Task scheduling method, task execution method, task scheduling system, task execution system and self-moving equipment

Abstract

The embodiment of the invention discloses a task scheduling method and system, a task execution method and system and self-moving equipment. The task scheduling method comprises the following steps: sending a mapping task instruction to a first self-moving device; receiving a planning map sent by the first self-moving device, wherein the planning map is obtained after the first self-moving device scans and maps the cargo container transportation tool by using a sensor carried by the first self-moving device; a carrying task is generated based on the map for planning, a carrying task instruction is sent to the second self-moving device, the carrying task instruction comprises a carrying task path, and the carrying task path is path information from the second starting position to the target storage location on the cargo container transportation tool. Aiming at the scene that the parking position and the parking posture of the cargo container transportation tool each time are different, it can be guaranteed that the self-moving equipment accurately executes the carrying task.

Description

Technical Field

[0001] The present application relates to the field of intelligent control technology, and particularly to a task scheduling method, a task execution method, a system and a self-mobile device. Background Art

[0002] Systems that use self-mobile devices such as AGVs (automated guided vehicles) for work have advantages such as high unmanned, automated, and intelligent levels, improving production efficiency and operation levels for industries such as warehousing, manufacturing, and logistics. As a relatively typical scenario, self-mobile devices are often responsible for handling tasks of cargo container transportation tools such as container trucks and container ships, mainly including loading / unloading, for example, transporting goods in the temporary storage area into the container truck carriage, or transporting the goods in the container truck carriage to the temporary storage area.

[0003] Since the docking positions and docking postures of cargo container transportation tools vary each time, how to ensure that self-mobile devices can accurately execute handling tasks has become an urgent problem to be solved. Summary of the Invention

[0004] In view of this, the present application provides a task scheduling method, a task execution method, a system and a self-mobile device to facilitate the accurate execution of handling tasks by self-mobile devices.

[0005] The present application provides the following solutions:

[0006] In a first aspect, a task scheduling method is provided, which is executed by a control system. The method includes:

[0007] Sending a mapping task instruction to a first self-mobile device;

[0008] Receiving a planning map sent by the first self-mobile device, where the planning map is obtained by the first self-mobile device scanning and mapping the cargo container transportation tool using sensors carried by the first self-mobile device;

[0009] Generating a handling task based on the planning map and sending a handling task instruction to a second self-mobile device. The handling task instruction includes a handling task path, and the handling task path is path information from a second starting position to a target storage location on the cargo container transportation tool;

[0010] Wherein, the first self-mobile device and the second self-mobile device are the same self-mobile device or different self-mobile devices.

[0011] Optionally, the mapping task instruction includes a static mapping path, and the static mapping path is path information from a first departure position to a target position, and the target position is within a preset range from the cargo container transportation vehicle;

[0012] The first departure position and the second departure position are the same position or different positions.

[0013] Optionally, before sending the mapping task instruction to the first mobile device, the method further includes:

[0014] The static mapping path is planned according to the working map and the location information of the cargo container transportation vehicle.

[0015] Optionally, the mapping task instruction further includes: information indicating unladen mapping or information indicating laden mapping.

[0016] Optionally, if the mapping task instruction includes information indicating cargo mapping, the static mapping path includes: a path from the first starting position to the temporary storage area and a path from the temporary storage area to the target position.

[0017] Optionally, the mapping task instruction further includes: a dynamic mapping path, and / or return path information, wherein the dynamic mapping path is path information from the target location into the loading space of the cargo container transportation vehicle.

[0018] Optionally, generating a transport task based on the planning map includes:

[0019] Determine the location of the target storage location on the cargo container transport vehicle and a dynamic transport path according to the planning map and the cargo size, wherein the dynamic transport path is a path from the target location to the target storage location, and the target location is within a preset range from the cargo container transport vehicle;

[0020] The transport task is generated according to the storage location in the temporary storage area, the transport scenario information and the dynamic transport path.

[0021] Optionally, before sending the transport task instruction to the second self-moving device, the method further includes:

[0022] The transport task path is generated according to the second departure position, the work map and the dynamic transport path.

[0023] Optionally, the type of the transport task is a loading task, and the transport task path includes: a path from the second departure position to the temporary storage area, a path from the temporary storage area to the target position, and a path from the target position to the target storage area; or,

[0024] The type of the handling task is an unloading task, and the handling task path further includes: a path from the target storage location to the temporary storage area location.

[0025] In a second aspect, a task execution method is provided, which is executed by a first self-moving device. The method includes:

[0026] In response to a mapping task instruction sent by a control system, control the first self-moving device to move from a first starting position to a target position, where the target position is within a preset range from a goods container transportation vehicle;

[0027] Use a sensor carried by the first self-moving device to scan and map the goods container transportation vehicle to obtain a map for planning;

[0028] Send the map for planning to the control system, and the map for planning is used to generate a handling task for the goods container transportation vehicle, and the handling task is executed by a second self-moving device;

[0029] Wherein, the first self-moving device and the second self-moving device are the same self-moving device or different self-moving devices.

[0030] Optionally, the mapping task instruction includes a static mapping path, and the static mapping path is path information from the first starting position to the target position.

[0031] Optionally, if the mapping task instruction includes information indicating mapping with goods loaded, then controlling the first self-moving device to move from the first starting position to the target position includes:

[0032] Control the first self-moving device to move from the first starting position to the temporary storage area location, carry goods from the temporary storage area location, and then move from the temporary storage area location to the target position.

[0033] Optionally, using a sensor carried by the first self-moving device to scan and map the goods container transportation vehicle to obtain a map for planning includes:

[0034] Control the first self-moving device to move from the target position and enter the loading space of the goods container transportation vehicle;

[0035] During the movement, use the sensor to scan environmental data, and use a SLAM module to obtain a second point cloud map from the target position to the loading space;

[0036] Project the second point cloud map onto the ground plane to obtain the map for planning.

[0037] Optionally, the mapping task instruction further includes: a dynamic mapping path, which is path information for entering the loading space of the cargo container transportation vehicle from the target position.

[0038] Optionally, controlling the first self-mobile device to move from the target position and enter the loading space of the cargo container transportation vehicle includes:

[0039] Controlling the first self-mobile device to start from the target position, move around the cargo container transportation vehicle to determine the position to enter the loading space, and enter the loading space from the determined position.

[0040] Optionally, projecting the second point cloud map onto the ground plane to obtain the planned map includes:

[0041] Intercepting the point cloud data within the operating height range of the cargo container transportation vehicle from the second point cloud map;

[0042] Projecting the intercepted point cloud data onto the ground plane and performing binarization processing to obtain the planned map.

[0043] Optionally, during the process of controlling the first self-mobile device to move from the first departure position to the target position, the method further includes: using the sensor to scan the environmental data, obtaining key frames from the first departure position to the target position by using the SLAM module, and splicing the key frames with the static point cloud map loaded when the first self-mobile device is initialized to obtain a first point cloud map.

[0044] Optionally, the method further includes:

[0045] Splicing the first point cloud map and the second point cloud map to obtain and store a third point cloud map.

[0046] Optionally, if the second self-mobile device and the first self-mobile device are the same self-mobile device, the second self-mobile device determines its pose according to the third point cloud map during the execution of the handling task; or,

[0047] If the second self-mobile device and the first self-mobile device are not the same self-mobile device, the method further includes: the first self-mobile device transmits the third point cloud map to the second self-mobile device so that the second self-mobile device determines its pose according to the third point cloud map during the execution of the handling task.

[0048] Optionally, if the second self - moving device and the first self - moving device are the same self - moving device, after scanning and mapping the cargo container transportation vehicle, the first self - moving device moves to the second departure position and waits for the handling task instruction sent by the control system;

[0049] Wherein, the first departure position and the second departure position are the same position or different positions.

[0050] In a third aspect, a system is provided, the system includes a control system, a first self - moving device, and a second self - moving device;

[0051] The control system is configured to send a mapping task instruction to the first self - moving device;

[0052] The first self - moving device is configured to, in response to the mapping task instruction, control the first self - moving device to move from the first departure position to a target position within a preset range from the cargo container transportation vehicle; use the sensor carried by the first self - moving device to scan and map the cargo container transportation vehicle to obtain a planned map; and send the planned map to the control system;

[0053] The control system is further configured to generate a handling task based on the planned map and send a handling task instruction to the second self - moving device, the handling task instruction includes a handling task path, and the handling task path is a path from the second departure position to the target storage location on the cargo container transportation vehicle;

[0054] The second self - moving device is configured to execute the handling task according to the handling task instruction;

[0055] Wherein, the first self - moving device and the second self - moving device are the same self - moving device or different self - moving devices, and the first departure position and the second departure position are the same position or different positions.

[0056] In a fourth aspect, a self - moving device is provided, the self - moving device includes:

[0057] A self - moving device body;

[0058] A sensor carried on the self - moving device body for scanning the cargo container transportation vehicle;

[0059] A memory for storing program instructions;

[0060] A processor coupled to the memory for reading the program instructions to execute the steps of the method described in the second aspect above.

[0061] According to the specific embodiments provided in the present application, the following technical effects are disclosed in the present application:

[0062] 1) In the present application, the control system adopts a two-stage task. First, it schedules the first self-mobile device to execute the mapping task. During the process of the first self-mobile device executing the mapping task, the sensor carried by the first self-mobile device is used to scan and map the cargo container transportation tool to obtain a planning map. Then, based on the planning map, the second self-mobile device is scheduled to execute the handling task. This two-stage task scheduling method can obtain the pose of the cargo container transportation tool in real time through the mapping task stage and obtain a planning map even if there are certain differences in the docking position and docking pose of the cargo container transportation tool each time, so as to ensure that the second self-mobile device executing the handling task in the second stage can accurately perform loading and unloading.

[0063] 2) Since the sensor carried by the first self-mobile device is used to scan and map the cargo container transportation tool, compared with the traditional method of externally placing sensors at the bridge connection, the construction difficulty and maintenance cost are reduced, and the calibration of the relationship between the two coordinate systems of the external sensor and the self-mobile device is also avoided. Therefore, it is more convenient to implement and has a lower cost.

[0064] 3) In the present application, according to the position information of the cargo container transportation tool and the static working map, the path from the first starting position to the target position is planned, and the path information is included in the mapping task instruction, so that when the first self-mobile device executes the mapping task, it can accurately reach the target position according to the path information, so that the first self-mobile device can start from the target position and use the sensor carried by itself to scan and map the cargo container transportation tool. This method reduces the accuracy requirement for the docking pose of the cargo container transportation tool and has higher compatibility with the diversity of the cargo container transportation tool.

[0065] 4) In the present application, during the process of the first self-mobile device moving from the target position and entering the loading space of the cargo container transportation tool, the sensor is used to scan the environmental data and the SLAM module is used to obtain the second point cloud map of entering the loading space from the target position. Then, the second point cloud map is projected onto the ground plane to obtain a planning map. The planning map generated in this way can accurately describe the pose of the cargo container transportation tool, so that the control system can generate a handling path based on the planning map and include it in the handling task instruction to guide the second self-mobile device to accurately execute the handling task.

[0066] 5) In this application, the point cloud data within the operating height range of the cargo container transport vehicle can be intercepted from the second point cloud map, and the intercepted point cloud data is projected onto the ground plane and binarized to obtain a planning map. This method not only reduces the amount of point cloud data for map processing but also can more accurately reflect the actual situation of the loading space of the cargo container transport vehicle in the planning map.

[0067] 6) In this application, the control system can accurately determine the position of the target storage location in the loading space of the cargo container transport vehicle and the path from the target position to the target storage location by using the planning map and the cargo size generated and sent by the first self - moving device, enabling the second self - moving device to precisely execute the handling task and improving the handling efficiency and safety.

[0068] 7) In this application, the first self - moving device can splice the key frames obtained from the first starting position to the target position with the static point cloud map loaded during initialization to obtain the first point cloud map, and can further splice the first point cloud map and the second point cloud map from the target position to the loading space to obtain the full - volume third point cloud map. This full - volume third point cloud map can be used to determine the pose during the process of the second self - moving device executing the handling task, ensuring that the second self - moving device accurately and efficiently executes the handling task.

[0069] 8) In this application, after receiving a new mapping task instruction, the first self - moving device clears the second point cloud map. On the one hand, it ensures that the second point cloud map is retained before all handling tasks are completed to ensure the normal completion of the handling tasks. On the other hand, it ensures that the second point cloud map is promptly cleared after all handling tasks are completed, saving the storage space of the first self - moving device and improving the performance of the first self - moving device.

[0070] Of course, not necessarily all of the above - mentioned advantages need to be achieved simultaneously for any invention of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of this application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0072] Figure 1 is the system architecture diagram applicable to the embodiments of this application;

[0073] Figure 2 is the flowchart of the task scheduling method provided by the embodiments of this application;

[0074] Figure 3 Detailed method flowchart executed by the control system provided in the embodiments of the present application;

[0075] Figure 4 Schematic diagram of the working area of the handling task provided in the embodiments of the present application;

[0076] Figure 5 Method flowchart of task execution provided in the embodiments of the present application;

[0077] Figure 6 Detailed method flowchart executed by the first self - moving device and the second self - moving device provided in the embodiments of the present application;

[0078] Figure 7 Schematic diagram of scanning the goods container transportation tool provided in the embodiments of the present application;

[0079] Figure 8 Schematic block diagram of the self - moving device provided in the embodiments of the present application. Detailed implementation manners

[0080] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0081] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms of "a", "the" and "said" used in the embodiments of the present invention and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise.

[0082] It should be understood that the term " / and / " used herein is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the front and rear associated objects.

[0083] Depending on the context, as used herein, the term "if" may be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detecting (stated condition or event)" may be interpreted as "when determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)". Additionally, the term "in accordance with" used herein is not limited to only depending on a certain object. For example, determining B in accordance with A may mean: only determining B in accordance with A, or partially determining B in accordance with A.

[0084] Due to the limited space in the cargo container transportation vehicle, in order to avoid collisions, there are high requirements for the positioning accuracy of the self - moving device. However, considering that there are certain differences in the docking position and docking attitude of the cargo container transportation vehicle each time, it is impossible to pre - establish a map for the cargo container transportation vehicle. In the existing implementation methods, some require installing external sensors near the cargo container transportation vehicle and scanning the cargo container transportation vehicle each time it arrives to establish a map. However, this method has at least the following drawbacks:

[0085] 1) To ensure the accuracy of map building, the external sensor needs to completely scan the cargo container transportation vehicle, especially the internal environment of the cargo container transportation vehicle, such as the interior of the carriage. Therefore, it usually needs to be placed at the bridging position between the outer platform edge and the cargo container transportation vehicle, and this bridging position is also the location where the self - moving device enters and exits the cargo container transportation vehicle, and a passage space needs to be left, which brings difficulties to the installation position of the external sensor and has extremely high construction requirements.

[0086] 2) Since the map obtained by scanning with the external sensor needs to be stitched with the static map of the self - moving device, it is necessary to calibrate the coordinate transformation relationship between the two maps, and the calibration accuracy requirement is very high. Otherwise, it will cause the self - moving device to collide inside the cargo container transportation vehicle, such as colliding with the carriage wall of the container truck.

[0087] 3) The external sensor requires additional power supply and network cable connections, and faces a semi - open outdoor environment. In order to avoid the influence of wind, rain, sun and exposure, it is necessary to protect and maintain the external sensor for a long time, thus bringing additional maintenance costs.

[0088] In view of this, the present application provides a new idea. To facilitate the understanding of the present application, first, the system architecture on which the present application is based will be described. Figure 1 An exemplary system architecture to which embodiments of the present application can be applied is shown, as Figure 1 shown in, this system architecture may include: a self - moving device and a control system.

[0089] Among them, the self - moving device refers to a tool equipped with an automatic guiding device such as electromagnetic or optical, controlled by a computer, with its own power or power conversion device, and capable of automatically moving along a specified path. In the embodiments of the present application, while the self - moving device can move, it can undertake certain tasks, such as transportation, handling (including picking up goods and unloading goods), etc. For example, the automatic moving device can be an AGV (Automated Guided Vehicle), a logistics robot, an intelligent forklift, etc.

[0090] In the embodiments of the present application, the self - moving device is installed with an on - vehicle software system, which has functions such as SLAM (Simultaneous Localization and Mapping), a map generation function for generating a planning map based on the mapping result, a motion control function for controlling the movement and work of the self - moving device, etc.

[0091] The control system (RCS) can be set on the server side and is responsible for scheduling each self - moving device, including task allocation, path planning, instruction issuance, etc. For details, please refer to the relevant records in the subsequent embodiments.

[0092] The above - mentioned control system can be set in an independent server, or in a server group, or in a cloud server. A cloud server, also known as a cloud computing server or a cloud host, is a host product in the cloud computing service system, which solves the problems of large management difficulty and weak service scalability existing in traditional physical hosts and virtual private servers (VPS, Virtual Private Server) services. In addition, the above - mentioned control system can also be set in a computer terminal with strong computing power.

[0093] It should be understood that Figure 1 the numbers of the self - moving devices and the control systems in

[0094] Figure 2 are only illustrative. According to the implementation requirements, there can be any number of self - moving devices and control systems. Figure 1 For the flowchart of the task scheduling method provided by the embodiments of the present application, this method can be executed by the RCS in the Figure 2 system shown. As shown in

[0095] Step 201: Send a mapping task instruction to the first self - moving device.

[0096] Step 203: Receive the planning map sent by the first self - moving device. The planning map is obtained by the first self - moving device scanning and mapping the cargo container transportation tool using the sensors carried by the first self - moving device.

[0097] Step 205: Generate a handling task based on the planned map, and send the handling task instruction to the second self-moving device. The handling task instruction includes a handling task path, and the handling task path is the path information from the second starting position to the target storage location on the cargo container transport vehicle. Among them, the first self-moving device and the second self-moving device are the same self-moving device or different self-moving devices.

[0098] It can be seen from the above process that in this application, the control system adopts a two-stage task. First, it schedules the first self-moving device to execute the mapping task. During the process of the first self-moving device executing the mapping task, the sensor carried by the first self-moving device is used to scan and map the cargo container transport vehicle to obtain the planned map. Then, based on the planned map, the second self-moving device is scheduled to execute the handling task. This two-stage task scheduling method can obtain the pose of the cargo container transport vehicle in real time through the mapping task stage and obtain the planned map even if the docking position and docking attitude of the cargo container transport vehicle are different each time, so as to ensure that the second self-moving device executing the handling task in the second stage can accurately perform loading and unloading.

[0099] In addition, since the sensor carried by the first self-moving device is used to scan and map the cargo container transport vehicle, compared with the traditional method of externally placing sensors at the bridge connection, the construction difficulty and maintenance cost are reduced, and the calibration of the relationship between the two coordinate systems of the external sensor and the self-moving device is also avoided. Therefore, it is more convenient to implement and the cost is lower.

[0100] The following describes in detail each step in the above process and the effects that can be further generated in combination with a specific embodiment. It should be noted that the "first", "second", etc. limitations involved in this disclosure do not have limitations in terms of size, order, quantity, etc., and are only used to distinguish by name.

[0101] In the embodiment of this application, after the control system is started, as Figure 3 shown, it can first perform the initialization process in step 301. The initialization process includes loading the working map, establishing a communication connection with each self-moving device, etc. Among them, the above working map can be a static environment map, including the road network information of the working environment where the self-moving device is located, that is, the working map is composed of multiple path segments connected and covers the working area of the self-moving device. In the embodiment of this application, the above working area mainly refers to areas such as warehouses, platforms, and temporary storage areas, and can include the position of boarding the cargo container transport vehicle, but usually does not include areas outside the position of boarding the cargo container transport vehicle (such as the area of the loading space of the container transport vehicle, etc.).

[0102] For easy understanding, in combination withFigure 4 Brief introductions are made to the above-mentioned regions. For example Figure 4 As shown in Figure 4 , when the self-mobile device is not performing work, it is usually located at its own parking position, which can be a position such as a warehouse, a shed, etc. The cargo container transport vehicle can be a truck, a cargo ship, a wing van, etc. The cargo container transport vehicle has a loading space, which can be a carriage, a platform, a rack, etc. The position where the goods are placed in the loading space is called a storage location. The cargo container transport vehicle usually stops at a designated position on the platform. The bridging position between the platform and the cargo container transport vehicle is usually used for the self-mobile device to board the transport vehicle. For example, it can be a boarding bridging position, a boarding ship bridging position, etc. When the self-mobile device is performing a handling task, it is necessary to move the goods in each storage location in the temporary storage area to the storage location of the cargo container transport vehicle (i.e., loading) or move the goods in the storage location of the cargo container transport vehicle to the storage location in the temporary storage area (i.e., unloading).

[0103] In the embodiment of the present application, the working map loaded during the initialization of the control system may include road network information of regions such as Figure 4 the warehouse, the temporary storage area, and the platform area as shown in Figure 4 . The working map can be composed of path segments connected end to end.

[0104] The target position can be a preset position in the working map. In the embodiment of the present application, the target position is usually a position within a preset range from the cargo container transport vehicle, and its function is to enable the self-mobile device (i.e., the first self-mobile device) performing the mapping task to start scanning the cargo container transport vehicle after reaching the target position. For example, the target position can be set as the position to board the transport vehicle. For example, if the cargo container transport vehicle is a container truck, the target position can be the boarding bridging position. For another example, if the cargo container transport vehicle is a cargo ship, the target position can be the boarding ship bridging position. For another example, if the cargo container transport vehicle is a wing van, the target position can be any position near the wing van.

[0105] In the embodiment of the present application, the above-mentioned target position can be one or multiple. For example, there may be multiple parking positions of container trucks in the working area, and each container truck has a boarding bridging position, so each container truck corresponds to its own target position.

[0106] For example Figure 3 As shown in Figure 3 , in step 302, the RCS receives a task start instruction, executes step 303, generates a mapping task and sends a mapping task instruction to the first self-mobile device.

[0107] The above task start instruction can be sent by the staff through the trigger terminal device. For example, when the staff determines that the cargo container transportation vehicle has docked at the platform position, they trigger the terminal device to send a task start instruction to the RCS through physical or virtual buttons on the terminal device, or by inputting an instruction, etc. In addition to being triggered by the staff, other methods can also be adopted.

[0108] After receiving the task start instruction, the RCS generates a mapping task. The process of generating the mapping task is mainly a path planning process, that is, according to the working map and the position information of the cargo container transportation vehicle, a path from the first starting position to the target position is planned.

[0109] Among them, the position information of the cargo container transportation vehicle can be obtained from the task start instruction. For example, the docking positions of each cargo container transportation vehicle can be numbered, and the number is carried in the task start instruction and sent to the RCS. The RCS can determine the approximate docking position of the cargo container transportation vehicle and the corresponding target position (for example, the position where one boards the cargo container transportation vehicle from the platform) information based on this number.

[0110] In the embodiment of the present application, a path segment refers to a smaller part or unit that constitutes a path. The planned path is a sequence of path segments connected end to end in sequence. The starting point of the first path segment is the starting point of this path planning, that is, the starting position of the first self-mobile device (referred to as the first starting position in the embodiment of the present application), and the ending point of the last path segment is the ending point of this path planning, that is, the target position.

[0111] Furthermore, each path segment in the planned path segment sequence corresponds to time window information. The so-called time window is the time information indicating the movement of the target self-mobile device on the corresponding path segment, usually represented by a time interval, that is, the time window. It can be understood that the target self-mobile device passes through the path segment within the time interval corresponding to the time window.

[0112] In this step, as one possible implementation method, a path search algorithm such as A-Star can be used to perform path planning on the target self-mobile device, generate a sequence of path segments from the starting point to the ending point, and use this sequence of path segments as the path corresponding to the mapping task.

[0113] As another more optimal implementation method, after using a path search algorithm such as A-Star to perform path planning on the target self-mobile device and generating a sequence of path segments from the starting point to the ending point, the sequence of path segments can be further optimized based on conflict detection, and the optimized sequence of path segments is used as the path corresponding to the mapping task.

[0114] The optimization based on conflict detection refers to comparing each path segment in the path segment sequence planned for the first self - moving device with the planned paths of other self - moving devices one by one to determine whether there is a conflict, and updating the time window information in the path judgment sequence based on the conflict detection result.

[0115] If there is the same path segment corresponding to the same time in the path segment sequence planned for the first self - moving device and the planned paths of other self - moving devices, it indicates that there may be a risk of collision between the first self - moving device and other self - moving devices. Therefore, there is a conflict in this path segment.

[0116] Or, if the distance between two path segments corresponding to the same time in the path segment sequence planned for the first self - moving device and the planned paths of other self - moving devices is not sufficient to accommodate the corresponding two self - moving devices, it indicates that there may be a risk of collision between the first self - moving device and other self - moving devices. Therefore, there is a conflict between these two path segments. Among them, when performing the detection, the safety distance corresponding to the two self - moving devices (the first self - moving device and other self - moving devices) can be determined according to their geometric dimensions; according to the safety distance, the distance between the current path segment sequence of the first self - moving device and the path segment corresponding to the same time in the planned path of another self - moving device is determined, and two path segments with a distance less than the above - mentioned safety distance have a conflict.

[0117] If a conflict is detected in a path segment in the current road segment fragment, in order to avoid collision, the first self - moving device can be made to wait for a period of time before this path segment. Therefore, a waiting time can be set before the path segment with a conflict in the current path segment sequence and the time window corresponding to each path segment can be updated. The waiting time set can take a fixed duration or can be determined according to the time window information corresponding to the conflicting path segment.

[0118] After the update, it can continue to go to perform conflict detection on the updated current path segment sequence until no conflict is detected. Through this planning method, it can be ensured that there is no conflict in the planned paths of all self - moving devices at the same time.

[0119] After obtaining the path information from the first departure position to the target position, this path information is called the static mapping path in the embodiments of the present application, and this static mapping path can be included in the mapping task instruction and sent to the first self - moving device.

[0120] Furthermore, the mapping task instruction can also include the path information for entering the loading space of the cargo container transportation vehicle from the target position, and this path information is called the dynamic mapping path in the embodiments of the present application.

[0121] Among them, since there is currently no accurate map of the cargo container transportation vehicle, the path information (i.e., the dynamic mapping path) for entering the loading space of the cargo container transportation vehicle from the target location can be preset with a low precision requirement. It is preset according to the approximate docking position and size of the cargo container transportation vehicle, as long as it ensures no collision with the cargo container transportation vehicle.

[0122] Furthermore, the mapping task instruction may also include return path information, which can be the path from the target location back to the first departure location, aiming to determine whether the first self-mobile device can return to the first departure location after completing the scanning of the cargo container transportation vehicle.

[0123] In addition, the above mapping task instruction can be divided into the following two cases:

[0124] One case is the no-load mapping instruction. In this case, information indicating no-load mapping can be included in the mapping task instruction. The so-called no-load mapping means that the first self-mobile device adopts a no-load form during the entire mapping process. In this case, the above static mapping path can be the path directly from the first departure location to the target location.

[0125] The other case is the load-carrying mapping instruction. In this case, information indicating load-carrying mapping can be included in the mapping task instruction. The so-called load-carrying mapping means that after the first self-mobile device picks up the goods from the temporary storage area bin, it carries the goods during the mapping process, so as to facilitate not having to pick up the goods from the temporary storage area bin again when performing the first handling task after completing the mapping, thereby improving efficiency. In this case, the above static mapping path includes: the path from the first departure location to the temporary storage area bin and the path from the temporary storage area bin to the target location.

[0126] Regarding the process of the first self-mobile device generating the planning map, refer to the relevant records in the subsequent embodiments. As Figure 3 shown, after RCS executes step 303, in step 304, it waits to receive the planning map from the first self-mobile device.

[0127] As Figure 3 shown, after RCS receives the planning map, it executes step 305 to generate a handling task list using the planning map.

[0128] The planning map generated by the first self - moving device is a two - dimensional map, which includes the area from the target position to the area on the cargo container transportation vehicle, such as the map information from the boarding bridge connection position to the cargo container transportation vehicle and inside the cargo container transportation vehicle. For example, it can be a planar map in the form of a grid, and each grid marks whether the area corresponding to this grid allows passage. The planning map can be used to generate the path of the handling task. When generating the handling task, mainly the path of the handling task is generated, that is, the path information from the starting position of the second self - moving device (referred to as the second starting position in the embodiments of this application) to the target storage location on the cargo container transportation vehicle.

[0129] In the embodiments of this application, the self - moving device for performing the mapping task and the self - moving device for performing the handling task can be the same self - moving device or different self - moving devices. If they are the same self - moving device, the above - mentioned first starting position and second starting position are usually the same. If they are different self - moving devices, the above - mentioned first starting position and second starting position are usually different.

[0130] In this step, according to the planning map and the cargo size, the position of the target storage location in the loading space of the cargo container transportation vehicle and the path from the target position to this target storage location can be determined. In the embodiments of this application, the path from the target position to the target storage location is called the dynamic handling path; according to the temporary storage area storage location, the handling scenario information, and the dynamic handling path, a handling task is generated.

[0131] Among them, since the planning map includes the map information of the loading space of the cargo container transportation vehicle, the position of the target storage location in the loading space of the cargo container transportation vehicle can be determined according to the cargo size, and these positions need to ensure that the goods can be accommodated in sequence. In addition, according to the planning map, path search algorithms such as GVD (Generalized Voronoi Diagram) and A - Star can be used to plan the path from the target position to the target storage location. Since the pose of the cargo container transportation vehicle is different, this path will be different, so this path is essentially a dynamic path.

[0132] In the embodiments of this application, the handling scenarios mainly include the loading scenario and the unloading scenario. Correspondingly, the handling tasks mainly include the loading task and the unloading task. The loading task refers to transporting the goods from the temporary storage area storage location to the target storage location in the loading space of the cargo container transportation vehicle, and the unloading task refers to transporting the goods from the target storage location in the loading space of the cargo container transportation vehicle to the temporary storage area.

[0133] As one of the feasible ways, a handling task list can be generated first. The handling task list includes at least one handling task. For the loading task, it is necessary to ensure that the order of the storage locations in the loading space of the cargo container transportation tool for each handling task is from the inside to the outside. For the unloading task, it is necessary to ensure that the order of taking out the storage locations from the loading space of the cargo container transportation tool for each handling task is from the outside to the inside.

[0134] For each handling task, a handling task path can be generated by using the second departure position, the working map, and the dynamic handling path. The handling task path includes at least the path from the second departure position to the target storage location.

[0135] Specifically, if the type of the handling task is a loading task, the handling task path (i.e., the path from the second departure position to the target storage location) includes: the path from the second departure position to the temporary storage area storage location, the path from the temporary storage area storage location to the target position, and the path from the target position to the target storage location, so as to complete the handling of the goods at the temporary storage area storage location from the second departure position to the target storage location in the loading space of the cargo container transportation tool.

[0136] As one of the feasible ways, if the mapping task instruction sent in step 303 includes information indicating mapping with goods loaded, and the type of the handling task is a loading task, the first handling task path can include: the path directly from the second departure position to the target storage location. Among them, the second departure position can be the mapping end position (i.e., the end point of the dynamic mapping path), any position inside or near the cargo container transportation tool, or a specified docking position.

[0137] Taking the second departure position as the mapping end position as an example, after the first self-moving device completes the mapping with goods loaded, it waits at the end point of the dynamic mapping path. After receiving the handling task instruction, it directly moves from the end point of the dynamic mapping path to the target storage location and places the goods at the target storage location, thereby improving the efficiency.

[0138] If the type of the handling task is an unloading task, in addition to the path from the second departure position to the target storage location, the handling task path can further include: the path from the target storage location to the temporary storage area storage location, so as to complete the handling of the goods at the target storage location in the loading space of the cargo container transportation tool from the second departure position to the temporary storage area storage location.

[0139] When planning the above paths, optimization based on conflict detection can also be further performed, that is, optimizing the time window information of the path segments in conflict with other self-moving devices based on conflict detection. The specific method can refer to the relevant records in the previous embodiments and will not be elaborated here.

[0140] And in step 306, send a handling task instruction to the second self-moving device.

[0141] For one handling task, RCS can send the handling task path information to the second self-moving device included in the handling instruction at one time, or segment the handling task path information and send it to the second self-moving device through multiple sub-instructions of the handling task respectively. This application does not limit this.

[0142] During the process of the second self-moving device executing the handling task, RCS communicates with the second self-moving device. As Figure 3 shown in step 307, obtain the status information of the second self-moving device. If receiving the information of the task status sent by the second self-moving device after completing the handling task, end the current handling task and execute step 308; otherwise, continue to step 307.

[0143] In step 308, determine whether all the handling tasks in the handling task list have been executed. If not, go to execute step 306 and send the handling instruction of the next handling task to the second self-moving device; if so, end Figure 3 the shown process.

[0144] Figure 5 It is a flowchart of the task execution method provided by an embodiment of this application. This method can be executed by the first self-moving device. As Figure 5 shown, this method can include the following steps:

[0145] Step 501: In response to the mapping task instruction sent by the control system, control the first self-moving device to move from the first starting position to the target position, and the target position is within a preset range from the cargo container transportation tool.

[0146] Step 503: Use the sensor carried by the first self-moving device to scan and map the cargo container transportation tool to obtain a planning map.

[0147] Step 505: Send the planning map to the control system. The planning map is used to generate a handling task for the cargo container transportation tool, and the handling task is executed by the second self-moving device; wherein, the first self-moving device and the second self-moving device are the same self-moving device or different self-moving devices.

[0148] The following combines a specific embodiment to describe each step in the above process and the further effects that can be generated in detail.

[0149] In the embodiment of this application, after the first self-moving device is started, as Figure 6As shown in [figure reference], the initialization process in step 601 can be executed first. This initialization process includes loading the static point cloud map, establishing a communication connection with the RCS, etc.

[0150] The static point cloud map is the point cloud map of the working environment where the first self-mobile device is located, covering the working area of the self-mobile device. In the embodiments of the present application, the above-mentioned working area mainly refers to areas such as warehouses, platforms, and temporary storage areas, which may include the positions for boarding the cargo container transportation vehicle, but usually does not include areas outside the positions for boarding the cargo container transportation vehicle (such as the area of the loading space of the container transportation vehicle, etc.).

[0151] In step 602, if a mapping task instruction sent by the RCS is received, then in step 603, according to the static mapping path included in the mapping task instruction, control the first self-mobile device to move from the first starting position to the target position.

[0152] The mapping task instruction includes at least the static mapping path, that is, the path information from the first starting position to the target position. The planning method of this path information can refer to the relevant records of the [embodiment reference] shown, and will not be elaborated here. Figure 3 shown embodiments, and will not be elaborated here.

[0153] As one possible implementation, if the mapping task instruction includes information indicating mapping while carrying goods, then control the first self-mobile device to move from the first starting position to the temporary storage area location, carry goods from the temporary storage area location, and then move from the temporary storage area location to the target position.

[0154] Furthermore, the mapping task instruction may also include a dynamic mapping path, that is, the path information from the target position to enter the loading space of the cargo container transportation vehicle. This path information can be pre-set with a relatively low accuracy requirement, pre-set according to the approximate docking position and size of the cargo container transportation vehicle, as long as it ensures no collision with the cargo container transportation vehicle.

[0155] Furthermore, the mapping task instruction may also include return path information. The return path information can be the path from the target position back to the first starting position, aiming to determine whether the first self-mobile device can return to the first starting position after completing the scanning of the cargo container transportation vehicle.

[0156] During the process of the first self-mobile device controlling itself to move from the first starting position to the target position according to the static mapping path included in the mapping task instruction, it uses the sensors (such as radar) carried by itself to scan the environmental data, and uses the SLAM module to obtain the first point cloud map from the first starting position to the target position.

[0157] Specifically, when the first self - moving device controls its movement according to the path information included in the mapping task instruction, the SLAM module can use the Local SLAM algorithm for positioning. Among them, the Local SLAM algorithm can include: splicing the point cloud of the key frames collected in real - time and the static point cloud map to obtain a first point cloud map, which can be regarded as the map obtained by aligning several latest key frames collected on the static point cloud map. Then, algorithms such as the GICP (Generalized Iterative Closest Point) algorithm are used to calculate the relative pose of the point cloud of the current frame with respect to the first point cloud map, thereby determining the current pose. Since the Local SLAM algorithm is an existing algorithm, it will not be elaborated here.

[0158] The following describes in detail step 503 above, that is, "scanning and mapping the cargo container transportation vehicle using the sensors carried by the first self - moving device to obtain a planning map".

[0159] After the first self - moving device moves to the target position, for example, after reaching the boarding bridge connection position, it executes step 604 to start extended mapping and obtain a second point cloud map. In step 605, it is determined whether it has moved to the task end point. If so, it executes step 606; otherwise, it returns to continue executing step 604.

[0160] The sensors carried by the self - moving device can include various types of radars such as lidar, millimeter - wave radar, ToF (Time of Flight) radar, and can further include visual sensors such as cameras.

[0161] The above - mentioned extended mapping process can include: moving along the dynamic mapping path included in the mapping task instruction from the target position and entering the loading space of the cargo container transportation vehicle, and using the carried sensors for scanning during the movement. During the whole process, the external and internal parts of the cargo container transportation vehicle can be scanned, and the SLAM module can establish a dynamic point cloud map of the cargo container transportation vehicle area, which is called the second point cloud map in the embodiments of the present application.

[0162] As Figure 7 shown in the figure, the dotted - line circle in the figure is part of the positions of the first self - moving device during movement. The first self - moving device enters the loading space of the cargo container transportation vehicle along the path shown by the red straight line L2 in the figure from the target position, and the blue dotted line L1 is the radar scanning area of the first self - moving device. During the movement, the first self - moving device initially scans the external environment of the cargo container transportation vehicle, and when it enters the cargo container transportation vehicle, it scans the internal environment of the cargo container transportation vehicle, and the obtained point cloud data forms the second point cloud map.

[0163] The first self - moving device does not have to reach the end in the loading space of the cargo container transportation vehicle, as long as it can scan all parts of the loading space.

[0164] For container trucks, container ships, etc., usually the position where they enter the loading space is the rear door. Therefore, container trucks and container ships usually align their rear doors with the boarding bridge connection position. Thus, it is relatively easy to roughly plan the dynamic mapping path for entering the loading space of the cargo container transportation vehicle from the target position, and include the dynamic mapping path information in the mapping task instruction. However, there are still some special cases. For example, the two - wing side plates of a wing van (also known as a wing - opening vehicle, two - wing vehicle, etc.) can be opened, and at the same time, the rear door of the carriage can also be opened. Therefore, the boarding entrance position is not determined, and thus it is impossible to roughly plan in advance the path information for entering the carriage of the wing van from the target position. For such special cases, after the first self - moving device reaches the target position, it can drive around the vehicle and collect images of the wing van through a visual camera, determine the boarding entrance position of the wing van by image recognition, and enter the interior of the carriage from this boarding entrance position, so as to complete the acquisition of point cloud data and establish the second point cloud map.

[0165] Among them, the SLAM module can store the scanned key - frame data (including point cloud data and corresponding pose information) in the memory of the self - moving device during the movement of the self - moving device. After reaching the end of the path, the key - frame data saved in the memory is stitched according to the pose information, and after the stitched point cloud data is down - sampled, the second point cloud map is formed.

[0166] After reaching the end of the path, step 606 is executed to stitch the first point cloud map and the second point cloud map to obtain and store the third point cloud map. It can be seen that the third point cloud map, as a full - scale point cloud map, can be used by the self - moving device (referred to as the second self - moving device in the embodiments of the present application) that performs subsequent handling tasks to determine its pose during the handling task.

[0167] After the first self - moving device reaches the end of the path (i.e., the path for entering the loading space of the cargo container transportation vehicle from the target position), if the space is sufficient, the first self - moving device can turn around and return along the return path information included in the mapping task instruction. If the space is not sufficient, the first self - moving device can first reverse along the return path information included in the mapping task instruction and return to the target position, and then turn around and continue to return to the first starting position along the return path information.

[0168] As another achievable way, if the first self-mobile device adopts the method of mapping while carrying goods, that is, the received mapping task instruction includes information indicating mapping while carrying goods, the first self-mobile device moves from the first starting position to the temporary storage area bin, after carrying the goods from the temporary storage area bin, moves from the temporary storage area bin to the target position, and then starts scanning and mapping along the dynamic mapping path. In this way, after the first self-mobile device completes mapping while carrying goods, it can wait at the end of the dynamic mapping path, or wait at any position near the goods container transportation vehicle, or wait at a designated docking position. Then the position where the first self-mobile device waits is the second starting position for subsequent carrying tasks.

[0169] In step 607, a planning map is generated using the second point cloud map.

[0170] In this step, the first self-mobile device can intercept the point cloud data within the target range from the second point cloud map, project the intercepted point cloud data onto the ground plane to obtain a planning map.

[0171] Among them, the target range refers to the operating height range of the goods container transportation vehicle, and an empirical value can be taken. For example, the height range of 0.2 meters to 2.5 meters is selected according to the usual height of the goods container transportation vehicle. It can also be set according to the actual scenario.

[0172] The planning map is a two-dimensional map. After projecting the intercepted point cloud data onto the ground plane, it is further binarized to obtain an initial map, and then the initial map is rasterized to obtain a raster map as the planning map. Among them, the rasterization process can include dividing the initial map into multiple grids, and determining the state of each grid, including the occupied state or the free state, according to the projection relationship between the point cloud data and each grid.

[0173] If the grid is occupied, it is determined that there is an obstacle in this grid and it is not passable; if the grid is not occupied, it is determined that there is no obstacle in this grid and it is passable. Among them, the state of the grid can be determined according to the number of point cloud points projected onto this grid. For example, if the number of point cloud points projected onto this grid exceeds a preset number threshold, it is determined that this grid is in the occupied state, otherwise it is determined to be in the free state. The preset number threshold can be determined according to empirical values and / or the degree of safety requirements, etc.

[0174] In addition to the raster map, the planning map can also adopt other forms of maps, such as a point density map, etc.

[0175] The planning map can adopt an image format, such as lossless compressed image formats like PNG (Portable Network Graphics) and BMP (Bitmap).

[0176] In step 608, the first self - moving device sends the planned map to the RCS.

[0177] So far, the mapping task of the first self - moving device has been completed. After receiving the planned map, the RCS generates a handling task and issues it to the second self - moving device. In the embodiments of the present application, the first self - moving device and the second self - moving device may be different self - moving devices. At this time, in order to ensure that the second self - moving device can complete pose determination when executing the handling task, the first self - moving device may provide the third point cloud map to the second self - moving device.

[0178] As one implementable way, the first self - moving device can directly transmit the third point cloud map to the second self - moving device, for example, by using near - field communication.

[0179] As another implementable way, the first self - moving device transmits the third point cloud map to the RCS, and the second self - moving device downloads the third point cloud map from the RCS.

[0180] As yet another implementable way, the third point cloud map of the first self - moving device can be copied to a storage system within the local area network, such as NAS (Network Attached Storage), and then the third point cloud map in the storage system is copied to the second self - moving device.

[0181] Other ways can also be used to implement providing the third point cloud map of the first self - moving device to the second self - moving device, which will not be listed one by one here.

[0182] The first self - moving device and the second self - moving device may be the same self - moving device. Taking the case where the two are the same self - moving device as an example, the first self - moving device continues to execute Figure 6 step 609 shown in [the figure], waits for the handling task instruction issued by the RCS. If the handling task instruction is received, step 610 is executed; otherwise, it continues to wait.

[0183] In step 610, according to the handling task path included in the handling task instruction, that is, the path information from the second starting position (when the first self - moving device and the second self - moving device are the same self - moving device, it can be the first starting position) to the target storage location on the cargo container transportation vehicle, the first self - moving device is controlled to move to the target storage location.

[0184] During the above movement of the first self - moving device, the SLAM module uses the third point cloud map to determine and adjust the pose, so as to ensure moving to the target storage location.

[0185] The above-mentioned handling task instruction may include the task type and the above path information. If the task type is a loading task, the first self-moving device reaches the temporary storage area location according to the path information from the second starting position, transports goods from the temporary storage area location and reaches the target position (such as the boarding bridge connection position) from the temporary storage area location, and then reaches the target location in the loading space of the goods container transport vehicle from the target position, and places the goods in the target location.

[0186] As another achievable method, if the first self-moving device previously adopted the method of mapping while carrying goods, then when executing the first loading task, it can directly reach the target location from the second starting position and place the already carried goods in the target location. For subsequent loading tasks, it goes to the temporary storage area location to pick up goods and then transports them to the target location and places them in the target location.

[0187] If the task type is an unloading task, the first self-moving device reaches the target location in the loading space of the goods container transport vehicle according to the path information from the second starting position, picks up goods from the target location and transports them to the temporary storage area location and places them in the temporary storage area location.

[0188] During the process of the first self-moving device executing the handling task, it reports status information to the RCS. In step 611, it is judged whether the handling task is completed. If the handling task is completed, step 612 is executed to report the information of the task completion status to the RCS; otherwise, step 611 is continued to be executed.

[0189] It should be noted here that if the path information in the handling task instruction adopts the method of being issued in segments, the first self-moving device will receive multiple sub-instructions corresponding to a handling task, and each sub-instruction contains a segment of path information. The first self-moving device moves according to the received sub-instructions and moves to the target location to complete the handling task.

[0190] After the first self-moving device reports the information of the task completion status, it can wait to receive a new handling task or a new mapping task.

[0191] Furthermore, since there may be multiple handling tasks in the handling task list formed at the RCS end, the second self-moving device receives the handling task instructions one by one and executes the handling tasks, and cannot know whether all the handling tasks in the entire handling task list are completed. Therefore, it can respond to receiving a new mapping task instruction and clear the second point cloud map. That is, receiving a new mapping task means that all the handling tasks in the handling task list are completed. Since the docking position and attitude of the goods container transport vehicle are different each time it arrives, the mapping task and the handling task need to be executed each time. Therefore, the second point cloud map used in the previous handling task is no longer applicable and can be cleared.

[0192] Doing so ensures, on the one hand, that the second point cloud map is retained until all handling tasks are completed to ensure the normal completion of the handling tasks, and on the other hand, that the second point cloud map is promptly cleared after all handling tasks are completed, saving the storage space of the first self-mobile device and improving the performance of the first self-mobile device.

[0193] The specific embodiments of this specification have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0194] The task processing system provided by the embodiments of this application includes a control system, a first self-mobile device, and a second self-mobile device.

[0195] The control system is configured to send a mapping task instruction to the first self-mobile device.

[0196] The first self-mobile device is configured to, in response to the mapping task instruction, control the first self-mobile device to move to a target position within a preset range from the cargo container transportation vehicle; use the sensors carried by the first self-mobile device to scan and map the cargo container transportation vehicle to obtain a planning map; and send the planning map to the control system.

[0197] The control system is further configured to generate a handling task based on the planning map and send a handling task instruction to the second self-mobile device. The handling task instruction includes a handling task path, which is a path from a second starting position to a target storage location on the cargo container transportation vehicle.

[0198] The second self-mobile device is configured to execute the handling task according to the handling task instruction.

[0199] Wherein, the first self-mobile device and the second self-mobile device are the same self-mobile device or different self-mobile devices, and the first starting position and the second starting position are the same position or different positions.

[0200] Regarding the functions and specific processing of the control system, the first self-mobile device, and the second self-mobile device in the system, refer to the relevant records in the previous method embodiments, which will not be elaborated here.

[0201] Figure 8 It is a schematic diagram of the composition of the self-mobile device provided by the embodiments of this application, as Figure 8As shown in the figure, the self - moving device includes: a self - moving device body 810, a sensor 820 mounted on the self - moving device body, a memory 830, and a processor 840.

[0202] Among them, the sensor 820 is used to scan the cargo container transportation vehicle.

[0203] The memory 830 is used to store program instructions.

[0204] The processor 840 is coupled to the memory 830 and is used to read the program instructions stored in the memory 830 to perform the following processing:

[0205] In response to the mapping task instruction sent by the control system, control the self - moving device to move from the starting position to the target position, where the target position is within a preset range from the cargo container transportation vehicle;

[0206] Use the scanning result of the sensor on the cargo container transportation vehicle to build a map to obtain a map for planning;

[0207] Send the map for planning to the control system, and the map for planning is used to generate a handling task for the cargo container transportation vehicle.

[0208] In some embodiments, the mapping task instruction may include a static mapping path, and the static mapping path is the path information from the starting position to the target position.

[0209] In some embodiments, if the mapping task instruction includes information indicating mapping with cargo, when the processor 840 controls the self - moving device to move from the starting position to the target position, it may specifically execute:

[0210] Control the self - moving device to move from the starting position to the staging area storage location, carry the cargo from the staging area storage location, and then move from the staging area storage location to the target position.

[0211] In some embodiments, when the processor 840 uses the sensor mounted on the self - moving device to scan and map the cargo container transportation vehicle, it may specifically execute:

[0212] Control the self - moving device to move from the target position and enter the loading space of the cargo container transportation vehicle;

[0213] During the movement, use the sensor to scan the environmental data, and use the SLAM module to obtain a second point cloud map from the target position to enter the loading space;

[0214] Project the second point cloud map onto the ground plane to obtain a map for planning.

[0215] In some embodiments, the above mapping task instruction further includes: a dynamic mapping path, which is path information for entering the loading space of the cargo container transportation vehicle from the target position; the processor 840 executes processing to control the self-mobile device to move from the target position and enter the loading space of the cargo container transportation vehicle according to the dynamic mapping path.

[0216] In some embodiments, when the processor 840 controls the self-mobile device to move from the target position and enter the loading space of the cargo container transportation vehicle, it specifically executes:

[0217] Control the self-mobile device to start from the target position, move around the cargo container transportation vehicle and determine the position to enter the loading space, and enter the loading space from the determined position.

[0218] In some embodiments, when the processor 840 projects the second point cloud map onto the ground plane to obtain a planning map, it can specifically execute:

[0219] Intercept the point cloud data within the operating height range of the cargo container transportation vehicle from the second point cloud map;

[0220] Project the intercepted point cloud data onto the ground plane and perform binarization processing to obtain a planning map.

[0221] In some embodiments, during the process of the processor 840 controlling the self-mobile device to move from the departure position to the target position, it further executes the following processing:

[0222] Obtain the environmental data scanned by the sensor, and use the SLAM module to obtain the key frames from the departure position to the target position, and splice the key frames with the static point cloud map loaded when the first self-mobile device is initialized to obtain the first point cloud map.

[0223] In some embodiments, the processor 840 further executes: splicing the first point cloud map and the second point cloud map to obtain and store the third point cloud map.

[0224] In some embodiments, the processor 840 further executes: in response to receiving a new mapping task instruction, clearing the second point cloud map.

[0225] In some embodiments, the sensor 820 may include radars of types such as lidar, millimeter wave radar, ToF (Time of Flight) radar, etc., and may further include visual sensors such as cameras.

[0226] In some embodiments, the processor 840 may be one or more. It may be implemented in the form of a general-purpose CPU, a microprocessor, an application specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute the above program instructions to implement the technical solutions provided in this application.

[0227] The memory 830 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc.

[0228] It should be noted that although the above self-moving device only shows the self-moving device body 810, the sensor 820, the memory 830, the processor 840, etc., in the specific implementation process, the self-moving device may also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above self-moving device may also only include the components necessary to implement the solution of this application, and does not necessarily include all the components shown in the figure.

[0229] Each embodiment in this specification is described in a progressive manner. The same or similar parts between each embodiment can be referred to each other, and the differences between each embodiment and other embodiments are emphasized. In particular, for the system or device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments. The system and device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0230] The embodiments of this application also provide a computer program product. When the computer program product runs on a computer, it causes the computer to execute the steps of the method described in the foregoing method embodiments.

[0231] The above has introduced the technical solution provided by this application in detail. Specific examples are used in this article to elaborate on the principle and implementation manner of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A task scheduling method, executed by a control system, characterized in that: The method comprises: Sending a mapping task instruction to a first mobile device; Receiving a planning map sent by the first self-mobile device, wherein the planning map is obtained by the first self-mobile device scanning and mapping the cargo container transportation vehicle using a sensor carried by the first self-mobile device; Generate a transport task based on the planning map, and send a transport task instruction to the second self-moving device, wherein the transport task instruction includes a transport task path, and the transport task path is path information from the second departure position to the target storage location on the cargo container transportation vehicle; The first self-moving device and the second self-moving device are the same self-moving device or different self-moving devices.

2. The method according to claim 1, characterized in that The mapping task instruction includes a static mapping path, where the static mapping path is path information from a first departure position to a target position, and the target position is within a preset range from the cargo container transportation vehicle; The first departure position and the second departure position are the same position or different positions.

3. The method according to claim 2, characterized in that Before sending the mapping task instruction to the first mobile device, the method further includes: The static mapping path is planned according to the working map and the location information of the cargo container transportation vehicle.

4. The method according to claim 2, characterized in that: The mapping task instruction also includes: information indicating empty-load mapping or information indicating loaded-load mapping.

5. The method according to claim 4, characterized in that If the mapping task instruction includes information indicating cargo mapping, the static mapping path includes: a path from the first starting position to the temporary storage area and a path from the temporary storage area to the target position.

6. The method according to claim 2, characterized in that The mapping task instruction also includes: a dynamic mapping path, and / or return path information, wherein the dynamic mapping path is path information from the target location into the loading space of the cargo container transportation vehicle.

7. The method according to claim 1, characterized in that Generating a transport task based on the planning map includes: Determine the location of the target storage location on the cargo container transport vehicle and a dynamic transport path according to the planning map and the cargo size, wherein the dynamic transport path is a path from the target location to the target storage location, and the target location is within a preset range from the cargo container transport vehicle; The transport task is generated according to the storage location in the temporary storage area, the transport scenario information and the dynamic transport path.

8. The method according to claim 7, characterized in that Before sending the transport task instruction to the second self-moving device, the method further includes: The transport task path is generated according to the second departure position, the work map and the dynamic transport path.

9. The method according to claim 7, characterized in that: The type of the transport task is a loading task, and the transport task path includes: a path from the second departure position to the temporary storage area, a path from the temporary storage area to the target position, and a path from the target position to the target storage area; or, The type of the transport task is an unloading task, and the transport task path further includes: a path from the target storage location to the temporary storage area storage location.

10. A task execution method, executed by a first self-mobile device, characterized in that: The method comprises: In response to a mapping task instruction sent by the control system, control the first self-moving device to move from a first starting position to a target position, wherein the target position is within a preset range from the cargo container transportation vehicle; Scanning and mapping the cargo container transportation vehicle using a sensor carried by the first self-moving device to obtain a planning map; Sending the planning map to the control system, the planning map is used to generate a handling task for the cargo container transportation vehicle, the handling task being performed by a second self-moving device; The first self-moving device and the second self-moving device are the same self-moving device or different self-moving devices.

11. The method according to claim 10, characterized in that The mapping task instruction includes a static mapping path, and the static mapping path is path information from the first starting position to the target position.

12. The method according to claim 10, characterized in that If the mapping task instruction includes information indicating cargo mapping, then controlling the first self-moving device to move from the first starting position to the target position includes: The first self-moving device is controlled to move from the first starting position to a temporary storage area, and after the goods are transported from the temporary storage area, the self-moving device is moved from the temporary storage area to the target position.

13. The method according to any one of claims 10 to 12, characterized in that The cargo container transportation vehicle is scanned and mapped using the sensor carried by the first self-moving device to obtain a planning map, including: Controlling the first self-moving device to move from the target location and enter the loading space of the cargo container transportation vehicle; Scanning environmental data using the sensor during the movement, and obtaining a second point cloud map from the target position into the loading space using a SLAM module; The second point cloud map is projected onto the ground plane to obtain the planning map.

14. The method according to claim 13, characterized in that The mapping task instruction also includes: a dynamic mapping path, and the dynamic mapping path is path information from the target location into the loading space of the cargo container transportation vehicle.

15. The method according to claim 13, characterized in that Controlling the first self-moving device to move from the target position and enter the loading space of the cargo container transportation vehicle includes: The first self-moving device is controlled to start from the target position, move around the cargo container transportation vehicle and determine the position where it enters the loading space, and enter the loading space from the determined position.

16. The method according to claim 13, characterized in that Projecting the second point cloud map onto the ground plane to obtain the planning map includes: intercepting point cloud data within the operating height range of the cargo container transportation vehicle from the second point cloud map; The intercepted point cloud data is projected onto the ground plane and binarized to obtain the planning map.

17. The method according to claim 13, characterized in that In the process of controlling the first self-moving device to move from a first starting position to a target position, the method also includes: using the sensor to scan environmental data, and using the SLAM module to obtain a key frame from the first starting position to the target position, and splicing the key frame with the static point cloud map loaded when the first self-moving device is initialized to obtain a first point cloud map.

18. The method according to claim 17, characterized in that The method further comprises: The first point cloud map and the second point cloud map are spliced ​​to obtain a third point cloud map.

19. The method according to claim 18, characterized in that If the second self-moving device and the first self-moving device are the same self-moving device, the second self-moving device determines a position and posture according to the third point cloud map during the process of performing the transport task; or, If the second self-moving device and the first self-moving device are not the same self-moving device, the method further includes: the first self-moving device transmits the third point cloud map to the second self-moving device, so that the second self-moving device determines the position and posture according to the third point cloud map during the execution of the transport task.

20. The method according to claim 10, characterized in that If the second self-moving device and the first self-moving device are the same self-moving device, after scanning and mapping the cargo container transportation vehicle, the first self-moving device moves to a second departure position and waits for a handling task instruction sent by the control system; The first departure position and the second departure position are the same position or different positions.

21. A system, characterized in that: The system includes a control system, a first self-moving device, and a second self-moving device; The control system is configured to send a mapping task instruction to the first self-mobile device; The first self-moving device is configured to, in response to the mapping task instruction, control the first self-moving device to move from a first starting position to a target position, wherein the target position is within a preset range from the cargo container transportation vehicle; use the sensor carried by the first self-moving device to scan and map the cargo container transportation vehicle to obtain a planning map; and send the planning map to the control system; The control system is further configured to generate a handling task based on the planning map and send a handling task instruction to the second self-moving device, wherein the handling task instruction includes a handling task path, and the handling task path is a path from the second departure position to the target storage location on the cargo container transportation vehicle; The second self-moving device is configured to perform the transport task according to the transport task instruction; The first self-moving device and the second self-moving device are the same self-moving device or different self-moving devices, and the first starting position and the second starting position are the same position or different positions.

22. A self-propelled device, characterized in that: The self-moving device comprises: Self-equipped device body; A sensor mounted on the main body of the self-moving device is used to scan the cargo container transportation vehicle; A memory for storing program instructions; A processor coupled to the memory is configured to read the program instructions to execute the steps of the method according to any one of claims 10 to 20.

Images