Method and system for controlling a handling machine and non-volatile computer readable recording medium

Abstract

A method and a system for controlling a handling machine and a non-volatile computer readable recording medium are provided. The method includes: analyzing image data to obtain contour surface data corresponding to a target object from the image data; analyzing the contour surface data to obtain characteristic data which reflects a posture of the target object in a physical space; generating control data according to the characteristic data, wherein the control data is suitable for controlling the handling machine to transport the target object in response to the posture of the target object in the physical space.

Description

[Technical Field]

[0001] This invention relates to a conveyor control technology, and more particularly to a conveyor control method, system, and non-volatile computer-readable recording medium. [Previous Technology]

[0002] With changes in transaction patterns and increasing demand for automated logistics management such as smart warehousing, more and more logistics operators hope to adopt automated handling devices to autonomously complete the handling and shelving of goods. However, existing image recognition technology cannot be directly applied to logistics management systems. This is because the goods to be handled and / or the pallets carrying the goods are often irregularly arranged in physical space. Therefore, even if the handling device can identify the goods to be handled, it still cannot accurately control the extension arm or clamp to insert into the pallet groove under the goods at a specific angle to handle the pallet along with the goods on it. In addition, the packaging of the goods to be handled and / or the appearance of the pallets carrying the goods may have defects or damage, which increases the difficulty of image recognition. [Summary of the Invention]

[0003] The present invention provides a method, system and non-volatile computer-readable recording medium for controlling a transport machine, which can improve the efficiency of the transport machine in performing automated cargo handling.

[0004] An embodiment of the present invention provides a transporter control method, comprising: analyzing image data to obtain contour surface data corresponding to a carrier in the image data; analyzing the contour surface data to obtain feature data of the carrier, wherein the feature data reflects the posture of the carrier in a physical space; and generating control data based on the feature data, wherein the control data is adapted to control the transporter to transport the carrier in response to the posture of the carrier in the physical space.

[0005] An embodiment of the present invention further provides a transporter control system, which includes a transporter and a control host. The control host is coupled to the transporter. The control host is used to analyze image data to obtain contour surface data corresponding to a carrier in the image data. The control host is further used to analyze the contour surface data to obtain feature data of the carrier, wherein the feature data reflects the posture of the carrier in physical space. The control host is further used to generate control data based on the feature data. The transporter is used to transport the carrier in response to the posture of the carrier in the physical space according to the control data.

[0006] An embodiment of the present invention further provides a non-volatile computer-readable recording medium storing code, the code being executed by a processor to: analyze image data to obtain contour surface data corresponding to a carrier in the image data; analyze the contour surface data to obtain feature data of the carrier, wherein the feature data reflects the posture of the carrier in physical space; and generate control data based on the feature data, wherein the control data is adapted to control the transporter to transport the carrier in response to the posture of the carrier in the physical space.

[0007] Based on the above, after analyzing image data to obtain contour surface data corresponding to the carrier in the image data, the contour surface data can be further analyzed to obtain feature data of the carrier, which reflects the posture of the carrier in the physical space. Then, control data can be generated based on the feature data. In particular, the control data is suitable for controlling the transport machine to transport the target object in response to the posture of the carrier in the physical space. This can effectively improve the efficiency of the transport machine in performing automated cargo handling.

Implementation Method

[0009] Figure 1 is a schematic diagram of a transporter control system according to an embodiment of the present invention. Referring to Figure 1, the system (also referred to as a transporter control system) 10 includes a transporter 11, a control host 12, and a carrier 13. The number of transporters 11, control host 12, and carrier 13 can be one or more, and the present invention does not limit this number.

[0010] The transporter 11 is used to transport the load 13. For example, the transporter 11 may have a moving and rotating mechanism to perform forward, backward, and / or turning actions on the ground. Furthermore, the transporter 11 may have extension arms 101 and 102. For example, the transporter 11 can control the extension arms 101 and 102 to move vertically or horizontally. Thus, the transporter 11 can use the extension arms 101 and 102 to transport the load 13. In one embodiment, the transporter 11 may be a forklift, pallet truck, stacker truck, forklift, or loader. In one embodiment, the extension arms 101 and 102 may also be mechanisms that function as clamps, pallets, or robotic arms for transporting the load 13, and the load 13 may be a pallet, tray, platform, or other flat or three-dimensional structure for carrying items. The control host 12 may be a desktop computer, laptop computer, tablet computer, industrial computer, server, or other type of computer device with data transmission and processing capabilities. The conveyor 11 can communicate with the control host 12.

[0011] In the embodiments shown in FIG. 1 and below, the carrier 13 is exemplified by a pallet. Goods can be placed on the carrier 13. The carrier 13 may have recesses 131 and 132 below. Recess 131 can be regarded as the insertion port of extension arm 101, and recess 132 can be regarded as the insertion port of extension arm 102. The conveyor 11 can insert extension arms 101 and 102 into recesses 131 and 132 respectively. After inserting extension arms 101 and 102 into recesses 131 and 132 respectively, the conveyor 11 can control extension arms 101 and 102 to lift the carrier 13. It should be noted that in other embodiments not mentioned, the carrier 13 may also include other types of carriers, as long as they can be moved by the conveyor 11. In addition, the appearance of the conveyor 11 in FIG. 1 is only schematic diagram, and its specific appearance may be changed according to the actual type of conveyor 11.

[0012] It should be noted that in the embodiment of FIG. 1, the extension arms 101 and 102 of the conveyor 11 are not aligned with the grooves 131 and 132 of the carrier 13. In this state, the extension arms 101 and 102 of the conveyor 11 cannot be smoothly inserted into the grooves 131 and 132 of the carrier 13 to move the carrier 13. The control host 12 can instruct the conveyor 11 to move to the appropriate position to move the carrier 13.

[0013] In one embodiment, the conveyor 11 is further provided with an image capturing interface 103. The image capturing interface 103 is used to capture external images. For example, the image capturing interface 103 may include optical elements such as a lens and a photosensitive element. In the embodiment of FIG1, the image capturing interface 103 may be disposed in front of the conveyor 11 to capture images in front of the conveyor 11. However, in one embodiment, the image capturing interface 103 may also be disposed at any position on the conveyor 11 to capture images from other directions.

[0014] In one embodiment, the image captured by the image capturing interface 103 (i.e., the target image) includes at least a portion of the image of the carrier 13 to be transported. That is, at least a portion of the image of the carrier 13 will appear in the target image. The image capturing interface 103 can generate image data DATA(image) based on the captured target image. The image data DATA(image) may carry information about the current posture of the carrier 13 in physical space. Wherein, physical space refers to the space where the carrier 13 and the transporter 11 actually exist. For example, the image data DATA(image) may reflect the relative positional relationship between the carrier 13 and the transporter 11 in physical space.

[0015] The transporter 11 can transmit image data DATA (image) to the control host 12. The control host 12 can analyze the image data DATA (image) to obtain contour surface data corresponding to the carrier 13 in the image data DATA (image). The control host 12 can analyze this contour surface data to obtain feature data of the carrier 13. This feature data can reflect the posture of the carrier 13 in the physical space. Then, the control host 12 can generate control data DATA (control) based on this feature data. The control data DATA (control) is adapted to control the transporter 11 to transport the carrier 13 in response to the posture of the carrier 13 in the physical space.

[0016] Figure 2 is a schematic diagram illustrating the movement of a control conveyor to transport a load according to an embodiment of the present invention. Referring to Figure 2, continuing from the embodiment of Figure 1, based on image data DATA, the control host 12 can generate control data DATA and transmit the control data DATA to the conveyor 11. The control data DATA may contain control signals instructing the conveyor 11 to move.

[0017] According to the control data (data), the transporter 11 can move to a position suitable for transporting the carrier 13 in response to the current posture of the carrier 13 in the physical space, as shown in FIG2. For example, in this position, the extension arms 101 and 102 of the transporter 11 can be aligned with the grooves 131 and 132 of the carrier 13. At this time, the transporter 11 can simply move forward to insert the extension arms 101 and 102 into the grooves 131 and 132 of the carrier 13 to move the carrier 13. In other words, in one embodiment, the control data (data) is adapted to drive the transporter 11 to insert the extension arms 101 and 102 into the grooves 131 and 132 of the carrier 13 to transport the carrier 13 by means of the extension arms 101 and 102.

[0018] In one embodiment of FIG. 2, during the movement of the transporter 11, the transporter 11 can continuously capture target images and transmit the corresponding image data DATA (image) back to the control host 12. Based on the continuously received image data DATA (image), the control host 12 can continuously correct the movement trajectory of the transporter 11 by means of control data DATA (control) until the transporter 11 moves to a position suitable for transporting the load 13.

[0019] It should be noted that, in another embodiment, the control host 12 can also be integrated into the conveyor 11. In this way, the conveyor 11 can complete automated conveying operations through its own image acquisition and data processing mechanisms.

[0020] FIG3 is a functional block diagram of a control host according to an embodiment of the present invention. Referring to FIG3, the control host 12 includes a processor 31, a storage circuit 32, and an output / output (I / O) interface 33. The processor 31 is used to control the overall or partial operation of the control host 12. For example, the processor 31 may include a central processing unit (CPU), or other programmable general-purpose or special-purpose microprocessors, digital signal processors (DSPs), programmable controllers, application-specific integrated circuits (ASICs), programmable logic devices (PLDs), or other similar devices or combinations thereof. It should be noted that in the following embodiments, the description of the processor 31 is equivalent to the description of the control host 12.

[0021] Storage circuitry 32 is coupled to processor 31 and used to store data. For example, storage circuitry 32 may include volatile storage circuitry and non-volatile storage circuitry. Volatile storage circuitry is used to volatilely store data. For example, volatile storage circuitry may include random access memory (RAM) or similar volatile storage media. Non-volatile storage circuitry is used to non-volatilely store data. For example, non-volatile storage circuitry may include read-only memory (ROM), solid-state disk (SSD), and / or hard disk drive (HDD) or similar non-volatile storage media.

[0022] The output / output interface 33 is coupled to the processor 31 and used to transmit signals. For example, the processor 31 may receive input signals or transmit output signals via the output / output interface 33. For example, the output / output interface 33 may include various input / output devices such as a network connection interface, mouse, keyboard, screen, touch panel, and / or speaker.

[0023] In one embodiment, the storage circuit 32 can be used to store image data 301. For example, the image data 301 can be stored in the storage circuit 32 according to the image data DATA (image) of FIG1. ​​The processor 31 can read the image data 301 from the storage circuit 32 and generate the control data DATA (control) of FIG2 according to the image data 301.

[0024] In one embodiment, the storage circuit 32 further stores an image recognition module 302. The image recognition module 302 can perform image recognition operations such as machine vision. The processor 31 can perform image recognition on the image data 301 (i.e., the data of the target image) using the image recognition module 302 and generate control data DATA (control) based on the recognition results. The image recognition module 302 can be trained to identify target objects (e.g., the carrier 13 in FIG. 1) from the image data 301. In particular, the image recognition module 302 can be trained to improve the accuracy of target object recognition.

[0025] In one embodiment, the image recognition module 302 can also be implemented as hardware circuitry. For example, the circuitry of the image recognition module 302 can be implemented inside the processor 31 or independently of the processor 31, and the present invention does not impose any limitations on this.

[0026] In one embodiment, the processor 31 may analyze the image data 301 via the image recognition module 302 to obtain contour surface data corresponding to the carrier 13 in the image data 301. For example, the processor 31 may identify one or more regions (also referred to as target regions) in the target image via the image recognition module 302. Each target region contains an image of the carrier 13 identified by the image recognition module 302. Then, the processor 31 may obtain the contour surface data corresponding to the carrier in the image data 301 based on the identified target regions.

[0027] Figure 4 is a schematic diagram of a target image according to an embodiment of the present invention. In this embodiment, image 41 (i.e., the target image) shows a carrier 13 and goods 15 (or other items) placed on top of the carrier 13. Referring to Figures 3 and 4, in this embodiment, image data 301 can reflect image 41. Specifically, image data 301 may include at least image color information and image size information of image 41.

[0028] In one embodiment, the processor 31 may analyze the image data 301 via the image recognition module 302 to identify the carrier 13 in the image 41. The image recognition module 302 may select the area where the carrier 13 is located as region 401. In other words, region 401 contains at least a portion of the image of the carrier 13 identified by the image recognition module 302.

[0029] FIG5 is a schematic diagram of the outline image of a carrier according to an embodiment of the present invention. Referring to FIG3 and FIG5, continuing with the embodiment of FIG4, the processor 31 can generate image 51 based on the recognition result of the image recognition module 302 for the carrier 13. For example, the processor 31 can filter out image data outside region 401 of FIG4 to generate image 51 based on the recognition result of the image recognition module 302 for the carrier 13. Therefore, image 51 may (only) contain the outline 501 of the carrier 13 within region 401. In one embodiment, the operation of filtering out image data outside region 401 can also be regarded as filtering out background image other than the image of the carrier 13. In one embodiment, image 51 is also referred to as the outline image of the carrier 13. The processor 31 can analyze the image data within the image range covered by the outline 501 to obtain information on the pixel distribution corresponding to the carrier 13 in the original image data 301. Then, the processor 31 can generate feature data of the carrier 13 based on this pixel distribution information.

[0030] Figure 6 is a schematic diagram illustrating feature data of a carrier according to an embodiment of the present invention. Referring to Figures 3 and 6, continuing from the embodiment of Figure 5, the outline 501 of the carrier 13 may be composed of multiple pixels 61. Each pixel 61 may also be called a feature point. Each pixel 61 corresponds to a virtual coordinate in the virtual space uv. The virtual space uv is composed of the u-axis plane and the v-axis plane. The u-axis plane and the v-axis plane are perpendicular to each other.

[0031] In one embodiment, the processor 31 can determine the feature vectors 601 and 602 of the carrier 13 in the virtual space uv based on the distribution of the pixels 61. Feature vector 601 reflects the position of the major axis of the contour 501 of FIG. 5 in the virtual space uv. Feature vector 602 reflects the position of the minor axis of the contour 501 in the virtual space uv. Feature vectors 601 and 602 can jointly reflect the posture of the carrier 13 in the virtual space uv.

[0032] In one embodiment, the processor 31 can obtain information about the angle Ø between feature vectors 601 and 602 in the virtual space uv and a reference plane 603. The processor 31 can obtain the relative positional relationship between the carrier 13 and the transporter 11 in the physical space based on the angle Ø information. Then, the processor 31 can generate control data DATA (control) based on this relative positional relationship.

[0033] Figure 7 is a schematic diagram illustrating the movement of a control conveyor to transport a load according to an embodiment of the present invention. Referring to Figures 3 and 7, continuing from the embodiment of Figure 6, in one embodiment, the processor 31 can map the included angle Ø in the virtual space uv to the included angle ϴ in the physical space. This mapping can be accomplished by a transformation equation. This included angle ϴ reflects an angular difference between the extension arms 101 and 102 of the conveyor 11 and the grooves 131 and 132 of the load 13. The processor 31 can generate control data DATA (control) based on this included angle ϴ. Thereby, the control data DATA (control) can drive the conveyor 11 to a position suitable for transporting the load 13, and the amount of movement of the conveyor 11 satisfies the angular difference defined by the included angle ϴ. At this position, the extension arms 101 and 102 of the conveyor 11 can be aligned with the grooves 131 and 132 of the load 13.

[0034] In one embodiment, the obtained contour surface data may also include contour data of images of different sides of the carrier 13. The processor 31 can generate corresponding feature data based on the contour data of images of different sides of the carrier 13.

[0035] FIG8 is a schematic diagram of the outline image of a carrier according to an embodiment of the present invention. Referring to FIG3 and FIG8, in one embodiment, it is assumed that image 81 is the target image. Processor 31 can identify outline surfaces 801 and 802 from image 81 via image recognition module 302. Outline surface 801 includes at least a portion of the image of one side (also referred to as the first side) of carrier 13. Outline surface 802 includes at least a portion of the image of the other side (also referred to as the second side) of carrier 13. Processor 31 can obtain outline surface data (also referred to as the first outline surface data) corresponding to outline surface 801 and outline surface data (also referred to as the second outline surface data) corresponding to outline surface 802 in image data 301 according to the recognition result of image recognition module 302. In other words, the first outline surface data includes data in image data 301 related to the image of the first side of carrier 13, while the second outline surface data includes data in image data 301 related to the image of the second side of carrier 13. The processor 31 can generate feature data of the carrier 13 based on the first contour surface data and the second contour surface data.

[0036] In one embodiment, the processor 31 can obtain the contour ratio reflected by at least one of the first contour surface data and the second contour surface data. The processor 31 can generate feature data of the carrier 13 based on this contour ratio. For example, the processor 31 can count the total number of pixels in a certain axis in the contour surfaces 801 and 802 respectively to obtain lengths D1 and D2. Lengths D1 and D2 can respectively reflect the length proportion of contour surfaces 801 and 802 in the total contour of the carrier 13. The processor 31 can generate feature data of the carrier 13 based on lengths D1 and D2. Then, the processor 31 can generate control data DATA (control) based on this feature data.

[0037] In one embodiment, the processor 31 can use the ratio of lengths D1 to D2 as characteristic data of the carrier 13. The processor 31 can map the ratio of lengths D1 to D2 to the included angle ϴ in the physical space. This mapping can be accomplished by a transformation equation. The processor 31 can generate control data DATA (control) based on this included angle ϴ to drive the conveyor 11 to a position suitable for conveying the carrier 13, and the amount of movement of the conveyor 11 satisfies the angle difference defined by the included angle ϴ. Specific operational details are described in the embodiment of FIG7, and will not be repeated here.

[0038] In one embodiment, the processor 31 can also evaluate the position and attitude information of the carrier in the physical space based on the obtained feature data (e.g., feature vectors 601 and 602 in FIG. 6). The processor 31 can generate the control data DATA (control) based on this information.

[0039] It should be noted that the foregoing embodiments all involve image recognition and feature data extraction for a single carrier in the physical space, thereby driving the transporter to move to the appropriate position to transport the carrier. However, in another embodiment, even if there are multiple carriers in the physical space (which may be stacked or dispersed), the control host can perform image recognition on each of these carriers one by one according to the operation methods mentioned in the foregoing embodiments and instruct the transporter to automatically perform subsequent transport actions.

[0040] An embodiment of the present invention also provides a non-volatile computer-readable recording medium. This non-volatile computer-readable recording medium stores program code. A processor in a computer (e.g., processor 31 in FIG3) can execute (or run) this program code to perform the aforementioned functions and operations.

[0041] FIG9 is a flowchart illustrating a transporter control method according to an embodiment of the present invention. Referring to FIG9, in step S901, image data is analyzed to obtain contour surface data corresponding to the carrier in the image data. In step S902, the contour surface data is analyzed to obtain feature data of the carrier, wherein the feature data reflects the posture of the carrier in the physical space. In step S903, control data is generated based on the feature data, wherein the control data is adapted to control the transporter to transport the carrier in response to the posture of the carrier in the physical space.

[0042] However, the steps in Figure 9 have been described in detail above, and will not be repeated here. It is worth noting that the steps in Figure 9 can be implemented as multiple code (e.g., software modules) or circuits (e.g., circuit modules), and this disclosure does not limit them. In addition, the method in Figure 9 can be used in conjunction with the above exemplary embodiments, or it can be used alone, and this disclosure does not limit it.

[0043] In summary, the main control device can evaluate the posture of the carrier in the physical space based on the information related to the carrier in the acquired image data, and then drive the transport machine to automatically move to a suitable position to transport the carrier based on this posture. In one embodiment, even if the placement position and / or angle of the carrier in the physical space is irregular, the transport machine can still automatically adjust the insertion angle of the extension arm relative to the carrier to smoothly lift and transport the carrier. This effectively improves the efficiency of the transport machine in performing automated cargo handling.

[0044] Although this disclosure has been disclosed above with reference to embodiments, it is not intended to limit this disclosure. Anyone skilled in the art can make some modifications and refinements without departing from the spirit and scope of this disclosure. Therefore, the scope of protection of this disclosure shall be determined by the appended claims. [Simplified Explanation of the Diagram]

[0008] Figure 1 is a schematic diagram of a transporter control system according to an embodiment of the present invention. Figure 2 is a schematic diagram of controlling the movement of a transporter to transport a load according to an embodiment of the present invention. Figure 3 is a functional block diagram of a control host according to an embodiment of the present invention. Figure 4 is a schematic diagram of a target image according to an embodiment of the present invention. Figure 5 is a schematic diagram of the outline image of a load according to an embodiment of the present invention. Figure 6 is a schematic diagram of feature data of a load according to an embodiment of the present invention. Figure 7 is a schematic diagram of controlling the movement of a transporter to transport a load according to an embodiment of the present invention. Figure 8 is a schematic diagram of the outline image of a load according to an embodiment of the present invention. Figure 9 is a flowchart of a transporter control method according to an embodiment of the present invention.

Claims

1. A method for controlling a conveyor, comprising: Analyze an image to obtain a contour surface data corresponding to a carrier in the image; analyze the contour surface data to obtain feature data of the carrier, wherein the feature data reflects the posture of the carrier in a physical space; and generate control data based on the feature data, wherein the control data is adapted to control the transporter to transport the carrier in response to the posture of the carrier in the physical space.

2. The conveyor control method as described in claim 1 further includes: A target image is captured by an image capturing interface, wherein the target image includes at least a portion of the image of the carrier; and image data is generated based on the captured target image.

3. The conveyor control method as described in claim 2, wherein the image capturing interface is disposed on the conveyor.

4. The conveyor control method as described in claim 1, wherein the step of analyzing the image includes: An image recognition module is used to perform image recognition on the image data, and the image recognition module is trained to identify the carrier from the image data.

5. The conveyor control method as claimed in claim 1, wherein the step of analyzing the contour surface data to obtain the characteristic data of the carrier includes: Analyze the contour surface data to obtain information on the pixel distribution corresponding to the carrier in the image data; And generate the feature data based on the information of the pixel distribution.

6. The conveyor control method as described in claim 5, wherein the step of generating the feature data based on the pixel distribution information includes: A feature vector is generated based on the information of the pixel distribution, wherein the feature vector is used to reflect the posture of the carrier in a virtual space.

7. The conveyor control method as described in claim 6, wherein the step of generating the control data based on the feature data includes: Obtain information about the angle between the feature vector and a reference plane in the virtual space; Based on the information of the included angle, a relative positional relationship between the carrier and the transporter in the physical space is obtained; and control data is generated based on the relative positional relationship.

8. The conveyor control method as claimed in claim 1, wherein the profile surface data includes a first profile surface data and a second profile surface data, and the step of analyzing the profile surface data to obtain the feature data of the carrier includes: Obtain the proportion of a profile reflected by at least one of the first profile surface data and the second profile surface data; And generate the feature data based on the proportion of the contour.

9. The conveyor control method as claimed in claim 8, wherein the first profile surface data includes data relating to an image of a first side of the carrier in the image data, and the second profile surface data includes data relating to an image of a second side of the carrier in the image data.

10. The transporter control method of claim 1, wherein the control data is adapted to drive the transporter to insert an extension arm into an insertion port of the carrier to transport the carrier by means of the extension arm.

11. A conveying machine control system, comprising: A conveyor belt; A control host is coupled to the transporter, wherein the control host is used to analyze an image data to obtain a contour surface data corresponding to a carrier in the image data, the control host is further used to analyze the contour surface data to obtain a feature data of the carrier, wherein the feature data reflects the posture of the carrier in a physical space, the control host is further used to generate control data based on the feature data, and the transporter is used to transport the carrier in response to the posture of the carrier in the physical space according to the control data.

12. The conveyor control system as described in claim 11, further comprising: An image capture interface is coupled to the control host, wherein the image capture interface is used to capture a target image, the target image including at least a portion of the image of the carrier, and the image capture interface is further used to generate image data based on the captured target image.

13. The transporter control system as claimed in claim 12, wherein the image capturing interface is disposed on the transporter.

14. The conveyor control system as claimed in claim 11, wherein the operation of analyzing the image includes: An image recognition module is used to perform image recognition on the image data, and the image recognition module is trained to identify the carrier from the image data.

15. The conveyor control system of claim 11, wherein the operation of analyzing the contour surface data to obtain the characteristic data of the carrier includes: Analyze the contour surface data to obtain information on the pixel distribution corresponding to the carrier in the image data; And generate the feature data based on the information of the pixel distribution.

16. The conveyor control system as claimed in claim 15, wherein the operation of generating the feature data based on the pixel distribution information includes: A feature vector is generated based on the information of the pixel distribution, wherein the feature vector is used to reflect the posture of the carrier in a virtual space.

17. The conveyor control system as claimed in claim 16, wherein the operation of generating the control data based on the characteristic data includes: Obtain information about the angle between the feature vector and a reference plane in the virtual space; Based on the information of the included angle, a relative positional relationship between the carrier and the transporter in the physical space is obtained; and control data is generated based on the relative positional relationship.

18. The conveyor control system of claim 11, wherein the profile surface data includes a first profile surface data and a second profile surface data, and the operation of analyzing the profile surface data to obtain the feature data of the carrier includes: Obtain the proportion of a profile reflected by at least one of the first profile surface data and the second profile surface data; And generate the feature data based on the proportion of the contour.

19. The transporter control system of claim 18, wherein the first profile surface data includes data relating to an image of a first side of the carrier in the image data, and the second profile surface data includes data relating to an image of a second side of the carrier in the image data.

20. The transporter control system of claim 11, wherein the transporter is further configured to insert an extension arm into an insertion port of the carrier according to the control data, so as to transport the carrier by means of the extension arm.

21. A non-volatile computer-readable recording medium, wherein the non-volatile computer-readable recording medium stores program code, and the program code is executed by a processor to: analyze image data to obtain contour surface data corresponding to a carrier in the image data; analyze the contour surface data to obtain feature data of the carrier, wherein the feature data reflects the orientation of the carrier in a physical space; and generate control data based on the feature data, wherein the control data is adapted to control a transporter to transport the carrier in response to the orientation of the carrier in the physical space.

Images