Picking method and picking control device

Abstract

Provided is a picking method for picking an object, said method including: controlling gripping of the object; acquiring information pertaining to a moment of a gripping position of the object; acquiring information on a gripping force for gripping the object; determining at least one of an acceleration and a speed during movement of the object on the basis of the moment and the gripping force; and controlling to move the gripped object at the acceleration and the speed of which at least one has been determined.

Description

Picking method and picking control device

[0001] The present disclosure relates to a picking method and a picking control device.

[0002] A substrate transport device that takes into account misalignment of substrates during transport is known. This substrate transport device transports substrates by suction. It includes a pressure detector that detects the pressure of a vacuum suction unit that suctions the substrates by vacuum pressure, a first pressure determination unit that compares the detected pressure value output from the pressure detector with a predetermined threshold value, a memory unit that stores the detected pressure values ​​for a certain number of substrates to be processed, a pressure value calculation unit that calculates the detected pressure values ​​stored in the memory unit for the certain number of substrates to be processed, a second pressure determination unit that compares the calculated value by the pressure value calculation unit with the predetermined threshold value, and a warning unit that outputs the determination result of the second pressure determination unit. The substrate transport device also includes a holding state determination unit that determines whether the substrates are being held in the vacuum suction unit. The holding state determination unit determines whether the substrates are being held in the vacuum suction unit and whether there is any misalignment. If the substrates are held in the correct position, the device continues operation (see Patent Document 1).

[0003] Japanese Patent Application Publication No. 2007-281073

[0004] The present disclosure provides a picking method and a picking control device that can improve the picking success rate for objects of various weights and shapes.

[0005] One aspect of the present disclosure is a picking method for picking an object, the picking method comprising: controlling the gripping of the object; acquiring information regarding a moment of the gripping position of the object; acquiring information regarding a gripping force for gripping the object; determining at least one of an acceleration and a velocity during movement of the object based on the moment and the gripping force; and controlling the gripped object to move at least one of the determined acceleration and velocity.

[0006] One aspect of the present disclosure is a picking control device that includes a processor and controls the picking of an object, wherein the processor controls the gripping of the object, acquires information regarding the moment of the gripping position of the object, acquires information regarding the gripping force used to grip the object, determines at least one of the acceleration and speed during movement of the object based on the moment and the gripping force, and controls the gripped object to move at least one of the determined acceleration and speed.

[0007] According to the present disclosure, the success rate of picking objects of various weights and shapes can be improved.

[0008] FIG. 1 is a block diagram showing an example of the configuration of a picking system in the first embodiment; FIG. 2 is an external perspective view showing an example of the configuration and installation environment of a robot device; FIG. 3 is a diagram for explaining inertial force and air resistance when the movement speed of a robot hand is high and the movement acceleration is large; FIG. 4 is a diagram for explaining inertial force and air resistance when the movement speed of a robot hand is low and the movement acceleration is small; FIG. 5 is a diagram for explaining inertial force and air resistance when the frontal projected area of ​​an object is large; A diagram for explaining inertial force and air resistance when the mass of an object is small. A diagram for explaining inertial force and air resistance when the mass of an object is large. A diagram for explaining inertial force and air resistance when the mass of an object is small. A flowchart (part 1) showing an example of operation of a robot control device. A flowchart (part 2) showing an example of operation of a robot control device. A perspective view of the exterior showing an example of the configuration and installation environment of a robot device in a modified example. A diagram for explaining inertial force and air resistance when the moving direction of the robot hand and the gripping direction by the gripper are the same. A diagram for explaining inertial force and air resistance when the moving direction of the robot hand and the gripping direction by the gripper are perpendicular.

[0009] Hereinafter, embodiments will be described in detail with reference to the drawings as appropriate. However, more detailed description than necessary may be omitted. For example, detailed description of well-known matters or redundant description of substantially identical configurations may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. Note that the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0010] (Background to the development of the embodiments of the present disclosure) The substrate transport device of Patent Document 1 takes into account the displacement of the substrate from a predetermined position during transport, but does not take into account the possibility of the substrate falling during transport. Furthermore, this substrate transport device picks up and transports flat substrates and chips of similar weight and shape, but is not designed to pick up other objects (items) of various weights and shapes.

[0011] Furthermore, in the substrate conveying device of Patent Document 1, since the objects to be picked are substrates, there is no variation in the thickness of the objects, and there is no need to consider the center of gravity of the objects. On the other hand, a picking system that picks PET bottles or cardboard boxes picks and conveys items of various weights and shapes. Therefore, when picking various items, it is necessary to consider, for example, the center of gravity. If the substrate conveying device of Patent Document 1 is applied to picking various items, the success rate of picking the items may decrease.

[0012] In the following embodiments, a picking method and a picking control device that can improve the success rate of picking objects of various weights and shapes will be described.

[0013] 1 is a diagram showing an example of the configuration of a picking system 5 according to a first embodiment. The picking system 5 includes a robot device 10 and a robot control device 100.

[0014] <Configuration of Robot Device> The robot device 10 is a picking robot that performs picking operations. In response to instructions from the robot control device 100, the robot device 10 picks up various objects WK (workpieces) to be picked up and stored in a storage container 31A, and moves them to an outgoing container 31B for placement (storage). The robot device 10 has a robot arm 12 and a robot hand 13. The robot arm 12 moves the robot hand 13 to any position in three-dimensional space. The robot hand 13 includes a suction pad 15. The suction pad 15 picks up the objects WK. The robot device 10 may be any type of picking robot, such as an orthogonal pickup robot, an orthogonal two-finger robot, or an articulated robot. The robot device 10 shown in FIG. 2 below is an example of the robot device 10, but the configuration of the robot device 10 is not limited thereto.

[0015] 2 is an external perspective view showing an example of the configuration and installation environment of the robot device 10. In the diagram with arrows indicating directions, the X axis indicates the front-to-rear direction, the Y axis indicates the left-to-right direction, and the Z axis indicates the up-to-down direction. The X axis and Y axis are orthogonal to each other and are included in a horizontal plane. The Z axis is included in a longitudinal plane.

[0016] The robot device 10 is a manipulator having a six-axis robot arm 12, and a base unit 21 is installed in a sorting area for objects WK, a production line, or the like. The base unit 21 adjusts, for example, the height at which the robot arm 12 can operate. The robot device 10 has the robot arm 12 and a robot hand 13. The robot arm 12 has, for example, a swivel unit 23 attached to the top of the base unit 21 and rotates horizontally, an upper arm 25 attached to the swivel unit 23 and swings back and forth, a forearm 27 attached to the upper arm 25 and swings up and down, and a wrist 29 attached to the forearm 27. The wrist 29 has a suction pump 14 and has three degrees of freedom.

[0017] The robot hand 13 is attached below the wrist 29, i.e., below the robot arm 12. The robot hand 13 has a suction pad 15 and a support pipe 16. The inside of the support pipe 16 is connected to the suction pump 14 above the support pipe 16. The suction pad 15 is attached below the support pipe 16. Therefore, when the suction pump 14 is activated, the pressure inside the support pipe 16 is reduced, for example, to a vacuum state, allowing the suction pad 15 to suction the object WK.

[0018] The robot arm 12 holds the robot hand 13 so that it can move freely in three mutually perpendicular directions. The robot device 10 also has a motor that supplies driving force to operate the robot arm 12, the robot hand 13, and the suction pump 14.

[0019] 2, containers 31 (e.g., storage container 31A, output container 31B) that transport objects WK can freely enter and exit the area around the robot device 10. For example, the robot device 10 can transfer objects WK from one container 31 (e.g., storage container 31A) to another container 31 (e.g., output container 31B) and can repackage objects WK between containers 31. The robot device 10 can move freely up and down (Z direction), back and forth (X direction), and left and right (Y direction) relative to the container 31, and can therefore approach any position within the container 31 and grasp the object WK.

[0020] 2, the objects WK to be picked include objects WK of various weights and shapes, such as rectangular parallelepiped objects WK, flat plate-shaped objects WK, and elongated objects WK.

[0021] Returning to FIG. 1 , the robot device 10 includes a camera 11 , a robot arm 12 , a robot hand 13 , and an adsorption pump 14 .

[0022] The camera 11 may include, for example, an overhead camera that captures an image of the inside of the container 31. The image captured by the overhead camera (overhead image) is used to recognize the state inside the container 31 and the state of the object WK inside the container 31. For example, the object WK can be recognized (detected) based on the overhead image. The overhead camera may be installed, for example, at any position on the robot arm 12 of the robot hand 13, or at another position on the robot device 10, or may be installed outside the robot device 10.

[0023] The camera 11 may include, for example, a distance camera. The distance camera may be, for example, a stereo camera, and the distance from the camera 11 (distance camera) to the object WK can be measured (detected, recognized) based on an image (distance image) captured by the distance camera. Therefore, the height (e.g., z coordinate) of the object WK in three-dimensional space can be measured based on this distance image. Note that instead of measuring the distance using a distance camera, the distance may be measured using another distance sensor. The distance camera may be installed, for example, at any position on the robot hand 13, or at another position on the robot device 10. Note that the overhead camera and the distance camera may be integrated into one unit.

[0024] <Configuration of Robot Control Device> The robot control device 100 controls the robot device 10 in real time to perform a desired picking operation. The robot control device 100 monitors the operation of the robot device 10 in real time and can send predetermined instruction information to the robot control device 100.

[0025] The robot controller 100 includes a processor 110 , a memory 120 , an input device 130 , and a communication device 140 .

[0026] The processor 110 may be configured using, for example, a Central Processing Unit (CPU), a Digital Signal Processor (DSP), or a Graphics Processing Unit (GPU). The processor 110 may be configured using various integrated circuits (for example, a Large Scale Integration (LSI) or a Field Programmable Gate Array (FPGA)). The processor 110 realizes various functions by executing programs stored in the memory 120. The processor 110 comprehensively controls each section of the robot control device 100 and performs various processes.

[0027] The processor 110 controls the operation of the robot device 10 via the communication device 140. For example, the processor 110 may control the operation of the robot arm 12 and the robot hand 13 of the robot device 10, thereby controlling the picking operation and gripping of the target object WK by the robot device 10. The processor 110 may instruct the camera 11 to capture an image and cause it to capture an image. The processor 110 may control the operation (on / off, starting, and stopping) of the suction pump 14 of the robot device 10.

[0028] The processor 110 acquires various types of information via the input device 130 or the communication device 140. The processor 110 acquires captured images captured by the camera 11, detection information detected by a sensor, etc. The processor 110 may detect various events based on the acquired captured images or detection information, etc. For example, the processor 110 may detect (recognize) information about the object WK stored inside the container 31 (e.g., the presence or absence, shape, weight, material, size, position, center of gravity position, and distance to the object WK).

[0029] The memory 120 includes a primary storage device (e.g., Random Access Memory (RAM) or Read Only Memory (ROM)). The memory 120 may include a secondary storage device (e.g., a Hard Disk Drive (HDD) or a Solid State Drive (SSD)) or a tertiary storage device (e.g., an optical disk or an SD card). The memory 120 may also be an external storage medium, or may be detachable from the robot control device 100. The memory 120 stores various data, information, programs, etc.

[0030] The memory 120 stores, for example, robot configuration information relating to the configuration of the robot device 10. The robot configuration information includes, for example, information on a structure type ID, a hand type ID, and robot installation coordinates. The structure type ID is information indicating the type of structure of the robot device 10 (e.g., Cartesian robot, vertical articulated robot, or other structure type). The hand type ID is information indicating the type of robot hand 13 (e.g., suction, two-fingered, multi-fingered, or other hand type). The robot installation coordinate information is information indicating the position where the robot device 10 is installed. In addition, in the case of a suction type, the robot configuration information may further include information such as the area of ​​the suction pads 15 and the number of suction pads 15.

[0031] The memory 120 stores object information related to the object WK. The object information stores information such as the object ID, the shape of the object WK, the material of the object WK, the weight of the object WK, and the size of the object WK. The shape of the object WK may include, for example, a box, a cylinder, or a bag, or a flat, elongated, or other shape. The material of the object WK may include, for example, paper, metal, plastic, or other materials. The object information may also include information such as the gripping position of the object WK (e.g., the suction position), the center of gravity of the object WK, the distance between the gripping position and the center of gravity of the object WK, the frontal projection area in the direction of movement of the object WK, and the air resistance coefficient of the object WK.

[0032] The input device 130 may include various buttons, keys, a keyboard, a touch panel, a microphone, a sensor, or other input devices. The input device 130 accepts input of various data, information, and the like. The input device 130 may be operated, for example, by an administrator or an operator who manages the robot control device 100. For example, a sensor may be provided inside or around each robot device 10. The sensor may include a vacuum sensor (e.g., a pressure sensor) that measures the degree of vacuum, a sensor that detects the state (position, angle, posture, etc.) of the robot arm 12 or the robot hand 13, and the like. The sensor may also include a sensor that detects the pressure applied to the gripping means (e.g., a suction pad, a gripper) when gripping the target object WK.

[0033] The communication device 140 communicates various data or information according to a wired or wireless communication method. The communication method used by the communication device 140 may include a local area network (LAN), a wide area network (WAN), a mobile phone network, or power line communication. The communication device 140 is connected to the robot device 10 and other external devices via a wired or wireless connection so as to be able to communicate with them.

[0034] For example, the communication device 140 sends an image capture instruction for the camera 11 to the robot device 10 and acquires an image captured by the camera 11 from the robot device 10. The communication device 140 sends an operation instruction for operating the robot arm 12, the robot hand 13, or the like to the robot device 10. The communication device 140 acquires information such as the position, angle, or posture of the robot arm 12, the robot hand 13, or the like from the robot device 10 (sensor).

[0035] It should be noted that only one robot control device 100 may be provided for a plurality of robot devices 10, or one may be provided for each robot device 10.

[0036] Although the robot control device 100 has been described as having each component and function in a single device, this is not limiting. For example, the components and functions of the robot control device 100 may be distributed and configured as a system (robot control system). The system may be configured as a cloud-based system on a network, or as an on-premise server device.

[0037] <Considerations on Gripping of Object WK by Robot Apparatus 10> Next, the gripping of the object WK by the robot apparatus 10 will be considered.

[0038] The gripping force W when the robot device 10 grips the object WK is determined based on the atmospheric pressure P0, the pressure P of the suction pads 15, the pad area A, and the number n of pads. When the robot device 10 suctions the object WK, the gripping force W is a suction force. The pressure P is the pressure of the suction pads 15 on the object WK. The pad area A is the area of ​​the suction surface of the suction pad 15. The number n of pads is the number of suction pads 15 provided on the robot device 10.

[0039] The gripping force W can be calculated, for example, according to the following formula (1): W=(P-P0)*A*n (formula 1) where "*" is a multiplication sign.

[0040] When the suction surface of the suction pad 15 is aligned along a horizontal plane and the robot device 10 picks up an object WK in a direction perpendicular to the suction pad 15, i.e., along the Z direction, the robot device 10 can hold the object WK with a gripping force W close to the theoretical value. On the other hand, when a force acts on the suction pad 15 in a shearing direction, particularly in a rotational direction, the gripping force W becomes smaller than the theoretical value, increasing the possibility of suction failure. Forces in the shearing direction and rotational direction can be defined by a moment M.

[0041] The moment M is determined based on the distance L between the gripping position p1 (suction position) of the target object WK and the center of gravity position p2, the inertial force Fa acting on the target object WK, and the air resistance Fd acting on the target object WK. The gripping position p1 is the reference position for the moment M. The gripping position p1 is the position where the suction pad 15 comes into contact with the target object WK and grips (suctions) the target object WK. The center of gravity position p2 is the center of gravity of the target object WK.

[0042] The moment M can be calculated, for example, according to the following formula (2): M=L*(Fa+Fd) (formula 2)

[0043] The inertial force Fa is determined based on the mass m and the movement acceleration a. The mass m is the mass of the object WK attracted to the suction pad 15. The movement acceleration a is the acceleration when the object WK attracted to the suction pad 15 moves.

[0044] The inertial force Fa can be calculated, for example, according to the following (Equation 3): Fa=-m*a (Equation 3) In other words, the inertial force Fa acts in the opposite direction to the direction in which the movement acceleration a acts.

[0045] Furthermore, when the attracted object WK undergoes rotational motion, the movement acceleration a is determined based on the movement velocity v, the rotation radius r, and the angular velocity ω. The movement velocity v is the movement velocity when the object WK moves. The rotation radius r is the rotation radius when the object WK rotates and moves. The angular velocity ω is the angular velocity when the object WK rotates and moves.

[0046] The movement acceleration a when the attracted object WK rotates can be calculated, for example, according to the following (Equation 4): a=v ２ / r=r*ω^2 (Equation 4) Here, "^" is an exponent (power) sign.

[0047] The air resistance Fd is determined based on the air density ρ, the air resistance coefficient Cd, the frontal projection area S, and the airspeed V. The frontal projection area S is the area of ​​the surface (front) projected in the direction of movement (direction of travel) of the object WK. The airspeed V is the airspeed of the adsorbed object WK during movement and includes the moving speed v. Therefore, when the wind speed is 0, the airspeed V is equal to the moving speed v. The air density ρ, the air resistance coefficient Cd, and the airspeed V may be known values ​​and may be stored, for example, in the memory 120. The air resistance coefficient Cd may be determined for each object WK and may be included in the object information and stored in the memory 120. The air resistance coefficient Cd may be omitted for simplification.

[0048] The air resistance Fd can be calculated, for example, according to the following (Equation 5): Fd=-1 / 2*ρ*Cd*S*V ２ (Equation 5) In other words, the air resistance Fd acts in the opposite direction to the direction in which the airspeed V acts.

[0049] It should be noted that the influence of the inertial force Fa is dominant on the moment M, except when the air resistance Fd is large and the moving speed v is high. In this case, the moment M may be derived in a simplified manner by considering only the inertial force Fa. In this case, the moment M can be calculated according to Equation 6: M=L*Fa (Equation 6)

[0050] In response to such a gripping force W and moment M, the processor 110 of the robot control device 100 limits at least one of the movement speed v and the movement acceleration a when the robot hand 13 grips (adsorbs) and moves the object WK, based on the gripping force W and the moment M. When limiting the movement speed v, the processor 110 sets, for example, an upper limit for the movement speed v and controls the movement speed v so that it is equal to or less than this upper limit. Similarly, when limiting the movement acceleration a, the processor 110 sets, for example, an upper limit for the movement acceleration a and controls the movement acceleration a so that it is equal to or less than this upper limit.

[0051] When determining the moving speed v and the moving acceleration a, the processor 110 calculates M / W, which is the ratio of the gripping force W to the moment M. When calculating M / W, the absolute values ​​of the moment M and the gripping force W are used. The ratio (M / W) is the ratio (proportion) of the moment M to the gripping force W. The larger the ratio (M / W), the larger the moment M relative to the gripping force W, making it more likely that the object WK will fall off (drop) from the suction pad 15. Therefore, when the ratio (M / W) is greater than a predetermined threshold th, the processor 110 limits the moving speed v and the moving acceleration a of the robot hand 13. This allows the robot control device 100 to simultaneously shorten the time it takes for the robot device 10 to transport the object WK and prevent the object WK from falling off.

[0052] Specifically, the processor 110 may calculate the gripping force W based on the atmospheric pressure P, the pressure P, the pad area A, and the number of pads n. The processor 110 may calculate the gripping force W according to the above (Equation 1).

[0053] The processor 110 may also calculate the moment M based on the distance L between the grip position p1 and the center of gravity p2 of the object WK, the inertial force Fa acting on the object WK, and the air resistance Fd acting on the object WK. The processor 110 may calculate the moment M according to the above (Equation 2).

[0054] The processor 110 may also calculate the inertial force Fa based on the mass m and the movement acceleration a. The processor 110 may calculate the inertial force Fa according to the above (Equation 3).

[0055] Furthermore, when the attracted object WK undergoes a rotational movement, the processor 110 may calculate the movement acceleration a based on the movement velocity v, the rotation radius r, and the angular velocity ω. The processor 110 may calculate the movement acceleration a according to the above (Equation 4).

[0056] The processor 110 may also calculate the air resistance Fd based on the air density ρ, the air resistance coefficient Cd, the frontal projection area S, and the airspeed V. The processor 110 may calculate the air resistance Fd according to the above (Equation 5).

[0057] Alternatively, the processor 110 may derive a simplified value of the moment M by taking into account only the inertial force Fa. The processor 110 may calculate the moment M according to the above (Equation 6).

[0058] The processor 110 may obtain information on each parameter for deriving the above-mentioned gripping force W and moment M from the memory 120, from a sensor, or from an external device via the communication device 140.

[0059] In this way, the processor 110 may obtain, by calculation, information on the gripping force W for gripping the target object WK. The processor 110 may obtain, by calculation, information on the moment M associated with the rotation when gripping the target object WK.

[0060] 3A is a diagram illustrating the inertial force Fa and the air resistance Fd when the movement speed v of the robot hand 13 is high (e.g., movement speed v1) and the movement acceleration is high (e.g., movement acceleration a1). FIG. 3B is a diagram illustrating the inertial force Fa and the air resistance Fd when the movement speed v of the robot hand 13 is low (e.g., movement speed v2) and the movement acceleration is low (e.g., movement acceleration a2). Note that the movement speed v1 is higher than the movement speed v2.

[0061] The faster the movement speed v of the robot hand 13, the faster the movement speed v of the object WK suctioned to the robot hand 13. Therefore, the air resistance Fd increases. Therefore, the moment M according to (Equation 2) increases, and the object WK is more likely to fall off the suction pad 15.

[0062] The slower the movement speed v of the robot hand 13, the slower the movement speed v of the object WK suctioned to the robot hand 13. Therefore, the inertial force Fa and the air resistance Fd become smaller. Therefore, the moment M becomes smaller according to (Equation 2), and the object WK is less likely to fall off the suction pad 15.

[0063] The state in Fig. 3A applies not only when the movement speed v of the robot hand 13 is high, but also when the movement acceleration a of the robot hand 13 is high (for example, movement acceleration a1). The state in Fig. 3B applies not only when the movement speed v of the robot hand 13 is low, but also when the movement acceleration a of the robot hand 13 is low (for example, movement acceleration a2). Note that the movement acceleration a1 is greater than the movement acceleration a2.

[0064] In response to this, the processor 110 controls at least one of the movement speed v and the movement acceleration a of the robot hand 13 based on the ratio (M / W). For example, if the ratio (M / W) is greater than a predetermined threshold th, at least one of the movement speed v and the movement acceleration a of the robot hand 13 is limited. For example, in the case of FIG. 3A , since at least one of the movement speed v and the movement acceleration a is large, the ratio (M / W) is greater than the threshold th, and the processor 110 limits at least one of the movement speed v and the movement acceleration a of the robot hand 13. For example, in the case of FIG. 3B , since at least one of the movement speed v and the movement acceleration a is small, the ratio (M / W) is equal to or less than the threshold th, and the processor 110 does not limit the movement speed v and the movement acceleration a of the robot hand 13.

[0065] The robot control device 100 can reduce the inertial force Fa by reducing the movement acceleration a, thereby reducing the moment M and preventing the object WK from falling off. The robot control device 100 can reduce the air resistance Fd by reducing the movement velocity v, thereby reducing the moment M and preventing the object WK from falling off.

[0066] Fig. 4A is a diagram illustrating the inertial force Fa and air resistance Fd when the frontal projected area S of the object WK is large (for example, frontal projected area S1). Fig. 4B is a diagram illustrating the inertial force Fa and air resistance Fd when the frontal projected area S of the object WK is small (for example, frontal projected area S2). Note that the frontal projected area S1 is larger than the frontal projected area S2. Fig. 4A also assumes that the moving speed v (moving speed v3) is very high and the object WK has a small mass.

[0067] Referring to (Equation 5), air resistance Fd is proportional to the frontal projected area S and proportional to the square of the speed. Therefore, the larger the frontal projected area S, the larger the air resistance Fd. Therefore, according to (Equation 2), the moment M becomes larger, and the object WK becomes more likely to fall off the suction pad 15. On the other hand, the smaller the frontal projected area S, the smaller the air resistance Fd. Therefore, according to (Equation 2), the moment M becomes smaller, and the object WK becomes less likely to fall off the suction pad 15.

[0068] In response to this, the processor 110 limits at least one of the movement speed v and the movement acceleration a of the robot hand 13 based on the ratio (M / W). For example, in the case of Fig. 4A, the frontal projection area S is large, so the ratio (M / W) is greater than the threshold value th, and the processor 110 limits at least one of the movement speed v and the movement acceleration a of the robot hand 13. For example, in the case of Fig. 4B, the frontal projection area S is small, so the ratio (M / W) is equal to or less than the threshold value th, and the processor 110 does not limit the movement speed v and the movement acceleration a of the robot hand 13.

[0069] Normally, the inertial force Fa is dominant over the air resistance Fd in the moment M. For example, as shown in FIG. 4B , when the movement speed v (e.g., movement speed v4) of the robot hand 13 is small, the frontal projection area S in the movement direction of the object WK is small, and the mass m of the object WK is large, the inertial force Fa is dominant over the air resistance Fd in the moment M. In this case, the processor 110 may simplify and calculate the moment M according to (Equation 6).

[0070] On the other hand, as shown in FIG. 4A, when the movement speed v (e.g., movement speed v3) of the robot hand 13 is very high, the frontal projection area S in the movement direction of the object WK is large, and the mass m of the object WK is small, the air resistance Fd becomes more dominant than the inertial force Fa in the moment M. In this case, the processor 110 can derive the moment M in a simplified manner by considering only the air resistance Fd. In this case, the processor 110 may calculate the moment M according to (Equation 7). M=L*Fd (Equation 7)

[0071] 5A is a diagram illustrating the inertial force Fa and the air resistance Fd when the distance L between the grip position p1 and the center of gravity p2 of the target object WK is large (for example, distance L1). FIG. 5B is a diagram illustrating the inertial force Fa and the air resistance Fd when the distance L between the grip position p1 and the center of gravity p2 of the target object WK is small (for example, distance L2). Note that distance L1 is larger than distance L2.

[0072] With reference to (Equation 2), the greater the distance L, the greater the moment M, and the more likely the object WK is to fall off the suction pad 15. On the other hand, the smaller the distance L, the smaller the moment M, and the more difficult it is for the object WK to fall off the suction pad 15. Therefore, even if the object WK to be attracted has the same mass m, the ease with which the object WK falls off differs depending on the distance L.

[0073] In response to this, the processor 110 controls at least one of the movement speed v and the movement acceleration a of the robot hand 13 based on the ratio (M / W). For example, in the case of Fig. 5A, the distance L is large, so the ratio (M / W) is larger than the threshold value th, and the processor 110 limits at least one of the movement speed v and the movement acceleration a of the robot hand 13. For example, in the case of Fig. 5B, the distance L is small, so the ratio (M / W) is equal to or smaller than the threshold value th, and the processor 110 does not limit the movement speed v and the movement acceleration a of the robot hand 13.

[0074] 6A is a diagram illustrating the inertial force Fa and the air resistance Fd when the mass m of the object WK is large (for example, mass m1). FIG. 6B is a diagram illustrating the inertial force Fa and the air resistance Fd when the mass m of the object WK is small (for example, mass m2). Note that mass m1 is larger than mass m2.

[0075] With reference to (Equation 3), the larger the mass m, the larger the inertial force Fa. Therefore, according to (Equation 2), the moment M becomes larger, and the target object WK becomes more likely to fall off the suction pad 15. On the other hand, the smaller the mass m, the smaller the inertial force Fa. Therefore, according to (Equation 2), the moment M becomes smaller, and the target object WK becomes less likely to fall off the suction pad 15. In other words, as shown in FIGS. 6A and 6B , even if the distance L between the grip position p1 and the center of gravity position p2 of the target object WK is the same, the likelihood of the target object WK falling off differs depending on the magnitude of the mass m.

[0076] In response to this, the processor 110 controls at least one of the movement speed v and the movement acceleration a of the robot hand 13 based on the ratio (M / W). For example, in the case of Fig. 6A, since the mass m is large, the ratio (M / W) becomes larger than the threshold value th, and the processor 110 limits at least one of the movement speed v and the movement acceleration a of the robot hand 13. For example, in the case of Fig. 6B, since the mass m is small, the ratio (M / W) becomes equal to or smaller than the threshold value th, and the processor 110 does not limit the movement speed v and the movement acceleration a of the robot hand 13.

[0077] <Operation of Robot Control Device> Next, the operation of the robot control device 100 will be described.

[0078] 7A and 7B are flowcharts showing an example of the operation of the robot control device 100. The processes in Fig. 7A and 7B are performed, for example, for each picking operation (each pick).

[0079] 7A, the processor 110 sets the movement speed v of the robot hand 13 to a movement speed vi, and sets the movement acceleration a of the robot hand 13 to a movement acceleration ai (S11). The movement speed vi is, for example, the maximum speed that can be set by the robot control device 100. The movement acceleration ai is, for example, the maximum acceleration that can be set by the robot control device 100. The movement speed vi is an example of an initial value of the movement speed v. The movement acceleration ai is an example of an initial value of the movement acceleration a.

[0080] The processor 110 controls the movement of the robot hand 13, and controls the suction pad 15 to contact and grasp the object WK (S12). The suction pad 15 contacts and grasps the object WK in accordance with the control of the processor 110. The suction of the object WK by the robot hand 13 is an example of grasping the object WK.

[0081] The processor 110 controls the robot hand 13 to move (rise) the object WK in the vertical direction (positive Z direction) at the movement speed vi and movement acceleration ai set in step S11 while grasping the object WK (S13).

[0082] The processor 110 determines whether the object WK has fallen off the suction pad 15 due to the lifting of the robot hand 13 (S14). For example, the processor 110 determines the degree of vacuum based on detection information from the vacuum sensor via the communication device 140 and determines whether the object WK is being gripped based on the degree of vacuum. The processor 110 may determine that the suction pad 15 is adsorbing the object WK when the degree of vacuum is higher than a predetermined value, and that the suction pad 15 is not adsorbing the object WK and has fallen off when the degree of vacuum is lower than the predetermined value. Here, the degree of vacuum is 100% in the case of an absolute vacuum and 0% when the pressure is the same as atmospheric pressure. It can be said that the degree of vacuum is high when the pressure is close to an absolute vacuum, and low when the pressure is opposite. The degree of vacuum may be expressed as an actual pressure instead of a percentage. The processor 110 may also acquire an image captured by the camera 11 and determine whether the object WK has fallen off based on the captured image.

[0083] If it is determined that the target object WK has fallen off the suction pad 15 (No in step S14), the processor 110 sets the movement speed v to movement speed v0 and the movement acceleration a to movement acceleration a0 (S15). The movement speed v0 is, for example, about 20% of the movement speed vi. The movement acceleration a0 is, for example, about 20% of the movement acceleration ai. Then, the process proceeds to step S12. The processor 110 then performs the processes of steps S12 and S13 again to retry the robot hand 13 grasping the target object WK and moving it in the vertical direction.

[0084] In other words, when the object WK is lifted vertically in step S13, no moment M is applied to the object WK. Therefore, the robot device 10 can exert a gripping force W close to the theoretical value shown in, for example, (Equation 1). If the object WK falls off at this time, it is possible that the mass m of the object WK is large, for example. Note that since the object WK has not been moved horizontally at the stage of step S13, there is a high possibility that the object WK will fall into the container 31 (e.g., storage container 31A). Therefore, the processor 110 can retry by limiting the movement speed v and movement acceleration a, as in step S15.

[0085] The processor 110, for example, acquires various types of information from the memory 120 and acquires various types of information detected by the sensors (various types of detection information) from the sensors. The processor 110 may also acquire various types of information from a server or the like that provides information via the communication device 140. This various information includes information (parameters) for deriving the moment M and the gripping force W. Therefore, at least a portion of this various information is an example of information related to the moment M of the gripping position of the target object WK.

[0086] For example, the processor 110 may acquire at least a portion of object information related to the object WK from the memory 120. For example, the processor 110 acquires various information including information on the mass m of the object WK, the distance L between the grip position p1 and the center of gravity p2 of the object WK, the frontal projection area S in the movement direction of the robot hand 13, and the air resistance coefficient Cd (S16). The processor 110 may acquire at least a portion of robot configuration information related to the configuration of the robot device 10 from the memory 120. For example, the processor 110 may acquire information on the area and number of suction pads 15. The processor 110 may acquire information such as the pressure of the suction pads 15, atmospheric pressure, and the speed and acceleration of the suction pads 15 (robot hand 13) from a sensor. The processor 110 may acquire information such as the speed and acceleration of the suction pads 15 (robot hand 13) from setting information (e.g., command values) stored in the memory 120.

[0087] Note that acquisition of at least some of this information may be omitted, or other information may be acquired. Note that instead of directly acquiring information on the frontal projection area S, the processor 110 may acquire information on the movement direction of the robot hand 13, acquire shape information and size information of the object WK, and derive (e.g., calculate) the frontal projection area S in the movement direction of the object WK based on the movement direction of the robot hand 13 and the shape and size of the object WK. Note that the processor 110 may derive (e.g., calculate) each of the above information based on, for example, an image captured by the camera 11 or detection information by a sensor.

[0088] The processor 110 calculates the moment M and the grip force W based on the acquired information (S17). For example, the processor 110 may calculate the moment M based on at least one of (Equation 2) to (Equation 7). For example, the processor 110 may calculate the grip force W based on (Equation 1).

[0089] Proceed to FIG. 7B. The processor 110 calculates the ratio (M / W) of the moment M to the gripping force W. The processor 110 determines whether the ratio (M / W) is greater than a threshold value th1, i.e., whether M / W > th1 is satisfied (S21). If M / W > th1 is not satisfied (No in step S21), the processor 110 determines that the moment M relative to the gripping force W is small, and therefore there is little possibility that the object WK will fall off even if it is gripped with the current gripping force W and moved (transported) in the horizontal direction. Therefore, the processor 110 controls the object WK to be transported without changing the set values ​​of the moving speed v and moving acceleration a (S25). Note that the horizontal movement of the object WK is, for example, movement between multiple containers 31, and is also referred to as transporting the object WK.

[0090] If M / W>th1 is satisfied (Yes in step S21), the processor 110 determines whether the ratio (M / W) is greater than a threshold value th2, i.e., whether M / W>th2 is satisfied (S22). Note that the threshold value th2 is greater than the threshold value th1. In other words, step S22 determines whether M / W is greater than the stricter threshold value th2.

[0091] If M / W>th2 is not satisfied (No in step S22), the processor 110 limits the movement speed v to a movement speed v1 and the movement acceleration a to a movement acceleration a1 (S23). The movement speed v1 is, for example, about 50% of the movement speed vi. The movement acceleration a1 is, for example, about 50% of the movement acceleration ai.

[0092] That is, in this case, the processor 110 slightly limits the moving speed v1 and the moving acceleration a1 because, taking the ratio (M / W) into consideration, there is a possibility that the object WK may fall off the suction pad 15 while being transported. Note that here, if the moving speed v0 and the moving acceleration a0 are set in step S15, the processor 110 may limit the moving speeds v1 and v0 to the stricter (smaller) one, or may limit the moving accelerations a1 and a0 to the stricter (smaller) one.

[0093] If M / W>th2 is satisfied (Yes in step S22), the processor 110 limits the movement speed v to movement speed v2 and the movement acceleration a to movement acceleration a2 (S24). The movement speed v2 is smaller than the movement speed v1. The movement acceleration a2 is smaller than the movement acceleration a1. The movement speed v2 is, for example, about 20% of the movement speed vi. The movement acceleration a2 is, for example, about 20% of the movement acceleration ai.

[0094] That is, in this case, when M / W is taken into consideration, the processor 110 greatly limits the moving speed v2 and the moving acceleration a2 because there is a high possibility that the object WK will fall off the suction pad 15 while being transported. Note that here, if the moving speed v0 and the moving acceleration a0 are set in step S15, the processor 110 may limit the moving speeds v2 and v0 to the stricter (smaller) one, or may limit the moving accelerations a2 and a0 to the stricter (smaller) one.

[0095] After processing step S23 or step S24, the processor 110 controls the robot hand 13 to transport the object WK while grasping the object WK at a limited movement speed v (vi, v0, v1 or v2) and movement acceleration a (ai, a0, a1 or a2) (S25).

[0096] The processor 110 may determine whether the transport of the object WK was successful. For example, the processor 110 may determine the degree of vacuum based on detection information from a vacuum sensor via the communication device 140 and determine whether the object WK is being gripped based on the degree of vacuum. The processor 110 may determine that the suction pad 15 is adsorbing the object WK when the degree of vacuum is higher than a predetermined value, and that the suction pad 15 is not adsorbing the object WK and has fallen off when the degree of vacuum is lower than the predetermined value. Here, the degree of vacuum is 100% in the case of an absolute vacuum and 0% when the pressure is the same as atmospheric pressure. A degree of vacuum close to an absolute vacuum is high, and vice versa. The degree of vacuum may be expressed as an actual pressure instead of a percentage. The processor 110 may obtain an image captured by the camera 11 and determine whether the transport of the object WK was successful based on the captured image.

[0097] If the transport of the object WK fails, the processor 110 may correct the threshold value th (e.g., threshold value th1, threshold value th2) that is compared with the ratio (M / W), for example, by reducing the threshold value th. This is because failure to transport the object WK despite limiting the moving speed v and the moving acceleration a is considered to be due to low accuracy of the threshold value th.

[0098] Furthermore, even if the transport of the object WK fails, for example, if the transport of the object WK is repeated a predetermined number of times and the transport failure continues, the processor 110 may correct (e.g., decrease) the threshold value th. For example, the processor 110 may correct the threshold value th when the transport failure rate reaches a predetermined value (e.g., 1%) or more. Note that instead of correcting the threshold value th, the movement speed v and the movement acceleration a may be corrected (e.g., decreased).

[0099] Note that the processor 110 may limit the movement speed v by limiting the movement acceleration a, rather than explicitly controlling the movement speed v. By reducing the movement acceleration a, the movement speed v is less likely to increase. Because the movement distance (e.g., the distance between the containers 31) by the robot hand 13 is relatively short, by reducing the movement acceleration a, the movement speed v can be limited to be small as a result.

[0100] If it is desired to avoid dropping the object WK as the robot hand 13 rises as much as possible, the processor 110 may add a restriction on the speed and acceleration using the following F / W ratio and another threshold th', based on the same concept as the speed and acceleration restriction based on the M / W ratio (M=M / W) of the moment M and the gripping force W and the threshold th in steps S16 to S22 described above. The F / W ratio is the ratio of the sum F of the inertial force Fa, the air resistance Fd, and the gravity Fg (F=Fa+Fd+Fg) to the gripping force W. Note that Fg=m*g, where m is the mass of the object WK and g is the gravitational acceleration.

[0101] In the operation example shown in FIGS. 7A and 7B , the processor 110 determines initial values ​​for the moving speed v and the moving acceleration a, and limits the moving speed v and the moving acceleration a according to the value of M / W. In this case, if the initial values ​​are set to the maximum speed and maximum acceleration at which the robot device 10 can move, or if they are set to a large value even if not the maximum, the processor 110 limits the moving speed v and the moving acceleration a, i.e., limits the set values ​​(actual speed) in a direction to decrease the moving speed v and the moving acceleration a. On the other hand, if the initial values ​​are set to values ​​close to 0 or a small value at which the robot device 10 can move, the processor 110 limits the moving speed v and the moving acceleration a, i.e., limits the set values ​​(actual speed) in a direction to increase the moving speed v and the moving acceleration a. Alternatively, the processor 110 may not set initial values ​​for the moving speed v and the moving acceleration a, and may directly determine the moving speed v and the moving acceleration a based on the moment M. The processor 110 may determine (limit) the moving speed v and the moving acceleration a by storing a table in the memory 120 that stores candidate values ​​for the moving speed v and the moving acceleration a and selecting candidate values ​​from the table based on the value of M / W, or may determine them steplessly without using a table.

[0102] In this way, the picking system 5 of this embodiment can predict to some extent whether the robot hand 13 is likely to drop the object WK depending on the configuration of the robot device 10 and the characteristics of the object WK. The robot control device 100 can increase the success rate of the picking operation (picking success rate) including transportation by transporting the object WK while limiting the movement speed v and movement acceleration a for an object WK that is likely to drop. Furthermore, for an object WK that is unlikely to drop, by not limiting the movement speed v and movement acceleration a, it is possible to transport the object WK as fast as possible and shorten the transportation time.

[0103] For example, if the target object WK is vertically long, the grip position p1 and the center of gravity p2 are far apart, and therefore a twisting (rotating) force is applied due to inertial force. In this case, it can be determined that there is a high possibility that the target object WK will be dropped. The twisting (rotating) force is represented by the moment M.

[0104] When gripping and moving the object WK, the picking system 5 focuses on the moment M. The smaller the moment M, the more difficult it is to drop the object WK, and the larger the moment M, the easier it is to drop the object WK. The robot control device 100 also focuses on the gripping force W. The larger the gripping force W, the more difficult it is to drop the object WK, and the smaller the gripping force W, the easier it is to drop the object WK. The robot control device 100 uses the moment M and the gripping force W to limit the movement speed v and the movement acceleration a depending on the ratio (M / W), thereby shortening the time it takes for the robot device 10 to transport the object WK and preventing the object WK from falling off.

[0105] Furthermore, when the inertial force Fa is dominant among the inertial force Fa and the air resistance Fd, the robot control device 100 can reduce the inertial force Fa and the moment M, thereby preventing the object WK from falling, by limiting the movement acceleration a in particular. Furthermore, when the air resistance Fd is dominant among the inertial force Fa and the air resistance Fd, the robot control device 100 can reduce the air resistance Fd and the moment M, thereby preventing the object WK from falling, by limiting the movement speed v.

[0106] Furthermore, the robot control device 100 makes it difficult for the target object WK to fall by controlling the speed and acceleration of the robot hand 13, thereby eliminating the need to change the suction pads 15 and other end effectors to suit the weight and shape of the target object WK. Therefore, the picking system 5 does not require a changing device or autochanger for changing the suction pads 15 and other end effectors, reducing costs and eliminating the need for time for changing them.

[0107] (Modification) The suction-type hand (robot hand 13) may not be the suction-type hand, but may be a hand of another type, for example, a gripper-type hand.

[0108] 8 is a perspective view showing an example of the configuration and installation environment of a robot device 10A according to a modified example. In FIG. 8, the same components as those in FIG. 2 are denoted by the same reference numerals, and the description thereof will be omitted or simplified.

[0109] Compared to the robot device 10, the robot device 10A has a gripper 18 and a support member 19 instead of the suction pump 14, the suction pad 15, and the support pipe 16. The gripper 18 and the support member 19 are included in a robot hand 13A.

[0110] The gripper 18 is, for example, a parallel gripper and a two-fingered hand, but may be a gripper other than a parallel gripper. The gripper 18 can be opened and closed under control of the processor 110 of the robot control device 100. The gripper 18 clamps and holds the object WK by closing the gripper 18, and releases the object WK by opening the gripper 18.

[0111] The support member 19 is attached below the wrist portion 29 and supports the gripper 18 .

[0112] The gripping force W of the robot device 10A is determined based on the static friction coefficient μ between the object WK and the gripper 18 and the normal force F when the gripper 18 grips the object WK. The gripping force W can be calculated, for example, according to the following (Equation 1). The gripping force W can also be said to be the holding force in the vertical direction exerted by the gripper 18. W=μ*F (Equation 8)

[0113] The processor 110 may calculate the gripping force W of the gripper 18 (robot hand 13) based on the static friction coefficient μ between the object WK and the gripper 18 and the normal force F when the gripper 18 grips the object WK. The processor 110 may calculate the gripping force W according to the above-mentioned (Equation 8). The processor 110 may acquire information on the static friction coefficient μ from, for example, the memory 120, a sensor, or an external device. The processor 110 may acquire information on the normal force F of the gripper 18 from a sensor.

[0114] When the gripper 18 grips the object WK, if the gripper 18 is no longer in a stationary state, the frictional force decreases, making the object WK more likely to fall.

[0115] In the robot device 10A, the moment M is small if the gripper 18 can grip the object WK near the center of gravity p2. Therefore, if the gripping force W in the vertical direction (Z direction) exceeds the weight of the object WK, the object WK is less likely to fall. On the other hand, when the robot device 10A grips the object WK with the gripper 18 at a gripping position p1 away from the center of gravity p2 of the object WK, the moment M occurs similarly to the robot device 10. The moment M may be derived according to the above-described (Equation 2) to (Equation 7), etc. Note that in the robot device 10A, the object WK is gripped by the gripper 18 rather than by suction with the suction pad 15. Therefore, in the description of the parameters for deriving the moment M, "suction" is treated as "grasping."

[0116] 9 is a diagram for explaining the inertial force Fa and the air resistance Fd when the movement direction of the robot hand 13 and the gripping direction (pinching direction, opening and closing direction) of the gripper 18 are the same direction. Here, both the movement direction and the gripping direction are the left-right direction in FIG.

[0117] 10 is a diagram for explaining the inertial force Fa and the air resistance Fd when the movement direction of the robot hand 13 and the gripping direction (squeezing direction) of the gripper 18 are perpendicular to each other. Here, the movement direction is the left-right direction in FIG. 10, and the gripping direction is the depth direction in FIG. 10.

[0118] In Fig. 9, the inertial force Fa and air resistance Fd acting in the movement direction can be suppressed by the normal force F of the gripper 18. As a result, the moment M is small, and the object WK is less likely to fall off the gripper 18. On the other hand, in Fig. 10, it is difficult to suppress the inertial force Fa and air resistance Fd acting in the movement direction by the normal force F of the gripper 18. As a result, the moment M is large, and the object WK is more likely to rotate, and the object WK is more likely to fall off the gripper 18.

[0119] In response to this, the processor 110 limits at least one of the movement speed v and the movement acceleration a of the robot hand 13 based on the ratio (M / W). For example, in the case of Fig. 9, the ratio (M / W) is smaller than the threshold value th, and the processor 110 does not limit the movement speed v and the movement acceleration a of the robot hand 13. For example, in the case of Fig. 10, the ratio (M / W) is equal to or smaller than the threshold value th, and the processor 110 limits at least one of the movement speed v and the movement acceleration a of the robot hand 13.

[0120] In this way, this embodiment can be applied even when the target object WK is pinched and grasped by the gripper 18 as in the robot device 10A.

[0121] (Summary of the embodiment) As described above, the present disclosure describes at least the following matters. Note that, in parentheses, examples of components corresponding to the above-described embodiment are shown, but the present disclosure is not limited to these.

[0122] (Item 1) A picking method for picking an object (object WK), comprising: controlling the gripping of the object; acquiring information on the moment (moment M) of the gripping position of the object; acquiring information on the gripping force (gripping force W) for gripping the object; determining at least one of an acceleration (movement acceleration a) and a speed (movement speed v) when the object moves based on the moment and the gripping force; and controlling the gripped object to move at least one of the determined acceleration and speed.

[0123] As a result, the picking method can determine at least one of the acceleration and speed of the object when it is moved, taking into account the gripping force used to grip the object and the moment generated in the object. This allows the object to be moved with a reduced moment generated when it is moved, preventing it from falling during movement. Therefore, the picking method can improve the success rate of picking objects of various weights and shapes.

[0124] (Item 2) The picking method according to Item 1, wherein determining at least one of the acceleration and the velocity includes correcting at least one of an initial value of the acceleration and an initial value of the velocity.

[0125] As a result, the picking method can modify (limit) the initial values ​​of acceleration and velocity, so that if the initial values ​​are small, the values ​​can be limited to be larger, and if the initial values ​​are large, the values ​​can be limited to be smaller.

[0126] (Item 3) The picking method according to Item 1 or 2, wherein determining at least one of the acceleration and the velocity includes limiting at least one of the acceleration and the velocity based on a ratio (M / W) of the moment to the gripping force.

[0127] This allows the picking method to limit at least one of acceleration and speed based on the ratio of the moment to the gripping force.

[0128] (Item 4) The picking method described in Item 3, wherein limiting at least one of the acceleration and the velocity includes: limiting at least one of the acceleration and the velocity to be smaller when the ratio of the moment to the gripping force is greater than a predetermined threshold (threshold th); and not limiting at least one of the acceleration and the velocity when the ratio of the moment to the gripping force is equal to or less than the predetermined threshold.

[0129] As a result, the picking method can limit at least one of the acceleration and speed during movement for an object whose ratio is greater than the threshold and is therefore likely to fall, thereby allowing the object to be successfully moved. Also, the picking method can successfully move an object whose ratio is equal to or less than the threshold and is therefore unlikely to fall, without limiting the acceleration and speed during movement.

[0130] (Item 5) The picking method according to any one of Items 1 to 4, wherein acquiring the information on the moment includes deriving the moment based on the distance between the gripping position of the object and the center of gravity of the object, and at least one of an inertial force acting on the object and air resistance acting on the object.

[0131] As a result, for example, the greater the distance between the grip position of the object and the center of gravity of the object, the greater the moment. For example, the greater the inertial force generated when the object moves, the greater the moment. For example, the greater the air resistance experienced by the object when moving, the greater the moment.

[0132] (Item 6) The picking method according to any one of Items 1 to 5, further comprising: controlling the object to move in a vertical direction; determining whether the grasped object has fallen during vertical movement; and, if it is determined that the object has fallen, restricting at least one of the acceleration and the velocity to be small, and gripping the object and moving the object in the vertical direction.

[0133] As a result, if the picking method fails to move vertically, there is a high possibility that the target will fall into the container it was stored in because there was no horizontal movement. Therefore, the picking method can increase the possibility of successfully moving the target vertically by limiting at least one of the acceleration and speed to a small value and retrying to grasp the target and move it horizontally.

[0134] (Item 7) The picking method according to any one of Items 1 to 6, wherein controlling the object to move includes controlling the object to move in a horizontal direction.

[0135] This allows the picking method to move (transport) the object horizontally while limiting at least one of the acceleration and speed as needed, thereby reducing the possibility of the object falling out of the container, even when the object is being picked up and transported from a container.

[0136] (Item 8) The picking method according to Item 4, further comprising: determining whether the transport of the object was successful; and correcting the threshold value to be smaller when it is determined that the transport of the object was unsuccessful.

[0137] If the transport of an object fails even when at least one of acceleration and speed is restricted as necessary, it is likely that the accuracy of the threshold value, which is the criterion for determining whether or not to restrict, is low. In contrast, the picking method can adjust the threshold value to further reduce the moment, making it easier to successfully transport the object. Therefore, the picking method can reduce the possibility of the object falling out of the container.

[0138] (Item 9) The picking method according to any one of Items 1 to 8, wherein the object is grasped by suction.

[0139] This allows the picking method to improve the success rate of picking objects of various weights and shapes, even when the objects are grasped by suction.

[0140] (Item 10) The picking method according to any one of Items 1 to 8, wherein the gripping of the object is gripping of the object by a gripper.

[0141] This allows the picking method to improve the success rate of picking objects of various weights and shapes, even when the objects are grasped by a gripper.

[0142] (Item 11) A picking control device (robot control device 100) that includes a processor (processor 110) and controls the picking of an object, wherein the processor: controls the gripping of the object; acquires information about the moment of the gripping position of the object; acquires information about the gripping force for gripping the object; determines at least one of the acceleration and speed during movement of the object based on the moment and the gripping force; and controls the gripped object to move at the acceleration and speed, at least one of which is determined.

[0143] This allows the picking control device to obtain the same effect as item 1.

[0144] Although various embodiments have been described above with reference to the drawings, it goes without saying that the present disclosure is not limited to such examples. It is clear that a person skilled in the art can conceive of various modifications or alterations within the scope of the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure. Furthermore, the components of the above-described embodiments may be combined in any manner without departing from the spirit of the invention.

[0145] In addition, the above embodiment may also be applicable to a program that realizes the functions of the warehouse management method, which is supplied to a computer (e.g., the robot control device 100) via a network or various storage media, and which is read and executed by the processor of this computer, as well as to the storage media on which this program is stored.

[0146] This disclosure is based on a Japanese patent application (Patent Application No. 2024-107397) filed on July 3, 2024, the contents of which are incorporated herein by reference.

[0147] The present disclosure is useful for a picking method and a picking control device that can improve the success rate of picking objects of various weights and shapes.

[0148] 5 Picking system 10, 10A Robot device 11 Camera 12 Robot arm 13, 13A Robot hand 14 Suction pump 15 Suction pad 16 Support pipe 18 Gripper 19 Support member 31 Container 31A Storage container 31B Outgoing container 100 Robot control device 110 Processor 120 Memory 130 Input device 140 Communication device WK Object

Claims

A picking method for picking an object, comprising: controlling the grasp of the object; obtaining information about a moment of a grip position of the object; acquiring information about a gripping force for gripping the object; determining at least one of an acceleration and a velocity of the object during movement based on the moment and the gripping force; controlling the grasped object to move at least one of the determined acceleration and velocity; A picking method having the following structure. 　 determining at least one of the acceleration and the velocity includes modifying at least one of an initial value of the acceleration and an initial value of the velocity; The picking method according to claim 1 . 　 determining at least one of the acceleration and the velocity includes limiting at least one of the acceleration and the velocity based on a ratio of the moment to the gripping force; The picking method according to claim 1 or 2. 　 Determining at least one of the acceleration and the velocity includes: If the ratio of the moment to the gripping force is greater than a predetermined threshold, limiting at least one of the acceleration and the velocity to be small; and not limiting at least one of the acceleration and the velocity when the ratio of the moment to the gripping force is equal to or less than the predetermined threshold. The picking method according to claim 3. 　 The acquiring of the moment information includes: deriving the moment based on a distance between a grip position of the object and a center of gravity position of the object, and at least one of an inertial force acting on the object and an air resistance acting on the object. The picking method according to claim 1 . 　 controlling the object to move vertically; determining whether the grasped object falls during vertical movement; When it is determined that the object has fallen, the method further includes: gripping the object and moving the object in a vertical direction while limiting at least one of the acceleration and the velocity to be small. The picking method according to claim 1 or 5. 　 Controlling the object to move includes: controlling the object to move horizontally; The picking method according to claim 1 or 5. 　 determining whether the object was successfully moved; correcting the threshold value to be smaller when it is determined that the movement of the object has failed. The picking method according to claim 4. 　 The gripping of the object is gripping of the object by suction. The picking method according to claim 1 or 5. 　 The gripping of the object is gripping of the object by a gripper. The picking method according to claim 1 or 5. 　 A picking control device that includes a processor and controls picking of an object, The processor: Controlling the grip of the object; acquiring information about a moment of a gripping position of the object; Acquire information about the gripping force used to grip the object; determining at least one of an acceleration and a velocity of the object during movement based on the moment and the gripping force; controlling the grasped object to move at least one of the determined acceleration and velocity; Picking control device.

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