Congestion area determination method, apparatus, device, and storage medium

Abstract

The application provides a congestion area determination method and device, equipment and a storage medium, relates to the technical field of robots, and is used for improving the identification accuracy of a congestion area. The method comprises the following steps: acquiring movement information of each robot in a target area; the movement information comprises a movement speed, a travel path and position information; and the congestion area in the target area is determined based on the movement information of each robot. The congestion area comprises N congestion robots with a movement speed less than a preset speed, N is a positive integer, the distance between each two adjacent congestion robots in the N congestion robots is less than or equal to a preset distance, and / or one of each two adjacent congestion robots blocks the travel path of the other.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and in particular to a method, apparatus, device, and storage medium for determining congested areas. Background Technology

[0002] In warehouse environments, multiple robots often cluster together, forming congested areas. These congested areas reduce robot handling efficiency, thus impacting the overall efficiency of the warehouse system. Therefore, accurately identifying congested areas in the warehouse environment is crucial for rationally planning robot travel paths. However, current technologies for identifying congested areas often rely on limited factors, making it difficult to pinpoint accurate congestion points. This often results in identified congested areas that are not actually congested. Summary of the Invention

[0003] To address the aforementioned technical issues, this application provides a method, apparatus, device, and storage medium for determining congested areas, thereby improving the accuracy of congested area identification.

[0004] In a first aspect, this application provides a method for determining a congested area. The method includes: acquiring movement information of each robot in a target area; the movement information includes movement speed, travel path, and location information; determining a congested area in the target area based on the movement information of each robot; wherein the congested area includes N congested robots with movement speeds less than a preset speed, where N is a positive integer; and the distance between any two adjacent congested robots is less than or equal to a preset distance, and / or, one of any two adjacent congested robots blocks the travel path of the other.

[0005] In one possible implementation, determining a congested area in a target region based on the movement information of each robot includes: determining a target robot; the target robot includes robots in a non-moving state in the target region; determining at least one congested robot that meets preset conditions; the preset conditions include a moving speed less than a preset speed, a travel path blocked by the target robot, and a distance between the robot and the target robot less than a preset distance; and determining the congested area based on the position information of at least one congested robot.

[0006] In one possible implementation, the target robot also includes a robot that satisfies one or more of the following: its travel path is blocked by a robot in a non-moving state, its moving speed is less than a preset speed, and its distance from the robot in a non-moving state is less than a preset distance.

[0007] In one possible implementation, determining the congested area based on the location information of at least one congestion robot includes: determining the congested area based on the location information of at least one congestion robot when the number of at least one congestion robot is greater than a preset number.

[0008] In one possible implementation, determining the congested area based on the location information of at least one congestion robot includes: determining the road segment where at least one congestion robot is located in the target area based on the location information of each congestion robot, and designating the road segment as the congested area.

[0009] In one possible implementation, determining the congested area based on the location information of at least one congestion robot includes: determining the congested area as the circumscribed graph including the location of at least one congestion robot, according to the location information of each congestion robot.

[0010] One possible implementation method also includes resetting each congestion robot to the target robot.

[0011] In one possible implementation, the method further includes: obtaining the number of congested areas in the target area to obtain a first statistical count of congested areas; updating the first statistical count based on statistical conditions to obtain a second statistical count of congested areas; the statistical conditions include treating two congested areas as one congested area when there is an overlapping area between any two congested areas.

[0012] In one possible implementation, the method further includes: replanning the driving path for the non-congested robot in the target area before it enters the congested area.

[0013] In one possible implementation, the method further includes: controlling the non-congested robot to stop and wait when the replanned driving path overlaps with the congested area, and / or controlling the non-congested robot to enter an avoidable state; the avoidable state is used to instruct the non-congested robot to drive into the nearest avoidance point to its current location.

[0014] The congestion area determination method provided in this application acquires the movement information of each robot in the target area, gaining a global understanding of the robot's movement speed, path, and position. Furthermore, based on the movement information of each robot, congestion areas within the target area are determined. Compared to related technologies that rely solely on the movement speed of a single robot to determine congestion areas, this application considers the driving relationships between robots in addition to their movement speed, such as the distance between robots and their obstruction relationships. As a result, the congestion areas determined by this application not only have slow robot speeds but also close intervals and clear obstruction relationships, reasonably reflecting real-world congestion scenarios and avoiding situations where two robots that are far apart or have no obstruction relationship are still identified as congested, thus improving the accuracy of congestion area identification.

[0015] Secondly, this application provides a congestion area determination device, which includes an acquisition unit and a determination unit. The acquisition unit is used to acquire the movement information of each robot in a target area. The movement information includes movement speed, travel path, and position information. The determination unit is used to determine the congestion area in the target area based on the movement information of each robot. The congestion area includes N congested robots with a movement speed less than a preset speed, where N is a positive integer. Furthermore, the distance between any two adjacent congested robots is less than or equal to a preset distance, and / or, one of any two adjacent congested robots blocks the travel path of the other.

[0016] In one possible implementation, the determining unit is specifically used for: determining a target robot; the target robot includes robots in a non-moving state in the target area; determining at least one congested robot that meets preset conditions; the preset conditions include a moving speed less than a preset speed, a travel path blocked by the target robot, and a distance between the robot and the target robot less than a preset distance; and determining a congested area based on the location information of at least one congested robot.

[0017] In one possible implementation, the target robot also includes a robot that satisfies one or more of the following: its travel path is blocked by a robot in a non-moving state, its moving speed is less than a preset speed, and its distance from the robot in a non-moving state is less than a preset distance.

[0018] In one possible implementation, the determining unit is specifically used to: determine the congested area based on the location information of the congested robots when the number of at least one congestion robot is greater than a preset number.

[0019] In one possible implementation, the determining unit is specifically used to: determine the road segment where at least one congestion robot is located in the target area based on the location information of each congestion robot, and designate the road segment as the congestion area.

[0020] In one possible implementation, the determining unit is specifically used to: determine the congestion area as the circumscribed graph including the location of at least one congestion robot, based on the location information of each congestion robot.

[0021] In one possible implementation, the determining unit is further configured to: reset each of the congestion robots to the target robot.

[0022] In one possible implementation, the acquisition unit is further configured to: acquire the number of congested areas in the target area to obtain a first statistical count of congested areas; update the first statistical count based on statistical conditions to obtain a second statistical count of congested areas; the statistical conditions include treating two congested areas as one congested area when there is an overlapping area between any two congested areas.

[0023] In one possible implementation, the determining unit is also used to: replan the driving path for the non-congested robot before it enters the congested area from the target area.

[0024] In one possible implementation, the determining unit is further configured to: control the non-congested robot to stop and wait when the replanned driving path overlaps with the congested area, and / or control the non-congested robot to enter an avoidable state; the avoidable state is used to instruct the non-congested robot to drive into the nearest avoidance point to its current location.

[0025] Thirdly, this application provides an electronic device, including: a processor and a memory; the memory stores instructions executable by the processor; the processor is configured to execute the instructions such that the electronic device implements the method of the first aspect described above.

[0026] Fourthly, this application provides a computer-readable storage medium, the readable storage medium comprising: software instructions; when the software instructions are executed in an electronic device, the electronic device causes the electronic device to implement the method described in the first aspect.

[0027] Fifthly, this application provides a computer program product that, when run in an electronic device, causes the electronic device to execute the methods related to the first aspect described above, thereby implementing the methods of the first aspect.

[0028] The beneficial effects of the second to fifth aspects mentioned above can be referred to the first aspect, and will not be repeated here. Attached Figure Description

[0029] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 A schematic diagram of the congestion area determination system provided in this application embodiment;

[0031] Figure 2 A schematic diagram illustrating the composition of the electronic device provided in the embodiments of this application;

[0032] Figure 3 A flowchart illustrating the congestion area determination method provided in this application embodiment;

[0033] Figure 4 This is a schematic diagram illustrating the determination of congested areas provided in an embodiment of this application;

[0034] Figure 5 This is another schematic diagram illustrating the determination of a congested area provided in an embodiment of this application;

[0035] Figure 6 This is a schematic diagram of path planning provided for an embodiment of this application;

[0036] Figure 7 This is a schematic diagram of the congestion path determination device provided in the embodiments of this application. Detailed Implementation

[0037] To enable those skilled in the art to better understand the technical solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0038] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0039] Furthermore, in the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The term "and / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, in the description of the embodiments of this application, "multiple" refers to two or more.

[0040] Before providing a detailed explanation of the embodiments of this application, some related terms and technologies involved in the embodiments of this application will be introduced first.

[0041] A robot is a machine that can perform tasks automatically. It can be directed by humans, run pre-programmed programs, or act according to principles established using artificial intelligence technology.

[0042] Mobile robots are robots that can autonomously navigate, locate, and move using positioning technology. When classified by structure, mobile robots can include wheeled robots, multi-legged robots, and autonomous vehicles operating indoors or in specific environments. When classified by application, mobile robots can include robotic vacuum cleaners, welcoming robots, food delivery robots, automated guided vehicles (AGVs), and educational robots with autonomous navigation capabilities.

[0043] With the increasing automation in manufacturing and logistics, AGVs have been widely used. These AGVs are equipped with automated guidance devices (e.g., electromagnetic or optical guides) and can automatically travel along a guided path while carrying objects. This guided path is usually planned for the AGV before it departs from its initial position.

[0044] In practical applications, AGVs are usually used in the form of systems. For example, an AGV system in a logistics warehouse includes: ground control equipment and multiple AGVs. The ground control equipment manages the multiple AGVs, for example, by planning corresponding guide paths for each of the multiple AGVs, and each AGV travels according to the corresponding guide path.

[0045] Specifically, the ground control device pre-stores an electronic map of the target environment, which contains multiple pre-set waypoints, each with a corresponding location within the target environment. When planning the AGV's travel path, the ground control device employs a path planning algorithm to sequentially select multiple waypoints from the pre-set waypoints between the AGV's initial position and the target position. The AGV's travel path is then formed by the AGV's initial position, the selected waypoints, and the target position.

[0046] However, in warehousing environments, multiple AGVs often cluster together, forming congestion zones. For example, if one AGV malfunctions and stops, it may obstruct the normal passage of subsequent AGVs, creating a congestion zone. The existence of congestion zones leads to low AGV handling efficiency, thus affecting the overall operational efficiency of the warehousing system. Therefore, accurately identifying congestion zones in the warehousing environment and rationally planning the AGV's travel paths is of great significance.

[0047] Some related technologies rely on the robot's movement speed to determine congestion and estimate a general congestion area based on the position of slower-moving robots. However, this method struggles to identify accurate congestion areas, often resulting in identified congestion zones that are not actually congested. For example, if an AGV needs to stop to unload goods, the technology might determine that the section of road where the AGV is located is congested, thus classifying that section as congested. But in reality, that section is not congested.

[0048] In view of the above problems, embodiments of this application provide a method, apparatus, device, and storage medium for determining congested areas. Compared with related technologies that rely solely on the movement speed of a single robot to determine congested areas, this application considers the driving relationships between robots in addition to their movement speed, such as the distance between robots in front and behind and their obstruction relationships. As a result, the congested areas determined by this application not only have slow robot speeds but also close intervals and clear obstruction relationships, which can reasonably reflect real congestion scenarios and avoid situations where two robots that are far apart or have no obstruction relationship are still identified as congested, thus improving the accuracy of congested area identification.

[0049] The method for determining congested areas provided in this application will be described in detail below with reference to the accompanying drawings.

[0050] The congestion area determination method provided in this application embodiment can be applied to a congestion area determination system. Figure 1 A schematic diagram of one structure of this congestion area determination system is shown. For example... Figure 1 As shown, the congestion area determination system 10 includes a congestion area determination device 11 and multiple robots 12. The congestion area determination device 11 and each robot 12 can be connected via a wired network or a wireless network.

[0051] Robot 12 may include sweeping robots, welcoming robots, food delivery robots, AGVs, and educational robots with autonomous navigation capabilities.

[0052] Correspondingly, multiple robots 12 can be deployed in the target area to perform preset tasks, such as deploying multiple AGVs in a logistics warehouse, which are responsible for transporting goods.

[0053] As described above, the congestion area determination device 11 and the robot 12 can be connected via a wired network or a wireless network. This wired or wireless network may include the ability to transmit relevant data from the robot 12 to the congestion area determination device 11.

[0054] In some embodiments, the wired or wireless network may include one or more communication media that enable the robot 12 to transmit real-time driving data directly to the congestion area determination device 11. In this embodiment, the robot 12 may modulate the driving data according to a communication standard (e.g., a wireless communication protocol) and transmit the modulated driving data to the congestion area determination device 11. The one or more communication media may include wireless and / or wired communication media, such as radio frequency (RF) spectrum or one or more physical transmission lines. Optionally, the one or more communication media may form part of a packet-based network, such as a local area network, a wide area network, or a global network (e.g., the Internet). Optionally, the one or more communication media may also include routers, switches, base stations, or other devices that facilitate communication between the robot 12 and the congestion area determination device 11.

[0055] The congestion area determination device 11 can be used to determine the congestion area in the target area based on the collected movement information of each robot 12. The specific determination process can refer to the congestion area determination method described in the following method embodiment, which will not be repeated here.

[0056] In some embodiments, the congestion area determination device 11 can also manage multiple robots 12, for example, by planning corresponding guidance paths for each of the multiple robots 12, and each robot 12 travels according to the corresponding guidance path. Alternatively, the congestion area determination device 11 can also control the travel status of each robot 12, such as controlling a certain robot 12 to stop moving.

[0057] The congestion area determination device 11 can be an electronic device with computing and processing capabilities, such as a computer or server.

[0058] The server can be a single server or a server cluster consisting of multiple servers. In some embodiments, the server cluster can also be a distributed cluster. Optionally, the server can also be implemented on a cloud platform, such as a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, inter-cloud, and multi-cloud, or any combination thereof. This application does not limit this aspect.

[0059] The execution entity of the congestion area determination method provided in this application embodiment can be the aforementioned congestion area determination device 11. As described above, the congestion area determination device 11 can be an electronic device with computing processing capabilities, such as a computer or server. Optionally, the congestion area determination device 11 can also be a processor (e.g., a central processing unit (CPU)) in the aforementioned electronic device; or, the congestion area determination device 11 can also be an application (APP) with fault analysis capabilities installed in the aforementioned electronic device; or, the congestion area determination device 11 can also be a functional module with fault analysis capabilities in the aforementioned electronic device, etc. This application embodiment does not impose any limitations on this.

[0060] This method can be executed by electronic devices with computing capabilities, such as storage devices, computers, and servers. Especially when integrated into storage devices, it can significantly improve the performance of those devices and enhance the user experience. For simplicity, the congestion area determination device 11 will be used as an example in the following description.

[0061] Figure 2 This is a schematic diagram illustrating the composition of an electronic device provided in an embodiment of this application. For example... Figure 2 As shown, the electronic device may include: a processor 20, a memory 21, a communication line 22, a communication interface 23, and an input / output interface 24.

[0062] The processor 20, memory 21, communication interface 23 and input / output interface 24 can be connected via communication line 22.

[0063] Processor 20 is used to execute instructions stored in memory 21 to implement the congestion area determination method provided in the following embodiments of this application. Processor 20 may be a CPU, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller (MCU) / single-chip microcomputer / microcontroller, a programmable logic device (PLD), or any combination thereof. Processor 20 may also be any other device with processing capabilities, such as a circuit, device, or software module; this application embodiment does not limit this. In one example, processor 20 may include one or more CPUs, for example... Figure 2 CPU0 and CPU1 in the example. As an optional implementation, the electronic device may include multiple processors; for example, in addition to processor 20, it may also include processor 25. Figure 2 (The example shown is a dashed line).

[0064] The memory 21 is used to store instructions. For example, the instructions may be computer programs. Optionally, the memory 21 may be a read-only memory (ROM) or other types of static storage devices that can store static information and / or instructions; it may also be a random access memory (RAM) or other types of dynamic storage devices that can store information and / or instructions; it may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, etc. The embodiments of this application do not limit this.

[0065] It should be noted that the memory 21 can exist independently of the processor 20, or it can be integrated with the processor 20. The memory 21 can be located inside or outside the electronic device, and this embodiment does not impose any restrictions on this.

[0066] Communication line 22 is used to transmit information between the components included in the electronic device.

[0067] Communication interface 23 is used to communicate with other devices (such as the aforementioned storage device 12) or other communication networks. These other communication networks can be Ethernet, radio access network (RAN), wireless local area network (WLAN), etc. Communication interface 23 can be a module, circuit, transceiver, or any device capable of enabling communication.

[0068] Input / output interface 24 is used to enable human-computer interaction between the user and the electronic device. For example, it enables action interaction or information exchange between the user and the electronic device.

[0069] For example, the input / output interface 24 can be a mouse, keyboard, display screen, or touch screen. Action interaction or information exchange between the user and the electronic device can be achieved through a mouse, keyboard, display screen, or touch screen.

[0070] It should be noted that, Figure 2 The structures shown do not constitute a limitation on electronic devices, except... Figure 2In addition to the components shown, electronic devices may include more or fewer components than illustrated, or combinations of certain components, or different component arrangements.

[0071] The following describes the method for determining congested areas provided in the embodiments of this application.

[0072] Figure 3 This is a flowchart illustrating the congestion area determination method provided in an embodiment of this application. Optionally, this method can be implemented by a person having the above-described... Figure 2 The electronic device with the hardware structure shown performs, such as Figure 3 As shown, the method includes S301 to S302.

[0073] S301. Obtain the movement information of each robot in the target area.

[0074] The movement information includes movement speed, travel path, and location information.

[0075] In some embodiments, multiple robots can be deployed in a target area to perform preset tasks, such as deploying multiple AGVs in a logistics warehouse to handle goods. Each robot can report its movement information to an electronic device via a wireless network. Correspondingly, the electronic device receives the movement information reported by each robot in the target area.

[0076] In other embodiments, the target area can be defined according to user needs. For example, based on user requirements, the electronic device can set a portion of a logistics warehouse as the target area. Alternatively, the electronic device can set a specific automated workshop in a factory as the target area.

[0077] S302. Based on the movement information of each robot, determine the congested areas in the target area.

[0078] The congested area includes N congestion robots with a moving speed less than a preset speed, where N is a positive integer; and the distance between any two adjacent congestion robots is less than or equal to a preset distance, and / or, one of any two adjacent congestion robots blocks the path of the other.

[0079] In one possible implementation, S302 can be implemented as follows: S3021, determine the target robot, wherein the target robot includes a robot in a non-moving state in the target area. Further, S3022, determine at least one congestion robot that meets preset conditions, wherein the preset conditions include a moving speed less than a preset speed, a travel path blocked by the target robot, and a distance less than a preset distance between the robot and the target robot. S3023, determine the congestion area based on the location information of at least one congestion robot.

[0080] In some embodiments, to determine congested robots in a target area, the electronic device can detect each robot in the target area based on its movement speed, identifying robots in a non-moving state as the first robot. Further, the electronic device can detect each robot in the target area based on its travel path and location information, identifying at least one congested robot blocked by the first robot, thus obtaining a set of congested robots corresponding to the first robot. The electronic device can determine the congested robots in the target area based on the set of congested robots corresponding to each target robot in the target area.

[0081] Specifically, the electronic device can identify a second robot from the set of congestion robots, wherein the second robot's moving speed is less than or equal to a preset speed, and the distance between the second robot and the first robot is less than or equal to a preset distance. Further, based on the first and second robots, the electronic device identifies congestion robots within a target area.

[0082] For example, the first robot and the second robot can be identified as congestion robots in the target area.

[0083] In other embodiments, the target robot also includes a robot that satisfies one or more of the following: its travel path is blocked by a robot in a non-moving state, its movement speed is less than a preset speed, and its distance from the robot in a non-moving state is less than a preset distance.

[0084] In other embodiments, after S3022 described above, the method further includes resetting each congestion robot to a target robot. That is, steps S3021-S3022 are repeated until all congestion robots in the target area that meet the criteria are identified.

[0085] For example, when the electronic device detects that the first robot cannot move, it detects which robots' subsequent paths are blocked by the first robot and records these blocked second robots as a set Set1. Further, the electronic device checks whether the distance between the second robot and the first robot in Set1 is less than a certain threshold and whether the speed is less than a certain threshold. If these conditions are met, the second robot is reset to the first robot, and the above detection steps are repeated until all robots that meet the preset conditions are identified.

[0086] In some embodiments, after identifying the congestion robots, in order to determine the congestion area, the electronic device can determine the road segment where at least one congestion robot is located in the target area based on the location information of each congestion robot, and designate the road segment as the congestion area.

[0087] In other embodiments, the electronic device can determine a congested area, including at least one congested robot, as a circumscribed shape (such as a circumscribed rectangle) based on the location information of each congestion robot.

[0088] In some embodiments, after identifying at least one congested robot corresponding to the target robot, the electronic device can count the number of at least one congested robot. If the number of at least one congested robot is greater than a preset number, congestion is determined to have occurred, and a congested area is determined based on the location information of the congested robots. If the number of at least one congested robot is less than or equal to the preset number, no congestion is determined to have occurred.

[0089] Understandably, through the above method, this application embodiment will only determine congestion when the number of congestion robots reaches a certain level. If the number of congestion robots is small, congestion will not be considered to have occurred. This raises the threshold for confirming congestion areas and avoids situations where congestion areas are easily identified but are not actually congested.

[0090] In some other embodiments, to facilitate the statistical analysis of congested areas, after identifying congested areas within a target area, the electronic device can obtain the number of congested areas in the target area, thus obtaining a first statistical count of congested areas. Further, the electronic device updates the first statistical count based on statistical conditions to obtain a second statistical count of congested areas; the statistical conditions include treating any two congested areas as a single congested area if there is an overlap between them.

[0091] like Figure 4 As shown, assuming the threshold for the number of congestion robots is 2, if Figure 4 If three robots are moving from left to right in the upper left corner, and the robot on the right is not moving, then the electronic device can identify the area formed by these three robots as a congested area, which is marked with a dashed box. Figure 4 There are two L-shaped congestion areas in the lower left corner. Because these two areas overlap, the electronic equipment can count them as one when counting congestion areas. Additionally, Figure 4 Although the two robots on the right side of the middle path have a path interference relationship, they do not generate a congestion area because the distance between them is far.

[0092] like Figure 5 As shown, if the number of robots in a group meets the requirements, and the congestion area is determined using a bounding rectangle, then this bounding rectangle needs to cover all the congested robots in the group. Additionally, if the shelf or bin on a robot is larger than the robot itself, then the shelf or bin needs to be covered. The electronic system can determine the congestion area by adding half the maximum length of the robot to the side length of the minimum bounding rectangle. For example, Figure 5The merged congestion area in the lower left corner can be represented by a large bounding rectangle with a dashed line.

[0093] The congestion area determination method provided in this application acquires the movement information of each robot in the target area, gaining a global understanding of the robot's movement speed, path, and position. Furthermore, based on the movement information of each robot, congestion areas within the target area are determined. Compared to related technologies that rely solely on the movement speed of a single robot to determine congestion areas, this application considers the driving relationships between robots in addition to their movement speed, such as the distance between robots and their obstruction relationships. As a result, the congestion areas determined by this application not only have slow robot speeds but also close intervals and clear obstruction relationships, reasonably reflecting real-world congestion scenarios and avoiding situations where two robots that are far apart or have no obstruction relationship are still identified as congested, thus improving the accuracy of congestion area identification.

[0094] In some embodiments, after identifying a congested area in the target region, the electronic device can notify other robots in the target region so that other robots wanting to pass through the region can avoid the congested area or be prevented from entering the congested area in a timely manner, thereby preventing the congestion area from expanding.

[0095] For example, electronic devices can replan the driving path of a non-congested robot in a target area before it enters a congested area.

[0096] In some embodiments, when the replanned driving path overlaps with a congested area, the electronic device can control the non-congested robot to stop and wait, and / or control the non-congested robot to enter an avoidable state; the avoidable state is used to instruct the non-congested robot to drive into the nearest avoidance point to its current location.

[0097] For example, after an electronic device identifies a congested area, if a robot outside the congested area needs to pass through it on its subsequent path, the corresponding planning strategy could include at least:

[0098] Strategy 1: Electronic devices can replan routes for robots operating in less congested areas. For example... Figure 6 As shown, the original path Path_a of the robot on the far left passes through the congested area within the black dashed box. The new path Path_b planned after replanning can avoid passing through the congested area.

[0099] In some embodiments, if the replanned new path still passes through congested areas, any of the following strategies can be implemented:

[0100] Strategy 2-1: Electronic devices control the parking of non-congested robots that are about to enter congested areas.

[0101] Strategy 2-2: Electronic devices control non-congested machines that are about to enter a congested area to enter an avoidance state, instructing non-congested machines to select an avoidance location where no vehicles are passing or a temporary accommodation point where no vehicles are staying.

[0102] In other embodiments, once the congestion area is cleared, the electronic device can control the parked robot to re-trigger movement.

[0103] The foregoing primarily describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the aforementioned functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0104] In an exemplary embodiment, this application also provides a congestion area determination device. Figure 7 This is a schematic diagram illustrating the composition of the congestion area determination device provided in an embodiment of this application. Figure 7 As shown, the congestion area determination device includes: an acquisition unit 401 and a determination unit 402.

[0105] The acquisition unit 401 is used to acquire the movement information of each robot in the target area; the movement information includes movement speed, travel path and position information; the determination unit 402 is used to determine the congested area in the target area based on the movement information of each robot; wherein, the congested area includes N congested robots with a movement speed less than a preset speed, where N is a positive integer; and, the distance between any two adjacent congested robots is less than or equal to a preset distance, and / or, one of any two adjacent congested robots blocks the travel path of the other.

[0106] In one possible implementation, the determining unit 402 is specifically used for: determining a target robot; the target robot includes a robot in a non-moving state in the target area; determining at least one congested robot that meets preset conditions; the preset conditions include a moving speed less than a preset speed, a travel path blocked by the target robot, and a distance between the robot and the target robot less than a preset distance; and determining a congested area based on the location information of at least one congested robot.

[0107] In one possible implementation, the target robot also includes a robot that satisfies one or more of the following: its travel path is blocked by a robot in a non-moving state, its moving speed is less than a preset speed, and its distance from the robot in a non-moving state is less than a preset distance.

[0108] In one possible implementation, the determining unit 402 is specifically used to: determine the congested area based on the location information of at least one congested robot when the number of at least one congested robot is greater than a preset number.

[0109] In one possible implementation, the determining unit 402 is specifically used to: determine the road segment where at least one congestion robot is located in the target area based on the location information of each congestion robot, and designate the road segment as the congestion area.

[0110] In one possible implementation, the determining unit 402 is specifically used to: determine the congestion area including the bounding rectangle of the location of at least one congestion robot based on the location information of each congestion robot.

[0111] In one possible implementation, the determining unit 402 is also used to: reset each congestion robot to the target robot.

[0112] In one possible implementation, the acquisition unit 401 is further configured to: acquire the number of congested areas in the target area to obtain a first statistical count of congested areas; update the first statistical count based on statistical conditions to obtain a second statistical count of congested areas; the statistical conditions include treating two congested areas as one congested area when there is an overlapping area between any two congested areas.

[0113] In one possible implementation, the determining unit 402 is further configured to: replan the driving path for the non-congested robot before it enters the congested area from the target area.

[0114] In one possible implementation, the determining unit 402 is further configured to: control the non-congested robot to stop and wait when the replanned driving path overlaps with the congested area, and / or control the non-congested robot to enter an avoidable state; the avoidable state is used to instruct the non-congested robot to drive into the avoidance point closest to its current position.

[0115] It should be noted that, Figure 7 The module division shown is illustrative and represents only one logical functional division; in actual implementation, other division methods are possible. For example, two or more functions can be integrated into a single processing module. These integrated modules can be implemented in hardware or as software functional units.

[0116] In an exemplary embodiment, this application also provides a readable storage medium including software instructions that, when run on an electronic device, cause the electronic device to perform any of the methods provided in the above embodiments.

[0117] In an exemplary embodiment, this application also provides a computer program product containing computer execution instructions, which, when run on an electronic device, causes the electronic device to perform any of the methods provided in the above embodiments.

[0118] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software programs, implementation can be, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer-executable instructions. When these computer-executable instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer-executable instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer-executable instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device containing one or more servers, data centers, etc., that can be integrated with the medium. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or solid-state disks (SSDs), etc.

[0119] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple instances. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0120] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of this application as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from the spirit and scope of this application. Thus, if such modifications and modifications of this application fall within the scope of the claims of this application and their equivalents, this application is also intended to include such modifications and modifications.

[0121] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining congested areas, characterized in that, The method includes: Acquire movement information of each robot in the target area; the movement information includes movement speed, travel path and position information; Based on the movement information of each robot, a congested area in the target area is determined; wherein, the congested area includes N congested robots with a movement speed less than a preset speed, where N is a positive integer; and, the distance between any two adjacent congested robots is less than or equal to a preset distance, and / or, one of any two adjacent congested robots blocks the travel path of the other. The step of determining congested areas in the target area based on the movement information of each robot includes: Identify the target robot; the target robot includes robots in the target area that are in a non-moving state; Detect the second robot whose travel path is blocked by the target robot to obtain a second set of robots; In the second set of robots, the second robot that meets the first condition is identified as the congestion robot; the first condition is that the distance to the target robot is less than or equal to the preset distance, and the moving speed is less than the preset speed. Each of the congestion robots is reset to the target robot, and the above steps are repeated until at least one congestion robot that meets the preset conditions is identified; the preset conditions include a moving speed less than the preset speed, a travel path blocked by the target robot, and a distance between the robot and the target robot less than the preset distance; The congestion area is determined based on the location information of the at least one congestion robot.

2. The method according to claim 1, characterized in that, The target robot also includes a robot that meets one or more of the following conditions: its travel path is blocked by the robot in the non-moving state, its moving speed is less than the preset speed, and its distance from the robot in the non-moving state is less than the preset distance.

3. The method according to claim 1 or 2, characterized in that, Determining the congested area based on the location information of the at least one congestion robot includes: If the number of at least one congestion robot is greater than a preset number, the congestion area is determined based on the location information of the at least one congestion robot.

4. The method according to claim 1 or 2, characterized in that, Determining the congested area based on the location information of the at least one congestion robot includes: Based on the location information of each congestion robot, the road segment where the at least one congestion robot is located in the target area is determined, and the road segment is designated as the congestion area.

5. The method according to claim 1 or 2, characterized in that, Determining the congested area based on the location information of the at least one congestion robot includes: Based on the location information of each congestion robot, the circumscribed graph including the location of the at least one congestion robot is determined as the congestion area.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the number of congested areas in the target area to obtain the first statistical count of congested areas; Based on statistical conditions, the first statistical quantity is updated to obtain a second statistical quantity of congested areas; the statistical conditions include treating any two congested areas as one congested area if there is an overlapping area between them.

7. The method according to claim 1, characterized in that, The method further includes: Before the non-congested robot in the target area enters the congested area, a new driving path is planned for the non-congested robot.

8. The method according to claim 7, characterized in that, The method further includes: If the replanned driving route overlaps with the congested area, the non-congested robot is controlled to stop and wait, and / or, the non-congested robot is controlled to enter an avoidable state; the avoidable state is used to instruct the non-congested robot to drive into the nearest avoidance point to its current location.

9. A device for determining congested areas, characterized in that, The device includes an acquisition unit and a determination unit; The acquisition unit is used to acquire the movement information of each robot in the target area; the movement information includes movement speed, travel path and position information; The determining unit is used to determine a congested area in the target area based on the movement information of each robot; wherein the congested area includes N congested robots with a movement speed less than a preset speed, where N is a positive integer; and the distance between any two adjacent congested robots is less than or equal to a preset distance, and / or, one of any two adjacent congested robots blocks the travel path of the other. The determining unit is specifically used for: Identify the target robot; the target robot includes robots in the target area that are in a non-moving state; Detect the second robot whose travel path is blocked by the target robot to obtain a second set of robots; In the second set of robots, the second robot that meets the first condition is identified as the congestion robot; the first condition is that the distance to the target robot is less than or equal to the preset distance, and the moving speed is less than the preset speed. Each of the congestion robots is reset to the target robot, and the above steps are repeated until at least one congestion robot that meets the preset conditions is identified; the preset conditions include a moving speed less than the preset speed, a travel path blocked by the target robot, and a distance between the robot and the target robot less than the preset distance; The congestion area is determined based on the location information of the at least one congestion robot; The determining unit is also used to reset each of the congestion robots to the target robot.

10. The apparatus according to claim 9, characterized in that, The target robot also includes a robot that satisfies one or more of the following: its travel path is blocked by the robot in the non-moving state, its moving speed is less than the preset speed, and its distance from the robot in the non-moving state is less than the preset distance; And / or, the determining unit is specifically used for: If the number of at least one congestion robot is greater than a preset number, the congestion area is determined based on the location information of the congestion robot; And / or, the determining unit is specifically used for: Based on the location information of each congestion robot, the road segment where the congestion robot is located in the target area is determined, and the road segment is designated as the congestion area; And / or, the determining unit is specifically used for: Based on the location information of each congestion robot, the circumscribed graph including the location of the at least one congestion robot is determined as the congestion area; And / or, the acquisition unit is further configured to: Obtain the number of congested areas in the target area to obtain the first statistical count of congested areas; Based on statistical conditions, the first statistical quantity is updated to obtain the second statistical quantity of congested areas; the statistical conditions include treating the two congested areas as one congested area when there is an overlapping area between any two congested areas. And / or, the determining unit is further configured to: Before the non-congested robot in the target area enters the congested area, the travel path of the non-congested robot is replanned; And / or, the determining unit is further configured to: If the replanned driving route overlaps with the congested area, the non-congested robot is controlled to stop and wait, and / or, the non-congested robot is controlled to enter an avoidable state; the avoidable state is used to instruct the non-congested robot to drive into the nearest avoidance point to its current location.

11. An electronic device, characterized in that, include: Processor and memory; The memory stores instructions that the processor can execute; When the processor is configured to execute the instructions, the electronic device performs the method as described in any one of claims 1-8.

12. A computer-readable storage medium, characterized in that, The readable storage medium includes: software instructions; When the software instructions are executed in an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-8.

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