CN116934188A

CN116934188A - Robot distribution result recognition method, apparatus, electronic device and medium

Info

Publication number: CN116934188A
Application number: CN202310855397.1A
Authority: CN
Inventors: 赵博学; 支涛
Original assignee: Beijing Yunji Technology Co Ltd
Current assignee: Beijing Yunji Technology Co Ltd
Priority date: 2023-07-12
Filing date: 2023-07-12
Publication date: 2023-10-24

Abstract

The disclosure relates to the technical field of robot control, and provides a robot distribution result identification method, a device, electronic equipment and a medium. The method comprises the following steps: receiving a delivery task, determining target goods and goods information of the target goods according to the delivery task, determining a storage warehouse and a target position of the target goods based on the goods information, placing the target goods in the corresponding storage warehouse, and going to the target position; a determination image is acquired at the target position, and a cargo distribution result is determined based on the determination image. The implementation mode can receive a delivery task, and determine the target goods and the goods information of the target goods according to the delivery task; determining a storage warehouse and a target position of the target cargo based on the cargo information; and placing the target goods in the corresponding storage warehouse, moving to the target position, acquiring a judging image at the target position, and determining a goods delivery result based on the judging image, so that the goods receiving judgment can be realized.

Description

Robot distribution result recognition method, apparatus, electronic device and medium

Technical Field

The disclosure relates to the technical field of robots, and in particular relates to a method, a device, electronic equipment and a medium for identifying a robot distribution result.

Background

At present, the Internet of things and intelligent home are the important development directions of a plurality of scientific and technological industries worldwide, and along with the development of artificial intelligence technology and the improvement of the requirements of people on living standard, the demand of robot goods distribution is increasing. As an intelligent product, robots are increasingly accepted by manufacturers, and meanwhile, the market prospect of the equipment is wide, and the requirements of the manufacturers on the distribution robots are higher.

Currently, a robot without a bin cover cannot recognize whether a user receives goods after delivering goods, and thus, a better scheme is needed.

Disclosure of Invention

In view of this, the embodiments of the present disclosure provide a method, an apparatus, an electronic device, and a medium for identifying a delivery result of a robot, so as to solve the problem that in the prior art, after delivering a delivery, a robot without a bin cover cannot identify whether a user receives the delivery.

In a first aspect of an embodiment of the present disclosure, a method for identifying a robot distribution result is provided, including: receiving a delivery task, and determining target goods and goods information of the target goods according to the delivery task; determining a storage warehouse and a target position of the target cargo based on the cargo information; placing the target goods in the corresponding storage warehouse and going to the target position; a determination image is acquired at the target position, and a cargo distribution result is determined based on the determination image.

In a second aspect of the embodiments of the present disclosure, there is provided a robot dispensing result recognition apparatus, including:

an information acquisition unit configured to receive a delivery task, determine a target cargo and cargo information of the target cargo according to the delivery task; a bin determination unit configured to determine a storage bin and a target position of a target cargo based on cargo information; a cargo delivery unit configured to place a target cargo in a corresponding storage bin and to travel to a target location; a determination image is acquired at the target position, and a cargo distribution result is determined based on the determination image.

In a third aspect of the disclosed embodiments, an electronic device is provided, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the above method when executing the computer program.

In a fourth aspect of the disclosed embodiments, a computer-readable storage medium is provided, which stores a computer program which, when executed by a processor, implements the steps of the above-described method.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required for the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings may be obtained according to these drawings without inventive effort for a person of ordinary skill in the art.

FIG. 1 is a schematic illustration of one application scenario of a robotic delivery outcome recognition method according to some embodiments of the present disclosure;

FIG. 2 is a flow chart of some embodiments of a robotic dispensing result recognition method according to the present disclosure;

FIG. 3 is a schematic diagram of the structure of some embodiments of a robotic dispensing result recognition device according to the present disclosure;

fig. 4 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be noted that, for convenience of description, only the portions related to the present application are shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

Fig. 1 is a schematic view of one application scenario of a robot delivery result recognition method according to some embodiments of the present disclosure.

In the application scenario of fig. 1, a computing device 101 may receive a delivery task, determine a target good and good information 102 for the target good based on the delivery task. The computing device 101 may then determine a storage bin and a target location 103 for the target good based on the good information 102. Thereafter, the computing device 101 may place the target good in a corresponding storage bin and travel to the target location 103. Finally, the computing device 101 may acquire the decision image 104 at the target location, determine the cargo delivery result based on the decision image 104, as indicated by reference numeral 105.

The computing device 101 may be hardware or software. When the computing device 101 is hardware, it may be implemented as a distributed cluster of multiple servers or terminal devices, or as a single server or single terminal device. When the computing device 101 is embodied as software (e.g., a program or system controlling a robot), it may be installed in the above-listed hardware devices. It may be implemented as a plurality of software or software modules, for example, for providing distributed services, or as a single software or software module. The present application is not particularly limited herein.

It should be understood that the number of computing devices in fig. 1 is merely illustrative. There may be any number of computing devices, as desired for an implementation.

Fig. 2 is a flow chart of some embodiments of a robotic dispensing result recognition method according to the present disclosure. The robotic dispensing result recognition method of fig. 2 may be performed by the computing device 101 of fig. 1. As shown in fig. 2, the robot distribution result recognition method includes:

step S201, receiving a delivery task, and determining the target goods and the goods information of the target goods according to the delivery task.

In some embodiments, determining the target cargo and cargo information for the target cargo according to the delivery mission comprises: determining target goods according to the delivery tasks, acquiring goods orders of the target goods, determining the quantity, the size and the type of the goods according to the goods orders, and generating goods information of the target goods according to the quantity, the size and the type of the goods.

In some embodiments, the executing body of the robotic delivery result recognition method (e.g., computing device 102 shown in fig. 1) may issue instructions of the server in response to the task for a set period of time. As an example, a delivery task may be understood as a task that a robot needs to deliver, for example, after a user places an order for goods, the robot receives an order for goods, the number of goods placed can be determined, and size information of the goods and the type of the goods can be determined through the goods identifier in the order for goods. The cargo information may also include other information, such as the need for refrigeration, etc., which is not particularly limited in this embodiment.

As an example, the robot receives a delivery task in a working period, and may acquire a corresponding cargo order, determine that the number of the ordered cargo is 3 according to the cargo order, and determine that the size information of the cargo is 20 cm in length, width and height according to the cargo identifier in the cargo order, and the type of the cargo is drinking water.

Step S202, determining a storage warehouse and a target position of the target cargo based on the cargo information.

In some embodiments, determining a storage bin and a target location for a target good based on the good information includes: and determining at least one target warehouse from the plurality of storage warehouses according to the type of the goods, determining a storage warehouse corresponding to the target goods according to the quantity of the goods, the size of the goods and the storage warehouse of the at least one target warehouse, and acquiring a target position from the goods order. The storage bin is a bin for storing and delivering cargoes, which is configured on the robot, and the number of the bins can be multiple. The target location is the destination of the dispatch, i.e., the shipping address.

Specifically, according to the number of cargoes, the size of cargoes and the storage bin of at least one target bin, the storage bin corresponding to the target cargo is determined, including: and carrying out size matching according to the size of the goods and the size information of the storage bin of at least one target bin, determining a first matching result, carrying out matching according to the number of the storage bins of at least one target bin and the number of the goods under the condition that the first matching result meets the size of the goods, determining a second matching result, and determining the storage bin corresponding to the target goods under the condition that the number of the goods is met. For example, the robot receives a delivery task in a working period, can acquire a corresponding goods order, can determine that the quantity of the ordered goods is 3 according to the goods order, can also determine that the size information of the goods is 20 cm long, wide and high according to the goods identification in the goods order, and the type of the goods is drinking water. Then the warehouse capable of storing food can be determined firstly, then whether the size of the warehouse capable of storing food can be used for containing the drinking water with the length, the width and the height of 20 cm or not is determined, and if the size of the warehouse capable of storing food can be used for containing the drinking water with the length, the width and the height of 20 cm, then whether the storage spaces of the warehouse are enough 3 or not is determined. And taking the warehouse as a storage warehouse corresponding to the target goods when the storage warehouse is enough.

Further, if the storage space of the warehouse is not enough 3, 3 cargoes may be respectively allocated to different warehouses. Or to other robots.

In step S203, the target cargo is placed in the corresponding storage warehouse and is moved to the target location.

In some embodiments, placing the target cargo in a corresponding storage bin and to the target location includes: the method comprises the steps of obtaining target goods through a taking device configured by a robot, controlling the taking device to place the target goods in a corresponding storage warehouse, carrying out route planning according to the current position and the target position of the robot, determining a target route, and going to the target position according to the target route. For example, after the storage warehouse is determined, the drinking water with the length, the width and the height of 20 cm can be placed in the corresponding warehouse by using a taking device on the robot, and route planning is performed by using the navigation module, so that a delivery route is determined, and delivery is performed according to the delivery route.

It should be noted that, the method of path planning may use a conventional technical means in the art, which is not described herein, and in addition, the route may be issued by the cloud device, so as to reduce the workload of the robot.

In practical applications, there may be multiple target positions in a task, and then a more efficient manner needs to be selected for delivery.

In some embodiments, when the target location is more than one, determining an order of the goods corresponding to the target location, determining order time according to the order of the goods, planning a route based on the order time and a positional relationship between the target locations, determining a target route, and sequentially going to more than one target location according to the target route. As an example, the number of ordered goods can be determined to be 2 according to the order of the goods, namely drinking water and snacks respectively, after the storage warehouse is determined, the drinking water and snacks can be placed in corresponding warehouse positions by using a taking device on a robot, the drinking water needs to be distributed to a position a, the snacks need to be distributed to a position B, then the route planning of the distribution route is performed by the time of placing the order preferentially, so that the distribution route is determined, and the distribution is performed according to the distribution route.

Step S204, acquiring a judging image at the target position, and determining the goods delivery result based on the judging image.

In some embodiments, acquiring a decision image at a target location, determining a cargo delivery result based on the decision image, includes: acquiring a judging image at a target position, determining a target doorplate based on the judging image, and carrying out image recognition based on the target doorplate; after the door corresponding to the target doorplate is identified to be opened, determining the action of the target person; and under the condition that the action of the target person is taking goods, determining the goods delivery result as delivery completion.

For example, after the door reaches the gate of the delivery site, the state of the door is acquired through the camera device, after the door is identified to be opened and the goods are taken away by someone, the goods delivery result is determined to be the delivery completion, and if the door is identified to be not opened or the goods are not taken after the door is opened, the goods delivery result is determined to be the non-delivery completion.

If the target positions are plural, the two target positions are close to each other, and when the goods at one of the target positions are delivered, the goods at the close positions can be preferentially delivered, so that the efficiency is improved, and the delivery time is not affected.

In some embodiments, the storage warehouse is unloaded to a preset position by a robot configured pick device upon completion of the target cargo delivery. For example, after the delivery is completed, and no other tasks, the warehouse may be unloaded to a standby point. The robot returns to the charging stake.

In addition, there may be cases where delivery fails, such as delivery messages being not acknowledged, resulting in delivery being unsuccessful. After the distribution failure of the set times, the alarm information can be sent to the management platform, and the management platform issues an instruction.

Any combination of the above optional solutions may be adopted to form an optional embodiment of the present application, which is not described herein.

The following are device embodiments of the present disclosure that may be used to perform method embodiments of the present disclosure. For details not disclosed in the embodiments of the apparatus of the present disclosure, please refer to the embodiments of the method of the present disclosure.

Fig. 3 is a schematic structural view of some embodiments of a robotic dispensing result recognition device according to the present disclosure. As shown in fig. 3, the robot dispensing result recognition apparatus includes: an information acquisition unit 301, a bin determination unit 302, a cargo delivery unit 303, and a result determination unit 304. Wherein the information acquisition unit 301 is configured to receive a delivery task, determine a target cargo and cargo information of the target cargo according to the delivery task, the bin determination unit 302 is configured to determine a storage bin and a target position of the target cargo based on the cargo information, the cargo delivery unit 303 is configured to place the target cargo in the corresponding storage bin and go to the target position result determination unit 304, and is configured to acquire a determination image at the target position, and determine a cargo delivery result based on the determination image.

In some optional implementations of some embodiments, the information acquisition unit 301 is further configured to: determining target goods according to the delivery tasks, acquiring goods orders of the target goods, determining the quantity, the size and the type of the goods according to the goods orders, and generating goods information of the target goods according to the quantity, the size and the type of the goods.

In some optional implementations of some embodiments, bin determination unit 302 is further configured to: and determining at least one target warehouse from the plurality of storage warehouses according to the type of the goods, determining a storage warehouse corresponding to the target goods according to the quantity of the goods, the size of the goods and the storage warehouse of the at least one target warehouse, and acquiring a target position from the goods order.

In some optional implementations of some embodiments, bin determination unit 302 is further configured to: and carrying out size matching according to the size of the goods and the size information of the storage bin of at least one target bin, determining a first matching result, carrying out matching according to the number of the storage bins of at least one target bin and the number of the goods under the condition that the first matching result meets the size of the goods, determining a second matching result, and determining the storage bin corresponding to the target goods under the condition that the number of the goods is met.

In some alternative implementations of some embodiments, the cargo delivery unit 303 is further configured to: the method comprises the steps of obtaining target goods through a taking device configured by a robot, controlling the taking device to place the target goods in a corresponding storage warehouse, carrying out route planning according to the current position and the target position of the robot, determining a target route, and going to the target position according to the target route.

In some alternative implementations of some embodiments, the cargo delivery unit 303 is further configured to: and under the condition that the target positions are more than one, determining the goods orders corresponding to the target positions, determining order time according to the goods orders, carrying out route planning based on the order time and the position relation between the target positions, determining a target route, and sequentially going to more than one target positions according to the target route.

In some optional implementations of some embodiments, the result determination unit 304 is further configured to: acquiring a judging image at a target position, determining a target doorplate based on the judging image, and carrying out image recognition based on the target doorplate; after the door corresponding to the target doorplate is identified to be opened, determining the action of the target person; and under the condition that the action of the target person is taking goods, determining the goods delivery result as delivery completion.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not constitute any limitation on the implementation process of the embodiments of the disclosure.

Referring now to FIG. 4, a schematic diagram of an electronic device 400 (e.g., computing device 101 of FIG. 1) suitable for use in implementing some embodiments of the present disclosure is shown. The server illustrated in fig. 4 is merely an example, and should not be construed as limiting the functionality and scope of use of the embodiments of the present disclosure in any way.

As shown in fig. 4, the electronic device 400 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 401, which may perform various suitable actions and processes according to a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage means 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the electronic device 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.

In general, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, magnetic tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the electronic device 400 to communicate with other devices wirelessly or by wire to exchange data. While fig. 4 shows an electronic device 400 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 4 may represent one device or a plurality of devices as needed.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via communications device 409, or from storage 408, or from ROM 402. The above-described functions defined in the methods of some embodiments of the present disclosure are performed when the computer program is executed by the processing device 401.

It should be noted that, in some embodiments of the present disclosure, the computer readable medium may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, the computer-readable signal medium may comprise a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be embodied in the apparatus; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: receiving a delivery task, and determining target goods and goods information of the target goods according to the delivery task; determining a storage warehouse and a target position of the target cargo based on the cargo information; and placing the target goods in the corresponding storage warehouse, moving to the target position, acquiring a judging image at the target position, and determining the goods delivery result based on the judging image.

Computer program code for carrying out operations for some embodiments of the present disclosure may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. The described units may also be provided in a processor, for example, described as: a processor includes an information acquisition unit, a bin determination unit, and a cargo delivery unit. The names of these units do not limit the unit itself in some cases, and for example, the information acquisition unit may also be described as "a unit that receives a delivery task, determines a target cargo according to the delivery task, and determines cargo information of the target cargo.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the application in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the application. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A robot delivery result recognition method, comprising:

receiving a delivery task, and determining target goods and goods information of the target goods according to the delivery task;

determining a storage warehouse and a target position of the target cargo based on the cargo information;

placing the target goods in corresponding storage bins and going to the target positions;

and acquiring a judging image at the target position, and determining a goods delivery result based on the judging image.

2. The robot dispensing result recognition method according to claim 1, wherein the determining the target goods and the goods information of the target goods according to the dispensing task includes:

determining target goods according to the delivery task, and acquiring a goods order of the target goods;

determining the cargo quantity, the cargo size and the cargo type of the cargo according to the cargo order;

and generating cargo information of the target cargo according to the cargo quantity, the cargo size and the cargo type.

3. The robot dispensing result recognition method of claim 2, wherein the determining the storage bin and the target location of the target cargo based on the cargo information comprises:

determining at least one target cargo hold from a plurality of said storage cargo holds according to said cargo type;

and determining a storage warehouse corresponding to the target cargo according to the cargo quantity, the cargo size and the storage warehouse of the at least one target warehouse, and acquiring a target position from the cargo order.

4. The method for recognizing a robot dispensing result according to claim 3, wherein the determining a storage bin corresponding to the target cargo according to the number of cargoes, the size of the cargoes, and the storage bin of the at least one target cargo comprises:

performing size matching according to the size information of the goods and the storage bin of the at least one target bin, and determining a first matching result;

under the condition that the first matching result meets the size of the goods, matching is carried out according to the number of storage bins of the at least one target bin and the number of goods, and a second matching result is determined;

and under the condition that the cargo quantity is met, determining a storage warehouse corresponding to the target cargo.

5. The method of claim 1, wherein said placing the target cargo in a corresponding storage bin and toward the target location comprises:

acquiring the target goods through a robot-configured taking device, and controlling the taking device to place the target goods in a corresponding storage warehouse;

carrying out route planning according to the current position of the robot and the target position, and determining a target route;

and going to the target position according to the target route.

6. The method as recited in claim 1, further comprising:

determining a goods order corresponding to the target position when the target position is more than one;

determining order time according to the goods order, and performing route planning based on the order time and the position relation between the target positions to determine a target route;

and sequentially going to more than one target positions according to the target route.

7. The method of claim 1, wherein the acquiring a decision image at the target location, determining a cargo delivery result based on the decision image, comprises:

acquiring a judging image at the target position, determining a target doorplate based on the judging image, and carrying out image recognition based on the target doorplate;

after the door corresponding to the target doorplate is identified to be opened, determining the action of the target person;

and under the condition that the action of the target person is taking goods, determining the goods delivery result as delivery completion.

8. A robot dispensing result recognition apparatus, comprising:

an information acquisition unit configured to receive a delivery task, determine a target cargo and cargo information of the target cargo according to the delivery task;

a bin determination unit configured to determine a storage bin and a target position of the target cargo based on the cargo information;

a cargo delivery unit configured to place the target cargo in a corresponding storage bin and to travel to the target location;

and a result determination unit configured to acquire a determination image at the target position, and determine a cargo distribution result based on the determination image.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 7.