WO2020134106A1 - 售货装置、物品的识别方法、装置和计算机可读存储介质 - Google Patents

售货装置、物品的识别方法、装置和计算机可读存储介质 Download PDF

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Publication number
WO2020134106A1
WO2020134106A1 PCT/CN2019/100181 CN2019100181W WO2020134106A1 WO 2020134106 A1 WO2020134106 A1 WO 2020134106A1 CN 2019100181 W CN2019100181 W CN 2019100181W WO 2020134106 A1 WO2020134106 A1 WO 2020134106A1
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WIPO (PCT)
Prior art keywords
resistor
weight
shelf layer
vending device
processor
Prior art date
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PCT/CN2019/100181
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English (en)
French (fr)
Inventor
刘自银
张夏杰
郭景昊
陈宇
刘巍
乌日尼
安山
姜博
吴江旭
刘朋樟
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Beijing Wodong Tianjun Information Technology Co Ltd
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Beijing Wodong Tianjun Information Technology Co Ltd
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Publication of WO2020134106A1 publication Critical patent/WO2020134106A1/zh
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Ceased legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/40—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight
    • G01G19/413—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means
    • G01G19/414—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups with provisions for indicating, recording, or computing price or other quantities dependent on the weight using electromechanical or electronic computing means using electronic computing means only
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/52—Weighing apparatus combined with other objects, e.g. furniture
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G3/00—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances
    • G01G3/12—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances wherein the weighing element is in the form of a solid body stressed by pressure or tension during weighing
    • G01G3/14—Weighing apparatus characterised by the use of elastically-deformable members, e.g. spring balances wherein the weighing element is in the form of a solid body stressed by pressure or tension during weighing measuring variations of electrical resistance
    • G01G3/142—Circuits specially adapted therefor
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07F—COIN-FREED OR LIKE APPARATUS
    • G07F11/00—Coin-freed apparatus for dispensing, or the like, discrete articles

Definitions

  • the present disclosure relates to the field of artificial intelligence technology, and in particular, to a vending device, an item identification method, an item identification device, and a computer-readable storage medium.
  • RFID Radio Frequency Identification
  • gravity recognition technology that installs a weight sensor on the shelf layer
  • image recognition technology based on product pictures.
  • a vending device including: one or more shelf layers provided in the vending device for placing merchandise; a weight sensor, a shelf layer is installed with a plurality of weight sensors Used to jointly measure the weight carried by the shelf layer and output a measurement signal, the multiple weight sensors are mounted on the same serial bus; the processor is electrically connected to the multiple weight sensors through the serial bus, It is used to determine the weight carried by the corresponding shelf layer according to the measurement signal, so as to identify the items taken out from the corresponding shelf layer according to the change of the carried weight.
  • the plurality of weight sensors are installed at intervals away from the center of the corresponding shelf layer along the circumferential direction of the corresponding shelf layer.
  • the plurality of weight sensors are a first weight sensor and a second weight sensor, which are respectively installed at both ends of the corresponding shelf layer.
  • the plurality of weight sensors are connected in parallel, and the measurement signal is a parallel voltage.
  • the first weight sensor includes a resistor R 1 , and the resistance of the resistor R 1 changes with external force;
  • the second weight sensor includes a resistor R′ 1 , and the resistance of the resistor R′ 1 Changes with external force; the first weight sensor and the second weight sensor are connected in parallel as a weighing unit.
  • the first end of the resistor R 1 is connected to a first terminal of a resistor R 2
  • the second terminal of resistor R 1 is connected to a first end of the resistor R 3 of the resistor R 2
  • the first end of the resistor R 4 is connected to the second terminal of resistor R 3 is connected to a second end of the resistor R 4
  • the second terminal of resistor R 1 is connected to a first power supply terminal
  • the second end of the resistor R 2 is connected to the second end of the power supply.
  • the resistance R 'of the first terminal 1 and the resistor R' 2 is connected to a first end of said resistor R '1 and a second end of the resistor R' 3 is connected to a first end of the resistance R 'and the second end of the resistor R 2' 4 is connected to a first end of said resistor R '3 with the second end of the resistor R' 4 is connected to a second end, said first resistor R '. 1 of The two ends are connected to the first end of the power supply, and the second end of the resistor R′ 2 is connected to the second end of the power supply.
  • the second end of resistor R 3 'end of the second connector 3 the end of the first resistor R 1 and the resistance R' of the first end of the resistor R 1 is connected
  • the first end of the resistor R′ 1 is connected to the first output end of the weighing unit
  • the second end of the resistor R′ 3 is connected to the second output end of the weighing unit.
  • the vending device further includes a signal amplifier, the plurality of weight sensors are connected in parallel to the signal amplifier, and the signal amplifier is connected to the processor through a serial bus.
  • the vending device further includes: a camera device electrically connected to the processor, for acquiring an image of the item.
  • the processor recognizes the article based on at least one of the change in the weight carried and the image processing result of the article.
  • the camera device includes an image processing unit for processing the image of the article to obtain the processing result.
  • a computing acceleration device electrically connected to the processor is used to process the image of the item and obtain the processing result.
  • an article identification method including:
  • Receiving measurement signals output by a plurality of weight sensors the plurality of weight sensors being installed on a shelf layer of a vending device for jointly measuring the weight borne by the shelf layer and outputting the measurement signal, the measurement signal according to the shelf layer
  • the output of the weight carried; the weight carried by the shelf layer is determined according to the measurement signal; the items taken out of the shelf layer are identified according to the change in the weight carried.
  • the plurality of weight sensors are connected in parallel; the measurement signal is a parallel voltage.
  • the identification method further includes: acquiring a processing result of the image of the item; identifying the item according to at least one of the change in the weight undertaken and the processing result.
  • the image of the item and the processing result are acquired by a camera device installed in the vending device.
  • an item identification device including: a memory; and a processor coupled to the memory, the processor configured to be based on instructions stored in the memory device, Perform the item identification method in any of the above embodiments.
  • a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the method for recognizing an article in any of the above embodiments is implemented.
  • FIG. 1 shows a block diagram of some embodiments of the vending device of the present disclosure
  • FIG. 2 shows a schematic diagram of some embodiments of the weight sensor installation of the present disclosure
  • FIG. 3 shows a schematic diagram of some embodiments of the weighing unit of the present disclosure
  • FIG. 4 shows a block diagram of some other embodiments of the vending device of the present disclosure
  • FIG. 5 shows a block diagram of still other embodiments of the vending device of the present disclosure
  • FIG. 6 shows a flowchart of some embodiments of the method for identifying an article of the present disclosure
  • FIG. 8 shows a block diagram of some embodiments of the article identification device of the present disclosure
  • FIG. 9 shows a block diagram of other embodiments of the article identification device of the present disclosure.
  • the present disclosure proposes a technical solution of a vending device that can be flexibly configured.
  • FIG. 1 shows a block diagram of some embodiments of the vending device of the present disclosure.
  • the vending device 1 includes a shelf layer 10, a plurality of weight sensors 11 and a processor 12.
  • the vending device 1 may be a vending cabinet, a shelf, or the like.
  • the plurality of weight sensors 11 are installed on the shelf layer 10, for example, may be installed on the bottom of the shelf layer 10, or may be enclosed in the shelf layer 10.
  • each shelf layer 10 may be installed with a weight sensor 11 to measure the weight of the shelf layer and output a measurement signal, or each shelf layer 10 may be installed with a plurality of weight sensors 11 to jointly measure the weight of the shelf layer and output One measurement signal.
  • each weight sensor 11 can be mounted as an independent device on the same serial bus and connected to the processor 12, the serial bus can use the 485 bus, CAN (Controller Area Network) bus Wait, each weighing unit uses the same communication protocol. In this way, as long as the device is mounted on the bus, the device can be added, and the number of weight sensors can be expanded.
  • the serial bus can use the 485 bus, CAN (Controller Area Network) bus Wait, each weighing unit uses the same communication protocol. In this way, as long as the device is mounted on the bus, the device can be added, and the number of weight sensors can be expanded.
  • multiple weight sensors 11 are connected in parallel to output a parallel voltage according to the weight carried by the shelf layer.
  • the processor 12 is connected to a plurality of weight sensors 11 for determining the weight carried by the shelf layer according to the parallel voltage, so as to identify the items taken out of the shelf layer according to the change in the carried weight.
  • the identification of the item may be performed on the vending device installed with the identification system 1, or after the identification in the cloud, the identification result is transmitted back to the vending device.
  • a plurality of weight sensors are spaced along the circumferential direction of the shelf layer.
  • a weight sensor can be installed according to FIG. 2.
  • FIG. 2 shows a schematic diagram of some embodiments of the weight sensor installation of the present disclosure.
  • the weight sensor 21 and the weight sensor 22 of the vending device are respectively installed at both ends of the shelf layer 20.
  • the jitter generated when the article is placed or removed from the shelf layer 20 is reduced, the stability time of the shelf layer 20 is reduced, and the influence of the torque caused by the jitter and instability on the measurement result is reduced , Which can improve accuracy.
  • the weight sensor 21 and the weight sensor 22 may be connected in parallel, and the parallel voltage is used as an output signal. In this way, the common output of the two weight sensors can be collected at the same time, avoiding the measurement time difference caused by the independent measurement of multiple weight sensors and the instability of the shelf layer, so that the accuracy can be improved.
  • a weight sensor may be installed at each of the four corners of the shelf layer; for a round or oval shelf layer, a weight sensor may be installed at intervals around the circumference of the shelf layer.
  • the first weight sensor includes a resistance R 1 , and the resistance value of R 1 changes with an external force.
  • a second weight sensor comprises a resistor R '1, R' 1 is changed with the resistance force.
  • the first weight sensor and the second weight sensor are connected in parallel as a weighing unit.
  • R 1 and R′ 1 are composed of an elastomer and a resistance strain gauge attached to the surface of the elastomer.
  • the elastic body is elastically deformed under the action of external force, so that the resistance strain gauge (ie, the conversion element) is also deformed accordingly. After the resistance strain gauge is deformed, the resistance value will change, and then this resistance change will be converted into an electrical signal (voltage or current) through the corresponding measurement circuit.
  • the weighing unit can be set by the embodiment in FIG. 3.
  • FIG. 3 shows a schematic diagram of some embodiments of the weighing unit of the present disclosure.
  • the weighing unit 3 includes a first weight sensor, a second weight sensor, a first output 31, a second output 32 and a power supply 33.
  • the first weight sensor is composed of R 1 , R 2 , R 3 and R 4 .
  • R 1 is a first end connected to the first end of R 2
  • R 1 is connected to a second end of the first end of R 3
  • R 2 is a second end connected to the first end of R 4
  • R 3 is the second The end is connected to the second end of R 4 .
  • the second end of R 1 is connected to the first end of the power supply 33, and the second end of R 2 is connected to the second end of the power supply.
  • the second weight sensor is composed of R′ 1 , R′ 2 , R′ 3 and R′ 4 .
  • R '1 and the first end of the R' 2 is connected to a first end
  • R '1 and the second end of the R' 3 is connected to a first end
  • R '2 and the second end of the R' 4 is connected to a first end of
  • R '3 and the second end of the R' 4 is connected to the second end.
  • the second end of R′ 1 is connected to the first end of the power supply 33
  • the second end of R′ 2 is connected to the second end of the power supply 33
  • a first weight sensor, a second weight sensor 33 is connected in parallel across the power supply, a first end of the 1 R '1 is connected to a first end, a second end of the R 3 and R' and R 3 are connected to the second end.
  • the output voltage between the output terminal 31 and the output terminal 32 of the weighing unit 3 is proportional to the external force received by the first weight sensor and the second weight sensor.
  • the first end of R′ 1 is connected to the output 31 of the weighing unit 3, and the second end of R′ 3 is connected to the output 32 of the weighing unit 3.
  • the weight carried by the shelf layer can be obtained by the output voltage between the output terminal 31 and the output terminal 32 of the weighing unit 3.
  • the common output of the two weight sensors can be collected at the same time, avoiding the measurement time difference caused by the independent measurement of multiple weight sensors and the instability of the shelf layer, so that the accuracy can be improved.
  • multiple weight sensors can be driven by one signal amplifier.
  • the vending device can be configured by the embodiment in FIG. 4.
  • FIG. 4 shows a block diagram of other embodiments of the vending device of the present disclosure.
  • the vending device 4 includes a shelf layer 10, a plurality of weight sensors 11, a processor 12 and a signal amplifier 43.
  • a signal amplifier may be connected to each weight sensor, and each signal amplifier is connected to the processor through the same serial bus.
  • multiple weight sensors 11 may be connected in parallel to the signal amplifier 43, and the signal amplifier 43 is connected to the processor 12 via a serial bus.
  • the solution in which the sales device 4 uses one signal amplifier to drive multiple weight sensors reduces costs.
  • the vending device 4 can make multiple weight sensors 11 measure the weight of the shelf layer at the same time, the processor 12 can query the signal amplifier 43 once to obtain the common measurement value of the multiple weight sensors 11 at the same time, Collaborative measurement to reduce system overhead and improve accuracy.
  • FIG. 5 shows a block diagram of still other embodiments of the vending device of the present disclosure.
  • the vending device 5 includes a shelf layer 10, a plurality of weight sensors 11, a processor 12 and an imaging device 54.
  • the imaging device 54 is connected to the processor and used to acquire the image of the article.
  • multiple camera devices 54 there may be multiple camera devices 54, which are connected to the processor 12 through a USB (Universal Serial Bus) or a network port.
  • USB Universal Serial Bus
  • multiple camera devices 54 can be connected to the processor 12 through multiple USB interfaces or USB HUB hubs.
  • multiple camera devices 54 can also be connected to the processor 12 through a switch.
  • the processor 12 recognizes the item based on at least one of the change in the weight that is borne and the processing result of the image of the item. For example, the recognition results of the weight sensor 11 and the camera 54 can be mutually verified, thereby improving the recognition rate.
  • the vending device 5 may further include a computing acceleration device 55 for processing the image of the item to obtain the processing result.
  • the processor 12 as a main control unit of the vending device 5 has control and calculation capabilities.
  • the processor 12 can collectively collect the measurement data of the plurality of weight sensors 11 and the camera device 54 and communicate with the cloud background.
  • the processor 12 is also responsible for driving the display device.
  • the computing acceleration device 55 may be a USB acceleration device or a PCIE (Peripheral Component Interconnect Express) acceleration device, such as a Movidius neural computing stick and an Intel HDDL computing card.
  • PCIE Peripheral Component Interconnect Express
  • the camera 54 may include an image processing unit 541, such as an AI (Artificial Intelligence) chip, for processing the image of the product, and obtaining the processing result.
  • AI Artificial Intelligence
  • the image processing unit 541 in the camera 54 can calculate the acquired item image through CNN (Convolutional Neural Networks) and other technologies, and perform further processing such as data analysis on the calculation result to obtain the item image. process result.
  • CNN Convolutional Neural Networks
  • the camera device 54 including the image processing unit 541 does not need to transmit a large amount of image and video stream data to the processor 12, but only needs to transmit the image processing result to the processor 12.
  • the requirements on the number of interfaces and bandwidth of the processor 12 are reduced, so that the vending device 5 is equipped with a large number of imaging devices 54 to improve the recognition rate.
  • multiple weight sensors are mounted on the same serial bus and connected to the processor, so that the number of sensors mounted on the system can be expanded according to actual needs, and the flexibility of the system is improved.
  • FIG. 6 shows a flowchart of some embodiments of the article recognition method of the present disclosure.
  • the method includes: step 610, receiving a measurement signal; step 620, determining the weight to bear; and step 630, identifying the removed item.
  • step 610 a measurement signal output by a plurality of weight sensors mounted on the same serial bus is received.
  • the plurality of weight sensors are installed on the shelf layer of the vending device, and the measurement signal is output according to the weight borne by the shelf layer.
  • the weight carried by the shelf layer is determined according to the measurement signal.
  • the measurement signal is a parallel voltage.
  • step 630 the items taken out of the shelf layer are identified based on the change in the weight carried.
  • the method may also be implemented through the embodiment in FIG. 7.
  • FIG. 7 shows a flowchart of other embodiments of the method for identifying an article of the present disclosure.
  • the method further includes: Step 710, acquiring the processing result of the image.
  • step 710 the processing result of the image of the article is acquired.
  • the image of the article and the processing result are acquired by the camera device installed in the vending device.
  • step 710 There is no execution order of step 710 and steps 610 and 620 in FIG. 6.
  • step 620 the article is identified based on at least one of the change in the weight carried and the processing result.
  • multiple weight sensors are mounted on the same serial bus and connected to the processor, so that the number of sensors mounted on the system can be expanded according to actual needs, and the flexibility of the system is improved.
  • FIG. 8 shows a block diagram of some embodiments of the article identification device of the present disclosure.
  • the article identification device 8 of this embodiment includes: a memory 81 and a processor 82 coupled to the memory 81.
  • the processor 82 is configured to execute the present disclosure based on instructions stored in the memory 81
  • the item identification method in any embodiment.
  • the memory 81 may include, for example, a system memory, a fixed non-volatile storage medium, and so on.
  • the system memory stores, for example, an operating system, application programs, a boot loader (Boot Loader), a database, and other programs.
  • FIG. 9 shows a block diagram of other embodiments of the article identification device of the present disclosure.
  • the article identification device 9 of this embodiment includes: a memory 910 and a processor 920 coupled to the memory 910.
  • the processor 920 is configured to execute any one of the foregoing based on instructions stored in the memory 910 The identification method of the article in the embodiment.
  • the memory 910 may include, for example, a system memory, a fixed non-volatile storage medium, and the like.
  • the system memory stores, for example, an operating system, application programs, a boot loader (Boot Loader), and other programs.
  • the item identification device 9 may further include an input-output interface 930, a network interface 940, a storage interface 950, and the like.
  • the interfaces 930, 940, 950 and the memory 910 and the processor 920 may be connected via a bus 960, for example.
  • the input and output interface 930 provides a connection interface for input and output devices such as a display, a mouse, a keyboard, and a touch screen.
  • the network interface 940 provides a connection interface for various networked devices.
  • the storage interface 950 provides a connection interface for external storage devices such as SD cards and U disks.
  • the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer usable non-transitory storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code .
  • a computer usable non-transitory storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • the method and system of the present disclosure may be implemented in many ways.
  • the method and system of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware.
  • the above sequence of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the sequence specifically described above unless specifically stated otherwise.
  • the present disclosure may also be implemented as programs recorded in a recording medium, which include machine-readable instructions for implementing the method according to the present disclosure.
  • the present disclosure also covers the recording medium storing the program for executing the method according to the present disclosure.

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Abstract

一种售货装置（1）、物品的识别方法、装置和计算机可读存储介质，涉及人工智能技术领域。售货装置（1）包括：设置在售货装置（1）内用于放置商品的一个或多个货架层（10，20）；重量传感器（11，21，22），一个货架层（10，20）安装有多个重量传感器（11，21，22）用于共同测量货架层（10，20）承担的重量并输出测量信号，多个重量传感器（11，21，22）挂载到同一条串行总线上；处理器（12），通过串行总线与多个重量传感器（11，21，22）电连接，用于根据测量信号确定相应的货架层（10，20）承担的重量，以便根据承担的重量的变化识别从相应的货架层（10，20）取出的物品。技术方案能够提高系统的灵活性。

Description

售货装置、物品的识别方法、装置和计算机可读存储介质
相关申请的交叉引用
本申请是以CN申请号为201811628621.9，申请日为2018年12月29日的申请为基础，并主张其优先权，该CN申请的公开内容在此作为整体引入本申请中。
技术领域
本公开涉及人工智能技术领域，特别涉及一种售货装置、物品的识别方法、物品的识别装置和计算机可读存储介质。
背景技术
随着零售业的发展，无人货架与无人货柜等智能零售终端成为下一个产品热点。
在相关技术中，在每件商品上添加电子标签的RFID(Radio Frequency Identification，射频识别)技术；在货架层安装重量传感器的重力识别技术；基于商品图片的图像识别技术。
发明内容
根据本公开的一些实施例，提供了一种售货装置，包括：设置在所述售货装置内用于放置商品的一个或多个货架层；重量传感器，一个货架层安装有多个重量传感器用于共同测量该货架层承担的重量并输出测量信号，所述多个重量传感器挂载到同一条串行总线上；处理器，通过所述串行总线与所述多个重量传感器电连接，用于根据所述测量信号确定所述相应的货架层承担的重量，以便根据所述承担的重量的变化识别从所述相应的货架层取出的物品。
在一些实施例中，所述多个重量传感器在远离所述相应的货架层中心的位置，沿所述相应的货架层的周向间隔安装。
在一些实施例中，所述多个重量传感器为第一重量传感器和第二重量传感器，分别安装在所述相应的货架层的两端。
在一些实施例中，所述多个重量传感器并联连接，所述测量信号为并联电压。
在一些实施例中，所述第一重量传感器包括电阻R 1，所述电阻R 1的阻值随外力改变；所述第二重量传感器包括电阻R′ 1，所述电阻R′ 1的阻值随外力改变；所述第一重 量传感器和所述第二重量传感器并联为一个称重单元。
在一些实施例中，所述电阻R 1的第一端与电阻R 2的第一端连接，所述电阻R 1的第二端与电阻R 3的第一端连接，所述电阻R 2的第二端与电阻R 4的第一端连接，所述电阻R 3的第二端与所述电阻R 4的第二端连接，所述电阻R 1的第二端与电源的第一端连接，所述电阻R 2的第二端与所述电源的第二端连接。
在一些实施例中，所述电阻R′ 1的第一端与电阻R′ 2的第一端连接，所述电阻R′ 1的第二端与电阻R′ 3的第一端连接，所述电阻R′ 2的第二端与电阻R′ 4的第一端连接，所述电阻R′ 3的第二端与所述电阻R′ 4的第二端连接，所述电阻R′ 1的第二端与所述电源的第一端连接，所述电阻R′ 2的第二端与所述电源的第二端连接。
在一些实施例中，所述电阻R 3的第二端与所述电阻R′ 3的第二端连接，所述电阻R 1的第一端与所述电阻R′ 1的第一端连接，所述电阻R′ 1的第一端与所述称重单元的第一输出端连接，所述电阻R′ 3的第二端与所述称重单元的第二输出端连接。
在一些实施例中，所述的售货装置，还包括：信号放大器，所述多个重量传感器并联后与所述信号放大器电连接，所述信号放大器通过串行总线与所述处理器连接。
在一些实施例中，所述的售货装置，还包括：与所述处理器电连接的摄像装置，用于获取所述物品的图像。所述处理器根据所述承担的重量的变化和所述物品的图像的处理结果中的至少一个，识别所述物品。
在一些实施例中，所述摄像装置包括图像处理单元，用于对所述物品的图像进行处理，获取所述处理结果。
在一些实施例中，与所述处理器电连接的计算加速设备，用于对所述物品的图像进行处理，获取所述处理结果。
根据本公开的另一些实施例，提供一种物品的识别方法，包括：
接收多个重量传感器输出的测量信号，所述多个重量传感器安装在售货装置的货架层用于共同测量该货架层承担的重量并输出所述测量信号，所述测量信号根据所述货架层承担的重量输出；根据所述测量信号，确定所述货架层承担的重量；根据所述承担的重量的变化识别从所述货架层取出的物品。
在一些实施例中，所述多个重量传感器并联连接；所述测量信号为并联电压。
在一些实施例中，所述的识别方法，还包括：获取所述物品的图像的处理结果；根据所述承担的重量的变化和所述处理结果中的至少一个，识别所述物品。
在一些实施例中，所述物品的图像和所述处理结果由安装在所述售货装置的摄像 装置获取。
根据本公开的又一些实施例，提供一种物品的识别装置，包括：存储器；和耦接至所述存储器的处理器，所述处理器被配置为基于存储在所述存储器装置中的指令，执行上述任一个实施例中的物品的识别方法。
根据本公开的再一些实施例，提供一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现上述任一个实施例中的物品的识别方法。
通过以下参照附图对本公开的示例性实施例的详细描述，本公开的其它特征及其优点将会变得清楚。
附图说明
此处所说明的附图用来提供对本公开的进一步理解，构成本申请的一部分，本公开的示意性实施例及其说明用于解释本公开，并不构成对本公开的不当限定。在附图中：
图1示出本公开的售货装置的一些实施例的框图；
图2示出本公开的重量传感器安装的一些实施例的示意图；
图3示出本公开的称重单元的一些实施例的示意图；
图4示出本公开的售货装置的另一些实施例的框图；
图5示出本公开的售货装置的又一些实施例的框图；
图6示出本公开的物品的识别方法的一些实施例的流程图；
图7示出本公开的物品的识别方法的另一些实施例的流程图；
图8示出本公开的物品的识别装置的一些实施例的框图；
图9示出本公开的物品的识别装置的另一些实施例的框图。
具体实施方式
下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本公开一部分实施例，而不是全部的实施例。以下对至少一个示例性实施例的描述实际上仅仅是说明性的，决不作为对本公开及其应用或使用的任何限制。基于本公开中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
除非另外具体说明，否则在这些实施例中阐述的部件和步骤的相对布置、数字表 达式和数值不限制本公开的范围。同时，应当明白，为了便于描述，附图中所示出的各个部分的尺寸并不是按照实际的比例关系绘制的。对于相关领域普通技术人员已知的技术、方法和设备可能不作详细讨论，但在适当情况下，所述技术、方法和设备应当被视为授权说明书的一部分。在这里示出和讨论的所有示例中，任何具体值应被解释为仅仅是示例性的，而不是作为限制。因此，示例性实施例的其它示例可以具有不同的值。应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步讨论。
本公开的发明人发现上述相关技术中存在如下问题：系统的灵活性较差，不能根据实际场景的需求进行相应的配置。鉴于此，本公开提出了一种能够进行灵活配置的售货装置的技术方案。
图1示出本公开的售货装置的一些实施例的框图。
如图1所示，售货装置1包括货架层10、多个重量传感器11和处理器12。售货装置1可以是售货柜、售货架等。多个重量传感器11安装在货架层10上，例如，可以安装在货架层10的底部，也可以封装在货架层10内。例如，货架层10可以为多个，每个货架层10都安装有多个重量传感器11。
在一些实施例中，每个货架层10可以安装一个重量传感器11测量该货架层的重量并输出测量信号，也可以每个货架层10安装多个重量传感器11共同测量该货架层的重量并输出一个测量信号。
在一些实施例中，每个重量传感器11可以作为独立设备挂载到同一条串行总线上与处理器12连接，串行总线可以采用485总线、CAN(Controller Area Network，控制器局域网络)总线等，每个称重单元采用相同的通信协议。这样，只要将设备挂载到总线上，即可完成设备的加入，重量传感器的数目可以进行扩展。
在一些实施例中，多个重量传感器11之间并联连接，用于根据货架层承担的重量输出并联电压。处理器12与多个重量传感器11连接，用于根据并联电压，确定货架层承担的重量，以便根据承担的重量的变化识别从货架层取出的物品。例如，物品的识别既可以在安装有识别系统1的售货装置上进行，也可以在云端进行识别后，将识别结果回传给售货装置。
在一些实施例中，在远离货架层中心的位置，多个重量传感器沿货架层的周向间隔安装。
这样，多个重量传感器采用并联连接，并以并联后的电压作为输出，从而确定货 架层重量的变化。同时采集多个重量传感器的共同测量结果，避免了各传感器单独测量、货架不稳定等不利因素造成的测量时间不同步问题，且无需在每个物品上添加电子标签，从而在较低成本下提高了物品识别的准确率。例如，可以根据图2安装重量传感器。
图2示出本公开的重量传感器安装的一些实施例的示意图。
如图2所示，售货装置的重量传感器21和重量传感器22，分别安装在货架层20的两端。这样，通过重量传感器21和重量传感器22的两端支撑，减轻物品放置或移出货架层20时产生的抖动，减少货架层20的稳定时间，降低由于抖动和不稳定造成的扭矩对测量结果的影响，从而可以提高准确率。
重量传感器21和重量传感器22可以是并联连接，以并联电压作为输出信号。这样，可以实现同时采集两个重量传感器的共同输出，避免多个重量传感器单独测量和货架层不稳定造成的测量时间差，从而可以提高准确率。
在一些实施例中，对于矩形货架层，可以在货架层的四角分别安装一个重量传感器；对于圆形或椭圆形货架层，可以在货架层的圆周附近间隔安装重量传感器。
在一些实施例中，第一重量传感器包括电阻R 1，R 1的阻值随外力改变。第二重量传感器包括电阻R′ 1，R′ 1的阻值随外力改变。第一重量传感器和第二重量传感器并联为一个称重单元。
例如，R 1和R′ 1由弹性体和粘贴在弹性体表面的电阻应变片组成。在外力作用下弹性体产生弹性变形，使电阻应变片(即转换元件)也随之产生变形。电阻应变片变形后，阻值将发生变化，再经相应的测量电路把这一电阻变化转换为电信号(电压或电流)。例如，可以通过图3中的实施例设置称重单元。
图3示出本公开的称重单元的一些实施例的示意图。
如图3所示，称重单元3包括第一重量传感器、第二重量传感器、第一输出端31、第二输出端32和电源33。
第一重量传感器由R 1、R 2、R 3和R 4组成。R 1的第一端与R 2的第一端连接，R 1的第二端与R 3的第一端连接，R 2的第二端与R 4的第一端连接，R 3的第二端与R 4的第二端连接。R 1的第二端与电源33的第一端连接，R 2的第二端与电源的第二端连接。
第二重量传感器由R′ 1、R′ 2、R′ 3和R′ 4组成。R′ 1的第一端与R′ 2的第一端连接，R′ 1的第二端与R′ 3的第一端连接，R′ 2的第二端与R′ 4的第一端连接，R′ 3的第二端与R′ 4的第二端连接。R′ 1的第二端与电源33的第一端连接，R′ 2的第二端与电源33的第二端连接
第一重量传感器、第二重量传感器并联在电源33的两端，R 1的第一端与R′ 1的第一端连接，R 3的第二端与R′ 3的第二端连接。
称重单元3的输出端31和输出端32之间的输出电压与第一重量传感器和第二重量传感器所受的外力成正比。R′ 1的第一端与称重单元3的输出端31连接，R′ 3的第二端与称重单元3的输出端32连接。通过称重单元3的输出端31和输出端32之间的输出电压即可获取货架层承担的重量。
这样，可以实现同时采集两个重量传感器的共同输出，避免多个重量传感器单独测量和货架层不稳定造成的测量时间差，从而可以提高准确率。
在一些实施例中，可以通过一个信号放大器驱动多个重量传感器。例如，可以通过图4中的实施例配置售货装置。
图4示出本公开的售货装置的另一些实施例的框图。
如图4所示，售货装置4包括货架层10、多个重量传感器11、处理器12和信号放大器43。
在一些实施例中，可以为每个重量传感器连接一个信号放大器，各信号放大器在通过同一条串行总线与处理器连接。
在一些实施例中，多个重量传感器11可以在并联后与信号放大器43连接，信号放大器43通过串行总线与处理器12连接。
相比较于每个重量传感器单独测量，每个重量传感器都连接一个单独的信号放大器的技术方案，售货装置4采用一个信号放大器驱动多个重量传感器的方案降低了成本。而且，售货装置4可以使得多个重量传感器11同时测量货架层的重量，处理器12查询一次信号放大器43就可以获取同一时刻多个重量传感器11的共同测量值，实现多个重量传感器11的协同测量，从而降低系统开销、提高准确率。
图5示出本公开的售货装置的又一些实施例的框图。
如图5所示，售货装置5包括货架层10、多个重量传感器11、处理器12和摄像装置54。
摄像装置54处理器连接，用于获取物品的图像。
在一些实施例中，摄像装置54可以为多个，通过USB(Universal Serial Bus，通用串行总线)或网口接入处理器12。例如，可以通过多个USB接口或者USB HUB集线器将多个摄像装置54接入处理器12，在需要网络传输的情况下，也可以通过交换机将多个摄像装置54接入处理器12。
处理器12根据承担的重量的变化和物品的图像的处理结果中的至少一个，识别物品。例如，可以利用重量传感器11和摄像装置54的识别结果互相验证，从而提高识别率。
在一些实施例中，售货装置5还可以包括计算加速设备55，用于对物品的图像进行处理，获取处理结果。
例如，处理器12作为售货装置5的主控单元，具备控制和计算能力。处理器12能够汇总收集多个重量传感器11和摄像装置54的测量数据，并与云端后台进行通信。在售货装置5配备显示设备的情况下，处理器12还负责驱动显示设备。
例如，计算加速设备55可以是USB加速设备或PCIE(Peripheral Component Interconnect Express，快速外设部件互连标准)加速设备，如Movidius神经计算棒和intel HDDL计算卡等。
在一些实施例中，摄像装置54可以包括图像处理单元541，例如，AI(Artificial Intelligence，人工智能)芯片，用于对所品的图像进行处理，获取处理结果。例如，摄像装置54中的图像处理单元541能够通过CNN(Convolutional Neural Networks，卷积神经网络)等技术对获取的物品图像进行计算，并对计算结果进行数据分析等进一步处理，从而获取物品图像的处理结果。
这样，采用包括图像处理单元541的摄像装置54无需向处理器12传输大量的图像、视频流数据，仅需传输图像处理结果到处理器12。降低了对处理器12的接口数目和带宽的要求，从而售货装置5搭载大量的摄像装置54，提高识别率。
在上述实施例中，多个重量传感器挂载到同一条串行总线上与处理器连接，使得系统挂载传感器的数量可以随实际需要进行扩展，提高了系统的灵活性。
图6示出本公开的物品的识别方法的一些实施例的流程图。
如图6所示，该方法包括：步骤610，接收测量信号；步骤620，确定承担的重量；和步骤630，识别取出的物品。
在步骤610中，接收挂载到同一条串行总线上的多个重量传感器输出的测量信号，多个重量传感器安装在售货装置的货架层，测量信号根据货架层承担的重量输出。
在步骤620中，根据测量信号，确定货架层承担的重量。例如，多个重量传感器并联连接，测量信号为并联电压。
在步骤630中，根据承担的重量的变化识别从货架层取出的物品。
在一些实施例中，还可以通过图7中的实施例实现本方法。
图7示出本公开的物品的识别方法的另一些实施例的流程图。
如图7所示，相比于图6的实施例，该方法还包括：步骤710，获取图像的处理结果。
在步骤710中，获取物品的图像的处理结果。例如，物品的图像和处理结果由安装在售货装置的摄像装置获取。
步骤710与图6中的步骤610、步骤620没有执行顺序。
在步骤620中，根据承担的重量的变化和处理结果中的至少一个，识别物品。
在上述实施例中，多个重量传感器挂载到同一条串行总线上与处理器连接，使得系统挂载传感器的数量可以随实际需要进行扩展，提高了系统的灵活性。
图8示出本公开的物品的识别装置的一些实施例的框图。
如图8所示，该实施例的物品的识别装置8包括：存储器81以及耦接至该存储器81的处理器82，处理器82被配置为基于存储在存储器81中的指令，执行本公开中任意一个实施例中的物品的识别方法。
其中，存储器81例如可以包括系统存储器、固定非易失性存储介质等。系统存储器例如存储有操作系统、应用程序、引导装载程序(Boot Loader)、数据库以及其他程序等。
图9示出本公开的物品的识别装置的另一些实施例的框图。
如图9所示，该实施例的物品的识别装置9包括：存储器910以及耦接至该存储器910的处理器920，处理器920被配置为基于存储在存储器910中的指令，执行前述任意一个实施例中的物品的识别方法。
存储器910例如可以包括系统存储器、固定非易失性存储介质等。系统存储器例如存储有操作系统、应用程序、引导装载程序(Boot Loader)以及其他程序等。
物品的识别装置9还可以包括输入输出接口930、网络接口940、存储接口950等。这些接口930、940、950以及存储器910和处理器920之间例如可以通过总线960连接。其中，输入输出接口930为显示器、鼠标、键盘、触摸屏等输入输出设备提供连接接口。网络接口940为各种联网设备提供连接接口。存储接口950为SD卡、U盘等外置存储设备提供连接接口。
本领域内的技术人员应当明白，本公开的实施例可提供为方法、系统、或计算机程序产品。因此，本公开可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本公开可采用在一个或多个其中包含有计算机可用程 序代码的计算机可用非瞬时性存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
至此，已经详细描述了根据本公开的物品信息处理方法、物品信息处理系统、物品信息处理装置和计算机可读存储介质。为了避免遮蔽本公开的构思，没有描述本领域所公知的一些细节。本领域技术人员根据上面的描述，完全可以明白如何实施这里公开的技术方案。
可能以许多方式来实现本公开的方法和系统。例如，可通过软件、硬件、固件或者软件、硬件、固件的任何组合来实现本公开的方法和系统。用于所述方法的步骤的上述顺序仅是为了进行说明，本公开的方法的步骤不限于以上具体描述的顺序，除非以其它方式特别说明。此外，在一些实施例中，还可将本公开实施为记录在记录介质中的程序，这些程序包括用于实现根据本公开的方法的机器可读指令。因而，本公开还覆盖存储用于执行根据本公开的方法的程序的记录介质。
虽然已经通过示例对本公开的一些特定实施例进行了详细说明，但是本领域的技术人员应该理解，以上示例仅是为了进行说明，而不是为了限制本公开的范围。本领域的技术人员应该理解，可在不脱离本公开的范围和精神的情况下，对以上实施例进行修改。本公开的范围由所附权利要求来限定。

Claims (16)

  1. 一种售货装置，包括：
    设置在所述售货装置内用于放置商品的一个或多个货架层；
    重量传感器，一个货架层安装有多个重量传感器用于共同测量该货架层承担的重量并输出测量信号，所述多个重量传感器挂载到同一条串行总线上；
    处理器，通过所述串行总线与所述多个重量传感器电连接，用于根据所述测量信号确定所述相应的货架层承担的重量，以便根据所述承担的重量的变化识别从所述相应的货架层取出的物品。
  2. 根据权利要求1所述的售货装置，其中，
    所述多个重量传感器在远离所述相应的货架层中心的位置，沿所述相应的货架层的周向间隔安装。
  3. 根据权利要求2所述的售货装置，其中，
    所述多个重量传感器为第一重量传感器和第二重量传感器，分别安装在所述相应的货架层的两端。
  4. 根据权利要求1所述的售货装置，其中，
    所述多个重量传感器并联连接；
    所述测量信号为并联电压。
  5. 根据权利要求4所述的售货装置，其中，
    所述多个重量传感器为第一重量传感器和第二重量传感器，所述第一重量传感器包括电阻R 1，所述R 1的阻值随外力改变，所述第二重量传感器包括电阻R′ 1，所述R′ 1的阻值随外力改变；
    所述第一重量传感器和所述第二重量传感器并联为一个称重单元。
  6. 根据权利要求5所述的售货装置，其中，
    所述电阻R 1的第一端与电阻R 2的第一端连接，所述电阻R 1的第二端与电阻R 3的第一端连接，所述电阻R 2的第二端与电阻R 4的第一端连接，所述电阻R 3的第二端与所述电阻R 4的第二端连接，所述电阻R 1的第二端与电源的第一端连接，所述电阻R 2的第二端与所述电源的第二端连接；
    所述电阻R′ 1的第一端与R′ 2的第一端连接，所述电阻R′ 1的第二端与R′ 3的第一端连接，所述电阻R′ 2的第二端与电阻R′ 4的第一端连接，所述电阻R′ 3的第二端与所述电阻R′ 4的第 二端连接，所述电阻R′ 1的第二端与所述电源的第一端连接，所述电阻R′ 2的第二端与所述电源的第二端连接；
    所述电阻R 3的第二端与所述电阻R′ 3的第二端连接，所述电阻R 1的第一端与所述电阻R′ 1的第一端连接，所述电阻R′ 1的第一端与所述称重单元的第一输出端连接，所述电阻R′ 3的第二端与所述称重单元的第二输出端连接。
  7. 根据权利要求4-6任一项所述的售货装置，还包括：
    信号放大器，所述多个重量传感器并联后与所述信号放大器电连接，所述信号放大器通过串行总线与所述处理器连接。
  8. 根据权利要求1-6任一项所述的售货装置，还包括：
    与所述处理器电连接的摄像装置，用于获取所述物品的图像；
    其中，
    所述处理器根据所述承担的重量的变化和所述物品的图像的处理结果中的至少一个识别所述物品。
  9. 根据权利要求8所述的售货装置，其中，
    所述摄像装置包括图像处理单元，用于对所述物品的图像进行处理，获取所述处理结果。
  10. 根据权利要求8所述的售货装置，还包括：
    与所述处理器电连接的计算加速设备，用于对所述物品的图像进行处理，获取所述处理结果。
  11. 一种物品的识别方法，包括：
    接收挂载到同一条串行总线上的多个重量传感器输出的测量信号，所述多个重量传感器安装在售货装置的货架层用于共同测量该货架层承担的重量并输出所述测量信号，所述测量信号根据所述货架层承担的重量输出；
    根据所述测量信号，确定所述货架层承担的重量；
    根据所述承担的重量的变化识别从所述货架层取出的物品。
  12. 根据权利要求11所述的识别方法，其中，
    所述多个重量传感器并联连接；
    所述测量信号为并联电压。
  13. 根据权利要求11所述的识别方法，还包括：
    获取所述物品的图像的处理结果；
    其中，所述确定所述货架层承担的重量包括：
    根据所述承担的重量的变化和所述处理结果中的至少一个，识别所述物品。
  14. 根据权利要求13所述的识别方法，其中，
    所述物品的图像和所述处理结果由安装在所述售货装置的摄像装置获取。
  15. 一种物品的识别装置，包括：
    存储器；和
    耦接至所述存储器的处理器，所述处理器被配置为基于存储在所述存储器装置中的指令，执行权利要求11-14任一项所述的物品的识别方法。
  16. 一种计算机可读存储介质，其上存储有计算机程序，该程序被处理器执行时实现权利要求11-14任一项所述的物品的识别方法。
PCT/CN2019/100181 2018-12-29 2019-08-12 售货装置、物品的识别方法、装置和计算机可读存储介质 Ceased WO2020134106A1 (zh)

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