JP2024094061A - Robot control device and robot teaching method - Google Patents

Abstract

To provide a robot control device capable of generating teaching data which appropriately grasps a target position on the basis of image information photographed by a camera a plurality of times, and conveys an object to the target position with high accuracy.SOLUTION: A robot control device 100 includes: image information acquisition means 110 for acquiring each image information which is photographed at at least two or more places; target position calculation means 120 for calculating target positions on the basis of the respective image information; robot position calculation means 130 for calculating a robot position of a conveyance robot 200; robot control means 140 for operating the conveyance robot 200 so that the robot position coincides with the target position; target position determination mans 150 for determining the target position on the basis of the target position calculated on the basis of image information at the target position and a moving position of the conveyance robot 200; and teaching data generation means 160 for storing the target position calculated on the basis of the image information at the moving position as teaching data, according to a determination result.SELECTED DRAWING: Figure 3

Description

The present invention relates to a robot control device and a robot teaching method.

In recent years, many robots have become popular in the industrial world. These robots are used, for example, for assembling, welding, and transporting electronic and mechanical parts, and are helping to streamline and automate factory production lines.

Transport robots used in semiconductor manufacturing equipment to transport wafers are taught to transport the wafers to the appropriate position, but the accuracy of this teaching depends on the knowledge and skill of the operator, and there are also cases where space saving is required to the extent that there is not enough space for the operator to work, so efforts are being made to automate the teaching process.

For example, in the wafer transport robot described in Patent Document 1, a camera attached to the hand captures an image of the wafer placed at the removal position, calculates three-dimensional information about the wafer based on the image captured by the camera, and moves the hand based on the three-dimensional information about the wafer to appropriately remove the wafer.

JP 2022-144478 A

However, with the wafer transport robot described in Patent Document 1, if the accuracy of the three-dimensional information of the wafer calculated based on the image captured by the camera is low, the actual position of the wafer cannot be determined, and the wafer may not be removed properly.

Furthermore, in automating teaching, it is necessary to properly grasp not only the three-dimensional information of the wafer, but also the target position to which the wafer will be transported. Even if the target position to which the wafer will be transported is determined by taking an image with a camera attached to the wafer transport robot and calculating the target position based on the image acquired by the camera, the target position may not be accurately grasped depending on the camera's performance and shooting conditions, and there is a risk of a discrepancy occurring with the position information based on the position and orientation of the wafer transport robot. As a result, it is not possible to generate teaching data for transporting the wafer to the target position with high accuracy, which gives rise to the problem that the wafer cannot be transported appropriately to the target position.

The present invention aims to provide a robot control device and a robot teaching method that can accurately grasp a target position based on image information captured multiple times by a camera and generate teaching data for transporting an object to the target position with high accuracy.

A robot control device according to one aspect of the present invention is a robot control device that controls a transport robot that transports a flat object, and includes: image information acquisition means that acquires image information captured at least at two or more locations by a camera attached to the transport robot so as to include a target position to which the transport robot moves; target position calculation means that calculates a target position based on each image information; robot position calculation means that calculates the robot position of the transport robot based on robot information including the state of each axis of the transport robot; robot control means that operates the transport robot so that the robot position coincides with the target position; target position determination means that determines the target position based on the target position and the target position calculated based on image information captured at the movement position to which the transport robot has moved so that the robot position coincides with the target position; and teaching data generation means that stores the target position calculated based on the image information captured at the movement position as teaching data according to the determination result.

According to this aspect, the image information acquisition means acquires each image information taken by the camera at least at two or more locations, and the target position calculation means calculates the target position based on each image information. The robot position calculation means calculates the robot position of the transport robot based on the robot information including the state of each axis of the transport robot, and the robot control means operates the transport robot so that the robot position coincides with the target position. The target position determination means determines the target position based on the target position and the target position calculated based on the image information taken at the movement position to which the transport robot has moved so that the robot position coincides with the target position, and the teaching data generation means stores the target position calculated based on the image information taken at the movement position according to the determination result as teaching data. This makes it possible to appropriately grasp the target position and generate teaching data for transporting the object to the target position with high accuracy, and as a result, the object can be transported to the target position with high accuracy by using the teaching data.

In the above aspect, the target position determination means determines whether the difference between the target position and the target position calculated based on image information captured at the movement position to which the transport robot has moved so that the robot position coincides with the target position is equal to or less than a threshold value, and if the difference is equal to or less than the threshold value, the teaching data generation means may store the target position calculated based on image information captured at the movement position as teaching data.

According to this aspect, the target position determination means determines whether the difference between the target position and the target position calculated based on image information captured at the movement position to the target position is equal to or less than a threshold value, so that the target position can be more appropriately determined.

In the above aspect, if the difference is not equal to or less than the threshold value, the robot control means may operate the transport robot so that the robot position coincides with the target position calculated based on the image information captured at the movement position.

According to this aspect, if the difference is not equal to or less than the threshold value, the movement of the transport robot, the acquisition of image information, and the calculation and determination of the target position are repeated, and once the difference converges and stabilizes, an appropriate target position can be identified.

A robot teaching method according to one aspect of the present invention is a robot teaching method executed by a robot control device that controls a transport robot that transports a flat object, and includes an image information acquisition step of acquiring image information captured by a camera attached to the transport robot so as to include a target position to which the transport robot will move, a target position calculation step of calculating the target position based on the image information, a robot position calculation step of calculating the robot position of the transport robot based on robot information including the state of each axis of the transport robot, a robot control step of operating the transport robot so that the robot position coincides with the target position, a target position determination step of determining the target position based on the target position and the target position calculated based on image information captured at a movement position to which the transport robot has moved so that the robot position coincides with the target position, and a teaching data generation step of storing the target position calculated based on the image information captured at the movement position as teaching data according to the determination result.

According to this aspect, in the image information acquisition step, image information captured by a camera is acquired, and in the target position calculation step, a target position is calculated based on each image information. In the robot position calculation step, a robot position of the transport robot is calculated based on robot information including the state of each axis of the transport robot, and in the robot control step, the transport robot is operated so that the robot position coincides with the target position. Then, in the target position determination step, the target position is determined based on the target position and the target position calculated based on image information captured at the movement position to which the transport robot has moved so that the robot position coincides with the target position, and in the teaching data generation step, the target position calculated based on the image information captured at the movement position according to the determination result is stored as teaching data. This makes it possible to appropriately grasp the target position and generate teaching data for transporting the object to the target position with high accuracy, and as a result, the object can be transported to the target position with high accuracy by using the teaching data.

A robot control device according to another aspect of the present invention is a robot control device that controls a transport robot that transports a flat object, and includes: image information acquisition means that acquires image information captured at least at two or more locations by a camera attached to the transport robot so as to include a target position to which the transport robot moves; target position calculation means that calculates a target position based on each image information; robot position calculation means that calculates the robot position of the transport robot based on robot information including the state of each axis of the transport robot; robot control means that operates the transport robot so that the robot position coincides with the target position; target position determination means that determines the target position based on the amount of movement of the transport robot so that the robot position coincides with the target position; and teaching data generation means that stores the target position or the movement position to which the transport robot has moved as teaching data depending on the determination result.

According to this aspect, the image information acquisition means acquires each piece of image information captured by a camera at least at two or more locations, and the target position calculation means calculates the target position based on each piece of image information. The robot position calculation means calculates the robot position of the transport robot based on robot information including the state of each axis of the transport robot, and the robot control means operates the transport robot so that the robot position coincides with the target position. The target position determination means determines the target position based on the movement position to which the transport robot has moved so that the robot position coincides with the target position, and the teaching data generation means stores the target position or the movement position to which the transport robot has moved as teaching data according to the determination result. This makes it possible to appropriately grasp the target position and generate teaching data for transporting the object to the target position with high accuracy, and as a result, the object can be transported to the target position with high accuracy by using the teaching data.

The present invention provides a robot control device and a robot teaching method that can accurately grasp a target position based on image information captured multiple times by a camera and generate teaching data for transporting an object to the target position with high accuracy.

1 is a schematic diagram showing a system configuration of a transfer robot system 10 according to an embodiment of the present invention. 2 is a diagram showing a state in which a transfer robot 200 according to an embodiment of the present invention transfers a wafer W. FIG. FIG. 2 is a functional block diagram showing each function of a robot control device 100 according to an embodiment of the present invention. 1 is a diagram showing an installation position 15 of the semiconductor manufacturing equipment, which is a target position to which the wafer W is transferred. 13 is a diagram showing the positional relationship between the target position and the TCP(T) of the hand 220 of the transport robot 200, the image being captured by the camera 240 at a position substantially in front of the installation position 15 so as to include the target position. 13 is a diagram showing a state in which the transport robot 200 has been moved so that the TCP(T) of the hand 220 of the transport robot 200 coincides with a target position G ₁ . 13 is a diagram showing a state in which the transport robot 200 has been moved so that the TCP(T) of the hand 220 of the transport robot 200 coincides with the target position G ₂ . 1 is a flowchart showing a process flow of a robot teaching method M100 executed by a transfer robot system 10 according to an embodiment of the present invention. 13 is a flowchart showing a process flow of another robot teaching method M200 executed by the transfer robot system 10 according to an embodiment of the present invention.

The following describes an embodiment of the present invention in detail with reference to the drawings. Note that the embodiment described below is merely a specific example for implementing the present invention, and is not intended to limit the interpretation of the present invention. In addition, to facilitate understanding of the description, the same reference numerals are used as far as possible for the same components in each drawing, and duplicate descriptions may be omitted.

<One embodiment>
[Configuration of the transport robot system]
1 is a schematic diagram showing a system configuration of a transport robot system 10 according to an embodiment of the present invention. As shown in FIG. 1, the transport robot system 10 includes a robot controller 100, a transport robot 200, a device controller 300, and a teach pendant 400.

The transport robot 200 is, for example, a six-axis vertical articulated type, and has a manipulator body 210, a hand 220 as an end effector, and a hand base (base) 230 to which the hand 220 is attached, and further, a camera 240 is disposed on the hand base 230. The camera 240 is, for example, configured as a stereo camera, with two cameras.

The robot control device 100 is a device that controls the operation of the transport robot 200. For example, the robot control device 100 is connected to a teach pendant 400 and can acquire operation instruction information input to the teach pendant 400. Based on the operation instruction information, the robot control device 100 starts and stops the transport robot 200, and operates each axis of the manipulator body 210 to remove an object, thereby operating the arms and hands 220.

The robot control device 100 also controls the device control device 300 to, for example, capture an image of the vicinity of the transport robot 200 using a camera 240 disposed on the transport robot 200, and acquire the captured image information.

As described above, the device control device 300 controls the operation of the camera 240 based on operational instructions from the robot control device 100, and sends the acquired image information to the robot control device 100.

Note that here, the device control device 300 is connected to the robot control device 100 via a cable and is a separate device from the robot control device 100, but the robot control device 100 may include its functions. In this case, the robot control device 100 and the device control device 300 configured as an integrated unit may be regarded as the robot control device.

The teach pendant 400 accepts input from the operator regarding operation instruction information for the transport robot 200, regarding the transport work of transporting an object. Typically, the operator uses the teach pendant 400 to input appropriate instruction information, for example, for starting and stopping the transport robot 200, as well as settings for the transport robot 200, the operation of the manipulator body 210 (arm) and hand 220, and the registration of teaching points.

In addition, in an embodiment of the present invention, the teaching points may be registered automatically by automatic teaching, rather than the operator using the teach pendant 400 to sequentially register teaching points on the operation path while operating the transport robot 200. Such automatic teaching is effective, for example, in environments or situations where there is insufficient space (work space) for the operator to enter.

In FIG. 1, the teach pendant 400 is connected to the robot control device 100 via a cable, but it may also be connected wirelessly. That is, the teach pendant 400 and the robot control device 100 may be provided with a communication unit that performs wireless communication. By connecting the robot control device 100 and the teach pendant 400 wirelessly, the worker can input operation instruction information while moving freely without being bothered by the presence of a cable or being restricted in the range of movement by the length of the cable.

[Wafer transportation]
Fig. 2 is a diagram showing a state in which a transfer robot 200 according to an embodiment of the present invention transfers a wafer W. As shown in Fig. 2, the transfer robot 200 installed in the working space 11 takes out the wafer W stored in the FOUPs 12 and 13, and transfers the wafer W held by a hand 220 to an installation position 14 or 15 of a semiconductor manufacturing apparatus.

Here, the transfer robot 200 transfers the wafer W stored in the FOUP 12 to the installation position 15, and more specifically, sets the center of gravity of the three pins 15A to 15C arranged at the installation position 15 as the target position, and installs the wafer W at the target position.

More specifically, the transport robot 200 operates the arms and hands 220 by operating each axis of the manipulator body 210 based on operation instruction information from the robot control device 100, and holds the wafer W stored in the FOUP 12, then transports it to the installation position 15 and installs it at the target position, which is the center of gravity of the three pins 15A to 15C. Here, it is preferable that the center of the wafer W is installed at the target position with high accuracy, and it is important for the robot control device 100 to properly grasp the target position. Then, the robot control device 100 operates the transport robot 200 so that the TCP (Tool Center Point) of the hand 220 in the transport robot 200 coincides with the target position, and the operation is preferably registered as teaching data.

[Configuration of the robot control device]
3 is a functional block diagram showing the functions of the robot control device 100 according to one embodiment of the present invention. As shown in FIG. 3, the robot control device 100 includes an image information acquisition unit 110, a target position calculation unit 120, a robot position calculation unit 130, a robot control unit 140, a target position determination unit 150, and a teaching data generation unit 160.

As shown in FIG. 1, the robot control device 100 is connected to the transfer robot 200, the device control device 300, and the teach pendant 400, and has many functions for performing various controls and processes. Here, the robot control device 100 is mainly shown with respect to the function of registering the target position to which the wafer W is to be transferred as teaching data, but it also has other configurations and functions.

The image information acquisition means 110 acquires image information captured at least at two or more locations by the camera 240 attached to the transport robot 200 so as to include the target position to which the transport robot 200 moves. For example, the image information acquisition means 110 captures images by the camera 240 so as to include three pins 15A to 15C arranged at the installation position 15 of the semiconductor manufacturing device.

In addition, at a position away from the installation position 15, for example, at a position where the transfer robot 200 holds the wafer W with the hand 220 and starts transferring it to the target position, or at a position approximately in front of the installation position 15 after starting the transfer, the camera 240 takes an image including the target position, and the image information acquisition means 110 acquires the first image information.

Then, as described below, at the target position calculated by the target position calculation means 120 based on the first image information, the camera 240 captures an image including the target position at the movement position, and the image information acquisition means 110 acquires a second image information. Furthermore, at the target position calculated based on the second image information, the camera 240 captures an image including the target position at the movement position, according to the determination result by the target position determination means 150, and the image information acquisition means 110 acquires a third image information. Thereafter, the image information acquisition means 110 may repeat the process of acquiring image information in the same manner according to the determination result by the target position determination means 150.

The target position calculation means 120 calculates the target position based on each piece of image information acquired by the image information acquisition means 110. For example, the target position calculation means 120 detects the positions of the three pins 15A to 15C from the image data of the image information acquired by the image information acquisition means 110 by image processing, and calculates the center of gravity position of the three pins 15A to 15C from the position information of the three pins 15A to 15C to determine the target position. As described above, the image information acquisition means 110 acquires each piece of image information captured at least in two or more locations. That is, the three pins 15A to 15C are each captured differently in each piece of image information captured by the camera 240, and the center of gravity position (target position) of the three pins 15A to 15C is calculated based on the three pins 15A to 15C in each piece of image information.

Figure 4 is a diagram showing the state of the installation position 15 of the semiconductor manufacturing equipment, which is the target position to which the wafer W is transported. In Figure 4, the installation position 15 of the semiconductor manufacturing equipment is shown as seen from the opening side for transporting the wafer W to the installation position 15, and three pins 15A to 15C are arranged at the installation position 15.

First, the image information acquisition means 110 acquires first image information captured by the camera 240 at a position substantially in front of the installation position 15 so as to include the three pins 15A to 15C arranged at the installation position 15. The target position calculation means 120 calculates the center of gravity _G1 of the three pins 15A to 15C based on the first image information, and sets it as the target position _G1 .

Next, the transfer robot 200 moves to the target position _G1 . The image information acquisition means 110 acquires second image information captured by the camera 240 at the movement position so as to include the three pins 15A to 15C arranged at the installation position 15. Similarly, the target position calculation means 120 calculates the center of gravity position _G2 of the three pins 15A to 15C based on the second image information, and sets it as the target position _G2 .

As described above, the camera 240 is composed of two cameras as a stereo camera and is attached to the hand base 230 of the transport robot 200. The three pins 15A to 15C arranged at the installation position 15 are photographed by the camera 240, but the first time, when the camera 240 is far from the installation position 15 or when the working space 11 is narrow due to the arrangement of equipment and facilities, the photographing conditions may not be constant and the image may not be properly photographed. That is, the target position G ₁ calculated based on the image information of the first time is shifted from the actual target position, and the transport robot 200 that has moved to the target position G ₁ may not have actually moved properly to the target position. The second time, the image information is photographed at the moving position where the transport robot 200 has moved to the target position G ₁ , so that the image information is photographed under photographing conditions different from those of the first time.

Then, the target position _G2 calculated based on the second image information is compared with the target position _G1 calculated based on the first image information to determine the target position. Details of the target position determination process will be described later, but if it cannot be determined as an appropriate target position, the transfer robot 200 is further moved to repeat the acquisition of image information for the Nth time, the calculation of the target position _Gn , and the comparison of the target position _Gn with Gn _-1 .

In this way, the target position calculation means 120 calculates the target position G _n (camera coordinate system) based on each piece of image information captured by the camera 240. The target position G _n may be recorded as XYZ coordinates in a three-dimensional space, for example, as a relative position coordinate from the camera 240, a relative position coordinate from a predetermined position of the hand base 230, or a relative position coordinate from a predetermined position of the hand 220 (for example, the tip (distal end) or the base (proximal end)).

Returning to FIG. 3, the robot position calculation means 130 calculates the robot position of the transport robot 200 based on the robot information including the state of each axis of the transport robot 200. For example, the robot position calculation means 130 calculates the position and orientation of the transport robot 200 based on the state of each axis of the transport robot 200 (information about angles, etc.) to calculate the robot position. Here, the robot position calculation means 130 calculates the TCP of the hand 220 in the transport robot 200 as the robot position. That is, the transport robot 200 grasps the TCP of the hand 220 in the transport robot 200 from the state of each axis of the transport robot 200 (robot coordinate system). The TCP may be recorded as XYZ coordinates in a three-dimensional space, for example, as a relative position coordinate from the camera 240, a relative position coordinate from a predetermined position of the hand base 230, or a relative position coordinate from a predetermined position of the hand 220 (for example, the tip (distal end) or the base (proximal end)).

The robot control means 140 operates the transport robot 200 so that the robot position, which is the TCP of the hand 220 in the transport robot 200 , coincides with the target position G _n calculated by the target position calculation means 120 .

For example, the robot control means 140 operates each axis of the manipulator body 210 in the transport robot 200 to operate the arm and hand 220 so that the TCP (robot coordinate system) of the hand 220 coincides with the center of gravity position (target position) G ₁ (camera coordinate system) of the three pins 15A to 15C calculated from the first image information.

Furthermore, the robot control means 140 operates each axis of the manipulator body 210 in the transport robot 200 to operate the arm and hand 220 so that the TCP (robot coordinate system) of the hand 220 coincides with the center of gravity position (target position) G ₂ (camera coordinate system) of the three pins 15A to 15C calculated from the second image information, according to the determination result by the target position determination means 150 described later. Thereafter, similarly, the robot control means 140 operates each axis of the manipulator body 210 in the transport robot 200 to operate the arm and hand 220 so that the TCP (robot coordinate system) of the hand 220 coincides with the center of gravity position (target position) G _n (camera coordinate system) according to the determination result by the target position determination means 150.

The target position determination means 150 determines the target position based on the target position G _n -1 and the target position G _n calculated based on image information (Nth time) captured at the movement position to which the transport robot 200 has moved so that the robot position, which is the TCP of the hand 220 in the transport robot 200, coincides with the target position G n- ₁ . In other words, the target position determination means 150 appropriately determines the target position based on the target position G _n -1 and the target position G _n .

For example, the target position determination means 150 compares a target position _G1 calculated based on the first image information with a target position G2 calculated based on the second image information acquired by moving the transport robot 200 to the target position _G1 and capturing an image at the target position G1. Specifically, the target position determination means ₁₅₀ determines whether the difference between the target position _G1 and the target position _G2 is equal to or smaller than a threshold value.

If the difference is equal to or less than the threshold, the teaching data generating means 160 (described later) generates teaching data, but if the difference is not equal to or less than the threshold, the robot control means 140 moves the transport robot 200 to the target position _G2 . The target position determination means 150 then determines whether the difference between the target position _G2 and the target position _G3 calculated based on the third image information captured and acquired at the movement position is equal to or less than the threshold. Similarly, thereafter, if the difference is equal to or less than the threshold, the teaching data generating means 160 (described later) generates teaching data, and if the difference is not equal to or less than the threshold, the robot control means 140 moves the transport robot 200, and the acquisition of image information by the image information acquiring means 110, the calculation of the target position by the target position calculating means 120, and the determination by the target position determining means 150 are repeated.

The threshold value may be set, for example, to about 0.01 mm to 0.05 mm, but is not limited to this range and may be set based on the required and allowable target position accuracy according to the type and size of the object being transported and the required product accuracy.

The teaching data generating means 160 stores the target position G _n calculated based on the image information captured at the movement position as teaching data in accordance with the determination result by the target position determining means 150. For example, when the target position determining means 150 determines that the difference between the target position G _n -1 and the target position G _n is equal to or smaller than a threshold value, the teaching data generating means 160 stores the target position G ₂ in a memory or the like as teaching data.

Specifically, when the target position determination means 150 determines that the difference between the target position _G1 and the target position _G2 is equal to or less than the threshold value, the teaching data generation means 160 stores the target position _G2 as teaching data in a memory or the like. On the other hand, when the target position determination means 150 determines that the difference between the target position _G1 and the target position _G2 is not equal to or less than the threshold value, the teaching data generation means 160 moves the transport robot 200 as described above, and when the target position determination means 150 determines that the difference between the target position _G2 and the target position _G3 is equal to or less than the threshold value, the teaching data generation means 160 stores the target position _G3 as teaching data in a memory or the like. Thereafter, the process is repeated in the same manner until the target position determination means 150 determines that the difference between the target position _Gn -1 and the target position _Gn is equal to or less than the threshold value and the target position determination means 150 stores the target position _Gn as teaching data in a memory or the like.

By repeating the movement of the transport robot 200, the photographing by the camera 240 (acquisition of image information), and the calculation and determination of the target position until the difference between the target positions calculated based on the image information photographed multiple times in this way becomes equal to or less than a threshold value, an appropriate target position can be stored as teaching data. As a result, according to the teaching data stored in this way, when the transport robot 200 takes out the wafer W stored in the FOUP 12 and transports the wafer W held by the hand 220 to the installation position 15 of the semiconductor manufacturing equipment, the transport robot 200 can transport the wafer W with high precision so that the TCP coincides with the center of gravity position (target position) of the three pins 15A to 15C arranged at the installation position 15.

[Moving the transport robot to the target position]
The manner in which the TCP of the hand 220 of the transfer robot 200 is moved to the center of gravity position (target position) of the three pins 15A to 15C will be described in detail with reference to FIGS. 5A to 5C.

Fig. 5A is a diagram showing the positional relationship between the target position and the TCP(T) of the hand 220 of the transport robot 200, captured by the camera 240 at a position substantially in front of the installation position 15 so as to include the target position. The target position shown in Fig. 5A is determined by calculating the center of gravity of the three pins 15A to 15C based on the first image information captured by the camera 240, and setting the center of gravity position as the target position _G1 . As shown in Fig. 5A, the robot control means 140 operates the transport robot 200 so that the TCP(T) of the hand 220 of the transport robot 200 coincides with the target position _G1 .

5B is a diagram showing a state in which the transport robot 200 is moved so that the TCP(T) of the hand 220 of the transport robot 200 coincides with the target position G _1. As shown in FIG 5B, the robot control means 140 operates the transport robot 200 so that the TCP(T) of the hand 220 of the transport robot 200 coincides with the target position G ₁ .

Then, the center of gravity positions of the three pins 15A to 15C are calculated based on the second image information captured by the camera 240, and the center of gravity positions are set as the target position _G2 . In the example shown in FIG. 5B, the target position _G1 (the TCP(T) of the hand 220 of the transport robot 200 that coincides with the target position _G1 ) and the target position _G2 do not coincide completely, but are slightly shifted. This is because the first image information and the second image information are captured by the camera 240 from different positions, and the three pins 15A to 15C are shown differently in each image information. Then, the center of gravity positions (target positions) of the three pins 15A to 15C are calculated based on the three pins 15A to 15C in each image information.

In this case, it is assumed that the target position determination means 150 determines that the difference d1 between the target positions G ₁ and G ₂ is not equal to or less than the threshold value.

5C is a diagram showing a state in which the transport robot 200 is moved so that the TCP(T) of the hand 220 of the transport robot 200 coincides with the target position _G2 . As shown in FIG 5C, the robot control means 140 operates the transport robot 200 so that the TCP(T) of the hand 220 of the transport robot 200 coincides with the target position _G2 .

Then, the center of gravity positions of the three pins 15A to 15C are calculated based on the third image information captured by the camera 240, and the center of gravity position is set as the target position _G3 . In the example shown in Fig. 5C, the target position _G2 (the TCP(T) of the hand 220 of the transport robot 200 that coincides with the target position _G2 ) does not coincide completely with the target position _G3 , but is slightly shifted. However, here, the difference d2 between the target position _G2 and the target position _G3 is quite small, and the target position determination means 150 determines that the difference d2 is equal to or smaller than a threshold value, and the teaching data generation means 160 stores the target position _G2 as teaching data.

Although a specific example has been described here in which the image information is acquired three times by the camera 240 and the difference d2 between the target position _G2 and the target position _G3 becomes equal to or less than the threshold value, a case is also conceivable in which the image information is acquired twice by the camera 240 and the difference d1 between the target position _G1 and the target position _G2 becomes equal to or less than the threshold value, and the target position _G2 is stored as teaching data. Also, a case is also conceivable in which the image information is acquired four or more times by the camera 240 and the calculation of the target position and the movement of the transport robot 200 are repeated until the difference between the target position Gn _{-1 and} the target position Gn becomes equal to or less than the threshold value.

[Teaching method for generating teaching data]
Next, a specific and detailed description will be given of a teaching method for generating teaching data for transporting an object to a target position by the transport robot 200.

Figure 6 is a flowchart showing the process flow of a robot teaching method M100 executed by a transport robot system 10 according to one embodiment of the present invention. As shown in Figure 6, the robot teaching method M100 includes steps S110 to S160, and each step is executed by a processor included in the robot control device 100 in the transport robot system 10.

In step S110, the image information acquisition means 110 acquires image information captured by the camera 240 attached to the transport robot 200, the image information including the target position to which the transport robot 200 will move. As a specific example, the image information acquisition means 110 acquires image information captured by the camera 240, the image information including the three pins 15A to 15C, at a position approximately in front of the installation position 15 after starting transport to the target position (image information acquisition step).

In step S120, the target position calculation means 120 calculates the target position _G1 based on the image information acquired in step S110 (target position calculation step). As a specific example, the target position calculation means 120 calculates the center of gravity positions of the three pins 15A to 15C and sets it as the target position _G1 .

In step S130, the robot position calculation means 130 calculates the robot position of the transport robot 200 based on the robot information including the state of each axis of the transport robot 200 (robot position calculation step). As a specific example, the robot position calculation means 130 calculates the TCP(T) of the hand 220 in the transport robot 200 as the robot position of the transport robot 200 based on the robot information including the state of each axis of the transport robot 200.

In step S140, the robot control means 140 operates the transport robot 200 so that the robot position calculated in step S130 coincides with the target position _G1 calculated in step S120 (robot control step). As a specific example, the robot control means 140 operates the transport robot 200 so that the TCP(T) of the hand 220 in the transport robot 200 coincides with the target position _G1 .

In step S150, the target position determination means 150 determines the target position based on the target position G _n -1 and the target position G _n calculated based on image information captured at the movement position to which the transport robot 200 has moved so that the robot position coincides with the target position G _n-1 (target position determination step).

As a specific example, step S150 includes steps S151 to S153, and in step S151, the image information acquisition means 110 acquires image information captured by the camera 240 to include the three pins 15A to _15C at a movement position to which the transport robot 200 has moved so that the robot position, which is the TCP(T) of the hand 220 in the transport robot 200, coincides with the target position G 1 calculated in step S120.

In step S152, the target position calculation means 120 calculates the positions of the centers of gravity of the three pins 15A to 15C based on the image information acquired in step S151, and sets the calculated positions as target position _G2 .

In step S153, the target position determination means 150 determines the target position based on the target position G ₁ calculated in step S120 and the target position G ₂ calculated in step S152. For example, the target position determination means 150 determines whether the difference between the target position G ₁ and the target position G ₂ is equal to or less than a threshold value, and if it is equal to or less than the threshold value ("Yes" in step S153), the process proceeds to step S160, and if it is not equal to or less than the threshold value ("No" in step S153), the process returns to step S140. That is, the processes of step S140 and steps S151 to S153 are repeated until the difference between the target position G _n-1 and the target position G _n becomes equal to or less than the threshold value.

In step S160, the teaching data generating means 160 stores the target position _G calculated in step S152 as teaching data (teaching data generating step). That is, when the difference between the target position G _n-1 and the target position G _n becomes equal to or smaller than a threshold value and the target position G _n calculated based on the image information converges and stabilizes, the target position G _n is stored as teaching data as an appropriate target position.

As described above, according to the transport robot system 10, robot control device 100, and robot teaching method M100 according to one embodiment of the present invention, the image information acquisition means 110 acquires image information captured at least at two or more locations by the camera 240, and the target position calculation means 120 calculates the target position G _n , which is the position of the center of gravity of the three pins 15A to 15C, based on each of the image information. The robot position calculation means 130 calculates the TCP of the hand 220 of the transport robot 200 based on robot information including the state of each axis of the transport robot 200, and the robot control means 140 operates the transport robot 200 so that the TCP of the hand 220 of the transport robot 200 coincides with the target position G _n . The target position determination means 150 determines whether the difference between the target position G _n -1 and the target position G _n is equal to or less than a threshold value, and the teaching data generation means 160 stores the target position G _n as teaching data in a memory or the like when it is determined that the difference between the target position G _n-1 and the target position G _n is equal to or less than a threshold value. By repeating the movement of the transport robot 200, the photographing by the camera 240 (acquisition of image information), the calculation and determination of the target position until the difference between the target position G _n -1 and the target position G _n calculated based on the image information photographed multiple times in this way becomes equal to or less than a threshold value, an appropriate target position can be stored as teaching data. As a result, according to the teaching data stored in this way, when the transport robot 200 takes out the wafer W stored in the FOUP 12 and transports the wafer W to the installation position 15 of the semiconductor manufacturing device while holding the wafer W in the hand 220, the transport robot 200 can transport the wafer W with high accuracy so that the TCP coincides with the target position.

In this embodiment, the target position determination means 150 determines that the difference between the target position G _n -1 and the target position G _n is equal to or less than a threshold value to determine the appropriate target position, but the present invention is not limited to this. For example, the appropriate target position may be determined based on the amount of movement of the transport robot 200.

Figure 7 is a flowchart showing the process flow of another robot teaching method M200 executed by the transport robot system 10 according to one embodiment of the present invention. As shown in Figure 7, the robot teaching method M200 includes steps S110 to S140, S251 to S254, and S260, and each step is executed by a processor included in the robot control device 100 in the transport robot system 10. Note that the robot teaching method M200 has some processes in common with the robot teaching method M100 shown in Figure 6, but here, the differences from the robot teaching method M100 will be mainly described in detail.

Steps S110 to S140 shown in FIG. 7 are similar to steps S110 to S140 shown in FIG. 6.

Step S251 corresponds to step S151 shown in FIG. 6. In step S251, the image information acquisition means 110 acquires image information captured by the camera 240 to include the three pins 15A to _15C at a movement position to which the transport robot 200 has moved so that the robot position, which is the TCP(T) of the hand 220 in the transport robot 200, coincides with the target position G 1 calculated in step S120.

Step S252 corresponds to step S152 shown in FIG. 6, and in step S252, the target position calculation means 120 calculates the positions of the centers of gravity of the three pins 15A to 15C based on the image information acquired in step S251, and sets this as the target position _G2 .

In step S253, the robot control means 140 operates the transport robot 200 so that the TCP(T) of the hand 220 of the transport robot 200 coincides with the target position G ₂ calculated in step S252.

In step S254, the target position determination means 150 determines the amount of movement of the transport robot 200 from the target position G ₁ to the target position G _2. For example, the target position determination means 150 determines whether the amount of movement of the transport robot 200 is equal to or less than a threshold, and if it is equal to or less than the threshold ("Yes" in step S254), the process proceeds to step S260, and if it is not equal to or less than the threshold ("No" in step S254), the process returns to step S251. That is, the processes of steps S251 to S254 are repeated until the amount of movement of the transport robot 200 from the target position G _n-1 to the target position G _n becomes equal to or less than the threshold.

6, and in step S260, the teaching data generating means 160 stores the target position G _n calculated in step S252 or the movement position of the transport robot 200 moved in step S254 as teaching data. That is, when the movement amount from the target position G _n-1 to the target position G _n becomes equal to or less than a threshold value and the target position G _n calculated based on the image information converges and stabilizes, the target position G _n or the movement position of the transport robot 200 moved to coincide with the target position G _n is stored as an appropriate target position and as teaching data.

In this way, the appropriate target position is determined based on the convergence and stabilization of the movement amount of the transport robot 200, and the target position is stored as teaching data.

In this embodiment, the camera 240 is configured as a stereo camera with two cameras attached to the hand base 230 of the transport robot 200, but this is not limited to this. As long as it can capture images of the three pins 15A to 15C so that they can be clearly recognized, it may be configured as one camera or three or more cameras, and may be attached to, for example, the arm or hand 220 of the manipulator body 210 instead of the hand base 230.

In addition, in this embodiment, a situation in which the object, the wafer W, is transported from FOUPs 12 and 13 to the installation positions 14 and 15 of the semiconductor control device has been described as an example, but the present invention is not limited to this, and the present invention may also be applied to a situation in which the object, the wafer W, is returned from the installation positions 14 and 15 of the semiconductor control device to the FOUPs 12 and 13.

Furthermore, the present invention may be applied, for example, to a situation where an aligner is used to adjust the direction or inclination of the wafer W. In this case, the installation position of the aligner that transports the wafer W may be appropriately calculated as the intermediate target position based on the image information from the camera 240. Specifically, the installation position of the aligner may be the center position of the suction pad when the wafer is placed on the suction pad, or the center position of the holding member when the wafer is held by its edge and installed. Then, the robot control means 140 operates the transport robot 200 so that the TCP of the hand 220 in the transport robot 200 matches the intermediate target position, and the teaching data generation means 160 stores the matching point as teaching data.

In the embodiment of the present invention, the object transported by the transport robot 200 has been described as a wafer, but this is not limited thereto. For example, the present invention may be applied to a transport robot that transports flat panels as objects, and may also be applied to a transport robot that transports flat objects.

Furthermore, the present invention is applicable not only to situations where an object is to be transported, but also to situations where an object such as a wafer is to be removed from a FOUP. The position of the wafer stored in the FOUP is set as the target position to which the transport robot 200 moves by photographing the wafer multiple times using a camera, calculating the target position with high accuracy, and storing the target position as teaching data. This allows the transport robot 200 to properly remove the wafer.

In addition, in the present invention, the target position is photographed multiple times using a camera, and the target position is calculated based on the image information, thereby improving the accuracy. However, at least one of the multiple photographs may be performed using a sensor, for example, instead of a camera or in combination with a camera. It is also possible to calculate the target position with high accuracy based on the acquired image information or sensor information.

The above-described embodiments are intended to facilitate understanding of the present invention, and are not intended to limit the present invention. The elements of the embodiments, as well as their arrangement, materials, conditions, shapes, sizes, etc., are not limited to those exemplified, and may be modified as appropriate. In addition, configurations shown in different embodiments may be partially substituted or combined.

10...Transport robot system, 11...Work space, 12, 13...FOUP, 14, 15...Installation position, 15A to 15C...Pins, 100...Robot control device, 110...Image information acquisition means, 120...Target position calculation means, 130...Robot position calculation means, 140...Robot control means, 150...Target position determination means, 160...Teaching data generation means, 200...Transport robot, 210...Manipulator body, 220...Hand, 230...Hand base (base), 240...Camera, 300...Device control device, 400...Teach pendant, d1, d2...Difference, G ₁ to G ₃ , G _n-1 , G _n ...Center of gravity position (target position), W...Wafer, M100, M200...Robot teaching method, S110 to S160, S151 to S153, S251 to S254...Each step of the robot teaching method

Claims (5)

A robot control device that controls a transport robot that transports a flat object,
an image information acquiring means for acquiring image information captured by a camera attached to the transport robot at at least two or more locations so as to include a target position to which the transport robot is to be moved;
a target position calculation means for calculating the target positions based on each of the image information;
a robot position calculation means for calculating a robot position of the transport robot based on robot information including a state of each axis of the transport robot;
a robot control means for operating the transport robot so that the robot position coincides with the target position;
a target position determination means for determining a target position based on the target position and a target position calculated based on image information captured at a movement position to which the transport robot is moved so that the robot position coincides with the target position;
and a teaching data generating means for storing, as teaching data, a target position calculated based on image information captured at the movement position according to the determination result.
Robot control device. the target position determination means determines whether a difference between the target position and a target position calculated based on image information captured at a movement position to which the transport robot has moved so that a position of the robot coincides with the target position is equal to or smaller than a threshold value;
When the difference is equal to or smaller than a threshold value, the teaching data generating means stores the target position calculated based on image information captured at the movement position as teaching data.
The robot control device according to claim 1 . When the difference is not equal to or less than the threshold value, the robot control means operates the transport robot so that the robot position coincides with a target position calculated based on image information captured at the movement position.
The robot control device according to claim 2 . A robot teaching method executed by a robot control device that controls a transport robot that transports a flat object, comprising:
an image information acquiring step of acquiring image information captured by a camera attached to the transport robot so as to include a target position to which the transport robot is moved;
a target position calculation step of calculating the target position based on the image information;
a robot position calculation step of calculating a robot position of the transport robot based on robot information including a state of each axis of the transport robot;
a robot control step of operating the transfer robot so that the robot position coincides with the target position;
a target position determination step of determining a target position based on the target position and a target position calculated based on image information captured at a movement position to which the transport robot is moved so that the robot position coincides with the target position;
and a teaching data generating step of storing, as teaching data, a target position calculated based on image information captured at the movement position according to the determination result.
A method for teaching a robot. A robot control device that controls a transport robot that transports a flat object,
an image information acquiring means for acquiring image information captured by a camera attached to the transport robot at at least two or more locations so as to include a target position to which the transport robot is to be moved;
a target position calculation means for calculating the target positions based on each of the image information;
a robot position calculation means for calculating a robot position of the transport robot based on robot information including a state of each axis of the transport robot;
a robot control means for operating the transport robot so that the robot position coincides with the target position;
a target position determination means for determining a target position based on an amount of movement of the transport robot so that a position of the robot coincides with the target position;
and a teaching data generating means for storing, as teaching data, the target position or a moving position to which the transport robot has moved according to the determination result.
Robot control device.

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