Input / output method, input / output program, and input / output device

Abstract

To provide a method for input / output adapted to relieve the burden imposed on an association of different devices.SOLUTION: A method for input / output according to an embodiment is to input an image captured by a camera, execute recognition processing to recognize a state of at least one of first and second devices to handle a to-be-transported object or a state of the to-be-transported object, based on an analysis result of the image, and output a signal to control the first or second device based on the recognition processing.SELECTED DRAWING: Figure 2

Description

Technical Field

[0001] Embodiments of the present invention relate to an input / output method, an input / output program, and an input / output device.

Background Art

[0002] In recent years, the handling volume of articles has increased at logistics distribution bases and the like, and the automation of article processing has been promoted. For example, in a warehouse, various automatic devices cooperate, and each device transfers an article or a material storing the article in accordance with an instruction from a higher-level device.

[0003] Known automatic devices include an autonomous mobile robot (abbreviated as AMR), a roll pallet tipper (abbreviated as RPT), a case transfer unit (abbreviated as CTU), and a conveyor.

[0004] For example, AMR-A transports and stops a pallet loaded with articles or the like to a predetermined area. AMR-B acquires the pallet transported to the predetermined area and transports it to a conveyor. The conveyor detects the pallet and transports the pallet to a predetermined area.

[0005] RPT receives a roll pallet, tilts the received roll pallet, and discharges the articles stored in the roll pallet to a conveyor or the like. The roll pallet is a pallet with a cart surrounded by fences on the sides.

[0006] CTU includes a fork mechanism that moves in the vertical direction. CTU travels toward the conveyor and stops in an area facing the end of the conveyor. CTU adjusts the height of the fork mechanism according to the height of the conveyor, receives a case or the like transported to the end of the conveyor with the fork mechanism, and transports the received case or the like to a predetermined area.

Prior Art Documents

Patent Documents

[0007] [Patent Document 1] Japanese Patent Publication No. 2022-52494 [Overview of the project] [Problems that the invention aims to solve]

[0008] Various automated machines are introduced into the warehouse to meet the requirements for handling goods, but a common interface (abbreviated as IF) is necessary to coordinate these automated machines.

[0009] When automated equipment has specialized specifications and lacks a general-purpose interface (IF), modifying the IF and conducting post-modification testing incurs significant costs, time, and resources. Furthermore, modifying older automated equipment can be difficult due to factors such as the end of support for that equipment. Additionally, connecting multiple types of automated equipment from multiple manufacturers requires presenting specifications and making modifications to each manufacturer, resulting in considerable effort, manpower, and cost. Moreover, the operation of the affected equipment may need to be stopped during the modification period, potentially reducing warehouse operational efficiency.

[0010] The problem that this invention aims to solve is to provide an input / output method, an input / output program, and an input / output device that reduce the burden of coordinating different devices. [Means for solving the problem]

[0011] The input / output method according to this embodiment inputs an image obtained by a camera, performs a recognition process to recognize the state of at least one of the first and second devices that process the conveyed object, or the state of the conveyed object, based on the results of the analysis of the image, and outputs a signal for controlling the first or second device based on the recognition process. [Brief explanation of the drawing]

[0012] [Figure 1]Figure 1 is a conceptual diagram showing an example of a warehouse system according to the first embodiment. [Figure 2] Figure 2 is a flowchart showing an example of the operation of the warehouse system according to the first embodiment. [Figure 3] Figure 3 shows an example of state recognition of AMR-A according to the first embodiment. [Figure 4] Figure 4 shows an example of state recognition of AMR-B according to the first embodiment. [Figure 5] Figure 5 shows an example of shape recognition by AMR-B according to the first embodiment. [Figure 6] Figure 6 is a conceptual diagram showing an example of a warehouse system according to the second embodiment. [Figure 7] Figure 7 is a flowchart showing an example of the operation of the warehouse system according to the second embodiment. [Figure 8] Figure 8 shows an example of AMR state recognition according to the second embodiment. [Figure 9] Figure 9 shows an example of RPT state recognition (ready to accept) according to the second embodiment. [Figure 10] Figure 10 shows an example of RPT state recognition (ready to operate) according to the second embodiment. [Figure 11] Figure 11 shows an example of AMR state recognition (acceptance complete) according to the second embodiment. [Figure 12] Figure 12 shows an example of RPT state recognition (item release complete) according to the second embodiment. [Figure 13] Figure 13 is a conceptual diagram showing an example of a warehouse system according to the third embodiment. [Figure 14] Figure 14 is a flowchart showing an example of the operation of a warehouse system according to the third embodiment. [Figure 15] Figure 15 shows an example of article state recognition according to the third embodiment. [Figure 16] Figure 16 shows an example of article shape recognition according to the third embodiment. [Figure 17] FIG. 17 is a conceptual diagram showing an example of a warehouse system according to the fourth embodiment. [Figure 18] FIG. 18 is a flowchart showing an example of the operation of the warehouse system according to the fourth embodiment. [[[[ID]] [Figure 19] FIG. 19 is a diagram showing an example of the state recognition of the AGV according to the fourth embodiment.

Embodiments for Carrying Out the Invention

[0013] <The First Embodiment> Hereinafter, the first embodiment will be described with reference to the drawings.

[0014] [Configuration] FIG. 1 is a conceptual diagram showing an example of a warehouse system according to the first embodiment. In the first embodiment, the automatic IF device 5 inputs an image from the camera 6, analyzes the image, executes a recognition process for recognizing the state of the first or second device that processes the conveyed object based on the analysis result of the image, and outputs a signal for controlling the first or second device based on the recognition process.

[0015] For example, the automatic IF device 5 executes a first recognition process for recognizing the state of the AMR-A411, which is the first device, based on the analysis result of the image, and outputs a first signal for controlling the AMR-B412, which is the second device, based on the first recognition result.

[0016] Also, the automatic IF device 5 executes a second recognition process for recognizing the state of the AMR-B412 based on the analysis result of the image, and outputs a second signal for controlling the AMR-A411 based on the second recognition result.

[0017] The automatic IF device 5 can operate the AMR-A411 and the AMR-B412 in cooperation by outputting the first and second signals in sequence.

[0018] As shown in Figure 1, the goods processing system S includes a Warehouse Management System (WMS) 1, a Warehouse Execution System (WES) 2, an AMR-A control device 311, an AMR-B control device 312, a conveyor control device 313, an AMR-A (hardware / firmware) 411, an AMR-B (hardware / firmware) 412, a pallet conveyor 413, and a camera 6.

[0019] AMR-A411 is an example of a first device for processing (transporting) conveyed objects. AMR-A412 is an example of a second device for processing (transporting) conveyed objects. Note that the first and second devices are not limited to AMRs, but may also be AGVs (Automated Guided Vehicles) or AGFs (Automated Guided Vehicle Forklifts), etc. For example, conveyed objects are equipment such as pallets for storing goods. There is one or more AMR-A411s, but in this embodiment, multiple units are assumed. There is one or more AMR-B412s, but in this embodiment, multiple units are assumed. There is one or more cameras 6, and each will be described in this embodiment.

[0020] WES2 includes an automatic IF (interface) device 5 as an input / output device. The automatic IF device 5 may be an internal component of WES2 or an external component of WES2.

[0021] WMS1 can be composed of one or more general-purpose computers, i.e., input / output interfaces, processors, and memory. The processor can be a CPU (central processing unit), MPU (microprocessing unit), or DSP (digital signal processor). WMS1 receives item orders from the higher-level server and transmits them to WES2.

[0022] An item order is an order specifying one or more items, and includes item information, order information, and delivery information. Item information includes the number of items, item identification information, item name, etc. Order information includes the order date and time and the person who placed the order, etc. Delivery information includes the delivery address, delivery date and time, and recipient, etc.

[0023] WES2 can be configured with one or more general-purpose computers, i.e., input / output interfaces, processors, and memory. The processor can be a CPU, MPU, or DSP. WES2 receives multiple item orders from WMS1, instructs the inbound and outbound of items based on the item orders, and receives the results. WES2 transmits the received results to WMS1.

[0024] The AMR-A control unit 311 can be configured with one or more general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the AMR-A control unit 311 is equipped with an IF 3111, which receives signals output from the automatic IF device 5. For example, these signals are commands, and these commands are Application Programming Interface (API) commands. The IF 3111 is also an API. Based on the received commands, the AMR-A control unit 311 outputs control signals to control the AMR-A 411.

[0025] The AMR-B control unit 312 can be configured with one or more general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the AMR-B control unit 312 includes an IF 3121, which receives signals output from the automatic IF device 5. For example, this signal is a command, and the command is an API command. Also, IF 3121 is an API. Based on the received command, the AMR-B control unit 312 outputs a control signal to control the AMR-B 412.

[0026] The conveyor control device 313 is one or more general-purpose computers or PLCs (Programmable Logic Controllers). That is, it can be composed of an IF, a processor, and memory, etc. The processor is a CPU, MPU, or DSP, etc. For example, the conveyor control device 313 is equipped with an IF 3131, which receives a signal output from the automatic IF device 5. For example, this signal is a command, and the command is an API command. Also, the IF 3131 is an API. Based on the received command, the conveyor control device 313 outputs a control signal to control the pallet conveyor 413.

[0027] The AMR-A411 (hardware / firmware) performs a first operation, which involves transporting an object from a first area to a second area and stopping in the second area, and a second operation, which involves moving from the second area to the first area and stopping in the first area, based on control signals from the AMR-A control device 311. For example, the AMR-A411 moves and stops so that the center of gravity of the AMR-A411 corresponds to the center of gravity of each area.

[0028] The AMR-B412 (hardware / firmware) performs the following actions based on control signals from the AMR-B control device 312: a third action of transporting an object from the second area to the third area, stopping in the third area, and placing the pallet onto the pallet conveyor 413; a fourth action of moving from the third area to the fourth area (retraction area) and stopping (retracting) in the fourth area; and a fifth action of moving from the fourth area to the second area and acquiring the pallet in the second area. For example, the AMR-B412 moves and stops so that the center of gravity of the AMR-B412 corresponds to the center of gravity of each area.

[0029] Camera 6 captures the operating areas of AMR-A411 and AMR-B412 and outputs the images obtained from the capture. For example, camera 6 captures the second and fourth areas and outputs the images obtained from the capture. Alternatively, multiple cameras 6 may be used, with the first camera 6 capturing the second area and outputting the image obtained from the capture, and another second camera 6 capturing the fourth area and outputting the image obtained from the capture.

[0030] The automatic IF device 5 can be composed of one or more general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the automatic IF device 5 includes a processor 51, an input IF 521, an output IF 522, and memory 53. The automatic IF device 5 is the main entity for executing input / output methods and input / output programs.

[0031] The processor 51 comprises an input unit 511, an image analysis unit 512, a recognition unit 513, a generation unit 514, and an output unit 515. The processor 51 realizes the functions of each unit by executing a program stored in the memory 53.

[0032] Input IF521 receives images obtained by camera 6, i.e., images output from camera 6, via wireless or wired connection.

[0033] The input unit 511 receives images from the input IF 521. The input unit 511 also receives dictionary data for image recognition. The dictionary data includes dictionary images (templates) for AMR-A411 and AMR-B412.

[0034] The image analysis unit 512 analyzes the input image and outputs the analysis results.

[0035] The recognition unit 513 performs a first recognition process to recognize the state of AMR-A411 based on the image analysis results and dictionary data. The recognition unit 513 also performs a second recognition process to recognize the state of AMR-B412 based on the image analysis results and dictionary data.

[0036] The generation unit 514 generates a first command for controlling AMR-B412 based on the first recognition process. The generation unit 514 also generates a second command for controlling AMR-A411 based on the second recognition process. The first command is a signal that causes AMR-B412 to perform the third operation. The second command is a signal that causes AMR-A411 to perform the second operation.

[0037] The output unit 515 outputs the generated first or second command.

[0038] Output IF522 outputs a first command to the AMR-B control unit 312 and a second command to the AMR-A control unit 311, either wirelessly or via a wired connection.

[0039] [Operation] Figure 2 is a flowchart showing an example of the operation of the warehouse system according to the first embodiment. ST111 to ST115 show an example of the operation of the AMR-A411, ST121 to ST127 show an example of the operation of the automatic IF device 5, and ST131 to ST134 show an example of the operation of the AMR-B412.

[0040] First, let's explain how the AMR-A411 works. Based on instructions from WES2 or image recognition results from camera 6, the automatic IF device 5 sends a command to the AMR-A control device 311. The AMR-A control device 311 sends a control signal to control the AMR-A411 based on the command. The AMR-A411 operates based on the control signal.

[0041] Based on the control signal, the AMR-A411 moves to the first area and loads the pallet (ST111). Alternatively, a person in charge may load the pallet onto the AMR-A411.

[0042] Based on the control signal, the AMR-A411 performs a first operation in which it transports the pallet from the first area to the second area (ST112) and stops in the second area (ST113). After the person in charge loads the pallet onto the AMR-A411, they may input a transport instruction to the AMR-A411, and the AMR-A411 may then perform this first operation based on this input.

[0043] Furthermore, when the AMR-A411 receives a control signal (second control signal) (ST114, YES), it performs a second operation based on the received control signal, moving from the second area to the first area and stopping in the first area (ST115).

[0044] Next, we will explain the operation of the automatic IF device 5. Input IF521 of the automatic IF device 5 receives the image from camera 6 (ST121).

[0045] Processor 51 receives an image from input IF521, analyzes the image, and outputs the analysis results.

[0046] The processor 51 performs a first recognition process to recognize the state of the AMR-A411 based on the analysis results and dictionary data (ST122).

[0047] The processor 51 determines whether the result of the first recognition process satisfies predetermined conditions (ST123). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0048] For example, if there is only one predetermined condition, the processor 51 determines whether the condition C111 for AMR-A411 to be recognized is met. If there are two predetermined conditions, in addition to condition C111, the processor 51 determines whether the change in the operating speed of AMR-A411 meets condition C112. Alternatively, in addition to condition C111, the processor 51 determines whether the stop area of ​​AMR-A411 meets condition C113. If there are three predetermined conditions, the processor 51 determines whether conditions C111, C112, and C113 are met.

[0049] If the processor 51 determines that a predetermined condition is met (ST123, YES), it generates a first command to control the AMR-B412 and outputs the first command. For example, if the AMR-A411 decelerates at a predetermined speed change and stops in the second region, the processor 51 determines that conditions C111, C112, and C113 are met. Output IF522 outputs the first command from the processor 51 to the AMR-B control device 312 (ST124).

[0050] The AMR-B control unit 312 receives a first command and outputs a first control signal based on the first command to the AMR-B 412. The AMR-B 412 performs a third operation based on the first control signal.

[0051] Furthermore, the processor 51 performs a second recognition process to recognize the state of the AMR-B412 based on the analysis results and dictionary data (ST125).

[0052] The processor 51 determines whether the result of the second recognition process satisfies predetermined conditions (ST126). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0053] For example, if there is only one predetermined condition, the processor 51 determines whether the condition C121 for AMR-B412 recognition is met. If there are two predetermined conditions, in addition to condition C121, the processor 51 determines whether the change in the operating speed of AMR-B412 meets condition C122. Alternatively, in addition to condition C121, the processor 51 determines whether the stop area of ​​AMR-B412 meets condition C123. If there are three predetermined conditions, the processor 51 determines whether conditions C121, C122, and C123 are met (ST126).

[0054] If the processor 51 determines that a predetermined condition is met (ST126, YES), it generates a second command to control the AMR-A411 and outputs the second command. For example, if the AMR-B412 decelerates at a predetermined speed change and stops in the fourth region, the processor 51 determines that conditions C121, C122, and C123 are met. Output IF522 outputs the second command from the processor 51 to the AMR-A control device 311 (ST127).

[0055] The AMR-A control unit 311 receives the second command and outputs a second control signal based on the second command to the AMR-A411. The AMR-A411 then performs the second operation based on the second control signal.

[0056] Next, I will explain how the AMR-B412 works. Based on instructions from WES2 or image recognition results from camera 6, the automatic IF device 5 sends a command to the AMR-B control device 312. The AMR-B control device 312 sends a control signal to control the AMR-B412 based on the command. The AMR-B412 operates based on the control signal.

[0057] For example, AMR-B412, which is evacuated in the fourth area, receives a first control signal from AMR-B control device 312 (ST131, YES), and based on the first control signal, performs a fifth operation in which it moves from the fourth area to the second area and acquires the pallet transported by AMR-A411 in the second area (ST132).

[0058] Furthermore, based on the first control signal, the AMR-B412 performs a third operation in which it transports the pallet from the second area to the third area, stops in the third area, and places the pallet onto the pallet conveyor 413 (ST133).

[0059] Furthermore, based on the first control signal, the AMR-B412 performs a fourth operation in which it moves from the third area to the fourth area (retraction area) and retracts (ST134).

[0060] Figure 3 is a diagram illustrating an example of state recognition of the AMR-A according to the first embodiment. In other words, it is a diagram illustrating the ST123 shown in Figure 2. Here, the processor 51 determines that the result of the first recognition process satisfies predetermined conditions if conditions C111, C112, and C113 are met. The processor 51 determines that the AMR-A411 has arrived in the second region and stopped if the predetermined conditions are met.

[0061] Condition C111 is the shape recognition of the AMR-A411. The processor 51 detects a segmentation (SG11) that resembles the AMR-A411 in the image and determines whether the similarity between the shape of the segmentation (SG11) and the shape of the AMR-A411 template (original) exceeds a threshold. The processor 51 determines that condition C111 is satisfied if the similarity exceeds the threshold.

[0062] In addition to the shape recognition of AMR-A411, AMR identification information recognition may be used, or alternatively, AMR identification information recognition may be used instead of the shape recognition of AMR-A411. All AMRs are provided with AMR identification information in the form of a combination of characters, numbers, symbols, etc., or AMR identification information in the form of a barcode or a two-dimensional code. The processor 51 recognizes the AMR identification information included in the captured image from the camera 6, compares the registered AMR identification information stored in the memory 53 with the recognized AMR identification information, and when they match, determines that the condition C111 is satisfied and recognizes that it is a predetermined AMR-A411.

[0063] Condition C112 is the recognition of the change in the operating speed of AMR-A411 from entry to stop. The processor 51 detects the characteristics of the change in the operating speed. For example, the processor 51 detects the speed (V1(t = 0)) at the time of entry into the region of the segmentation (SG11), and the speeds (V1(t)) and (V1(T1)=0) after entry into the region of the segmentation (SG11). Here, T1 is the time from the entry into the region of the segmentation (SG11) to the stop.

[0064] The processor 51 recognizes AMR-A411 based on the characteristics of the change in the operating speed. For example, when the change in the operating speed meets the standard, the processor 51 recognizes this change in the operating speed as the change in the operating speed of AMR-A411, and based on this recognition, determines that the condition C112 is satisfied. For example, the processor 51 determines that the condition C112 is satisfied if v1 < V1(0) < v2 and t1 < T1 < t2 are satisfied based on the reference values v1, v2, t1, and t2.

[0065] Condition C113 is the recognition of the stop position of AMR-A411. The processor 51 recognizes the stop of AMR-A411 based on the positional relationship between the reference point of the stop region and the reference point of AMR-A411. For example, the processor 51 detects the position information (P1) of the segmentation corresponding to the second region (stop region), detects the position information (P2) of the segmentation (SG11) that looks like AMR-A411, and detects the deviation (relative position) between P1 and P2 that serves as the reference point.

[0066] The processor 51 determines whether the distance between the centroid positions of the reference points P1 and P2 is within a certain expected value, i.e., within the range of the lower and upper limits. If the distance between the centroid positions is within the range of the lower and upper limits, the processor 51 recognizes that the AMR-A411 has stopped, and based on this recognition, determines that condition C113 is satisfied.

[0067] Figure 4 shows an example of state recognition of AMR-B according to the first embodiment. That is, it is a diagram for explaining ST126 shown in Figure 2. Here, the processor 51 determines that the result of the second recognition process satisfies predetermined conditions if conditions C121, C122, and C123 are met. If the predetermined conditions are met, the processor 51 determines that the AMR-B412 has arrived at the fourth area (retraction position) and stopped.

[0068] Condition C121 is the shape recognition of the AMR-B412. The processor 51 detects a segmentation (SG12) that resembles the AMR-B412 in the image and determines whether the similarity between the shape of the segmentation (SG12) and the shape of the AMR-B412 template (original) exceeds a threshold. The processor 51 determines that condition C121 is satisfied if the similarity exceeds the threshold.

[0069] In addition to the shape recognition of AMR-B412, AMR identification information recognition may also be used, or AMR identification information recognition may be used instead of the shape recognition of AMR-B412.

[0070] Condition C122 is the recognition of changes in the operating speed of the AMR-B412 from entry to stopping. The processor 51 detects the characteristics of the changes in operating speed. For example, the processor 51 detects the speed (V2(t=0)) when entering the segmentation (SG12) region, and the speed (V2(t)) and (V2(T2)=0) after entering the segmentation (SG12) region. Note that T2 is the time from entry into the segmentation (SG12) region to stopping.

[0071] Based on the characteristics of the operating speed change, the processor 51 recognizes AMR-B412. For example, when the operating speed change meets the criteria, the processor 51 recognizes this operating speed change as the operating speed change of AMR-B412, and based on this recognition, determines that condition C122 is satisfied. For example, the processor 51 determines that condition C122 is satisfied if v3 < V2(0) < v4 and t3 < T2 < t4 are satisfied based on the reference values v3, v4, t3, and t4.

[0072] Condition C123 is the recognition of the stop position of AMR-B412. The processor 51 recognizes the stop of AMR-A412 based on the positional relationship between the reference point of the stop area and the reference point of AMR-B412. For example, the processor 51 detects the position information (P3) of the segmentation corresponding to the fourth area (stop area), detects the position information (P4) of the segmentation (SG12) resembling AMR-B412, and detects the deviation (relative position) between P3 and P4.

[0073] The processor 51 determines whether the distance of the center-of-gravity position between P3 and P4 is within the expected constant value, that is, within the range of the lower limit and the upper limit. When the distance of the center-of-gravity position is within the range of the lower limit and the upper limit, the processor 51 recognizes that AMR-B412 has stopped, and based on this recognition, determines that condition C123 is satisfied.

[0074] FIG. 5 is a diagram showing an example of the shape recognition of AMR-B according to the first embodiment. Memory 53 registers (stores) images of all AMR templates (originals). Processor 51 compares the image of the detected segmentation (SG12) with the registered template images. If the similarity between the image of the detected segmentation (SG12) and the template image of AMR-B412 exceeds a threshold, processor 51 recognizes the detected segmentation (SG12) as AMR-B412. If the similarity between the image of the detected segmentation (SG12) and the template image of AMR-B412 does not exceed a threshold, processor 51 recognizes the detected segmentation (SG12) as not being AMR-B412. If the similarity between the image of the detected segmentation (SG12) and the template image of another AMR exceeds a threshold, processor 51 recognizes the detected segmentation (SG12) as another AMR.

[0075] As described above, the automatic IF device 5 of the first embodiment takes images captured by the camera 6 as input and outputs signals such as API commands for controlling each device, such as the AMR-A411 and AMR-B412. The automatic IF device 5 analyzes the input images, recognizes the state (state transition) of one device based on the analysis results, and outputs signals such as API commands for controlling the other device based on the recognition results.

[0076] If each control device, such as the AMR-A control device 311 and the AMR-B control device 312, which control each device, is equipped with an API, then modification of the IF of each control device becomes unnecessary. Thus, according to the first embodiment, when coordinating the operation of each device, the burden of coordination can be reduced. Furthermore, by making the automatic IF device 5 independent from WES2, even if a system failure occurs in WES2, each device can be operated in coordination.

[0077] In the first embodiment, the case in which the automatic IF device 5 is applied to a total of two processing units of two types, such as AMR-A411 and AMR-B412, was described. However, the automatic IF device 5 may also be applied to a total of three or more processing units of three or more types. Furthermore, the control target of the automatic IF device 5 is not limited to AMRs; it may also be an older type of processing unit or a general-purpose conveyor. In addition, the control device connecting the automatic IF device 5 and the controlled processing unit may be implemented as a PLC (Programmable Logic Controller).

[0078] <Second Embodiment> The second embodiment will now be described with reference to the drawings. Components that use the same reference numerals as those used in the first embodiment are substantially the same as those in the first embodiment, and their descriptions will be omitted as appropriate.

[0079] [composition] Figure 6 is a conceptual diagram showing an example of a warehouse system according to the second embodiment. In the second embodiment, the automatic IF device 5 receives an image from the camera 6, analyzes the image, performs a recognition process to recognize the state of at least one of the first and second devices that process the conveyed objects based on the image analysis results, and outputs a signal to control the first or second device based on the recognition process.

[0080] For example, the automatic IF device 5 performs a first recognition process to recognize the states of the first device, AMR412, and the second device, RPT422, based on the image analysis results, and outputs a first signal to control the AMR412 based on the first recognition results.

[0081] Furthermore, the automatic IF device 5 performs a second recognition process to recognize the states of AMR412 and RPT422 based on the image analysis results, and outputs a second signal for controlling RPT422 based on the second recognition result.

[0082] Furthermore, the automatic IF device 5 performs a third recognition process to recognize the state of the RPT422 based on the image analysis results, and outputs a third signal to control the AMR412 based on the third recognition result.

[0083] The automatic IF device 5 can operate the AMR412 and RPT422 in coordination by outputting the first, second, and third signals in sequence.

[0084] As shown in Figure 6, the item processing system S comprises WMS1, WES2, AMR control device 321, RPT control device 322, AMR (hardware / firmware) 421, RPT (hardware) 422, automatic IF device 5, and camera 6. AMR421 corresponds to AMR-A411, and its description is omitted here.

[0085] The AMR control device 321 can be composed of one or more general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the AMR control device 321 includes an IF 3211, which receives first and third signals output from the automatic IF device 5. For example, the first signal is a first command, and the first command is an API command. The third signal is a third command, and the third command is an API command. Also, IF 3211 is an API. Based on the received first command, the AMR control device 321 outputs a first control signal to control the AMR 421, and based on the received third command, it outputs a third control signal to control the AMR 421.

[0086] The RPT control device 322 can be composed of one or more dedicated devices, PLCs, or general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the RPT control device 322 is a switch BOT and is equipped with an IF 3221, which receives a second signal output from the automatic IF device 5. For example, the second signal is a second command, and the second command is an API command. Also, IF 3221 is an API. Based on the received second command, the RPT control device 322 outputs a second control signal to control the RPT 422.

[0087] Based on control signals from the AMR control device 321, the AMR421 performs the following actions: a first action of transporting equipment from the first area to the second area and stopping in the second area; a second action of setting the equipment on the RPT422; a third action of moving away from the RPT422 and stopping in the third area; and a fourth action of retrieving the equipment set on the RPT422. For example, the AMR421 moves and stops so that the center of gravity of the AMR421 corresponds to the center of gravity of each area.

[0088] The RPT422 receives equipment such as roll pallets, tilts the received roll pallets, and releases the items stored in the roll pallets onto a conveyor or the like. A roll pallet is a pallet with a trolley and its sides are enclosed by a fence. Based on a control signal from the RPT control device 322, the RPT422 receives the equipment set by the AMR421 and then performs a fifth operation in which it releases the items from the equipment to a predetermined position.

[0089] Camera 6 captures the operating area of ​​the AMR421 and the RPT422, and outputs the image obtained from the capture. For example, camera 6 captures the second area and the RPT422, and outputs the image obtained from the capture. Alternatively, multiple cameras 6 may be used, with the first camera 6 capturing the third area and outputting the image obtained from the capture, and another second camera 6 capturing the RPT422 and outputting the image obtained from the capture.

[0090] The basic configuration of the automatic IF device 5 is as described in the first embodiment.

[0091] The input unit 511 receives an image from the input IF 521. The input unit 511 also receives dictionary data for image recognition. The dictionary data includes dictionary images (templates) for AMR421 and RPT422. For example, the dictionary data includes dictionary images of RPT422 in the state after it has accepted the roll palette and in the state before it accepts the roll palette.

[0092] The image analysis unit 512 analyzes the input image and outputs the analysis results.

[0093] The recognition unit 513 performs first and second recognition processes to recognize the states of AMR421 and RPT422 based on the image analysis results and dictionary data. The recognition unit 513 also performs a third recognition process to recognize the state of RPT422 based on the image analysis results and dictionary data.

[0094] The generation unit 514 generates a first command to control AMR421 based on the first recognition process. The generation unit 514 also generates a third command to control RPT422 based on the second recognition process. The generation unit 514 also generates a second command to control AMR421 based on the third recognition process. The first command is a signal that causes AMR421 to perform the second operation. The second command is a signal that causes AMR-A411 to perform the fifth operation. The third command is a signal that causes AMR-A411 to perform the fourth operation.

[0095] The output unit 515 outputs the generated first, second, or third command.

[0096] Output IF522 outputs a first command to the AMR control device 321, a second command to the RPT control device 322, and a third command to the AMR control device 321, either wirelessly or via a wired connection.

[0097] [Operation] Figure 7 is a flowchart showing an example of the operation of the warehouse system according to the second embodiment. ST211 to ST218 show an example of the operation of AMR421, ST221 to ST230 show an example of the operation of automatic IF device 5, and ST231 to ST233 show an example of the operation of RPT422.

[0098] First, let's explain how the AMR421 works. Based on instructions from WES2 or image recognition results from camera 6, the automatic IF device 5 sends a command to the AMR control device 321. The AMR control device 321 sends a control signal to control the AMR421 based on the command. The AMR421 operates based on the control signal.

[0099] Based on the control signal, the AMR421 moves to the first area and loads the roll pallet (ST211). Alternatively, an operator may load the roll pallet onto the AMR421.

[0100] Based on the control signal, the AMR421 performs a first operation in which it transports the roll pallet from the first area to the second area (ST212) and stops in the second area (ST213). After the person in charge loads the pallet onto the AMR421, they may input a transport instruction to the AMR421, and the AMR421 will perform the first operation based on this input.

[0101] Furthermore, when the AMR421 receives a control signal (first control signal) (ST214, YES), it performs a second operation based on the received control signal to set the roll pallet onto the RPT422 (ST215), and then performs a third operation to retract from the RPT422 (ST216).

[0102] Furthermore, when the AMR421 receives a control signal (the third control signal) (ST217, YES), it performs a fourth operation based on the received control signal to retrieve the roll pallet set in the RPT422 (ST218).

[0103] Next, we will explain the operation of the automatic IF device 5. Input IF521 of the automatic IF device 5 receives the image from camera 6 (ST221).

[0104] Processor 51 receives an image from input IF521, analyzes the image, and outputs the analysis results.

[0105] The processor 51 performs a first recognition process (ST222) to recognize the states of AMR421 and RPT422 based on the analysis results and dictionary data.

[0106] The processor 51 determines whether the result of the first recognition process satisfies predetermined conditions (ST223). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0107] For example, the predetermined conditions are conditions C21, C22, C23, and C24, and the processor 51 determines whether or not conditions C21, C22, C23, and C24 are met.

[0108] If the processor 51 determines that a predetermined condition is met (ST223, YES), it generates a first command to control the AMR421 and outputs the first command (ST224). For example, when the AMR421 decelerates at a predetermined speed change and stops in the second area, the processor 51 determines that conditions C21, C22, and C23 are met (roll pallet transport completed). Furthermore, if the RPT422 is not accepting a roll pallet (empty), the processor 51 determines that condition C24 is met (ready to accept roll pallet). Output IF522 outputs the first command from the processor 51 to the AMR control device 321 (ST224).

[0109] The AMR control device 321 receives a first command and outputs a first control signal based on the first command to the AMR 422. The AMR 422 performs a second operation based on the first control signal.

[0110] Furthermore, the processor 51 performs a second recognition process (ST225) to recognize the states of AMR421 and RPT422 based on the analysis results and dictionary data.

[0111] The processor 51 determines whether the result of the second recognition process satisfies predetermined conditions (ST226). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0112] For example, if there are two predetermined conditions, the processor 51 determines whether condition C25, which indicates that a roll pallet is set in the RPT422, is met, and whether conditions C26, C27, and C28, which indicate that the AMR421 has been evacuated from the RPT422, are met.

[0113] If the processor 51 determines that a predetermined condition is met (ST226, YES), it generates a second command to control the RPT422 and outputs the second command. For example, when the RPT422 completes accepting the roll pallet, the processor 51 determines that condition C25 is met (roll pallet acceptance complete), and when the AMR421 completes its retraction, the processor 51 determines that conditions C26, C27, and C28 are met (retraction complete). The output IF522 outputs the second command from the processor 51 to the RPT control device 322 (ST227).

[0114] The RPT control device 322 receives the second command and outputs a second control signal based on the second command to the RPT 422. The RPT 422 performs the fifth operation based on the second control signal. Alternatively, the RPT 422 is switched on by the RPT control device 322, which is a switch BOT, and performs the fifth operation based on the switch-on.

[0115] Furthermore, the processor 51 performs a third recognition process (ST228) to recognize the state of the RPT422 based on the analysis results and dictionary data.

[0116] The processor 51 determines whether the result of the third recognition process satisfies predetermined conditions (ST229). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0117] For example, if there is only one predetermined condition, the processor 51 determines whether or not condition C29, which indicates that the items on the roll pallet set in the RPT422 have been released, is met.

[0118] If the processor 51 determines that a predetermined condition is met (ST229, YES), it generates a third command to control the AMR 421 and outputs the third command. For example, when the RPT 422 completes the release of the items contained in the roll pallet, the processor 51 determines that condition C29 is met (item release complete). Output IF 522 outputs the third command from the processor 51 to the AMR control device 321 (ST230).

[0119] The AMR control device 321 receives a third command and outputs a third control signal based on the third command to the AMR421. The AMR421 then performs a fourth operation based on the third control signal.

[0120] Next, I will explain how the LPT422 works. For example, LPT422 accepts the roll pallet being transported by AMR421 and enters a state of acceptance completion. After transporting the roll pallet, AMR421 moves to a retraction area and enters a retraction state. The automatic IF device 5 recognizes these states based on image analysis and sends a second command to the LPT control device 322.

[0121] The LPT control device 322 transmits a second control signal to control the LPT 422 based on the second command. The LPT 422, in the acceptance complete state, receives the second control signal (ST231, YES) and performs the fifth operation based on the received second control signal (ST232). Alternatively, the LPT control device 322, which is a switch BOT, turns on the switch of the LPT 422 based on the second command (ST231, YES). The LPT 422 performs the fifth operation based on the switch being turned on (ST232). That is, the LPT 422 tilts the roll pallet and releases the items stored in the roll pallet onto a conveyor or the like based on the second control signal or the switch being turned on (ST232). The LPT 422 completes the release and returns to the retracted state (ST233).

[0122] The automatic IF device 5 recognizes this retracted state based on image analysis and sends a third command to the AMR control device 321. The AMR control device 321 sends a third control signal to control the AMR 421 based on the third command. The AMR 421 performs a fourth operation to retrieve the roll pallet from the LPT 422 based on the third control signal.

[0123] Figure 8 is a diagram illustrating an example of AMR state recognition according to the second embodiment. Specifically, it is a diagram illustrating conditions C21, C22, and C23 in ST223 shown in Figure 7. Here, the processor 51 determines that the AMR421 has reached the second region and stopped if conditions C21, C22, and C23 are met.

[0124] Condition C21 is the shape recognition of AMR421. The processor 51 detects a segmentation (SG21) that resembles AMR421 in the image and determines whether the similarity between the shape of the segmentation (SG21) and the shape of the AMR421 template (original) exceeds a threshold. The processor 51 determines that condition C21 is satisfied if the similarity exceeds the threshold.

[0125] In addition to the shape recognition of AMR421, AMR identification information recognition may be used, or alternatively, AMR identification information recognition may be used instead of the shape recognition of AMR421. All AMRs are provided with AMR identification information in the form of a combination of characters, numbers, symbols, etc., or AMR identification information in the form of a barcode or two-dimensional code. The processor 51 recognizes the AMR identification information included in the captured image from the camera 6, compares the recognized AMR identification information with the registered AMR identification information stored in the memory 53, and when they match, determines that condition C21 is satisfied and recognizes that it is a predetermined AMR421.

[0126] Condition C22 is the recognition of the change in the operating speed of AMR421 from entry to stop. The processor 51 detects the characteristics of the change in the operating speed. For example, the processor 51 detects the speed (V1(t = 0)) when entering the region of segmentation (SG21), and the speeds (V1(t)) and (V1(T1)=0) after entering the region of segmentation (SG21). Here, T1 is the time from when entering the region of segmentation (SG21) to stopping.

[0127] The processor 51 recognizes AMR421 based on the characteristics of the change in the operating speed. For example, when the change in the operating speed meets the standard, the processor 51 recognizes this change in the operating speed as the change in the operating speed of AMR421 and determines that condition C22 is satisfied based on this recognition. For example, the processor 51 determines that condition C22 is satisfied if v1 < V1(0) < v2 and t1 < T1 < t2 are satisfied based on the reference values v1, v2, t1, and t2.

[0128] Condition C23 is the recognition of the stop position of AMR421. The processor 51 recognizes the stop of AMR421 based on the positional relationship between the reference point of the stop region and the reference point of AMR421. For example, the processor 51 detects the position information (P1) of the segmentation corresponding to the second region (stop region), detects the position information (P2) of the segmentation (SG21) that seems to be AMR421, and detects the deviation (relative position) between P1 and P2 that serves as the reference point.

[0129] The processor 51 determines whether the distance between the centroid positions of the reference points P1 and P2 is within a certain expected value, i.e., within the range of the lower and upper limits. If the distance between the centroid positions is within the range of the lower and upper limits, the processor 51 recognizes that the AMR421 has stopped, and based on this recognition, determines that condition C23 is satisfied.

[0130] Figure 9 shows an example of RPT state recognition (ready to accept) according to the second embodiment. That is, it is a diagram for explaining condition C24 in ST223 shown in Figure 7. The processor 51 determines whether condition C24 is met. Condition C24 is the state recognition of RPT422. Memory 53 stores a template of the initial state (no roll palette) in which RPT422 has not accepted the roll palette. The processor 51 detects a segmentation (SG22) that resembles RPT422 in the image and determines whether the similarity between the shape of the segmentation (SG22) and the shape of the initial state template exceeds a threshold. If the similarity exceeds the threshold, the processor 51 determines that condition C24 is met. In other words, the processor 51 determines that RPT422 is in an initial state where it has not accepted the roll palette, and determines that RPT422 is ready to accept the roll palette.

[0131] Figure 10 shows an example of RPT state recognition (acceptance complete) according to the second embodiment. Specifically, we will explain condition C25 in ST226 shown in Figure 7. The processor 51 determines whether condition C25 is met. Condition C25 is the state recognition of RPT422. Memory 53 stores a template of the acceptance complete state in which RPT422 has accepted the roll palette. The processor 51 detects a segmentation (SG22) that appears to be RPT422 in the image and determines whether the similarity between the shape of the segmentation (SG22) and the shape of the acceptance complete state template exceeds a threshold. If the similarity exceeds the threshold, the processor 51 determines that condition C25 is met. In other words, the processor 51 determines that the acceptance of the roll palette has been completed in RPT422.

[0132] Figure 11 is a diagram illustrating an example of AMR state recognition (evacuation complete) according to the second embodiment. Specifically, it is a diagram for explaining the conditions C26, C27, and C28 of ST226 shown in Figure 7. Here, the processor 51 determines that the AMR421 has arrived in the evacuation area and that the evacuation is complete if conditions C26, C27, and C28 are met.

[0133] Condition C26 is the shape recognition of AMR421. The processor 51 detects a segmentation (SG21) that resembles AMR421 in the image and determines whether the similarity between the shape of the segmentation (SG21) and the shape of the AMR421 template (original) exceeds a threshold. The processor 51 determines that condition C26 is satisfied if the similarity exceeds the threshold.

[0134] Condition C27 is the recognition of changes in the operating speed of the AMR421 from entry to stopping. The processor 51 detects the characteristics of the changes in operating speed. For example, the processor 51 detects the speed (V1(t=0)) when entering the segmentation (SG21) region, and the speed (V1(t)) and (V1(T1)=0) after entering the segmentation (SG21) region. Note that T1 is the time from entry into the segmentation (SG21) region to stopping.

[0135] The processor 51 recognizes the AMR421 based on the characteristics of the change in the operating speed. For example, when the change in the operating speed meets the standard, the processor 51 recognizes this change in the operating speed as the change in the operating speed of the AMR421, and determines that the condition C27 is met based on this recognition. For example, the processor 51 determines that the condition C27 is met if v1 < V1(0) < v2 and t1 < T1 < t2 are satisfied based on the reference values v1, v2, t1, and t2.

[0136] The condition C28 is the recognition of the stop position of the AMR421. The processor 51 recognizes the stop of the AMR421 based on the positional relationship between the reference point of the stop area and the reference point of the AMR421. For example, the processor 51 detects the position information (P1) of the segmentation corresponding to the evacuation area, detects the position information (P2) of the segmentation (SG21) that looks like the AMR421, and detects the deviation (relative position) between P1 and P2 that serves as the reference point.

[0137] The processor 51 determines whether the distance of the center-of-gravity position between P1 and P2 serving as the reference point is within the expected fixed value, that is, within the range of the lower limit and the upper limit. When the distance of the center-of-gravity position is within the range of the lower limit and the upper limit, the processor 51 recognizes that the AMR421 has stopped, and determines that the condition C28 is met based on this recognition.

[0138] FIG. 12 is a diagram showing an example of the state recognition (completion of article release) of the RPT according to the second embodiment. That is, it is a diagram for explaining the condition C29 of ST_{229} shown in FIG. 7. The processor 51 determines whether condition C29 is met. Condition C29 is the state recognition of the RPT422. Memory 53 stores a template of the state in which the RPT422 has finished releasing items from the roll pallet (the state in which it has accepted an empty roll pallet). After outputting the second command to the RPT control device 322 (ST227), the processor 51 detects segmentation (SG22) that resembles the RPT422 in the image for a certain period of time, and determines whether the similarity between the shape of the segmentation (SG22) and the shape of the template for the state in which the RPT422 has finished releasing items from the roll pallet exceeds a threshold. The processor 51 determines that condition C29 is met if the similarity exceeds the threshold, provided that it is within a certain period of time after outputting the second command to the RPT control device 322. In other words, the processor 51 determines that the RPT422 has finished releasing items from the roll pallet.

[0139] As described above, the automatic IF device 5 of the second embodiment takes images captured by the camera 6 as input and outputs signals such as API commands for controlling each device, such as the AMR421 and RPT422. The automatic IF device 5 analyzes the input images, recognizes the state (state transition) of each device based on the analysis results, and outputs signals such as API commands for controlling a predetermined device based on the recognition results.

[0140] If each control device, such as the AMR control device 321 and the RPT control device 322, which control each device, is equipped with an API, then modification of the IF of each control device becomes unnecessary. Thus, according to the second embodiment, when coordinating the operation of each device, the burden of coordination can be reduced. Furthermore, by making the automatic IF device 5 independent from WES2, even if a system failure occurs in WES2, each device can be operated in coordination.

[0141] <Third Embodiment> The third embodiment will now be described with reference to the drawings. Components that use the same reference numerals as those used in the first embodiment are substantially the same as those in the first embodiment, and their descriptions will be omitted as appropriate.

[0142] [composition] Figure 13 is a conceptual diagram showing an example of a warehouse system according to the third embodiment. In the third embodiment, the automatic IF device 5 receives an image from the camera 6, analyzes the image, performs a recognition process to recognize the state of the transported object based on the image analysis results, and outputs a signal to control the first device that transports the transported object based on the recognition process.

[0143] For example, the automatic IF device 5 performs a first recognition process to recognize the state of the conveyed object being transported on the conveyor 432 based on the image analysis results, and outputs a first signal to control the CTU 431 based on the first recognition result.

[0144] The automatic IF device 5 can coordinate the conveying by the conveyor 432 and the CTU 431 by outputting a first signal.

[0145] As shown in Figure 13, the item processing system S includes WMS1, WES2, CTU control device 331, conveyor control device 332, CTU (hardware / firmware) 431, conveyor 432, automatic IF device 5, and camera 6.

[0146] The CTU control unit 331 can be composed of one or more general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the CTU control unit 331 includes an IF 3311, which receives a first signal output from the automatic IF device 5. For example, the first signal is a first command, and the first command is an API command. Also, the IF 3311 is an API. Based on the received first command, the CTU control unit 331 outputs a first control signal to control the CTU 431.

[0147] The conveyor control device 332 can be composed of one or more dedicated devices, PLCs, or general-purpose computers, i.e., an IF, processor, and memory. The processor can be a CPU, MPU, or DSP. For example, the conveyor control device 332 receives a second signal output from the automatic IF device 5 and outputs a second control signal to control the conveyor 432 based on the second signal. Alternatively, the conveyor control device 332 may not receive an output from the automatic IF device 5.

[0148] The CTU431 is equipped with a vertically moving fork mechanism. Based on a first control signal from the CTU control device 331, the CTU431 performs a first operation. For example, as a first operation, the CTU431 travels toward the conveyor 432, stops in the area opposite the end of the conveyor 432, adjusts the height of the fork mechanism to match the height of the conveyor 432, receives the conveyed object that has stopped at the end of the conveyor 432 with the fork mechanism, and transports the received object to a predetermined area.

[0149] The conveyor 432 transports the object set at the transport start position toward the end based on a control signal from the conveyor control device 332. The conveyor 432 is equipped with multiple sensors along the transport path to detect the transported object. Based on the detection results of the transported object, the conveyor 432 starts or stops the transport of the object. The transported object is an article.

[0150] [Operation] Figure 14 is a flowchart showing an example of the operation of a warehouse system according to the third embodiment. ST311 to ST315 show an example of the operation of conveyor 432, ST321 to ST326 show an example of the operation of automatic IF device 5, and ST331 to ST333 show an example of the operation of CTU 431.

[0151] First, let's explain the operation of conveyor 432. Based on a control signal from the conveyor control device 332, the conveyor 432 transports the item set at the transport start position toward the end (ST311). Based on a signal from a sensor, the conveyor 432 detects the item being transported. When the conveyor 432 detects an item approaching the end (ST312, YES), it stops transporting the item (ST313). The item is then located at the end.

[0152] The conveyor 432 detects the item located at the end based on the signal from the sensor. When the conveyor 432 detects the movement (carrying) of the item at the end (ST314, YES), it sets the next item to the transport start position (ST315).

[0153] Next, we will explain the operation of the automatic IF device 5. Input IF521 of the automatic IF device 5 receives the image from camera 6 (ST321).

[0154] Processor 51 receives an image from input IF521, analyzes the image, and outputs the analysis results.

[0155] The processor 51 performs a first recognition process (ST322) to recognize the state (presence or absence) of the items on the conveyor 432 based on the analysis results and dictionary data.

[0156] The processor 51 determines whether the result of the first recognition process satisfies predetermined conditions (ST323). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0157] For example, if there is only one predetermined condition, the processor 51 determines whether the condition C31 for recognition of the item is met. If there are two predetermined conditions, in addition to condition C31, the processor 51 determines whether the change in the operating speed of the item satisfies condition C32. Alternatively, in addition to condition C31, the processor 51 determines whether the stopping area of ​​the item satisfies condition C33. If there are three predetermined conditions, the processor 51 determines whether conditions C31, C32, and C33 are met.

[0158] If the processor 51 determines that predetermined conditions are met (ST323, YES), it generates a first command to control the CTU 431 and outputs the first command. For example, if an item decelerates at a predetermined speed change and stops in the stopping area, the processor 51 determines that conditions C31, C32, and C33 are met. Output IF522 outputs the first command from the processor 51 to the CTU control device 331 (ST324).

[0159] The CTU control device 331 receives a first command and outputs a first control signal based on the first command to the CTU 431. The CTU 431 performs a first operation based on the first control signal.

[0160] Furthermore, the processor 51 performs a second recognition process to recognize the state of the items on the conveyor 432 based on the analysis results and dictionary data (ST325). For example, when an item that has stopped in the stopping area is carried by the CTU 431, the processor 51 determines that a predetermined condition is met (ST326, YES) and performs the first recognition process again (ST322).

[0161] Next, I will explain how the CTU431 works. The automatic IF device 5 sends a command to the CTU control device 331 based on the image recognition result from the camera 6. The CTU control device 331 sends a control signal to control the CTU 431 based on the command. The CTU 431 operates based on the control signal.

[0162] For example, when the CTU 431 is retracting, it receives a first control signal from the CTU control device 331 (ST331, YES), and based on the first control signal, it moves toward the conveyor 432, stops in the area opposite the end of the conveyor 432, adjusts the height of the fork mechanism to match the height of the conveyor 432, and receives the item that has stopped at the end of the conveyor 432 with the fork mechanism (ST332). The CTU 431 then transports the received item to a predetermined area (ST333).

[0163] Figure 15 is a diagram illustrating an example of article state recognition according to the third embodiment. That is, it is a diagram illustrating the ST323 shown in Figure 14. Here, the processor 51 determines that the article has arrived at the stopping area and stopped if conditions C31, C32, and C33 are met.

[0164] Condition C31 is the recognition of the shape of an object. The processor 51 detects object-like segmentation (SG3) in the image and determines whether the similarity between the shape of the segmentation (SG3) and the shape of the object template (original) exceeds a threshold. The processor 51 determines that condition C31 is satisfied if the similarity exceeds the threshold.

[0165] Furthermore, in addition to object shape recognition, object identification information recognition may be used, or object identification information recognition may be used instead of object shape recognition. All objects are assigned object identification information consisting of a combination of letters, numbers, and symbols, or object identification information consisting of a barcode or two-dimensional code. The processor 51 recognizes the object identification information contained in the image captured from the camera 6, compares the registered object identification information stored in the memory 53 with the recognized object identification information, and if they match, determines that condition C31 is satisfied and recognizes that it is a specified object.

[0166] Condition C32 is the recognition of the change in the operating speed of an article from entry to stop. The processor 51 detects the characteristics of the change in the operating speed. For example, the processor 51 detects the speed (V1(t = 0)) at the time of entry into the region of segmentation (SG3), and the speeds (V1(t)) and (V1(T1) = 0) after entry into the region of segmentation (SG3). Here, T1 is the time from the entry into the region of segmentation (SG3) to the stop.

[0167] Based on the characteristics of the change in the operating speed, the processor 51 recognizes the article. For example, when the change in the operating speed meets the standard, the processor 51 recognizes this change in the operating speed as the change in the operating speed of the article, and determines that condition C32 is satisfied based on this recognition. For example, based on the reference values v1, v2, t1, t2, if v1 < V1(0) < v2 and t1 < T1 < t2 are satisfied, the processor 51 determines that condition C32 is satisfied.

[0168] Condition C33 is the recognition of the stop position of the article. The processor 51 recognizes the stop of the article based on the positional relationship between the reference point of the stop region and the reference point of the article. For example, the processor 51 detects the position information (P1) of the segmentation corresponding to the stop region, detects the position information (P2) of the segmentation (SG3) that seems to be the article, and detects the deviation (relative position) between P1 and P2 that is the reference point.

[0169] The processor 51 determines whether the distance of the center-of-gravity position between P1 and P2 that is the reference point is within the expected fixed value, that is, within the range of the lower limit and the upper limit. When the distance of the center-of-gravity position is within the range of the lower limit and the upper limit, the processor 51 recognizes that it is the stop of the article, and determines that condition C33 is satisfied based on this recognition.

[0170] FIG. 16 is a diagram showing an example of the shape recognition of an article according to the third embodiment. Memory 53 registers (stores) images of all items or templates (originals) of specified items. Processor 51 compares the image of the detected segmentation (SG3) with the registered template image. If the similarity between the image of the detected segmentation (SG3) and the image of the item template exceeds a threshold, Processor 51 recognizes the detected segmentation (SG3) as an item. If the similarity between the image of the detected segmentation (SG3) and the image of the item template does not exceed a threshold, Processor 51 recognizes the detected segmentation (SG3) as not being an item.

[0171] As described above, the automatic IF device 5 of the third embodiment takes images captured by the camera 6 as input and outputs signals such as API commands for controlling devices such as the CTU431. The automatic IF device 5 analyzes the input images, recognizes the state (state transition) of the transported object based on the analysis results, and outputs signals such as API commands for controlling devices such as the CTU431 based on the recognition results. If devices such as the CTU431 have an API, modification of the device's IF is unnecessary. In this way, the third embodiment can reduce the burden of device coordination. Furthermore, by making the automatic IF device 5 independent from WES2, the operation of each device can continue even if a WES2 system failure occurs.

[0172] <Fourth Embodiment> The fourth embodiment will now be described with reference to the drawings. Components that use the same reference numerals as those used in the first embodiment are substantially the same as those in the first embodiment, and their descriptions will be omitted as appropriate.

[0173] [composition] Figure 17 is a conceptual diagram showing an example of a warehouse system according to the fourth embodiment. In the fourth embodiment, the automatic IF device 5 receives an image from the camera 6, analyzes the image, performs a recognition process to recognize the state of at least one of the first and second devices that process the conveyed object based on the image analysis results, and outputs a signal to control at least one of the first and second devices based on the recognition process. By outputting a signal, the automatic IF device 5 can coordinate the operation of an AGV 441, which is an example of the first device, and an EV (elevator) 442, which is a series of the second devices.

[0174] As shown in Figure 17, the item handling system S comprises WMS1, WES2, AGV control device 341, EV control device 342, AGV (hardware / firmware) 441, EV442, automatic IF device 5, and camera 6. Camera 6 is installed on each floor and inside EV442, and photographs the entrances and exits to EV442 on each floor, as well as the interior of EV442.

[0175] The AGV control device 341 can be configured with one or more general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the AGV control device 341 includes an IF 3411, which receives signals (e.g., API commands) output from the automatic IF device 5 and outputs control signals to control the AGV 441 based on the received commands.

[0176] The EV control device 342 can be composed of one or more dedicated devices, PLCs, or general-purpose computers, i.e., an IF, a processor, and memory. The processor is a CPU, MPU, or DSP, etc. For example, the EV control device 342 includes an IF 3421, which receives signals (e.g., API commands) output from the automatic IF device 5 and outputs control signals to control the EV 442.

[0177] [Operation] Figure 18 is a flowchart showing an example of the operation of the warehouse system according to the fourth embodiment. ST411 to ST416 show an example of the operation of AGV441, ST421 to ST430 show an example of the operation of automatic IF device 5, and ST431 to ST436 show an example of the operation of EV442.

[0178] First, let's explain how the AGV441 works. AGV441 starts operation based on a control signal from AGV control device 341 (ST411), moves to the first area which is the target area, and stops (ST412). For example, the first area is directly in front of the entrance / exit of EV442.

[0179] Furthermore, AGV441 receives a second control signal in response to the second command (ST413, YES), moves to the second area which is the target area, and stops (ST414). For example, the second area is a predetermined area within EV442, and AGV441 enters EV442 and stops based on the second control signal.

[0180] Furthermore, AGV441 receives a second control signal in response to the second command (ST415, YES), moves to the third area which is the target area, and stops (ST416). For example, the third area is a predetermined area outside EV442, and AGV441 exits EV442 and stops based on the second control signal.

[0181] Next, we will explain the operation of the automatic IF device 5. Input IF521 of the automatic IF device 5 receives the image from camera 6 (ST421).

[0182] The processor 51 receives an image from the input IF 521, analyzes the image, and outputs the analysis result. Based on the analysis result and dictionary data, the processor 51 performs a first recognition process to recognize the state of the AGV 441 (ST422).

[0183] The processor 51 determines whether the result of the first recognition process satisfies predetermined conditions (ST423). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0184] If the processor 51 determines that a predetermined condition is met (ST423, YES), it generates a first command to control the EV442 and a second command to control the AGV441, and outputs the first and second commands. For example, if the AGV441 decelerates at a predetermined speed change and stops in the first area, the processor 51 determines that a predetermined condition is met. Output IF522 outputs the first command from the processor 51 to the EV control device 342 and the second command to the AGV control device 341 (ST424).

[0185] Furthermore, the processor 51 recognizes the AGV 441 that has stopped in the first area based on the AGV travel plan stored in the memory 53. For example, the processor 51 recognizes the destination floor of the AGV 441 that has stopped in the first area based on the agreement between predetermined AGV identification information included in the AGV travel plan and the AGV identification information read from the image analysis results, and the destination (target floor) included in the AGV travel plan, and generates a third command.

[0186] The EV control device 342 receives a first command and outputs a first control signal based on the first command to the EV442. The EV442 performs a first operation based on the first control signal and opens the door.

[0187] The AGV control device 341 receives the second command and outputs a second control signal to the AGV 441 based on the second command. The AGV 441 performs the second operation based on the second control signal, enters the EV 442, and stops.

[0188] Furthermore, the processor 51 performs a second recognition process (ST425) to recognize the state of the AGV 441 based on the analysis results and dictionary data. The processor 51 determines whether the result of the second recognition process satisfies predetermined conditions (ST426). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0189] If the processor 51 determines that a predetermined condition is met (ST426, YES), it outputs a third command. For example, if the AGV 441 decelerates at a predetermined speed change and stops in the second area, the processor 51 determines that a predetermined condition is met. Output IF 522 outputs the third command from the processor 51 to the EV control device 342 (ST427).

[0190] The EV control device 342 receives a third command and outputs a third control signal based on the third command to the EV442. Based on the third control signal, the EV442 performs a third action, closing the doors, moving to the destination floor, stopping at the destination floor, and opening the doors.

[0191] Furthermore, the processor 51 performs a fourth recognition process (ST428) to recognize the state of the AGV 441 based on the analysis results and dictionary data. The processor 51 determines whether the result of the fourth recognition process satisfies predetermined conditions (ST429). The predetermined conditions can be one or more, and whether there is one or more predetermined conditions is determined according to the needs of the warehouse system.

[0192] If the processor 51 determines that a predetermined condition is met (ST429, YES), it generates a fourth command to control the AGV 441 and a fifth command to control the EV 432, and outputs the fourth and fifth commands. For example, if the AGV 441 is stopped in the second area and the door of the EV 432 is open, the processor 51 determines that the predetermined condition is met. Output IF522 outputs the fourth command from the processor 51 to the AGV control device 341 and the fifth command from the processor 51 to the EV control device 342 (ST430).

[0193] The AGV control device 341 receives the fourth command and outputs a fourth control signal based on the fourth command to the AGV 441. The AGV 441 performs the fourth operation based on the fourth control signal, exits the EV 442, and stops.

[0194] The EV control device 342 receives the fifth command and outputs a fifth control signal based on the fifth command to the EV442. The EV442 performs the fifth operation based on the fifth control signal and closes the door.

[0195] Next, I will explain how the EV442 works. For example, a stationary EV442 receives a first control signal from the EV control device 342 (ST431, YES), and based on the first control signal, performs a first operation and opens the door (ST432).

[0196] After opening the door, AGV441 performs a second action based on the second control signal, enters EV442, and stops.

[0197] Next, EV442 receives a third control signal from EV control device 342 (ST433, YES), and based on the third control signal, performs a third action: closes the doors, moves to the destination floor, stops at the destination floor, and opens the doors (ST434).

[0198] After opening the door, AGV441 performs a fourth action based on the fourth control signal, exits EV442, and stops.

[0199] Next, EV442 receives a fifth control signal from EV control device 342 (ST435, YES), and based on the fifth control signal, performs a fifth operation and closes the door (ST436).

[0200] Figure 19 is a diagram illustrating an example of AGV state recognition according to the fourth embodiment. In other words, it is a diagram illustrating the ST422 and other components shown in Figure 18. Here, the processor 51 determines that the AGV has arrived at the stop area and stopped if conditions C41, C42, and C43 are met.

[0201] Condition C41 is the shape recognition of the AGV. The processor 51 detects a segmentation (SG4) that seems to be the AGV441 included in the image, and determines whether the similarity between the shape of the segmentation (SG4) and the shape of the template (original) of the AGV441 exceeds a threshold value. When the similarity exceeds the threshold value, the processor 51 determines that condition C41 is satisfied.

[0202] In addition to the shape recognition of the AGV441, AGV identification information recognition may be used, or alternatively, AGV identification information recognition may be used instead of the shape recognition of the AGV441. All AGV441s are given AGV identification information in the form of a combination of characters, numbers, symbols, etc., or AGV identification information in the form of a barcode or two-dimensional code. The processor 51 recognizes the AGV identification information included in the captured image from the camera 6, collates the registered AGV identification information stored in the memory 53 with the recognized AGV identification information, and when they match, determines that condition C41 is satisfied and recognizes that it is a predetermined AGV441.

[0203] Condition C42 is the recognition of the change in the operating speed of the AGV441 from entry to stop. The processor 51 detects the characteristics of the change in the operating speed. For example, the processor 51 detects the speed (V1(t = 0)) when entering the area of the segmentation (SG4), and the speeds (V1(t)) and (V1(T1)=0) after entering the area of the segmentation (SG4). Here, T1 is the time from when entering the area of the segmentation (SG4) to stopping.

[0204] The processor 51 recognizes the AGV441 based on the characteristics of the change in the operating speed. For example, when the change in the operating speed meets the standard, the processor 51 recognizes this change in the operating speed as the change in the operating speed of the AGV441, and based on this recognition, determines that condition C42 is satisfied. For example, based on the reference values v1, v2, t1, t2, if v1 < V1(0) < v2 and t1 < T1 < t2 are satisfied, the processor 51 determines that condition C42 is satisfied.

[0205] Condition C43 is the recognition of the stopping position of AGV441. The processor 51 recognizes the stopping of AGV441 based on the positional relationship between the reference point of the stopping area and the reference point of AGV441. For example, the processor 51 detects the position information (P1) of the segmentation corresponding to the stopping area, detects the position information (P2) of a segmentation (SG4) that resembles AGV441, and detects the deviation (relative position) between the reference points P1 and P2.

[0206] The processor 51 determines whether the distance between the centroid positions of the reference points P1 and P2 is within a certain expected value, i.e., within the range of the lower and upper limits. If the distance between the centroid positions is within the range of the lower and upper limits, the processor 51 recognizes that the AGV 441 has stopped, and based on this recognition, determines that condition C43 is satisfied.

[0207] As described above, the automatic IF device 5 of the fourth embodiment takes images captured by the camera 6 as input and outputs signals such as API commands for controlling devices such as the AGV 441 and EV 442. The automatic IF device 5 analyzes the input images, recognizes the state (state transition) of the AGV 441 based on the analysis results, and outputs signals such as API commands for controlling devices such as the AGV 441 and EV 442 based on the recognition results. If devices such as the AGV control device 341 and EV control device 342 are equipped with APIs, modification of the device's IF is unnecessary. In this way, the fourth embodiment can reduce the burden of device coordination. Furthermore, by separating the automatic IF device 5 from WES2, the operation of each device can continue even if a WES2 system failure occurs.

[0208] The program according to this embodiment may be transferred while stored in an electronic device such as an automatic IF device 5, or it may be transferred without being stored in an electronic device. In the latter case, the program may be transferred via a network, or it may be transferred while stored in a storage medium. The storage medium is a non-temporary tangible medium. The storage medium is a computer-readable medium. The storage medium can be any medium that is capable of storing a program and can be read by a computer, such as an optical disc or memory card, and its form is not limited. The electronic device downloads the program transferred (provided) via a network and installs it into memory, or reads the program from the storage medium and installs it into memory.

[0209] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents. The invention described in the original claims of this application is listed below. [Note 1] Input the image obtained by taking a picture with a camera. Based on the analysis results of the aforementioned image, a recognition process is performed to recognize the state of at least one of the first and second devices that process the conveyed object, or the state of the conveyed object. An input / output method that outputs a signal for controlling the first or second device based on the recognition process. [Note 2] The input / output method of Appendix 1, which performs a first recognition process to recognize the state of the first device based on the results of the analysis of the aforementioned image, and outputs a first signal for controlling the second device based on the first recognition process. [Note 3] The input / output method of Appendix 2, which performs a second recognition process to recognize the state of the second device based on the analysis results of the aforementioned image, and outputs a second signal for controlling the first device based on the second recognition process. [Note 4] The first device performs a first operation of transporting the object from a first area to a second area, and a second operation of moving from the second area to the first area. The second device performs a third operation, which is to transport the object from the second area to the third area. The input / output method of Appendix 3, wherein the first signal is a command to cause the second device to perform the third operation. [Note 5] The input / output method of Appendix 4, wherein the second signal is a command to cause the first device to perform the second operation. [Note 6] The input / output method described in Appendix 2 includes recognizing a change in the speed of the first device that transports the transported object. [Note 7] The input / output method of Appendix 6, wherein the first recognition process includes recognizing the first device based on the characteristics of the speed change. [Note 8] The input / output method of Appendix 2, wherein the first recognition process includes recognizing the cessation of the first device that transports the transported object. [Note 9] The input / output method of Appendix 8, wherein the first recognition process includes recognizing the first device based on the positional relationship between the reference point of the stopping area and the reference point of the first device. [Note 10] The input / output method of Appendix 1, which performs a first recognition process to recognize the state of the first and second devices based on the results of the analysis of the aforementioned image, and outputs a first signal for controlling the first device based on the first recognition process. [Note 11] The input / output method of Appendix 10, which performs a second recognition process to recognize the state of the first and second devices based on the results of the analysis of the aforementioned image, and outputs a second signal for controlling the second device based on the second recognition process. [Note 12] The input / output method of Appendix 11, which performs a third recognition process to recognize the state of the second device based on the analysis results of the aforementioned image, and outputs a third signal for controlling the first device based on the third recognition process. [Note 13] The aforementioned transported object is equipment for storing articles, The first device performs a first operation to transport the equipment from the first area to the second area, a second operation to set the equipment in the second device, a third operation to withdraw from the second device, and a fourth operation to retrieve the equipment set in the second device. The second device, after receiving the equipment set by the first device, performs a fifth operation to release the article from the equipment to a predetermined position. The first recognition process includes recognizing the completion of the transport of the equipment to the second area by the first device, and recognizing the completion of the preparation for receiving the equipment by the second device. The input / output method of Appendix 12, wherein the first signal is a signal that causes the first device to perform the second operation. [Note 14] The second recognition process includes recognizing the completion of the acceptance of the equipment by the second device and recognizing the completion of the retraction of the first device. This includes, The input / output method of Appendix 13, wherein the second signal is a signal that causes the second device to perform the fifth operation. [Note 15] The third recognition process includes recognizing the completion of the release of the article, The input / output method of Appendix 14, wherein the third signal is a signal that causes the first device to perform the fourth operation. [Note 16] The input / output method of Appendix 1, wherein a first recognition process is performed to recognize the state of the transported object based on the results of the analysis of the aforementioned image, and a first signal is output for controlling the first device based on the first recognition process, the first signal being a signal that causes the first device to receive and transport the transported object. [Note 17] On the computer, The procedure for inputting images obtained by taking pictures with a camera, A procedure for performing a recognition process to recognize the state of at least one of the first and second devices that process the conveyed object, or the state of the conveyed object, based on the results of the analysis of the aforementioned image, An input / output program for performing a procedure to output a signal for controlling the first or second device based on the aforementioned recognition process. [Note 18] An input interface for inputting images obtained from camera shooting, A processor that performs recognition processing to recognize the state of at least one of the first and second devices that process the conveyed object, or the state of the conveyed object, based on the results of the analysis of the aforementioned image, Based on the recognition process, an output interface outputs a signal for controlling the first or second device, An input / output device equipped with the following features. [Explanation of symbols]

[0210] S... Material handling system 1…WMS 2…WES 311…AMR-A control unit 312…AMR-B control unit 313... Conveyor control device 321...AMR control device 322...RPT control device 331...CTU Control Unit 332... Conveyor control device 341...AGV control device 342…EV control device 411…AMR-A 412…AMR-B 413... Pallet conveyor 421…AMR 422...RPT 431…CTU 432... Conveyor 441…AGV 442…EV 5…Automatic IF device 51… Processor 511...Input section 512...Image Analysis Department 513...Recognition section 514...Generation section 515...Output section 521... Input IF 522…Output IF 53…Memory 6... Camera

Claims

1. Input the image obtained by taking a picture with a camera. Based on the analysis results of the aforementioned image, a recognition process is performed to recognize the state of at least one of the first and second devices that process the conveyed object, or the state of the conveyed object. An input / output method that outputs a signal for controlling the first or second device based on the recognition process, Based on the analysis results of the aforementioned image, a first recognition process is performed to recognize the state of the first device, and based on the first recognition process, a first signal is output for controlling the second device. The first recognition process includes an input / output method that recognizes a change in the speed of the first device that transports the transported object.

2. The input / output method according to claim 1, comprising: performing a second recognition process to recognize the state of the second device based on the results of the analysis of the aforementioned image; and outputting a second signal for controlling the first device based on the second recognition process.

3. The first device performs a first operation of transporting the object from a first area to a second area, and a second operation of moving from the second area to the first area. The second device performs a third operation of transporting the transported object from the second area to the third area. The input / output method according to claim 2, wherein the first signal is a command to cause the second device to perform the third operation.

4. The input / output method according to claim 3, wherein the second signal is a command to cause the first device to perform the second operation.

5. The input / output method of claim 1, wherein the first recognition process includes recognizing the first device based on the characteristics of the speed change.

6. The input / output method of claim 1, wherein the first recognition process includes recognizing the cessation of the first device that transports the transported object.

7. The input / output method of claim 6, wherein the first recognition process includes recognizing the first device based on the positional relationship between a reference point in the stopping area and a reference point in the first device.

8. The input / output method according to claim 1, comprising: performing a first recognition process to recognize the state of the first and second devices based on the results of the analysis of the aforementioned image; and outputting a first signal for controlling the first device based on the first recognition process.

9. The input / output method of claim 8, comprising: performing a second recognition process to recognize the state of the first and second devices based on the results of the analysis of the aforementioned image; and outputting a second signal for controlling the second device based on the second recognition process.

10. The input / output method of claim 9, comprising: performing a third recognition process to recognize the state of the second device based on the results of the analysis of the aforementioned image; and outputting a third signal for controlling the first device based on the third recognition process.

11. The aforementioned transported object is equipment for storing articles, The first device performs a first operation of transporting the equipment from the first area to the second area, a second operation of setting the equipment into the second device, a third operation of withdrawing from the second device, and a fourth operation of retrieving the equipment set in the second device. The second device, after receiving the equipment set by the first device, performs a fifth operation to release the article from the equipment to a predetermined position. The first recognition process includes recognizing the completion of the transport of the equipment to the second area by the first device, and recognizing the completion of the preparation for receiving the equipment by the second device. The input / output method of claim 10, wherein the first signal is a signal that causes the first device to perform the second operation.

12. The second recognition process includes recognizing the completion of the acceptance of the equipment by the second device and recognizing the completion of the retraction of the first device. The input / output method of claim 11, wherein the second signal is a signal that causes the second device to perform the fifth operation.

13. The third recognition process includes recognizing the completion of the release of the article, The input / output method of claim 12, wherein the third signal is a signal that causes the first device to perform the fourth operation.

14. Based on the analysis results of the aforementioned image, a first recognition process is performed to recognize the state of the conveyed object, and based on the first recognition process, a first signal is output for controlling the first device. The input / output method according to claim 1, wherein the first signal is a signal that causes the first device to receive and transport the transported object.

15. On the computer, The procedure for inputting images obtained by taking pictures with a camera, A procedure for performing a recognition process to recognize the state of at least one of the first and second devices that process the conveyed object, or the state of the conveyed object, based on the results of the analysis of the aforementioned image, An input / output program for performing a procedure to output a signal for controlling the first or second device based on the recognition process, The procedure for performing the recognition process includes a procedure for performing a first recognition process that recognizes the state of the first device based on the results of the image analysis, The procedure for outputting the aforementioned signal includes a procedure for outputting a first signal for controlling the second device based on the first recognition process, The first recognition process includes an input / output program that recognizes a change in the speed of the first device that transports the transported object.

16. An input interface for inputting images obtained from camera shooting, A processor that performs recognition processing to recognize the state of at least one of the first and second devices that process the conveyed object, or the state of the conveyed object, based on the analysis results of the aforementioned image, Based on the recognition process, an output interface outputs a signal for controlling the first or second device, Equipped with, The processor performs a first recognition process to recognize the state of the first device based on the results of the image analysis. The output interface outputs a first signal for controlling the second device based on the first recognition process. The input / output device includes the recognition of a change in speed of the first device that transports the transported object.

Images