A control method and device for a logistics intelligent mobile body

Abstract

This application discloses a control method and device for a logistics intelligent mobile body, belonging to the field of logistics automation technology. It includes: acquiring task instructions, which include a combined loading scheme consisting of multiple standardized cargo boxes of different specifications, determined by a cloud scheduling module based on cargo attributes, and the location of the pickup point; navigating to the pickup point; upon arrival, controlling the hatch to open, and performing automatic loading operations on each standardized cargo box through a composite mechanical actuator, including controlling a vertical lifting mechanism to support the two side wings of the cargo box and raise it a preset distance to detach it from the support surface, and then controlling a horizontal moving mechanism to move the cargo box to a designated position within the cargo hold; after loading is completed, executing the transportation task and providing status feedback. This invention, through the coordination of cloud-based on-demand combination of cargo boxes and specific linked loading and unloading actions at the mobile body end, achieves variable transportation volume and fully automated loading and unloading, solving the problems of fixed cargo hold capacity and reliance on manual loading and unloading in existing technologies, thus improving logistics efficiency and scenario adaptability.

Description

Technical Field

[0001] This application relates to the field of logistics automation technology, and in particular to a control method and device for a logistics intelligent mobile body. Background Technology

[0002] With the continuous growth of logistics demand, the pressure on last-mile delivery in closed and semi-closed campuses such as universities, hospitals, airports, and office buildings is increasing daily. Existing delivery methods mainly rely on manually driven vehicles or manual handling, which suffers from low efficiency, linearly increasing labor costs with business scale, and difficulty in long-term sustainability. Furthermore, security or management restrictions in some areas prevent direct access for personnel, further limiting the applicability of traditional delivery methods. Therefore, providing a more intelligent and efficient mobile control solution has become a pressing technical problem to be solved in this field. Summary of the Invention

[0003] In view of the above problems, this application provides a control method and device for intelligent logistics mobile bodies to improve efficiency and make transportation more convenient. The specific solution is as follows:

[0004] The first aspect of this application provides a control method for a logistics intelligent mobile body, comprising:

[0005] Obtain task instructions, which include a combined loading scheme determined by the cloud scheduling module based on the cargo attributes in the logistics demand data. The combined loading scheme consists of multiple standardized cargo boxes with different specifications. The logistics demand data also includes pickup point location information.

[0006] Navigate to the pickup point based on the pickup point location information;

[0007] Upon arrival at the pickup point, the control door opens, and each standardized cargo box is automatically loaded via a composite mechanical actuator. The composite mechanical actuator includes a horizontal moving mechanism and a vertical lifting mechanism. The automatic loading operation includes: controlling the vertical lifting mechanism to support the wings on both sides of the standardized cargo box and raise it a preset distance so that the standardized cargo box is detached from the support surface; and controlling the horizontal moving mechanism to move the standardized cargo box to a designated position within the cargo hold.

[0008] After the automatic loading operation is completed, the transportation task is executed, and the task execution status is reported back to the cloud scheduling module.

[0009] In one possible implementation, the cargo attributes include at least one of cargo volume, cargo weight, cargo quantity, and temperature control requirements;

[0010] The combined loading scheme is generated by the cloud scheduling module based on the cargo attributes, selecting standardized cargo boxes of corresponding specifications and functional types from haploid, diploid, and triploid cargo boxes, and determining their combined quantity; wherein, the volume of the diploid cargo box is twice that of the haploid cargo box, and the volume of the triploid cargo box is three times that of the haploid cargo box, and the functional types include ordinary storage boxes, insulated boxes, and refrigerated boxes.

[0011] In one possible implementation, the task instruction is issued by the cloud scheduling module after selecting the target object from multiple candidate objects based on the real-time location, remaining power, current task status, and configured double-sided cargo box type of each logistics intelligent mobile body in the park.

[0012] In one possible implementation, the execution of the transportation task includes: acquiring destination location information, constructing or matching an environmental map in real time through SLAM and visual fusion positioning, planning a driving route, and driving to the destination according to the driving route.

[0013] In one possible implementation, the method further includes: performing an automatic unloading operation upon arrival at the destination; the automatic unloading operation includes:

[0014] Control the opening of the hatch;

[0015] The horizontal moving mechanism is controlled to move the vertical lifting mechanism to the location of the standardized cargo box to be unloaded.

[0016] Control the vertical lifting mechanism to rise to support the wings on both sides of the standardized cargo box;

[0017] The vertical lifting mechanism is controlled to continue rising the preset distance so that the standardized cargo box is removed from the support position below it;

[0018] The horizontal movement mechanism is controlled to cause the standardized cargo box to extend horizontally to the outside of the cargo hold;

[0019] The vertical lifting mechanism is controlled to descend so as to place the standardized cargo box on the support surface of the unloading area.

[0020] In one possible implementation, the horizontal moving mechanism includes a slide rail and an electric push rod, the electric push rod being used to drive the slide rail to extend and retract in the horizontal direction; the vertical lifting mechanism includes an electric slide table, the electric slide table being used to drive the slider to move up and down in the vertical direction; the electric push rod is disposed on the slider.

[0021] In one possible implementation, communication with the cloud scheduling module is via the MQTT protocol. The task instructions are obtained through the topic subscription / publishing mechanism of the MQTT protocol, and the running status data is uploaded to the cloud scheduling module via the MQTT protocol at a preset frequency.

[0022] In one possible implementation, the operational status data includes real-time location, remaining battery power, driving speed, the operational status of the composite mechanical actuator, the location information of the standardized cargo box, and task execution progress; upon receiving an adjustment instruction issued by the cloud scheduling module based on the operational status data, the adjustment instruction is executed, and the adjustment instruction includes a pause loading / unloading instruction, a route adjustment instruction, and a task reassignment instruction.

[0023] In one possible implementation, the task instruction further includes delivery mode information, which is determined by the cloud scheduling module based on the logistics demand data and at least one of real-time status, delivery route distance, and order timeliness requirements; the delivery mode includes one of direct delivery mode, sorting and consolidation mode, and unmanned freight mode.

[0024] In the direct delivery mode, the transportation task from the pickup point to the destination is executed directly without transshipment;

[0025] In the sorting and consolidation mode, the standardized cargo boxes are transported to the exchange station for order collection and classification, and then the centralized distribution task is carried out;

[0026] In the unmanned freight mode, after local pickup and loading are completed, the standardized cargo box is transferred to an unmanned freight vehicle, which then performs trunk line transportation.

[0027] A second aspect of this application provides a control device for a logistics intelligent mobile body, comprising:

[0028] The task acquisition module is used to acquire task instructions. The task instructions include a combined loading scheme determined by the cloud scheduling module based on the cargo attributes in the logistics demand data. The combined loading scheme consists of multiple standardized cargo boxes with different specifications. The logistics demand data also includes pickup point location information.

[0029] The motion navigation module is used to navigate to the pickup point based on the pickup point location information;

[0030] The loading and unloading control module is used to control the hatch to open upon arrival at the pickup point and to perform automatic loading operations via a composite mechanical actuator. The composite mechanical actuator includes a horizontal moving mechanism and a vertical lifting mechanism. The automatic loading operation includes: controlling the vertical lifting mechanism to support the wings on both sides of the standardized cargo container and raise it a preset distance to detach the standardized cargo container from the support surface; controlling the horizontal moving mechanism to move the standardized cargo container to a designated position within the cargo hold; and...

[0031] The transportation execution module is used to execute the transportation task after the automatic loading operation is completed, and to report the task execution status to the cloud scheduling module.

[0032] A third aspect of this application provides a computer program product including computer-readable instructions that, when executed on an electronic device, cause the electronic device to implement the control method for a logistics intelligent mobile body as described in the first aspect or any implementation thereof.

[0033] A fourth aspect of this application provides an electronic device, including at least one processor and a memory connected to the processor, wherein:

[0034] The memory is used to store computer programs;

[0035] The processor is used to execute the computer program so that the electronic device can implement the control method of the intelligent mobile logistics body of the first aspect or any implementation thereof.

[0036] The fifth aspect of this application provides a computer storage medium carrying one or more computer programs, which, when executed by an electronic device, enable the electronic device to implement the control method for a logistics intelligent mobile body as described in the first aspect or any implementation thereof.

[0037] By employing the aforementioned technical solution, the control method for the intelligent mobile logistics vehicle provided in this application acquires a combined loading scheme consisting of multiple standardized cargo boxes of different specifications, generated by a cloud-based scheduling module based on cargo attributes. Automatic loading is then executed according to this scheme, allowing the cargo hold volume for a single transport to be configured on demand based on cargo volume, weight, quantity, and other attributes. This avoids the problem of multiple round trips caused by the inability to expand fixed cargo hold capacity, effectively improving single-delivery efficiency and equipment space utilization. After the mobile vehicle arrives at the pickup point, a composite mechanical actuator, including a horizontal movement mechanism and a vertical lifting mechanism, is controlled to execute a specific sequence of linked actions: supporting the wings, rising a preset distance to detach from the support surface, and translating into the cargo hold. This achieves reliable, damage-free automatic grasping and stacking of standardized cargo boxes of different specifications, eliminating reliance on manual labor in cargo loading and unloading, and opening up key links in the entire process automation, thereby improving logistics efficiency and scenario adaptability. Attached Figure Description

[0038] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0039] Figure 1 A flowchart of a control method for a logistics intelligent mobile body provided in this application;

[0040] Figure 2 This application provides an external structural diagram of a cabin.

[0041] Figure 3 An internal structural diagram of a cabin is provided for this application;

[0042] Figure 4 An internal structural diagram of another type of cabin provided in this application;

[0043] Figure 5 A structural diagram of a composite mechanical actuator provided in this application;

[0044] Figure 6 Another view of a composite mechanical actuator provided for this application;

[0045] Figure 7 A structural diagram of a control device for a logistics intelligent mobile body provided in this application;

[0046] Figure 8 This is a structural diagram of an electronic device provided in this application. Detailed Implementation

[0047] The embodiments of this application are described below with reference to the accompanying drawings. The terminology used in the implementation section of this application is for explaining specific embodiments only and is not intended to limit the scope of this application.

[0048] The embodiments of this application will now be described with reference to the accompanying drawings. Those skilled in the art will recognize that, with technological advancements and the emergence of new scenarios, the technical solutions provided in the embodiments of this application are equally applicable to similar technical problems.

[0049] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms are interchangeable where appropriate; this is merely a way of distinguishing objects with the same attributes in the embodiments of this application. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion, so that a process, method, system, product, or apparatus that comprises a series of elements is not necessarily limited to those elements, but may include other elements not explicitly listed or inherent to those processes, methods, products, or apparatuses.

[0050] Existing unmanned delivery vehicles, such as some six-wheeled autonomous delivery vehicles, typically employ an integrated, fixed-volume cargo compartment design. This design suffers from the following technical drawbacks: First, the fixed cargo compartment capacity is not scalable, resulting in low space utilization and limited single-trip transport capacity when dealing with goods of varying sizes and quantities. This necessitates multiple round trips or the deployment of multiple devices, leading to high energy consumption and equipment depreciation costs per unit of cargo transport. Second, the loading and unloading process relies on manual opening of the cargo doors, preventing true end-to-end automation and making the loading and unloading stage a human-intensive bottleneck in the fully automated process. Third, multi-device scheduling usually uses individual vehicles as task allocation units, failing to allow for refined transportation unit combinations based on cargo attributes (such as volume and temperature control requirements), thus hindering the improvement of equipment resource utilization. Fourth, the chassis design of existing small delivery vehicles is often oriented towards regular urban sidewalks, resulting in insufficient passability and all-weather operation capabilities for complex road environments common in industrial parks, such as steps, ramps, and water accumulation.

[0051] To address the aforementioned problems, this application provides a control method for a logistics intelligent mobile entity. The control method for the logistics intelligent mobile entity according to this application embodiment will be described in detail below with reference to the accompanying drawings.

[0052] Reference Figure 1 , Figure 1 A flowchart illustrating a control method for a logistics intelligent mobile body provided in an embodiment of this application is shown below. Figure 1As shown in the figure, the control method of a logistics intelligent mobile body provided in this application embodiment may include steps S101 to S104, which are described in detail below.

[0053] Step S101: Obtain task instructions. The task instructions include a combined loading scheme determined by the cloud scheduling module based on the cargo attributes in the logistics demand data. The combined loading scheme consists of multiple standardized cargo boxes with different specifications. The logistics demand data also includes pickup point location information.

[0054] Specifically, the intelligent logistics vehicle obtains task instructions from the cloud-based scheduling module via a wireless communication network. These task instructions are pre-generated by the cloud-based scheduling module based on logistics demand data. Specifically, users submit logistics demand information through mobile applications or web terminals. The cloud-based scheduling module identifies and parses this information, extracting key parameters such as cargo attributes and pickup point location information to generate corresponding structured logistics demand data. Cargo attributes include, for example, cargo volume (e.g., 0.1 cubic meters) and cargo weight (e.g., 10 kilograms). The logistics demand data also includes pickup point location information, such as the coordinates of a pickup point in a teaching building within the park.

[0055] Based on the aforementioned cargo attributes, the cloud-based scheduling module determines a combined loading scheme. For example, for a batch of cargo with a total volume of 0.2 cubic meters and a total weight of 15 kilograms, the cloud-based scheduling module determines a combined loading scheme consisting of two single-unit cargo boxes. This combined loading scheme specifies the quantity and specifications of the standardized cargo boxes required for this transportation task. The standardized cargo boxes have uniform bottom dimensions (e.g., 400mm long × 300mm wide) and outward-extending wing structures on both sides, enabling them to be grasped by the same set of mechanical actuators.

[0056] The task instruction includes the above-mentioned combined loading scheme and pickup point location information. The cloud scheduling module sends the task instruction to the selected target logistics intelligent mobile body through the topic subscription / publish mechanism of the MQTT (Message Queuing Telemetry Transport) protocol.

[0057] Step S102: Navigate to the pickup point based on the pickup point location information.

[0058] Specifically, after receiving the task instruction, the mobile unit extracts the pickup point location information. Using its onboard navigation system, including LiDAR, a vision camera, and an Inertial Measurement Unit (IMU), the mobile unit employs SLAM (Simultaneous Localization and Mapping) technology to build a real-time environmental map and determine its own pose. It then plans the optimal driving path from its current location to the pickup point and drives the mobile execution unit to autonomously travel along this path to the pickup point. The mobile execution unit utilizes a chassis structure with high off-road and waterproof performance, coupled with a drive motor and transmission system, enabling it to carry the container module and cargo for multi-scenario, long-distance transportation.

[0059] Step S103: Upon arrival at the pickup point, the control door opens, and an automatic loading operation is performed on each standardized cargo container via a composite mechanical actuator. The composite mechanical actuator includes a horizontal movement mechanism and a vertical lifting mechanism. The automatic loading operation includes: controlling the vertical lifting mechanism to support the wings on both sides of the standardized cargo container and raise it a preset distance so that the standardized cargo container is detached from the support surface; and controlling the horizontal movement mechanism to move the standardized cargo container to a designated position within the cargo hold.

[0060] Specifically, after the mobile unit arrives at the pickup point, the vehicle-side control unit uses the SLAM fusion positioning unit to accurately locate the pickup point and sends an "alignment confirmation" command to the cabin 1 electronic control unit to ensure that the hatch is aligned with the pickup and placement area. Subsequently, the cabin electronic control unit drives the hatch actuator to control the hatch to open automatically.

[0061] After the hatch is opened, the mobile unit automatically loads each standardized cargo container 2 specified in the combined loading scheme sequentially using its built-in composite mechanical actuators. (Refer to...) Figures 2 to 6 As shown, the composite mechanical actuator includes a horizontal moving mechanism and a vertical lifting mechanism.

[0062] In this embodiment, the horizontal movement mechanism includes a slide rail 7 and an electric push rod 6. The electric push rod 6 drives the slide rail 7 to extend and retract horizontally. The vertical lifting mechanism includes an electric slide table 4, which drives the slider 6 to rise and fall vertically. The electric push rod 6 is mounted on the slider, allowing the lifting component to move with the slider 5 in both horizontal and vertical degrees of freedom. This structure, composed of a slide rail, an electric push rod, and an electric slide table, serves as the core execution mechanism for loading and unloading goods. Power is provided by the electric push rod, and the slide rail and electric slide table achieve precise horizontal and vertical displacement, completing automatic loading, unloading, stacking, and multi-unit loading and unloading operations. The electric slide table 4 uses a stepper motor 3 and a lead screw 8 to achieve vertical movement of the slider.

[0063] For each standardized cargo container to be loaded, the specific sequence of actions for the automatic loading operation is as follows:

[0064] First, the container's electronic control unit controls the electric push rod to start, causing the slide rail to extend fully in the horizontal direction, so that the vertical lifting mechanism and its lifting components extend to the side of the standardized cargo box to be loaded, aligning with the two wings of the cargo box to be loaded.

[0065] Next, the electronic control unit controls the electric slide to move the lifting component upwards, precisely supporting the wings on both sides of the standardized cargo box. After being lifted into position, the electronic control unit controls the slide to continue rising a preset distance, for example, 30mm, so that the bottom of the standardized cargo box is completely detached from the support surface of the picking point below, avoiding friction or jamming during translation. Throughout the process, the electronic control unit collects real-time data on the displacement of the robotic arm and the lifting height to ensure precise and stable movements.

[0066] Then, the container's electronic control unit controls the electric push rod to run in the opposite direction, driving the slide rail to smoothly retract the standardized cargo box in the horizontal direction until the standardized cargo box is completely inside the cargo hold.

[0067] Finally, the container's electronic control unit controls the slide to slowly descend, smoothly placing the standardized cargo box into the pre-planned designated position within the cargo hold, completing the loading of a single standardized cargo box. The electronic control unit then feeds back the loading completion data to the vehicle-side control unit.

[0068] Repeat the above actions of extending, lifting slightly, retracting, and lowering until all standardized cargo containers specified in the combined loading plan are loaded.

[0069] Step S104: After the automatic loading operation is completed, execute the transportation task and report the task execution status to the cloud scheduling module.

[0070] Specifically, after all standardized cargo containers are loaded, the container's electronic control unit drives the hatch to close, simultaneously uploading the "hat closed" status to the vehicle-side control unit. The vehicle-side control unit integrates the cargo assembly information, cargo manifest, and robotic arm operating status data, uploading this data to the cloud-based scheduling module via the MQTT protocol. Subsequently, the mobile unit executes the transportation task according to the destination location information in the mission instructions, traveling towards the destination along the planned route. During mission execution, the mobile unit continuously reports the mission execution status to the cloud-based scheduling module, such as "loading complete," "transporting," and "arrived at destination," enabling global monitoring and subsequent scheduling by the cloud.

[0071] As can be seen from the above, the control method of this intelligent logistics mobile body obtains a combined loading scheme composed of multiple standardized cargo boxes of different specifications generated by the cloud scheduling module based on cargo attributes, and executes automatic loading according to the scheme. This allows the cargo hold volume of a single transport to be configured as needed according to the cargo volume, weight, quantity and other attributes, avoiding the problem of multiple round trips caused by the inability to expand the fixed cargo hold capacity, and effectively improving the efficiency of a single delivery and the utilization rate of equipment space.

[0072] By controlling a composite mechanical actuator, including a horizontal moving mechanism and a vertical lifting mechanism, to execute a specific sequence of linked actions after the mobile body arrives at the pickup point, reliable and non-destructive automatic grabbing and stacking of standardized cargo boxes of different specifications is achieved, eliminating the reliance on human labor in the cargo loading and unloading process and opening up the key link of full-process automation.

[0073] By placing the decision-making power for combined loading schemes in the cloud scheduling module, and combining the real-time location, power level, task status, and type of the mobile vehicle to select the target mobile vehicle, the refined scheduling and resource optimization of transportation tasks are realized, thereby improving the overall efficiency of multi-mobile vehicle collaborative operations.

[0074] In another embodiment, to enable the transportation of more types of goods and improve the comprehensiveness of transportation, the goods attributes include at least one of the following: goods volume, goods weight, goods quantity, and temperature control requirements.

[0075] The combined loading scheme is generated by the cloud-based scheduling module based on the cargo attributes, selecting standardized containers of corresponding specifications and functional types from haploid, diploid, and triploid containers, and determining the combined quantity. The volume of a diploid container is twice that of a haploid container, and the volume of a triploid container is three times that of a haploid container. Functional types include ordinary storage containers, insulated containers, and refrigerated containers.

[0076] Specifically, the cargo attributes in logistics demand data include not only cargo volume and weight, but also cargo quantity and temperature control requirements. For example, an order might contain two refrigerated items and three general items. Temperature control requirements refer to the specific temperature range that the goods need to be maintained during transportation; for example, fresh food requires a refrigerated environment of 0-8℃, while hot meals require a warming environment of 50-60℃.

[0077] The standardized cargo containers come in three fixed-volume sizes: haploid, diploid, and triploid. The diploid container has twice the volume of the haploid container, and the triploid container has three times the volume of the haploid container. Each haploid container forms a continuous, uninterrupted storage space without internal partitions. All haploid containers have the same bottom dimensions (e.g., 400mm long x 300mm wide), allowing for stackable loading within the transport unit.

[0078] Meanwhile, standardized cargo containers are categorized by function into ordinary storage containers, insulated containers, and refrigerated containers. Ordinary storage containers are used for transporting goods at ambient temperatures. Insulated containers achieve passive insulation by filling the container walls with insulation materials (such as polyurethane foam). Refrigerated containers further integrate refrigeration modules (such as thermoelectric coolers or compressor refrigeration units) to achieve active refrigeration.

[0079] When generating combined loading plans, the cloud-based scheduling module selects standardized containers of corresponding specifications and functional types from haploid, diploid, and triploid containers based on cargo volume, weight, quantity, and temperature control requirements, and determines the combination quantity. For example, for an order containing two refrigerated items (0.02 cubic meters each) and three general cargo items (0.03 cubic meters each), the cloud-based scheduling module might generate the following combined loading plan: one haploid refrigerated container (for the two refrigerated items) and one diploid general cargo container (for the three general cargo items). This on-demand combination method satisfies the temperature control requirements of different goods while maximizing the use of cargo hold space, thereby improving cargo transportation efficiency.

[0080] In some embodiments, to further optimize the transportation process and improve transportation efficiency, the task instruction is issued by the cloud scheduling module after selecting the target object from multiple candidate objects based on the real-time location, remaining power, current task status and configured double-sided cargo box type of each logistics intelligent mobile body in the park.

[0081] Specifically, after determining the combined loading plan, the cloud scheduling module does not randomly assign mobile vehicles, but intelligently selects them based on the real-time status of each intelligent logistics mobile vehicle in the park.

[0082] For example, multiple intelligent logistics mobile units are deployed in the park. Each mobile unit continuously reports its own operating status data to the cloud scheduling module via the MQTT protocol, including real-time location (e.g., provided by SLAM system or GPS positioning unit), remaining power (e.g., current power is 85%), current task status (e.g., idle, performing a task, charging), and the currently configured double-body cargo container type (e.g., a double-body ordinary container is currently loaded in the cargo hold).

[0083] After generating the combined loading plan, the cloud scheduling module calculates the overall cost of each candidate mobile vehicle to perform the task using a scheduling algorithm. Factors influencing the overall cost calculation include: the distance between the mobile vehicle's current location and the pickup point (the closer the distance, the lower the cost), whether the remaining battery power is sufficient to complete the round trip (insufficient battery power increases the cost or the vehicle is excluded), the current task status (idle mobile vehicles are given priority), and whether the currently configured double-body cargo box type is compatible with the combined loading plan (for example, if the mobile vehicle is already loaded with some cargo boxes, it is necessary to determine whether the remaining space can accommodate the cargo boxes in this plan).

[0084] Based on the above comprehensive cost calculation, the cloud scheduling module selects the target mobile unit with the optimal comprehensive cost from multiple candidate units and issues the task instruction to that target mobile unit. For example, there are two idle mobile units: Mobile unit A is 100 meters away from the pickup point and has 90% battery, while Mobile unit B is 200 meters away from the pickup point and has 60% battery. Although both are idle, Mobile unit A is closer, has more battery power, and has a lower comprehensive cost. The cloud scheduling module selects Mobile unit A as the target mobile unit to issue the task instruction.

[0085] This approach enables refined scheduling of transportation tasks and optimized allocation of logistics resources, avoiding overuse or depletion of power of a single mobile vehicle, and improving the overall efficiency of collaborative operations among multiple mobile vehicles.

[0086] Furthermore, when the mobile vehicle is performing a specific transportation task, it can obtain the destination location information, construct or match the environmental map in real time through SLAM and visual fusion positioning, plan the driving route, and drive to the destination according to the driving route.

[0087] For example, the destination is the unloading point of an office building within the park. The mobile device employs a localization scheme that combines laser SLAM and visual SLAM. The mobile device is equipped with a lidar and a visual camera. The lidar measures the distance and angle information of objects in the surrounding environment by emitting laser beams and receiving reflected signals, generating a two-dimensional or three-dimensional point cloud map. The visual camera acquires environmental image information and identifies salient visual landmarks in the environment through feature point extraction and matching algorithms (such as ORB features and SIFT features).

[0088] The SLAM fusion localization unit fuses and matches LiDAR point cloud data with visual feature point data to construct an environmental map in real time and simultaneously determine the precise pose (position and attitude) of the moving object within the map. Simultaneously, the moving object is equipped with an inertial measurement unit (IMU) to measure its angular velocity and acceleration, providing short-term trajectory estimation when LiDAR or visual camera data is temporarily unavailable (e.g., when traversing a textureless white wall area), ensuring the continuity of localization.

[0089] Even in indoor or semi-obscured areas with weak GPS signals, this fusion positioning solution can achieve centimeter-level real-time positioning accuracy, supports dynamic environmental map updates and relocation, and is suitable for autonomous navigation needs in mixed indoor and outdoor scenarios such as hospitals and campuses.

[0090] After obtaining precise positioning and an environmental map, the path planning module of the mobile entity plans a collision-free travel path with optimal length or travel time based on the current location, destination location, and environmental map. Planning algorithms may include, for example, A* algorithm, Dijkstra's algorithm, or RRT (Rapidly-exploring Random Tree) algorithm. The mobile execution unit drives the mobile entity to safely travel to its destination along the planned path.

[0091] Upon arrival at the destination, an automatic unloading operation is performed, which includes:

[0092] Control hatch opens;

[0093] The horizontal moving mechanism is controlled to drive the vertical lifting mechanism to the location of the standardized cargo box to be unloaded;

[0094] Control the vertical lifting mechanism to rise to support the wings on both sides of the standardized cargo box;

[0095] Control the vertical lifting mechanism to continue rising a preset distance so that the standardized cargo box is removed from its supporting position below;

[0096] The horizontal movement control mechanism causes the standardized cargo box to extend horizontally to the outside of the cargo hold;

[0097] Control the vertical lifting mechanism to lower the standardized cargo box and place it on the support surface of the unloading area.

[0098] For example, after the mobile vehicle arrives at the destination unloading point, the vehicle-side control unit completes precise positioning through the SLAM positioning unit and sends a "prepare for unloading" command to the container's electronic control unit. The container's electronic control unit responds to this command by driving the door actuator, controlling the door to open automatically.

[0099] Then, the container's electronic control unit activates the electric push rod of the horizontal movement mechanism, causing the slide rail and vertical lifting mechanism to move horizontally, thus moving the lifting component to the location of the standardized cargo container to be unloaded inside the cargo hold. Specifically, the lifting component is aligned with the underside of the wings on both sides of the standardized cargo container.

[0100] Next, the container's electronic control unit controls the electric slide of the vertical lifting mechanism to raise the slider, causing the lifting components to contact and support the wings on both sides of the standardized cargo box. The electronic control unit verifies the lifting height in real time to ensure the container is stable and prevents tilting or slipping.

[0101] Then, the container control unit controls the electric slide to continue rising the preset distance (e.g., 30mm) so that the bottom of the standardized cargo box is completely detached from its supporting position below (e.g., the cargo hold floor or the top of another cargo box stacked below).

[0102] Then, the container's electronic control unit controls the electric push rod to push the slide rail, carrying the standardized cargo box to extend horizontally to the unloading area outside the cargo hold.

[0103] Finally, the container's electronic control unit controls the electric slide to slowly descend, smoothly placing the standardized cargo box onto the support surface of the unloading area (such as the ground or unloading platform), completing the unloading. The electronic control unit then feeds back the unloading completion data to the vehicle-side control unit.

[0104] If the combined loading scheme includes multiple standardized cargo boxes, repeat the above steps until all standardized cargo boxes that need to be unloaded have been unloaded. After unloading is completed, the container electronic control unit drives the hatch to close, and the vehicle-side control unit uploads the "unloading complete" status to the cloud scheduling module via the MQTT protocol.

[0105] In some embodiments, refer to Figure 5 and Figure 6 As shown, the lifting component includes a slide rail 7 and an electric push rod 6. The slide rail 7 is a precision linear guide, providing low-friction, high-rigidity horizontal guidance. The electric push rod 6 is a DC motor-driven screw transmission mechanism, with its push rod body fixedly connected to the slide rail 7. When the motor of the electric push rod 6 rotates forward or reverse, the push rod extends or retracts, thereby driving the slide rail 7 to extend or retract horizontally. The stroke of the electric push rod 6 is, for example, 500 mm, which is sufficient to completely push a standardized cargo container from inside the cargo hold to the external unloading area.

[0106] The electric slide 4 consists of a stepper motor 3, a lead screw 8, and a slider 5. The stepper motor 3 drives the lead screw 8 to rotate, and the rotational motion of the lead screw 8 is converted into the linear motion of the slider 5 through a nut, thereby causing the slider 5 to rise and fall vertically. The lifting component is fixedly installed on the slider of the electric slide and rises and falls together with the slider 5. Its horizontal part is used to extend under the standardized cargo box wings to provide lifting force.

[0107] By mounting the electric push rod on the slider—that is, fixing the base of the electric push rod to the slider of the electric slide table—the entire horizontal movement mechanism (slide rail and electric push rod) can rise and fall vertically with the slider. Simultaneously, the vertical lifting mechanism (electric slide table) is connected to the horizontal movement mechanism via a slide rail, allowing it to extend and retract horizontally along the slide rail. This enables the lifting components to move independently or collaboratively in both horizontal and vertical degrees of freedom, completing precise gripping, lifting, translating, and placing operations on standardized cargo boxes.

[0108] In some embodiments, communication with the cloud scheduling module is achieved via the MQTT protocol. Task instructions are obtained through the topic subscription / publishing mechanism of the MQTT protocol, and running status data is uploaded to the cloud scheduling module at a preset frequency via the MQTT protocol.

[0109] The mobile device communicates with the cloud scheduling module via the MQTT protocol. MQTT is a lightweight messaging protocol based on a publish / subscribe model, designed for embedded and IoT scenarios with limited bandwidth and unstable networks. It enables efficient and reliable data communication between devices through low-overhead, low-power message interaction.

[0110] Specifically, the cloud scheduling module is configured with an MQTT Broker (message broker server). The mobile device, acting as an MQTT client, establishes a long-lived connection with the MQTT Broker.

[0111] Regarding task instruction acquisition, after generating a task instruction, the cloud scheduling module publishes the task instruction message to a specific MQTT topic, such as " / fleet / vehicle_{mobile ID} / task". The target mobile entity pre-subscribes to the topic corresponding to its own ID, and when a new message is published on that topic, the mobile entity can receive and parse the task instruction in real time. This topic-based subscription / publishing mechanism enables accurate and reliable delivery of task instructions.

[0112] Regarding the uploading of operational status data, during task execution, each mobile vehicle encapsulates its operational status data into messages at a preset frequency (e.g., once every 5 seconds) and publishes them to a specific MQTT topic, such as " / fleet / vehicle_{mobile ID} / status". The cloud scheduling module subscribes to the status topics of all mobile vehicles, thereby enabling it to receive and monitor the operational status of all mobile vehicles within the entire park in real time. This mechanism ensures that the cloud scheduling module can obtain a global, real-time view of the logistics network status, providing a data foundation for dynamic scheduling decisions.

[0113] The operational status data includes real-time location, remaining battery power, driving speed, the operational status of the composite mechanical actuators, the location information of the standardized cargo box, and the task execution progress. Upon receiving adjustment instructions from the cloud scheduling module based on the operational status data, the system executes these instructions, which include instructions to pause loading and unloading, adjust the route, and reassign tasks.

[0114] The runtime status data uploaded by the mobile entity to the cloud scheduling module via the MQTT protocol includes the following specific content:

[0115] Real-time location: provided by the SLAM fusion positioning unit of the moving body or the GPS positioning unit of the container, for example, expressed in latitude and longitude coordinates or local coordinate system coordinates of the park.

[0116] Remaining power: Provided by the battery management system, such as the current remaining power percentage (e.g., 75%) or remaining driving range (e.g., 15 kilometers).

[0117] Travel speed: provided by the motor encoder or wheel speed sensor of the moving actuator, for example, the current speed is 1.2 m / s.

[0118] The operational status of the composite mechanical actuator is collected and fed back in real time by the housing electrical control unit. Status values ​​such as "extending", "lifting completed", "retracting", "placement completed", and "idle" are collected, as well as the displacement of the robotic arm and the operating parameters of the slide rail / electric push rod.

[0119] The location information of standardized cargo containers is provided by location detection sensors (such as photoelectric switches and micro switches) in the cargo hold, such as "Position 1: Haploid refrigerated container in place", "Position 2: Empty", "Position 3: Diploid ordinary container in place".

[0120] Task execution progress: calculated by the vehicle-side control unit, such as "60% of the journey has been traveled", "2 out of 3 cargo boxes have been loaded", and "Estimated remaining time: 5 minutes".

[0121] The cloud-based scheduling module receives and analyzes the aforementioned operational status data in real time to monitor tasks and issue early warnings for anomalies. For example, if the duration of the robotic arm's "extend" action exceeds the normal threshold (e.g., it normally takes 3 seconds to complete, but has lasted for 10 seconds without completion), it is determined to be an "robotic arm action timeout" anomaly; if the remaining battery power is detected to be below the safety threshold (e.g., below 20%), it is determined to be an "insufficient battery power" anomaly; and if severe congestion is detected ahead of the planned path of the mobile vehicle through global traffic data analysis, it is determined to be an "path congestion" anomaly.

[0122] When the above-mentioned anomalies occur, the cloud scheduling module sends adjustment instructions to the mobile vehicle via the MQTT protocol. These adjustment instructions may include:

[0123] Pause loading / unloading instruction: Instructs the moving body to immediately stop the current robotic arm movement, maintain the current state, and wait for further instructions or manual intervention for troubleshooting.

[0124] Route adjustment command: The cloud scheduling module replans a driving route for the mobile vehicle to avoid congested sections and sends the new route to the mobile vehicle, which then adjusts its driving according to the new route.

[0125] Task reassignment instruction: When a mobile device's battery is low or it experiences a fault that cannot be recovered on its own, the cloud scheduling module will reassign the currently unfinished task (or remaining sub-task) to another mobile device in a better state. After receiving the instruction, the original mobile device will proceed to the charging station or standby point according to the instruction content.

[0126] When a mobile unit receives an adjustment instruction from the cloud-based scheduling module, it immediately interrupts its current process, parses and executes the instruction, and simultaneously sends the result back to the cloud via the MQTT protocol. This approach establishes a complete closed-loop control and dynamic scheduling mechanism, ensuring stable and efficient execution of logistics tasks even in dynamic and complex environments.

[0127] In other embodiments, to enable the mobile entity to adaptively execute the optimal delivery strategy, the system's flexibility in adapting to different business scenarios and unforeseen circumstances is improved. The task instruction also includes delivery mode information, which is determined by the cloud scheduling module based on at least one of the following: logistics demand data, real-time status, delivery route distance, and order timeliness requirements. The delivery mode includes one of the following: direct delivery mode, sorting and consolidation mode, and unmanned freight mode.

[0128] In the direct delivery mode, the transportation task is carried out directly from the pickup point to the destination without transshipment.

[0129] In the sorting and consolidation model, standardized cargo boxes are transported to the exchange station for order collection and classification, and then centralized distribution tasks are carried out.

[0130] In unmanned freight mode, after local pickup and loading are completed, standardized cargo boxes are transferred to unmanned freight vehicles, which then perform trunk line transportation.

[0131] Specifically, the scheduling algorithm of the cloud-based scheduling module performs multi-dimensional data fusion analysis on the received structured logistics demand data. The fused data includes: cargo size and weight information, double-layer cargo box type (haploid, diploid, triploid), real-time location of intelligent logistics mobile vehicles, remaining load capacity, exchange station inventory status, delivery route distance, order timeliness requirements, and unmanned freight vehicle operating status, etc.

[0132] After data fusion, the cloud-based scheduling algorithm comprehensively assesses factors such as transportation distance, order quantity, delivery time requirements, and geographical area to generate delivery mode decision data and determine the optimal delivery mode. The delivery modes include the following three:

[0133] Direct Delivery Mode: When the delivery distance is short (e.g., less than 500 meters), the order is single, and there is an urgent delivery requirement, the system selects direct delivery mode. In this mode, the mobile device directly performs the transportation task from the pickup point to the destination without any transfers. For example, a user orders an emergency medicine, the delivery distance is 300 meters, and delivery is required within 30 minutes. The cloud determines it to be in direct delivery mode, the mobile device loads the medicine box, and directly navigates to the destination to complete the delivery.

[0134] Sorting and Consolidation Mode: When multiple orders exist with the same delivery direction and a suitable transportation distance (e.g., 500 meters to 2 kilometers), the system selects the sorting and consolidation mode. In this mode, mobile units first transport standardized cargo boxes to the exchange station. The exchange station is used to centrally store cargo boxes of different specifications and functions, and classifies them according to their specifications and functional attributes. At the exchange station, the sorting system completes the aggregation and classification of orders, potentially recombining cargo boxes from different sources but with the same destination. Then, the original mobile unit or other idle mobile units perform the centralized delivery task. For example, if three different users place orders, all destined for the same office building, the cloud determines it to be in sorting and consolidation mode. The three mobile units pick up their respective pickup points, converge at the exchange station, and load them onto a single mobile unit for centralized delivery in one go, reducing delivery frequency and resource waste.

[0135] Unmanned Freight Mode: When there are a large number of orders and the delivery distance is long (e.g., more than 2 kilometers) or cross-regional transportation is required, the system selects the unmanned freight mode. In this mode, after the mobile units complete local pickup and loading, they transfer standardized cargo boxes to unmanned freight vehicles, which then perform trunk line transportation. For example, if a large quantity of goods in Park A needs to be transported to Park B, 5 kilometers away, the cloud determines that the unmanned freight mode is selected. Multiple mobile units complete pickup and loading within Park A, and then sequentially transfer the cargo boxes to unmanned freight vehicles waiting at the park's entrance. Once fully loaded, the unmanned freight vehicles autonomously drive along the main road to Park B, where mobile units within Park B complete the last-mile delivery.

[0136] By including delivery patterns determined by the cloud based on multidimensional data in the task instructions, the mobile entity can adaptively execute the optimal delivery strategy, adapt to diverse logistics needs in closed / semi-closed scenarios, and improve the overall scheduling flexibility and transportation efficiency of the system.

[0137] This application centrally receives and models logistics demands through a unified scheduling and decision-making module. It combines the global equipment status (logistics intelligent mobile units, logistics nodes, etc.) to intelligently determine the delivery mode and coordinate the allocation of tasks among multiple execution units. At the same time, it relies on the combined multi-body cargo compartment and automatic loading and unloading mechanism to increase the single delivery volume of a single intelligent mobile unit. Therefore, it can effectively avoid the problems of path conflict, task waiting, resource idleness and low loading and unloading efficiency caused by traditional manual scheduling or independent operation of single equipment, thereby significantly improving the overall execution efficiency of logistics tasks within the park.

[0138] The system autonomously completes core processes such as logistics demand allocation, transportation route planning, automatic loading and unloading of goods, and full-process task monitoring, significantly reducing reliance on manual handling, delivery, scheduling, and loading / unloading. Furthermore, the collaborative operation of multiple intelligent mobile entities does not require a linear increase in human input with the scale of operations. Therefore, it can significantly reduce the intensity of human input and labor costs in the long term, thereby solving the problem of unsustainable labor costs as business scale grows.

[0139] By monitoring the entire logistics process through real-time task status feedback, self-calibration and safety testing of mechanical actuators, and a closed-loop confirmation mechanism, problems such as loading and unloading failures, route obstruction, and equipment malfunctions can be detected and dealt with in a timely manner. At the same time, the enclosed double-body cargo hold and unmanned operation reduce cargo damage and personnel contact risks, thus effectively improving the overall reliability and safety of the logistics system.

[0140] The above describes a control method for a logistics intelligent mobile body provided by the embodiments of this application. The following will describe the apparatus for implementing the above control method for a logistics intelligent mobile body.

[0141] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a control device for a logistics intelligent mobile body provided in an embodiment of this application. Figure 7 As shown, the control device for this intelligent mobile logistics system includes:

[0142] The task acquisition module 701 is used to acquire task instructions. The task instructions include a combined loading scheme determined by the cloud scheduling module based on the cargo attributes in the logistics demand data. The combined loading scheme consists of multiple standardized cargo boxes with different specifications. The logistics demand data also includes pickup point location information.

[0143] The motion navigation module 702 is used to navigate to the pickup point based on the pickup point location information;

[0144] The loading and unloading control module 703 is used to control the hatch to open upon arrival at the pickup point and to perform automatic loading operations via a composite mechanical actuator. The composite mechanical actuator includes a horizontal movement mechanism and a vertical lifting mechanism. The automatic loading operation includes: controlling the vertical lifting mechanism to support the wings on both sides of the standardized cargo container and raise it a preset distance to detach the standardized cargo container from the support surface; controlling the horizontal movement mechanism to move the standardized cargo container to a designated position within the cargo hold; and...

[0145] The transportation execution module 704 is used to execute transportation tasks after the automatic loading operation is completed and to report the task execution status to the cloud scheduling module.

[0146] In one possible implementation, cargo attributes include at least one of cargo volume, cargo weight, cargo quantity, and temperature control requirements; the combined loading scheme in the task acquisition module 701 is generated by the cloud scheduling module based on cargo attributes, selecting standardized cargo boxes of corresponding specifications and functional types from haploid, diploid, and triploid cargo boxes, and determining their combined quantity; wherein, the volume of the diploid cargo box is twice that of the haploid cargo box, the volume of the triploid cargo box is three times that of the haploid cargo box, and the functional types include ordinary storage boxes, insulated boxes, and refrigerated boxes.

[0147] In one possible implementation, the task instruction in the task acquisition module 701 is issued by the cloud scheduling module after selecting the target object from multiple candidate objects based on the real-time location, remaining power, current task status, and configured double-body cargo box type of each logistics intelligent mobile body in the park.

[0148] In one possible implementation, the process of performing a transportation task in the transportation execution module 704 includes: obtaining destination location information, constructing or matching an environmental map in real time through SLAM and visual fusion positioning, planning a driving route, and driving to the destination according to the driving route.

[0149] In one possible implementation, the loading / unloading control module 703 is further configured to: perform an automatic unloading operation upon arrival at the destination; the automatic unloading operation includes:

[0150] Control hatch opens;

[0151] The horizontal moving mechanism is controlled to drive the vertical lifting mechanism to the location of the standardized cargo box to be unloaded;

[0152] Control the vertical lifting mechanism to rise to support the wings on both sides of the standardized cargo box;

[0153] Control the vertical lifting mechanism to continue rising a preset distance so that the standardized cargo box is removed from its supporting position below;

[0154] The horizontal movement control mechanism causes the standardized cargo box to extend horizontally to the outside of the cargo hold;

[0155] Control the vertical lifting mechanism to lower the standardized cargo box and place it on the support surface of the unloading area.

[0156] In one possible implementation, the horizontal movement mechanism of the loading and unloading control module 703 includes a slide rail and an electric push rod, the electric push rod being used to drive the slide rail to extend and retract in the horizontal direction; the vertical lifting mechanism includes an electric slide table, the electric slide table being used to drive the slider to rise and fall in the vertical direction; the electric push rod is mounted on the slider.

[0157] In one possible implementation, the task acquisition module 701 communicates with the cloud scheduling module via the MQTT protocol. Task instructions are acquired through the topic subscription / publishing mechanism of the MQTT protocol, and running status data is uploaded to the cloud scheduling module at a preset frequency via the MQTT protocol.

[0158] In one possible implementation, the operational status data in the task acquisition module 701 includes real-time location, remaining battery power, driving speed, the action status of the composite mechanical actuator, the location information of the standardized cargo box, and the task execution progress; when receiving adjustment instructions issued by the cloud scheduling module based on the operational status data, the adjustment instructions are executed, including instructions to pause loading and unloading, instructions to adjust the route, and instructions to reassign tasks.

[0159] In one possible implementation, the task instruction in the task acquisition module 701 also includes delivery mode information. The delivery mode is determined by the cloud scheduling module based on logistics demand data and at least one of real-time status, delivery route distance, and order timeliness requirements. The delivery mode includes one of direct delivery mode, sorting and consolidation mode, and unmanned freight mode.

[0160] In direct delivery mode, the transportation task from the pickup point to the destination is executed directly without transshipment;

[0161] In the sorting and consolidation model, standardized cargo boxes are transported to the exchange station for order collection and classification, and then centralized distribution tasks are carried out;

[0162] In unmanned freight mode, after local pickup and loading are completed, standardized cargo boxes are transferred to unmanned freight vehicles, which then perform trunk line transportation.

[0163] This application also provides an electronic device in its embodiments. (See reference...) Figure 8 The diagram illustrates a structural schematic suitable for implementing the electronic device in the embodiments of this application. The electronic device in the embodiments of this application may include, but is not limited to, devices such as MCU (Microcontroller Unit) and CPU (Central Processing Unit). Figure 8The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0164] like Figure 8 As shown, the electronic device may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage device 808 into a random access memory (RAM) 803. When the electronic device is powered on, the RAM 803 also stores various programs and data required for the operation of the electronic device. The processing unit 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0165] Typically, the following devices can be connected to I / O interface 805: input devices 806 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 807 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 808 including, for example, memory cards, hard drives, etc.; and communication devices 809. Communication device 809 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 8 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have alternatively.

[0166] This application also provides a computer program product including computer-readable instructions, which, when executed on an electronic device, cause the electronic device to implement any of the control methods for a logistics intelligent mobile body provided in this application.

[0167] This application also provides a computer-readable storage medium carrying one or more computer programs. When the one or more computer programs are executed by an electronic device, the electronic device can implement any of the control methods for intelligent mobile logistics provided in this application.

[0168] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and 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. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0169] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0170] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0171] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A control method for an intelligent mobile logistics entity, characterized in that, include: Obtain task instructions, which include a combined loading scheme determined by the cloud scheduling module based on the cargo attributes in the logistics demand data. The combined loading scheme consists of multiple standardized cargo boxes with different specifications. The logistics demand data also includes pickup point location information. Navigate to the pickup point based on the pickup point location information; Upon arrival at the pickup point, the control door opens, and each standardized cargo box is automatically loaded via a composite mechanical actuator. The composite mechanical actuator includes a horizontal moving mechanism and a vertical lifting mechanism. The automatic loading operation includes: controlling the vertical lifting mechanism to support the wings on both sides of the standardized cargo box and raise it a preset distance so that the standardized cargo box is detached from the support surface; and controlling the horizontal moving mechanism to move the standardized cargo box to a designated position within the cargo hold. After the automatic loading operation is completed, the transportation task is executed, and the task execution status is reported back to the cloud scheduling module.

2. The control method for intelligent mobile logistics units according to claim 1, characterized in that, The cargo attributes include at least one of the following: cargo volume, cargo weight, cargo quantity, and temperature control requirements. The combined loading scheme is generated by the cloud scheduling module based on the cargo attributes, selecting standardized cargo boxes of corresponding specifications and functional types from haploid, diploid, and triploid cargo boxes, and determining their combined quantity; wherein, the volume of the diploid cargo box is twice that of the haploid cargo box, and the volume of the triploid cargo box is three times that of the haploid cargo box, and the functional types include ordinary storage boxes, insulated boxes, and refrigerated boxes.

3. The control method for intelligent mobile logistics entities according to claim 2, characterized in that, The task instruction is issued by the cloud scheduling module after selecting the target object from multiple candidate objects based on the real-time location, remaining power, current task status, and configured double-sided cargo box type of each intelligent logistics mobile body in the park.

4. The control method for intelligent mobile logistics entities according to claim 1, characterized in that, The execution of the transportation task includes: obtaining destination location information, constructing or matching an environmental map in real time through SLAM and visual fusion positioning, planning a driving route, and driving to the destination according to the driving route.

5. The control method for a logistics intelligent mobile body according to claim 4, characterized in that, Also includes: Upon arrival at the destination, an automatic unloading operation is performed; the automatic unloading operation includes: Control the opening of the hatch; The horizontal moving mechanism is controlled to move the vertical lifting mechanism to the location of the standardized cargo box to be unloaded. Control the vertical lifting mechanism to rise to support the wings on both sides of the standardized cargo box; The vertical lifting mechanism is controlled to continue rising the preset distance so that the standardized cargo box is removed from the support position below it; The horizontal movement mechanism is controlled to cause the standardized cargo box to extend horizontally to the outside of the cargo hold; The vertical lifting mechanism is controlled to descend so as to place the standardized cargo box on the support surface of the unloading area.

6. The control method for a logistics intelligent mobile body according to claim 1, characterized in that, The horizontal moving mechanism includes a slide rail and an electric push rod, the electric push rod being used to drive the slide rail to extend and retract in the horizontal direction; the vertical lifting mechanism includes an electric slide table, the electric slide table being used to drive the slider to rise and fall in the vertical direction; the electric push rod is disposed on the slider.

7. The control method for a logistics intelligent mobile body according to claim 1, characterized in that, The system communicates with the cloud scheduling module via the MQTT protocol. The task instructions are obtained through the topic subscription / publishing mechanism of the MQTT protocol, and the running status data is uploaded to the cloud scheduling module via the MQTT protocol at a preset frequency.

8. The control method for a logistics intelligent mobile body according to claim 7, characterized in that, The operational status data includes real-time location, remaining battery power, driving speed, the operational status of the composite mechanical actuator, the location information of the standardized cargo box, and task execution progress. Upon receiving an adjustment instruction issued by the cloud scheduling module based on the operational status data, the adjustment instruction is executed. The adjustment instruction includes a pause loading / unloading instruction, a route adjustment instruction, and a task reassignment instruction.

9. The control method for a logistics intelligent mobile body according to claim 1, characterized in that, The task instruction also includes delivery mode information, which is determined by the cloud scheduling module based on the logistics demand data and at least one of the following: real-time status, delivery route distance, and order timeliness requirements; the delivery mode includes one of the following: direct delivery mode, sorting and consolidation mode, and unmanned freight mode. In the direct delivery mode, the transportation task from the pickup point to the destination is executed directly without transshipment; In the sorting and consolidation mode, the standardized cargo boxes are transported to the exchange station for order collection and classification, and then the centralized distribution task is carried out; In the unmanned freight mode, after local pickup and loading are completed, the standardized cargo box is transferred to an unmanned freight vehicle, which then performs trunk line transportation.

10. A control device for an intelligent mobile logistics system, characterized in that, include: The task acquisition module is used to acquire task instructions. The task instructions include a combined loading scheme determined by the cloud scheduling module based on the cargo attributes in the logistics demand data. The combined loading scheme consists of multiple standardized cargo boxes with different specifications. The logistics demand data also includes pickup point location information. The motion navigation module is used to navigate to the pickup point based on the pickup point location information; The loading and unloading control module is used to control the hatch to open upon arrival at the pickup point and to perform automatic loading operations via a composite mechanical actuator. The composite mechanical actuator includes a horizontal moving mechanism and a vertical lifting mechanism. The automatic loading operation includes: controlling the vertical lifting mechanism to support the wings on both sides of the standardized cargo container and raise it a preset distance to detach the standardized cargo container from the support surface; controlling the horizontal moving mechanism to move the standardized cargo container to a designated position within the cargo hold; and... The transportation execution module is used to execute the transportation task after the automatic loading operation is completed, and to report the task execution status to the cloud scheduling module.

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