ROBOT SYSTEM, PROCESSING METHOD, AND PROGRAM

Abstract

This robot system comprises: a setting means for setting restrictions on the range for the height to which an object is lifted, with a reference surface serving as a reference such height; and a calculation means for calculating, on the basis of the restrictions set by the setting means, a path on which the object is moved to a destination.

Description

[Technical Field]

[0001] The present disclosure relates to a robotic system, a processing method, and program Regarding. [Background technology]

[0002] Robots are used in various fields, including logistics. Some robots operate autonomously. Patent Document 1 discloses, as a related technology, a technology relating to a picking device that safely places an object while taking clearance into consideration. Furthermore, Patent Document 2 discloses, as a related technology, a technology relating to an article picking device that determines an approach path for grasping an object. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-181573 [Patent Document 2] Japanese Patent Application Laid-Open No. 2010-012567 Summary of the Invention [Problem to be solved by the invention]

[0004] With the technologies described in Patent Documents 1 and 2, it is difficult to avoid damage to an object if the object falls while the robot is moving it to its destination. Therefore, one of the objects of the present disclosure is to provide a robot system or the like that can reduce the possibility of damage to an object even if the object falls while the robot is moving it to its destination.

[0005] The aspects of the present disclosure provide a robot system, a processing method, and program One of the aims is to provide [Means for solving the problem]

[0006] In order to achieve the above object, according to one aspect of the present disclosure, a robot system includes: The system comprises a setting means for setting a restriction on the range of height for lifting an object relative to a reference plane, a calculation means for calculating a route for moving the object to a destination based on the restriction set by the setting means, and a processing means for setting an area where an obstacle exceeding a predetermined height exists as a no-entry area for the object and outputting an instruction to display the set no-entry area. .

[0007] To achieve the above object, according to another aspect of the present disclosure, a processing method includes: The computer sets a restriction on the range of heights to which the object can be lifted relative to a reference plane, calculates a path for moving the object to a destination based on the restriction, sets an area where an obstacle exceeding a predetermined height exists as a no-entry area for the object, and outputs an instruction to display the set no-entry area. .

[0008] To achieve the above object, according to another aspect of the present disclosure, a program includes: The method causes a computer to execute the following: setting a restriction on a range of heights for lifting an object relative to a reference plane; calculating a path for moving the object to a destination based on the set restriction; setting an area where an obstacle exceeding a predetermined height exists as a no-entry area for the object; and outputting an instruction to display the set no-entry area. . [Effects of the Invention]

[0009] According to each aspect of the present disclosure, even if an object falls while the robot is moving the object to its destination, the possibility of damage can be reduced. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a robot system according to a first embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram illustrating an example of the configuration of a control device according to the first embodiment of the present disclosure. [Figure 3] FIG. 2 is a first diagram showing an example of a GUI that accepts input of constraints in the first embodiment of the present disclosure. [Figure 4] FIG. 10 is a second diagram showing an example of a GUI that accepts input of constraints in the first embodiment of the present disclosure. [Figure 5] FIG. 2 is a diagram showing a first example of movement of an object when a constraint is set in the first embodiment of the present disclosure. [Figure 6] FIG. 10 is a diagram showing a second example of the movement of an object when a constraint is set in the first embodiment of the present disclosure. [Figure 7] FIG. 10 is a diagram showing a third example of the movement of an object when a constraint is set in the first embodiment of the present disclosure. [Figure 8] FIG. 2 is a diagram illustrating an example of the configuration of a generation unit according to the first embodiment of the present disclosure. [Figure 9]FIG. 4 is a diagram illustrating an example of a sequence of an initial plan generated by a generating unit according to the first embodiment of the present disclosure. [Figure 10] FIG. 4 is a diagram illustrating an example of a control signal of an initial plan generated by a control unit according to the first embodiment of the present disclosure. [Figure 11] FIG. 2 is a diagram illustrating an example of a processing flow of the robot system according to the first embodiment of the present disclosure. [Figure 12] FIG. 11 is a diagram illustrating an example of a GUI that accepts input of constraints in the second embodiment of the present disclosure. [Figure 13] FIG. 10 is a diagram showing an example of specifying a constraint using a feature in a modified example of the second embodiment of the present disclosure. [Figure 14] FIG. 10 is a diagram showing an example of the arrangement of buffer materials in the third embodiment of the present disclosure. [Figure 15] FIG. 1 is a diagram illustrating a robot system 1 having a minimum configuration according to an embodiment of the present disclosure. [Figure 16] FIG. 2 is a diagram illustrating an example of a processing flow of a robot system 1 having a minimum configuration according to an embodiment of the present disclosure. [Figure 17] FIG. 1 is a schematic block diagram illustrating the configuration of a computer according to at least one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, the embodiments will be described in detail with reference to the drawings. First Embodiment A robot system 1 according to a first embodiment of the present disclosure is a system for moving an object M placed at one position to another position. By setting a lifting height for the object M as a constraint on the movement path of the object M, the system reduces the possibility of the object M being damaged even if it falls. The reference height for the lifting height of the object M is each point on a reference plane. Examples of the reference plane include the surface of an obstacle that can be seen from above in the height direction in an area where an obstacle exists within the area where the object M can move from the start point to the destination, and the floor surface in an area where no obstacle exists. This floor surface is flush with the pedestal 402, which will be described later. The reference plane may also be a plane with a constant absolute value in the height direction (for example, the height direction is the z-axis direction, and if the floor surface is not flat, a plane that includes the lowest point in the height direction and is parallel to a plane including the x-axis and y-axis). The robot system 1 is a system that is installed in, for example, a warehouse in a logistics center. Hereinafter, when simply referring to "the height to which the object M is lifted," the reference height is assumed to be the reference plane. Obstacles are all objects other than the object M that the robot 40 moves to its destination and that exist within the imaging range of the imaging device 50, which will be described later. Therefore, the cardboard box C containing the object M, which will be described later, and a container (for example, a tray T), which will be described later, are also considered obstacles.

[0012] (Robot system configuration) Fig. 1 is a diagram illustrating an example of the configuration of a robot system 1 according to a first embodiment of the present disclosure. As shown in Fig. 1, the robot system 1 includes a control device 2, a robot 40, and a photographing device 50. Note that Fig. 1 also illustrates an obstacle O as an obstacle other than a cardboard box C and a container (e.g., a tray T). Fig. 1 also illustrates a floor F.

[0013] FIG. 2 is a diagram illustrating an example of the configuration of the control device 2 according to the first embodiment of the present disclosure. As shown in FIG. 2, the control device 2 includes an input unit 201, a generation unit 202, a control unit 203, and a management unit 204.

[0014] The input unit 201 inputs task goals and constraints to the generation unit 202. Examples of task goals include information indicating the type of object M, the number of objects M to be moved, the origin of the object M, and the destination of the object M. Examples of constraints include a no-entry area when moving the object M, and an area in which the robot 40 cannot move. The constraints on the no-entry area when moving the object M and the no-movement area of ​​the robot 40 when moving the object M include a constraint on the height to which the object M must be lifted while moving the object M from the origin to the destination, in other words, a constraint on the height from a reference plane of a robot arm 401 (described later) that grasps the object M. The input unit 201 may receive an input from the user as a task goal, such as "move three parts A from tray A to tray B," and specify that the type of object M to be moved is part A, the quantity of objects M to be moved is three, the source of object M is tray A, and the destination of object M is tray B, and input the specified information to the generation unit 202. The input unit 201 may also receive from the user a constraint on the height at which object M is lifted while moving object M from the source to the destination (that is, a constraint on the height from a reference plane to the robot arm 401 that grips object M), and input the specified information to the generation unit 202. The constraint on the height at which object M is lifted may be different at different points on the reference plane.

[0015] FIG. 3 is a first diagram illustrating an example of a GUI for accepting input of constraints in the first embodiment of the present disclosure. FIG. 4 is a second diagram illustrating an example of a GUI for accepting input of constraints in the first embodiment of the present disclosure. The input unit 201 is, for example, a display device having a touch panel function. In this case, the input unit 201 accepts, for example, a constraint on the height at which the object M is to be lifted, via a GUI (Graphical User Interface) such as those shown in FIGS. 3 and 4. Examples of the reference plane include the surface of an obstacle that can be seen from the height direction in an area where the object M can move between the source and destination, and the floor surface in an area where no obstacles exist. The reference plane may also be a plane whose absolute height in the height direction is constant. The example shown in FIG. 3 is an example of a GUI that allows setting upper and lower limits for the height at which the object M is to be lifted. The upper and lower limits are set within a range determined to prevent damage to the object M even if it falls. The lower limit is set within a range where the object M does not come into contact with the reference plane. 4 is an example of a GUI in which the height to lift the target object M is set as a fixed value. Note that in the GUI shown in FIG. 3, the input unit 201 may set the fixed value by the user inputting the same value for the upper limit value and the lower limit value.

[0016] FIG. 5 is a diagram illustrating a first example of the movement of the object M when a constraint is set in the first embodiment of the present disclosure. FIG. 5 illustrates an example of the movement of the object M when, in the area where the object M can move from the start point to the destination point, the surface of the obstacle visible from the height direction in the area where the obstacle exists and the floor surface in the area where the obstacle does not exist are set as reference planes, and upper and lower limits for the height at which the object M is lifted are set as constraints. In this example, the difference between the floor surface and the upper and lower limits for the height at which the object M is lifted, which are set as the reference plane, is the same as the difference between the upper and lower limits for the height at which the object M is lifted, which are set as the reference plane, the surface of the obstacle (in this case, the tray T). In this case, the object M is controlled by the control device 2 to move between the upper and lower limits of the height set using the floor surface as the reference plane. Thereafter, the object M is lifted by the height of the tray T and controlled by the control device 2 to move between the upper and lower limits of the height set using the surface of the obstacle as the reference plane.

[0017] FIG. 6 is a diagram illustrating a second example of the movement of the object M when a constraint is set in the first embodiment of the present disclosure. FIG. 6 illustrates an example of the movement of the object M when, in the area where the object M can move from the start point to the destination point, the surface of the obstacle that can be seen from the height direction in the area where the obstacle exists and the floor surface in the area where the obstacle does not exist are set as reference planes, and the height to which the object M is lifted is set as a fixed value as a constraint. In this example, the object M is controlled by the control device 2 to move at a constant height with the floor surface as the reference plane. The object M is lifted to maintain a constant height with the surface of the obstacle O as the reference plane, and is controlled by the control device 2 to pass through the obstacle O. After passing through the obstacle O, the object M is again controlled by the control device 2 to move at a constant height with the floor surface as the reference plane. The object M is then lifted by the height of the tray T and controlled by the control device 2 to move at a constant height with the surface of the obstacle as the reference plane.

[0018] 7 is a diagram illustrating a third example of movement of the object M when a constraint is set in the first embodiment of the present disclosure. FIG. 7 illustrates an example of movement of the object M when a plane with a constant absolute value in the height direction (for example, the height direction is the z-axis direction, and if the floor surface is not flat, a plane that includes the lowest point in the height direction and is parallel to a plane including the x-axis and y-axis) is the reference plane, and the height to which the object M is lifted is set as a fixed value as a constraint. In this example, the object M is controlled by the control device 2 to move at a constant height with the floor surface as the reference plane. Note that when the fluctuation in the vertical height of the object M is small or minimal, the possibility of the robot 40 dropping the object M can be reduced.

[0019] Fig. 8 is a diagram illustrating an example of the configuration of the generation unit 202 according to the first embodiment of the present disclosure. As shown in Fig. 8, the generation unit 202 includes a first processing unit 202a, a second processing unit 202b, a third processing unit 202c, a fourth processing unit 202d, and a fifth processing unit 202e.

[0020] The first processing unit 202a recognizes the robot 40. For example, the first processing unit 202a recognizes a robot model using CAD (Computer Aided Design) data. This CAD data includes information indicating the shape of the robot 40 and information indicating the range of movement, such as the reach range of the robot arm 401. The shape includes dimensions. The CAD data is, for example, drawing data designed using CAD.

[0021] The first processing unit 202a also recognizes the environment around the robot 40. For example, the first processing unit 202a acquires images captured by the camera device 50. The images captured by the camera device 50 include information captured by the camera and depth information. This depth information corresponds to colored point cloud data, which will be described later. The first processing unit 202a recognizes the position and shape of obstacles from the acquired images. Here, obstacles refer to all objects present within the camera range of the camera device 50, other than the target object M that the robot 40 is to move to its destination. The camera device 50, as will be described later, is capable of acquiring three-dimensional information of objects within the camera range. Therefore, the first processing unit 202a can recognize the environment around the robot 40, including the position and shape of obstacles. Note that the first processing unit 202a is not limited to recognizing the environment around the robot 40 from images captured by the camera device 50. For example, the first processing unit 202a may recognize the environment around the robot 40 using a three-dimensional occupancy map (Octomap), CAD data, AR (Augmented Reality) markers, etc. The CAD data includes information indicating the shape of an obstacle. The shape includes dimensions.

[0022] Furthermore, the first processing unit 202a recognizes a release position at the destination of the target object M. For example, when the destination is a container (e.g., a tray T), the first processing unit 202a recognizes the release position by machine learning using model-based matching. Model-based matching is a method of determining the position and orientation of an object by using image data obtained from a camera or the like and shape and structure data of the object (in this case, a container) whose position and orientation is to be acquired, and matching the shape and structure data with the object extracted from the image. Note that the first processing unit 202a is not limited to a unit that recognizes the release position by machine learning using model-based matching. For example, the first processing unit 202a may recognize the release position by using an AR marker.

[0023] Furthermore, the second processing unit 202b recognizes a pedestal 402 of the robot 40, which will be described later. For example, the second processing unit 202b recognizes the pedestal 402 by acquiring CAD data. This CAD data includes information indicating the shape of the pedestal 402. The shape includes dimensions. This allows the second processing unit 202b to recognize the Z coordinate of the top surface of the pedestal 402 in that coordinate system as the height of the pedestal 402. Note that if no CAD data for the pedestal 402 exists, the second processing unit 202b may extract information about the working surface of the pedestal 402 using a plane equation, and recognize the average value of the Z coordinate of the point cloud in that coordinate system as the height of the pedestal 402.

[0024] The third processing unit 202c determines whether or not it is necessary to preserve the object M. For example, based on a flag indicating whether or not to preserve the object M, the third processing unit 202c preserves the object M when the flag is set. Furthermore, the third processing unit 202c does not preserve the object M when the flag is not set.

[0025] Furthermore, the third processing unit 202c recognizes the state (i.e., position and posture) of the object M. For example, the third processing unit 202c recognizes the position of the object M by performing machine learning using model-based matching. Furthermore, the third processing unit 202c recognizes the posture of the object M by using a technique for generating a bounding box, such as an axis-aligned bounding box (AABB) or an oriented bounding box (OBB), for the object M whose position has been identified. Note that the third processing unit 202c may classify the object M using clustering, which is one of the machine learning techniques, for the image captured by the image capture device 50, and identify the state of the object M by using a technique for generating a bounding box.

[0026] Furthermore, the third processing unit 202c acquires the height of the object M. For example, the third processing unit 202c recognizes the object M by acquiring CAD data. This CAD data includes information indicating the shape of the object M. The shape includes dimensions. This allows the third processing unit 202c to recognize the Z coordinate of the object M in that coordinate system as the height of the object M. Note that the third processing unit 202c may recognize the height of the object M by subtracting the Z coordinate of the base 402 from the Z coordinate of the top surface of the object M.

[0027] The fourth processing unit 202d sets a range of heights to lift the object M. For example, the fourth processing unit 202d receives setting information on the lifting height for each object M input from the input unit 201 via the GUI. The fourth processing unit 202d may also receive the setting information on the lifting height for each object M from a pre-prepared configuration file that includes information on the range of heights to lift the object M. The fourth processing unit 202d then stores the received setting information on the lifting height for each object M. As a result, the setting information on the lifting height for each object M is set.

[0028] It should be noted that some objects M are unlikely to be damaged even if dropped. For such objects M, there is no need to set a range of heights for lifting the object M. Therefore, status information indicating that a range of heights for lifting the object M has been set (for example, "1") and status information indicating that a range of heights for lifting the object M has not been set (for example, "0") may be set.

[0029] The fifth processing unit 202e generates an initial plan sequence that indicates the flow of motion of the robot 40, based on the task target determined by processing by the first processing unit 202a, the second processing unit 202b, and the third processing unit 202c, and the constraints, including the constraint on the range of height for lifting the object M, determined by processing by the fourth processing unit 202d. For example, the fifth processing unit 202e acquires the task target from the first processing unit 202a, the second processing unit 202b, and the third processing unit 202c. The fifth processing unit 202e also acquires the range of height for lifting the object M from the fourth processing unit 202d. The fifth processing unit 202e adds the acquired constraint on the range of height for lifting the object M to the constraints input from the input unit 201. Then, based on the acquired task goal and constraints, the fifth processing unit 202e generates information indicating each state of the robot 40 at each time step from the state at the source of the object M to the state at the destination of the object M (such as the type of object M, the position and posture of the robot 40, the grip strength of the object M, and the actions of the robot 40 (including, for example, a reach action to approach the object M, a pick action to pick the object M, an arm movement action to properly move the picked object to the destination, and a release action to place the object)), which is necessary for the control unit 203 to generate a control signal for controlling the robot 40. In other words, the information indicating each state of the robot 40 at each time step from the state at the source of the object M to the state at the destination of the object M, which is necessary for the control unit 203 to generate a control signal for controlling the robot 40, is a sequence. The fifth processing unit 202e may be realized using artificial intelligence (AI) technology including temporal logic, reinforcement learning, optimization technology, and the like.

[0030] 9 is a diagram showing an example of a sequence TBL1 of an initial plan generated by the generating unit 202 according to the first embodiment of the present disclosure. For example, the sequence TBL1 of the initial plan generated by the generating unit 202 is a sequence indicating each state of the robot 40 for each n time step from the origin to the destination of the object M, as shown in FIG.

[0031] The control unit 203 generates a control signal for controlling the robot 40 based on a sequence input from the outside (i.e., the generation unit 202). Note that the control unit 203 may generate a control signal that optimizes an evaluation function when generating the control signal. Examples of the evaluation function include a function that represents the amount of energy consumed by the robot 40 when moving the object M, and a function that represents the distance along the path along which the object M is moved. The control unit 203 outputs the generated control signal to the robot 40 and the management unit 204.

[0032] 10 is a diagram showing an example of the control signal Cnt of the initial plan generated by the control unit 203 according to the first embodiment of the present disclosure. For example, the control signal Cnt of the initial plan generated by the control unit 203 is, for example, each control signal for n time steps from the origin to the destination of the object M, as shown in FIG.

[0033] The robot 40 includes a robot arm 401 and a base 402. The robot arm 401 is connected to the base 402. The robot arm 401 grasps an object M and moves the object M from a starting point to a destination point in response to a control signal output by the control unit 203.

[0034] The image capturing device 50 captures an image of the state of the object M. The image capturing device 50 is, for example, a depth camera, and is capable of identifying the state (i.e., the position and posture) of the object M. The image captured by the image capturing device 50 is represented, for example, by colored point cloud data, and includes three-dimensional information of the captured object. The image capturing device 50 outputs the captured image to the generation unit 202.

[0035] The management unit 204 estimates the current states of the robot 40 and the object M based on the sequence output by the generation unit 202 and the control signal output by the control unit 203. The current states of the robot 40 and the object M estimated by the management unit 204 are ideal states that the robot 40 and the object M should be in at the present time.

[0036] 11 is a diagram showing an example of a processing flow of the robot system 1 according to the first embodiment of the present disclosure. Next, processing performed by the robot system 1 will be described with reference to FIG.

[0037] The first processing unit 202a recognizes the environment around the robot 40 (step S1). For example, the first processing unit 202a acquires an image captured by the imaging device 50. The first processing unit 202a recognizes the position and shape of an obstacle from the acquired image. The first processing unit 202a also recognizes a release position at the destination of the object M. For example, when the destination is a container (e.g., a tray T), the first processing unit 202a recognizes the release position by performing machine learning using model-based matching.

[0038] The second processing unit 202b recognizes the base 402 of the robot 40 (step S2). For example, the second processing unit 202b obtains the height of the base 402 by acquiring CAD data.

[0039] The third processing unit 202c determines whether or not it is necessary to preserve the object M (step S2). For example, based on a flag indicating whether or not to preserve the object M, the third processing unit 202c preserves the object M when the flag is set. Furthermore, the third processing unit 202c does not preserve the object M when the flag is not set.

[0040] When the third processing unit 202c determines that the object M needs to be preserved (a pick object is set in FIG. 11) (YES in step S3), it recognizes the state (i.e., the position and orientation) of the object M (step S4). For example, the third processing unit 202c recognizes the position and orientation of the object M by using model-based matching, machine learning, or a technique for generating a bounding box such as AABB or OBB.

[0041] The third processing unit 202c acquires the height of the object M (step S5). For example, the third processing unit 202c recognizes the object M by acquiring CAD data.

[0042] The fourth processing unit 202d sets a range of heights for lifting the object M (step S6). For example, the fourth processing unit 202d receives setting information for the height for lifting each object M input from the input unit 201 via the GUI.

[0043] The fifth processing unit 202e generates an initial plan sequence that indicates the flow of operation of the robot 40 based on the work goal determined by processing by the first processing unit 202a, the second processing unit 202b, and the third processing unit 202c, and constraints including a constraint on the range of height to which the object M can be lifted determined by processing by the fourth processing unit 202d.

[0044] For example, the fifth processing unit 202e acquires the task target from the first processing unit 202a, the second processing unit 202b, and the third processing unit 202c. The fifth processing unit 202e also acquires the range of heights for lifting the object M from the fourth processing unit 202d (step S7). The fifth processing unit 202e adds the acquired constraint of the range of heights for lifting the object M to the constraints input from the input unit 201. Then, based on the acquired task goal and constraints, the fifth processing unit 202e generates (calculates) information indicating each state of the robot 40 for each time step from the state at the origin of the object M to the state at the destination of the object M (such as the type of object M, the position and posture of the robot 40, the grip strength of the object M, and the operation of the robot 40 (including, for example, a reach operation to approach the object M, a pick operation to pick the object M, an arm movement operation to properly move the picked object to the destination, and a release operation to place the object)) which is necessary for the control unit 203 to generate a control signal for controlling the robot 40 (step S8). In other words, the information indicating each state of the robot 40 for each time step from the state at the origin of the object M to the state at the destination of the object M, which is necessary for the control unit 203 to generate a control signal for controlling the robot 40, is a sequence. The fifth processing unit 202e outputs the generated sequence to the control unit 203 and the management unit 204 (step S9).

[0045] Furthermore, if the third processing unit 202c determines that there is no need to preserve the object M (no pick object is set in Figure 11) (NO in step S3), the robot system 1 calculates a path under conditions that do not include a restriction on the range of height to which the object M can be lifted, moves the object M to the destination along that path, and returns to the processing of step S1.

[0046] (advantage) The robot system 1 according to the first embodiment of the present disclosure has been described above. In the robot system 1, the fourth processing unit 202d (an example of a setting means) sets a restriction on the range of height to which the object M can be lifted relative to a reference plane. The fifth processing unit 202e (an example of a calculation means) calculates a path for moving the object M to a destination based on the restriction set by the fourth processing unit 202d.

[0047] By doing so, the robot system 1 can reduce the possibility of damage to the object even if the object falls while the robot is moving the object to its destination.

[0048] Second Embodiment Next, a robot system 1 according to a second embodiment of the present disclosure will be described. The robot system 1 according to the second embodiment calculates a path for moving the object M to a destination using a constraint that further limits the movement range of the object M as specified by the user, in addition to the constraints in the robot system 1 according to the first embodiment.

[0049] FIG. 12 is a diagram illustrating an example of a GUI that accepts input of constraints in the second embodiment of the present disclosure. For example, as shown in part (a) of FIG. 12, in a state in which the GUI displays an object M, a release location as a destination, an obstacle O, a cardboard box C, and a tray T, the user inputs constraints by, for example, specifying with a finger an allowable range from the object M to the destination on the input unit 201. The input unit 201 accepts the input constraints. In this case, the fourth processing unit 202d acquires the constraints from the input unit 201 and adds them to the constraints already set. The fifth processing unit 202e performs the same calculations as the fifth processing unit 202e according to the first embodiment for the allowable range indicated by the added constraints.

[0050] Also, as shown in part (b) of FIG. 12, it is assumed that the user inputs a constraint to the input unit 201 by specifying with a finger one possible route from the object M to the destination. The input unit 201 accepts this input constraint. In this case, the fourth processing unit 202d acquires this constraint from the input unit 201 and adds this constraint to the constraints that have already been set. The fifth processing unit 202e performs the same calculation as the fifth processing unit 202e according to the first embodiment on the route indicated by the added constraint. If the fifth processing unit 202e is unable to calculate a route that satisfies the constraint, it may notify the user that there is no route that satisfies the constraint.

[0051] Note that, at the stage when the fifth processing unit 202e acquires the height constraint from the fourth processing unit 202d, the fifth processing unit 202e takes the height constraint into consideration and, if there is an obstacle (for example, obstacle O) that is determined to be high, sets the obstacle O as a no-entry area for the object M. Then, the fifth processing unit 202e may instruct the input unit 201 to display the no-entry area on the GUI.

[0052] (advantage) The robot system 1 according to the second embodiment of the present disclosure has been described above. In the robot system 1, the fourth processing unit 202d acquires this constraint from the input unit 201 and adds this constraint to the constraints that have already been set. The fifth processing unit 202e performs the same calculation as the fifth processing unit 202e according to the first embodiment for the movable range indicated by the added constraint.

[0053] In this way, the robot system 1 can make the object M pass through a path that the user thinks is less likely to cause the object M to fall.

[0054] <Modification of the second embodiment> Next, a robot system 1 according to a modification of the second embodiment of the present disclosure will be described. In the robot system 1 according to the second embodiment, a user may specify a movable range from the object M to the destination using a feature such as a guide tape. FIG. 13 is a diagram illustrating an example of specifying a constraint using a feature in the modification of the second embodiment of the present disclosure. For example, the image capture device 50 captures an image of the feature as shown in FIG. 13. The input unit 201 receives an image of the feature. The input unit 201 may then identify the range specified by the feature in the image as a constraint on the movable range from the object M to the destination. The fourth processing unit 202d may acquire this constraint from the input unit 201 and add it to the constraints already set. The fifth processing unit 202e may perform the same calculation as the fifth processing unit 202e according to the first embodiment for the movable range indicated by the added constraint. In this manner, the robot system 1 allows the object M to pass through a path that the user considers to be less likely to cause the object M to fall.

[0055] <Third embodiment> Next, a robot system 1 according to a third embodiment of the present disclosure will be described. The robot system 1 according to the third embodiment includes a buffer material B, such as a cushion, that reduces impact even when the object M falls into an area where the movement of the object M in the height direction is predicted to be greater than or equal to a threshold value. FIG. 14 is a diagram illustrating an example of the arrangement of the buffer material B according to the third embodiment of the present disclosure. For example, the fifth processing unit 202e may instruct the control unit 203 to arrange the buffer material B along the entire calculated path. Furthermore, for example, when the fifth processing unit 202e acquires a height constraint from the fourth processing unit 202d, the fifth processing unit 202e may instruct the control unit 203 to arrange the buffer material B around the obstacle O if the height of the obstacle (e.g., obstacle O) is determined to be high, taking the height constraint into consideration. Note that the buffer material B may be arranged by the user. Also, in the third embodiment, for example, the user may set the movement range of the object M via the input unit 201, as described with reference to FIG. 12. Furthermore, in the area where the buffer material B is arranged in this manner, the height restriction may be relaxed (specifically, the upper limit of the height may be increased).

[0056] (advantage) The robot system 1 according to the third embodiment of the present disclosure has been described above. The robot system 1 includes a buffer material B such as a cushion that reduces impact even when the object M falls into an area where the movement of the object M in the height direction is predicted to be greater than or equal to a threshold value.

[0057] By doing so, the robot system 1 can reduce the possibility of damage to the target object M when it falls, compared to a robot system 1 that does not have the buffer material B.

[0058] <Modification of the third embodiment> Next, a robot system 1 according to a modification of the third embodiment of the present disclosure will be described. The robot system 1 according to the modification of the third embodiment may be provided with a new obstacle O that reduces the movement of the object M in the height direction in an area where the movement of the object M in the height direction is predicted to be greater than a threshold value. By doing so, the robot system 1 can reduce the possibility of damage to the object M if it falls, compared to a robot system 1 that does not include the new obstacle O.

[0059] Next, processing of a robot system 1 with a minimum configuration according to an embodiment of the present disclosure will be described. FIG. 15 is a diagram illustrating a robot system 1 with a minimum configuration according to an embodiment of the present disclosure. The robot system 1 with a minimum configuration according to an embodiment of the present disclosure includes a fourth processing unit 202d (an example of a setting means) and a fifth processing unit 202e (an example of a calculation means). The fourth processing unit 202d sets a constraint on the range of height to which the object M is lifted relative to a reference plane. The fourth processing unit 202d can be realized, for example, using the function of the fourth processing unit 202d illustrated in FIG. 8. The fifth processing unit 202e calculates a path for moving the object M to a destination based on the constraint set by the fourth processing unit 202d. The fifth processing unit 202e can be realized, for example, using the function of the fifth processing unit 202e illustrated in FIG. 8.

[0060] Next, a description will be given of the processing of the robot system 1 with a minimum configuration according to an embodiment of the present disclosure. Fig. 16 is a diagram showing an example of a processing flow of the robot system 1 with a minimum configuration according to an embodiment of the present disclosure. Here, the processing of the robot system 1 with a minimum configuration will be described with reference to Fig. 16.

[0061] The fourth processing unit 202d sets a restriction on the range of height to which the object M is lifted relative to a reference plane (step S101). The fifth processing unit 202e calculates a path for moving the object M to a destination based on the restriction set by the fourth processing unit 202d (step S102).

[0062] The above has described a robot system 1 with a minimum configuration according to an embodiment of the present disclosure. This robot system 1 can reduce the possibility of damage to an object even if the object falls while the robot is moving it to its destination.

[0063] The order of the processes in the embodiments of the present disclosure may be changed as long as the processes are performed appropriately.

[0064] Although the embodiments of the present disclosure have been described, the robot system 1, the control device 2, the input unit 201, the generation unit 202, the control unit 203, the management unit 204, the robot 40, the image capture device 50, and other control devices may have a computer device inside. The above-described processing steps are stored in the form of a program on a computer-readable recording medium, and the above processing is performed by the computer reading and executing the program. Specific examples of computers are shown below.

[0065] FIG. 17 is a schematic block diagram showing the configuration of a computer according to at least one embodiment. As shown in FIG. 17, the computer 5 includes a CPU 6, a main memory 7, a storage 8, and an interface 9. For example, the robot system 1, the control device 2, the input unit 201, the generation unit 202, the control unit 203, the management unit 204, the robot 40, the imaging device 50, and other control devices are implemented in the computer 5. The operation of each of the processing units described above is stored in the storage 8 in the form of a program. The CPU 6 reads the program from the storage 8, loads it into the main memory 7, and executes the above-described processing in accordance with the program. The CPU 6 also allocates storage areas in the main memory 7 corresponding to each of the storage units described above in accordance with the program.

[0066] Examples of storage 8 include a hard disk drive (HDD), a solid state drive (SSD), a magnetic disk, a magneto-optical disk, a compact disc read-only memory (CD-ROM), a digital versatile disc read-only memory (DVD-ROM), and a semiconductor memory. Storage 8 may be an internal medium directly connected to the bus of computer 5, or an external medium connected to computer 5 via interface 9 or a communication line. In addition, when this program is distributed to computer 5 via a communication line, computer 5 that receives the program may load the program into main memory 7 and execute the above-mentioned processing. In at least one embodiment, storage 8 is a non-transitory tangible storage medium.

[0067] The program may also implement some of the functions described above. Furthermore, the program may be a file that can implement the functions described above in combination with a program already stored in the computer device, a so-called differential file (differential program).

[0068] Although several embodiments of the present disclosure have been described, these embodiments are merely examples and do not limit the scope of the disclosure. Various additions, omissions, substitutions, and modifications may be made to these embodiments without departing from the spirit of the disclosure.

[0069] Note that part or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0070] (Appendix 1) a setting means for setting a restriction on a range of heights for lifting an object relative to a reference plane; a calculation means for calculating a path for moving the object to a destination based on the constraints set by the setting means; A robot system comprising:

[0071] (Appendix 2) The reference surface is In an area where the object can move between the origin and destination, the surface of the obstacle that can be seen from the height direction in an area where the obstacle exists, and the floor surface in an area where the obstacle does not exist. 10. The robotic system of claim 1.

[0072] (Appendix 3) The reference surface is In the area in which the object can move between the origin and destination, the altitude as an absolute value in the height direction is a plane that is constant. 10. The robotic system of claim 1.

[0073] (Appendix 4) a receiving means for receiving the height constraint via a GUI (Graphical User Interface); Equipped with The setting means setting the constraint on the height accepted by the accepting means; 4. The robot system according to claim 1,

[0074] (Appendix 5) The setting means setting different constraints on the height at different points on the reference plane; 5. The robot system according to claim 1,

[0075] (Appendix 6) a buffer material is provided in an area where the movement of the object in the height direction is predicted to be greater than or equal to a threshold value; 6. The robot system according to any one of claims 1 to 5.

[0076] (Appendix 7) a new obstacle is provided in an area where the movement of the object in the height direction is predicted to be greater than or equal to a threshold value; 7. The robot system according to any one of claims 1 to 6.

[0077] (Appendix 8) The setting means Set a new constraint, via GUI, on the range of a route along which the object designated by the user should be moved to the destination. 8. The robot system of claim 1.

[0078] (Appendix 9) The setting means Using the feature, a range of a route along which the object designated by the user is moved to a destination is set as a new constraint. 8. The robot system of claim 1.

[0079] (Appendix 10) Set a constraint on the range of heights to which the object can be lifted relative to the reference plane; calculating a path for moving the object to the destination based on the set constraints; Processing method.

[0080] (Appendix 11) Setting a height constraint for the range of heights to which the object is lifted relative to a reference plane; calculating a path for moving the object to a destination based on the set constraints; A recording medium on which a program that causes a computer to execute the above is stored. [Industrial Applicability]

[0081] According to each aspect of the present disclosure, even if an object falls while the robot is moving the object to its destination, the possibility of damage can be reduced. [Explanation of symbols]

[0082] 1. Robot System 2. Control device 5. Computer 6 CPU 7. Main memory 8. Storage 9. Interface 40. Robot 50. Imaging device 201 Input section 202...Generation section 202a... First processing section 202b... Second processing section 202c...Third processing section 202d...Fourth processing section 202e 5th processing section 203 Control unit 204...Management Department B...Buffer material C···Cardboard F...Floor surface M...Object O... Obstacle T···Tray

Claims

1. a setting means for setting a restriction on a range of heights for lifting an object relative to a reference plane; a calculation means for calculating a path for moving the object to a destination based on the constraints set by the setting means; a processing means for setting an area where an obstacle exceeding a predetermined height exists as a no-entry area for the object, and outputting an instruction to display the set no-entry area; A robot system comprising:

2. The reference surface is In an area where the object can move between the origin and destination, the surface of the obstacle that can be seen from the height direction in an area where the obstacle exists, and the floor surface in an area where the obstacle does not exist. The robot system of claim 1 .

3. The reference surface is In the area in which the object can move between the origin and destination, the altitude as an absolute value in the height direction is a plane that is constant. The robot system of claim 1 .

4. a receiving means for receiving the height constraint via a GUI (Graphical User Interface); Equipped with The setting means setting the constraint on the height accepted by the accepting means; The robot system according to any one of claims 1 to 3.

5. The setting means setting different constraints on the height at different points on the reference plane; The robot system according to any one of claims 1 to 4.

6. a buffer material is provided in an area where the movement of the object in the height direction is predicted to be greater than or equal to a threshold value; The robot system according to any one of claims 1 to 5.

7. a new obstacle is provided in an area where the movement of the object in the height direction is predicted to be greater than or equal to a threshold value; The robot system according to any one of claims 1 to 6.

8. The setting means via a GUI, setting a range of a route along which the object designated by the user is to be moved to a destination as a new constraint; The robot system according to any one of claims 1 to 7.

9. A computer comprising: Set a constraint on the range of heights to which the object can be lifted relative to the reference plane; calculating a path for moving the object to a destination based on the set constraints; setting an area where an obstacle exceeding a predetermined height exists as a no-entry area for the object, and outputting an instruction to display the set no-entry area; Processing method.

10. Setting a height constraint for the range of heights to which the object is lifted relative to a reference plane; calculating a path for moving the object to a destination based on the set constraints; setting an area where an obstacle exceeding a predetermined height exists as a no-entry area for the object, and outputting an instruction to display the set no-entry area; A program that causes a computer to execute the following.

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