altitude, as well as the heading deviation between the current heading and the target docking heading, are obtained in real time through laser ranging, GNSS, etc.; the anti-interference PID algorithm is used to dynamically output attitude angle control commands according to the magnitude of the deviation, with the extracted altitude compensation and heading correction parameters as the target, and the altitude angle, heading angle and roll angle are adjusted. The medium and heavy-duty truck side adjusts driving status data and prepares the cargo hold based on the dynamic docking plan; The suspension coordination control module adjusts the real-time driving speed and reduces the amplitude of driving bumps by adjusting the suspension damping coefficient and docking time window of the medium and heavy trucks in the dynamic docking plan through the CAN bus; the data acquisition module increases the frequency of cargo compartment status acquisition, and the lidar sends the loading and unloading port coordinate correction value in real time. For precision / cold chain cargo, clamp fixation or temperature control is enabled.

[0019] S42: Both parties coordinate and prepare for and confirm the docking window; The cloud-based system exchanges and schedules data in real time with both the low-altitude aircraft and the medium and heavy-duty truck via a communication module. After receiving feedback from both sides (such as the aircraft being successfully adjusted or the truck being ready), the cloud-based system will confirm whether to proceed to the docking phase. If there is any abnormal feedback or time misalignment, the cloud-based system will immediately readjust the docking plan and reissue it. The cloud platform monitors the actual movement of low-altitude aircraft and medium- and heavy-duty trucks in real time to confirm that the aircraft and truck reach the docking position within the set docking time window. S43: Conduct actual dynamic takeoff and landing docking; When the low-altitude aircraft approaches the medium and heavy-duty truck, the aircraft will continue to adjust its attitude and flight path according to real-time data to accurately dock with the cargo hold. The cargo hold of the medium and heavy-duty truck will adjust its position and status according to the dynamic docking plan (such as opening the loading and unloading port, adjusting the suspension, etc.) to ensure that the docking position and angle of the cargo hold and the aircraft match. During the docking process, the low-altitude aircraft and the medium and heavy-duty truck maintain dynamic coordination. After the low-altitude aircraft successfully docks with the medium- and heavy-duty truck, the system sends a success notification via the communication module; the cloud records the docking data and generates a docking report based on the status of the aircraft and the truck.

[0020] This invention uses a cloud-based dynamic scheduling algorithm module to receive and process data from the aircraft and truck in real time, precisely controlling the aircraft's flight path, attitude adjustment, and the truck's suspension system. During execution, the cloud monitors the docking process in real time, and if any anomaly is detected (such as time misalignment or abnormal feedback), the docking plan is immediately adjusted and new instructions are issued to ensure the efficiency and safety of the docking process.

[0021] This invention receives real-time data from medium and heavy-duty trucks via the cloud, including information such as cargo status, cargo hold position, and driving status, and dynamically coordinates this data with the take-off and landing plans of the aircraft. The aircraft can intelligently adjust itself based on the real-time status of the trucks, enabling collaborative scheduling between the aircraft and trucks, reducing waiting time and empty operation, and improving resource utilization efficiency.

[0022] This invention, through precise dynamic docking path adjustment and aircraft attitude control, can adjust the aircraft's flight path and speed based on real-time data, avoiding unnecessary detours and energy waste, thereby improving the aircraft's operating efficiency and extending its endurance.

[0023] The present invention has been described in the above-described embodiments; however, these embodiments are merely examples for implementing the present invention. It must be noted that the disclosed embodiments do not limit the scope of the present invention. Conversely, any modifications and refinements made without departing from the spirit and scope of the present invention are within the scope of patent protection of the present invention.

Claims

1. A method for precise dynamic take-off and landing docking between a low-altitude aircraft and a medium-to-heavy-duty truck, characterized in that: Includes the following steps: S1: Collect data from medium and heavy-duty trucks and upload it to the cloud; The data acquisition module collects data from medium and heavy-duty trucks via TBOX, and the vehicle data transmission module uploads the collected data and corresponding timestamps to the cloud. S2: The cloud receives data from medium and heavy-duty trucks and generates a dynamic docking plan; S21: Verify the received data from the medium and heavy-duty truck end; The verification includes integrity verification, accuracy verification, and timeliness verification. S22: Build a 3D dynamic scene based on the verified data; S221: Real-time synchronization data from low-altitude aircraft; S222: Cloud-based construction of 3D dynamic scenes; S223: Receive data and update model status in real time; S3: Generate and distribute dynamic docking plans; S4: Performs dynamic takeoff and landing with precise docking; S41: Low-altitude aircraft and medium- and heavy-duty trucks conduct dynamic coordination preparation; S42: Both parties coordinate and prepare for and confirm the docking window; S43: Conduct actual dynamic take-off and landing docking.

2. The method for precise dynamic take-off and landing docking of a low-altitude aircraft and a medium-to-heavy-duty truck as described in claim 1, characterized in that: In step S1, the medium and heavy-duty truck terminal data includes cargo data, time and air conditioning scheduling data, driving status data, cargo compartment status data, and medium and heavy-duty truck equipment parameters; The cargo data includes cargo weight and cargo type; The driving status data includes real-time driving speed and driving bump amplitude; The time-space scheduling data includes the real-time estimated time to reach the target transfer point and the coordinates of the target transfer point location; The cargo hold status data includes the real-time location coordinates of the medium and heavy-duty truck cargo hold and the real-time loading and unloading port status of the medium and heavy-duty truck cargo hold. The equipment parameters for medium and heavy-duty trucks include cargo compartment structure parameters, suspension system parameters, and loading / unloading port structure parameters.

3. The method for precise dynamic take-off and landing docking of low-altitude aircraft and medium-heavy trucks as described in claim 1, characterized in that: The specific details of step S22 are as follows: S221: Real-time synchronization data from low-altitude aircraft; The real-time data from the low-altitude aircraft is uploaded to the cloud via DBOX synchronization. The low-altitude aircraft data includes basic flight data, equipment status data, environmental perception data, low-altitude aircraft physical parameters, and timestamps. S222: Cloud-based construction of 3D dynamic scenes; The cloud performs integrity, accuracy, and timeliness checks on the received low-altitude aircraft data. After the checks are completed, the cloud-based digital twin scene construction module aligns the medium and heavy truck data and the low-altitude aircraft data according to the timestamp. The aligned low-altitude aircraft data and medium and heavy truck data are then imported into the medium and heavy truck 3D model that is completely consistent with the equipment parameters of the medium and heavy truck and the low-altitude aircraft 3D model that is completely consistent with the physical parameters of the low-altitude aircraft. The digital twin scene construction module uses digital twin technology to import the three-dimensional models of medium and heavy trucks and low-altitude aircraft into a three-dimensional dynamic scene that is consistent with the physical space of the actual driving section of the low-altitude aircraft and medium and heavy trucks; S223: Receive data and update model status in real time; The cloud system imports the verified data from the low-altitude aircraft and medium- and heavy-duty truck into the corresponding 3D models of the low-altitude aircraft and medium- and heavy-duty truck in real time, updates the status of the 3D models of the low-altitude aircraft and medium- and heavy-duty truck in real time, performs dynamic simulation, and generates the motion trajectories of the low-altitude aircraft and medium- and heavy-duty truck.

4. The method for precise dynamic take-off and landing docking of low-altitude aircraft and medium-heavy trucks as described in claim 1, characterized in that: In step S3, the dynamic scheduling algorithm module extracts data from the low-altitude aircraft and the medium and heavy-duty truck. Based on the dynamic simulation of the three-dimensional models of the low-altitude aircraft and the medium and heavy-duty truck in the three-dimensional dynamic scene, a dynamic docking plan is generated. The dynamic docking plan includes the docking time window, docking position, attitude adjustment angle of the low-altitude aircraft, and suspension damping coefficient of the medium and heavy-duty truck. The digital twin scenario construction module simulates the generated dynamic docking plan until it is determined that the plan is feasible; otherwise, the dynamic scheduling algorithm module regenerates the dynamic docking plan.

5. The method for precise dynamic take-off and landing docking of a low-altitude aircraft and a medium-to-heavy-duty truck as described in claim 1, characterized in that: The specific details of step S4 are as follows: S41: Low-altitude aircraft and medium- and heavy-duty trucks conduct dynamic coordination preparation; The cloud-based system uses a communication module to send the dynamic docking plan to the DBOX on the low-altitude aircraft and the TBOX on the medium and heavy-duty truck. The low-altitude aircraft adjusts its flight path and attitude angle based on a dynamic docking plan. The medium and heavy-duty truck side adjusts driving status data and prepares the cargo hold based on the dynamic docking plan; S42: Both parties coordinate and prepare for and confirm the docking window; The cloud-based system exchanges and schedules data in real time with both the low-altitude aircraft and the medium and heavy-duty truck via a communication module. After receiving feedback from both sides, the cloud will confirm whether to enter the docking phase. If there are any abnormalities or time discrepancies in the feedback, the cloud will readjust the docking plan and reissue it. The cloud platform monitors the actual movement of low-altitude aircraft and medium- and heavy-duty trucks in real time to confirm that the aircraft and truck reach the docking position within the set docking time window. S43: Conduct actual dynamic takeoff and landing docking; When the low-altitude aircraft approaches the medium and heavy-duty truck, the aircraft will continue to adjust its attitude and flight path according to real-time data to accurately dock with the cargo hold. The cargo hold of the medium and heavy-duty truck will adjust its position and status according to the dynamic docking plan to ensure that the docking position and angle of the cargo hold and the aircraft match. During the docking process, the low-altitude aircraft and the medium and heavy-duty truck will maintain dynamic coordination. After the low-altitude aircraft successfully docks with the medium- and heavy-duty truck, the system sends a success notification via the communication module; the cloud records the docking data and generates a docking report based on the status of the aircraft and the truck.

6. A dynamic take-off and landing precision docking system based on a low-altitude aircraft and a medium-to-heavy-duty truck for implementing the method described in claims 1-5, characterized in that: The system includes a low-altitude aircraft terminal, a cloud terminal, and a medium- and heavy-duty truck terminal; The low-altitude aircraft terminal uses the DBOX smart terminal as its core carrier and includes a multi-source fusion positioning module, an anti-turbulence attitude control module, and a communication module. The medium and heavy-duty truck terminal uses TBOX as its core carrier and includes a data acquisition module, a vehicle-to-everything (V2X) data transmission module, and a suspension coordination control module. The cloud platform is based on the vehicle-air-road-cloud intelligent network system, which includes a digital twin scenario construction module, a dynamic scheduling algorithm module, and a communication module.

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