Interference check device

Abstract

The purpose of the present invention is to model the shapes of a robot and a surrounding obstacle with a small amount of data, and to improve the accuracy of checking interference.　An interference check device for checking interference between a robot and a surrounding obstacle, the interference check device comprising: an inclusive cuboid set conversion unit for converting each of the robot and the surrounding obstacle into a three-dimensional model of a set of cuboids; and an interference determination unit for determining whether or not there is interference between the three-dimensional model of the robot and the three-dimensional model of the surrounding obstacle by simulation of motions of the three-dimensional models of the robot and surrounding obstacle based on a motion program.

Description

[Technical field]

[0001] The present invention relates to an interference checking device. [Background technology]

[0002] In order to search for the robot's motion path, interference checks are performed in the virtual environment between the robot and surrounding obstacles such as peripheral equipment and safety fences. In this regard, a technique is known for performing an interference check using triangular mesh data constituting a three-dimensional model of the robot and surrounding obstacles in order to determine interference between the robot and surrounding obstacles (see, for example, Patent Document 1). There is also known a technology that uses a polyhedron equivalent to a simple convex hull to perform high-speed processing involving interference calculations for free-form surfaces expressed by high-order curved surface formulas or three-dimensional shapes composed of multiple free-form surfaces. For example, see Patent Document 2. There is also known a technique for checking interference between a robot and surrounding obstacles using a voxel model having a plurality of voxels, or a voxel model having voxelized spheres and cylinders (see, for example, Patent Document 3). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2020-179441 A [Patent Document 2] JP 2002-342395 A [Patent Document 3] JP 2012-232408 A Summary of the Invention [Problem to be solved by the invention]

[0004] In Patent Document 1, when an interference check is performed using a three-dimensional model of triangular meshes, accurate determination results can be obtained, but there is a problem that the calculation cost becomes very high (especially when a large number of triangular meshes are involved). Furthermore, in Patent Document 2, depending on the shape of surrounding obstacles, the space occupied by the convex hull may be larger than the actual shape, which may reduce the accuracy of the interference check. Furthermore, in Patent Document 3, the spheres and cylinders included in the voxel model are larger than the actual robot and surrounding obstacles, and there is a problem that when the robot and surrounding obstacles are close to each other, interference always occurs.

[0005] Therefore, it is desirable to model the shapes of the robot and surrounding obstacles with a small amount of data while improving the accuracy of interference checks. [Means for solving the problem]

[0006] One aspect of the interference check device disclosed herein is an interference check device that performs interference check between a robot and surrounding obstacles, and includes an enclosing rectangular parallelepiped set conversion unit that converts each of the robot and the surrounding obstacles into a 3D model that is a set of rectangular parallelepipeds, and an interference determination unit that determines whether or not there is interference between the 3D model of the robot and the 3D model of the surrounding obstacles by simulating the operation of the 3D models of the robot and the surrounding obstacles based on an operation program. Effect of the Invention

[0007] According to one aspect, it is possible to improve the accuracy of interference checks while modeling the shapes of a robot and surrounding obstacles with a small amount of data. [Brief description of the drawings]

[0008] [Figure 1] FIG. 2 is a functional block diagram illustrating an example of a functional configuration of an interference check device according to an embodiment. [Diagram 2] FIG. 1 is a diagram showing an example of 3D CAD data of surrounding obstacles. [Diagram 3] FIG. 13 is a diagram showing an example of a cut surface in the case of a robot. [Figure 4] 3 is a diagram showing an example of a three-dimensional model of a set of rectangular parallelepipeds of the surrounding obstacles shown in FIG. 2. [Diagram 5] 3 is a diagram showing an example of a three-dimensional model of a convex hull of the surrounding obstacles shown in FIG. 2. [Figure 6] 5 is a diagram showing an example of a case where a margin is set for a set of rectangular parallelepipeds of the surrounding obstacles shown in FIG. 4. FIG. [Figure 7] 10 is a flowchart illustrating an interference check process of the interference checking device. [Figure 8] 13 is a flowchart illustrating a three-dimensional model conversion process of the interference checking device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] <One embodiment> FIG. 1 is a functional block diagram illustrating an example of the functional configuration of an interference checking device according to an embodiment. 1, the interference check device 1 is a known computer, and includes a control unit 10, an input unit 11, a display unit 12, and a storage unit 13. The control unit 10 includes a containing rectangular parallelepiped set conversion unit 101, and a simulation execution unit 102. The containing rectangular parallelepiped set conversion unit 101 includes a simplified range setting unit 111, a point cloud data conversion unit 112, a genetic point cloud data division unit 113, a minimum total volume search unit 114, and a margin setting unit 115. The simulation execution unit 102 includes a coordinate system conversion unit 121, and an interference determination unit 122. The interference check device 1 may be connected to a robot control device (not shown) that controls the operation of a robot (not shown) via a network such as a LAN (Local Area Network) or the Internet. Alternatively, the interference check device 1 may be directly connected to the robot control device (not shown) via a connection interface (not shown).

[0010] <Input section 11> The input unit 11 is, for example, a keyboard or a touch panel disposed on a display unit 12 described later. As described later, the input unit 11 receives, from a user such as a worker, the number of rectangular parallelepipeds when a three-dimensional model of a robot (not shown), a peripheral device (not shown), or a peripheral obstacle such as a safety fence is regarded as a collection of rectangular parallelepipeds.

[0011] <Display section 12> The display unit 12 is, for example, a liquid crystal display, and displays the determination results by the interference checking device 1, etc.

[0012] <Storage section 13> The storage unit 13 is a solid state drive (SSD) or a hard disk drive (HDD), and may store various operation programs for operating a robot or peripheral devices (not shown). The storage unit 13 also includes an operation log storage unit 131 and a shape data storage unit 132. As described below, the operation log memory unit 131 stores, as an operation log, three-dimensional coordinate values ​​indicating the position and posture of the robot and each of the rectangular prism collections of surrounding obstacles, as well as the time, by the interference determination unit 122 executing a simulation of the operation program using a three-dimensional model of the robot and each of the rectangular prism collections of surrounding obstacles converted by the enclosing rectangular prism collection conversion unit 101 based on shape data such as 3D CAD data that three-dimensionally represents the robot (not shown) and its peripheral equipment and surrounding obstacles such as safety fences. The shape data storage unit 132 stores shape data such as 3D CAD data of a robot (not shown) and 3D CAD data of surrounding obstacles (not shown).

[0013] <Control unit 10> The control unit 10 has a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a CMOS (Complementary Metal-Oxide-Semiconductor) memory, etc., which are configured to be able to communicate with each other via a bus, and are well known to those skilled in the art. The CPU is a processor that controls the entire interference check device 1. The CPU reads out the system program and application program stored in the ROM via the bus, and controls the entire interference check device 1 according to the system program and application program. As a result, as shown in FIG. 1, the control unit 10 is configured to realize the functions of the containing rectangular parallelepiped set conversion unit 101 and the simulation execution unit 102. The containing rectangular parallelepiped set conversion unit 101 is also configured to realize the functions of the simplified range setting unit 111, the point cloud data conversion unit 112, the genetic point cloud data division unit 113, the minimum total volume search unit 114, and the margin setting unit 115. The simulation execution unit 102 is also configured to realize the functions of the coordinate system conversion unit 121 and the interference determination unit 122. Various data such as temporary calculation data and display data are stored in the RAM. The CMOS memory is backed up by a battery (not shown), and is configured as a non-volatile memory that retains its memory state even when the power supply of the interference check device 1 is turned off.

[0014] <Containing rectangular parallelepiped set conversion unit 101> The enclosing rectangular parallelepiped set conversion unit 101, for example, as a pre-processing of the main processing of the simulation execution unit 102 described later, converts the shape data (3D CAD data) of the robot and surrounding obstacles (not shown) stored in the shape data storage unit 132 of the storage unit 13 into a 3D model of a collection of rectangular parallelepipeds. Below, we will explain the operation of the containing rectangular parallelepiped set conversion unit 101, and the functions of the simplified range setting unit 111, point cloud data conversion unit 112, genetic point cloud data division unit 113, minimum total volume search unit 114, and margin setting unit 115 that constitute the containing rectangular parallelepiped set conversion unit 101.

[0015] <Simplified range setting unit 111> The simplified range setting unit 111 displays, for example, 3D CAD data as shape data of nearby obstacles on the display unit 12, and sets a range to be used for interference check from among the shape data of the nearby obstacles based on an input operation of the input unit 11 by the user. Fig. 2 is a diagram showing an example of shape data of a nearby obstacle, in which the shape data (3D CAD data) of the nearby obstacle is shown, the shape of the nearby obstacle on the XY plane as viewed from the positive Z-axis direction. 2, the simplified range setting unit 111 receives, for example, a designation of a range indicated by a dashed line in shape data (3D CAD data) of a surrounding obstacle based on an input operation by a user on the input unit 11. The simplified range setting unit 111 sets the received range as a designated range. In this way, the interference check device 1 can simplify the interference check by performing the interference check only in the range in which the robot (not shown) actually operates.

[0016] <Point cloud data conversion unit 112> The point cloud data conversion unit 112 converts, for example, using a known method of conversion to point cloud data, into point cloud data of the robot and point cloud data of the surrounding obstacles in the specified range set by the simplified range setting unit 111, based on the 3D CAD data of the robot (not shown) and the surrounding obstacles stored in the shape data storage unit 132 of the storage unit 13.

[0017] <Genetic point cloud data division unit 113> The genetic point cloud data division unit 113, for example, calculates an evaluation value for each combination of multiple cut planes that divides the point cloud data of the robot and surrounding obstacles converted by the point cloud data conversion unit 112 into the number of rectangular prisms input by the user, and repeatedly recalculates the evaluation value for each combination of multiple cut planes that are newly generated based on a known genetic algorithm for a predetermined maximum number of iterations. Specifically, for example, when the number n of rectangular parallelepipeds is input by a user via the input unit 11, the genetic point cloud data division unit 113 randomly generates k combinations of (n-1) cutting planes that divide the point cloud data of a robot (or surrounding obstacles) not shown into n pieces (n and k are integers greater than or equal to 2). Fig. 3 is a diagram showing an example of a cut surface in the case of a robot. In Fig. 3, the robot is shown by a solid line, and a 3D model of a collection of robot cuboids is shown by a dashed line. Fig. 3 also shows a case where the number n of cuboids input by the user as the 3D model of the collection of robot cuboids is 8, and 7 cut surfaces are shown by thick solid lines. The genetic point cloud data division unit 113 calculates the volume of a rectangular parallelepiped that includes each of the n pieces of point cloud data divided by the (n-1) cut planes for each of the k combinations, and calculates the total volume of the set of rectangular parallelepipeds of the robot (or surrounding obstacles) as an evaluation value for each combination of the (n-1) cut planes. The genetic point cloud data division unit 113 repeats recalculation of the evaluation values ​​of the (n-1) cut planes for each of the k combinations newly generated by genetic operations based on the genetic algorithm for a preset maximum number of repetitions. The number of cutting planes that divide the point cloud data into n pieces is not limited to (n-1) pieces, and may be less than (n-1) pieces.

[0018] <Minimum total volume search unit 114> The minimum total volume search unit 114 searches for the (n-1) cut planes having the highest evaluation value among the (n-1) cut planes in each of the k combinations, that is, the (n-1) cut planes having the smallest total volume of the set of rectangular parallelepipeds in the 3D model of the robot (or surrounding obstacles), not shown, as optimal cut planes. As shown in FIG. 3, the minimum total volume search unit 114 selects the set of rectangular parallelepipeds divided by the optimal (n-1) cut planes as the 3D model of the robot (or surrounding obstacles), not shown.

[0019] FIG. 4 is a diagram showing an example of a three-dimensional model of a set of rectangular parallelepipeds of the surrounding obstacles shown in FIG. As shown in FIG. 4, the three-dimensional model of the surrounding obstacles shown in FIG. 2 is a collection of two rectangular parallelepipeds 200(1) and 200(2) indicated by thick dashed lines within a specified range set by simplified range setting unit 111, and the section between rectangular parallelepipeds 200(1) and 200(2) is the cut surface. FIG. 5 is a diagram showing an example of a three-dimensional model of a convex hull of the surrounding obstacles shown in FIG. As shown in Fig. 5, the 3D model of the convex hull of the surrounding obstacles shown by the thick dashed line is larger than the actual shape of the surrounding obstacles, as described above. In contrast, the 3D model of the set of rectangular parallelepipeds of the surrounding obstacles in Fig. 4 shows a size almost equal to the actual shape of the surrounding obstacles. This enables the interference checking device 1 to perform interference checking with high accuracy.

[0020] <Margin setting unit 115> The margin setting unit 115 sets a margin for a three-dimensional model of a set of rectangular parallelepipeds of the robot and surrounding obstacles (not shown). Specifically, the margin setting unit 115 sets a preset margin amount d in each of the X-axis, Y-axis, and Z-axis directions, as shown in FIG. 6, for each rectangular parallelepiped of a set of rectangular parallelepipeds of the robot and surrounding obstacles (not shown).

[0021] The above preprocessing by the enclosing rectangular parallelepiped set conversion unit 101 makes it possible to avoid using triangular meshes in the original 3D CAD data of the robot and surrounding obstacles, thereby reducing the calculation cost of interference checks.

[0022] <Simulation execution unit 102> Based on the operation program, the simulation execution unit 102 executes a simulation as a main process in which the 3D models of the robot and surrounding obstacles, which are each a collection of rectangular parallelepipeds converted by the enclosing rectangular parallelepiped set conversion unit 101 as preprocessing, are operated, and checks for the presence or absence of interference between the 3D model of the robot and the 3D models of the surrounding obstacles. The operation of the simulation execution unit 102 will be described below with reference to the functions of the coordinate system conversion unit 121 and the interference determination unit 122 that constitute the simulation execution unit 102.

[0023] <Coordinate system conversion unit 121> For example, when a simulation of an operation program is executed by the simulation execution unit 102, the coordinate system conversion unit 121 updates the position and posture of a three-dimensional model of a collection of rectangular parallelepipeds of the robot and surrounding obstacles (not shown) in accordance with the operation of the robot and surrounding obstacles.

[0024] <Interference determination unit 122> The interference determination unit 122 determines whether or not there is interference between the 3D model of the robot and the 3D models of surrounding obstacles by simulating the operation of a 3D model of the robot (not shown) and a collection of rectangular parallelepipeds of surrounding obstacles based on an operation program by the simulation execution unit 102. Specifically, for example, during a simulation of an operation program by the simulation execution unit 102, the interference determination unit 122 stores three-dimensional coordinate values ​​indicating the positions and attitudes of the sets of rectangular parallelepipeds of the robot and surrounding obstacles and times as an operation log in the operation log storage unit 131. The interference determination unit 122 detects rectangular parallelepipeds that spatially interfere with each other at the same time between the operation logs of the robot and surrounding obstacles, and determines whether or not there is interference. The interference determination unit 122 may display the determination result on the display unit 12. This allows the user to understand the positional relationship between the robot and surrounding obstacles.

[0025] <Interference check process of interference check device 1> Next, the flow of the interference check process of the interference check device 1 will be described with reference to FIG. 7 is a flowchart illustrating the interference check processing of the interference check device 1. The flow shown here is executed every time an interference check instruction for a robot (not shown) is received from the user via the input unit 11.

[0026] In step S1, when the enclosing rectangular parallelepiped set conversion unit 101 receives an instruction to convert a 3D model of a set of rectangular parallelepipeds of a robot from a user via the input unit 11, the enclosing rectangular parallelepiped set conversion unit 101 executes a 3D model conversion process to convert the shape data (3D CAD data) of the robot stored in the shape data storage unit 132 into a 3D model of a set of rectangular parallelepipeds of the robot. The detailed flow of the 3D model conversion process will be described later.

[0027] In step S2, similar to the case of the robot in step S1, the enclosing rectangular parallelepiped set conversion unit 101 executes a 3D model conversion process to convert the shape data (3D CAD data) of the surrounding obstacles stored in the shape data storage unit 132 into a 3D model of a set of rectangular parallelepipeds of the surrounding obstacles.

[0028] In step S3, the simulation execution unit 102 (interference determination unit 122) executes a simulation based on the operation program to operate the 3D model of the collection of rectangular parallelepipeds of the robot converted in step S1 and the 3D model of the collection of rectangular parallelepipeds of surrounding obstacles converted in step S2, and determines whether or not there is interference between the 3D model of the robot and the 3D models of the surrounding obstacles.

[0029] In step S4, the simulation execution unit 102 (interference determination unit 122) displays the determination result on the display unit 12.

[0030] <3D model conversion process of interference check device 1> FIG. 8 is a flowchart illustrating the detailed processing contents of the three-dimensional model conversion processing shown in steps S1 and S2 in FIG.

[0031] In step S21, the enclosing rectangular parallelepiped set conversion unit 101 receives an instruction to convert the 3D model of the set of rectangular parallelepipeds of the robot (or surrounding obstacles) from the user via the input unit 11, and reads the shape data (3D CAD data) of the received robot (or surrounding obstacles) from the shape data storage unit 132.

[0032] In step S22, the enclosing rectangular parallelepiped set conversion unit 101 determines whether the shape data read in step S21 is a nearby obstacle. If the shape data is a nearby obstacle, the process proceeds to step S23. On the other hand, if the shape data is not a nearby obstacle, that is, if the shape data is a robot, the process proceeds to step S24.

[0033] In step S23, the simplified range setting unit 111 displays, for example, shape data (3D CAD data) of nearby obstacles on the display unit 12, and accepts and sets a specified range to be used for interference check from the shape data of the nearby obstacles based on an input operation of the input unit 11 by the user.

[0034] In step S24, the point cloud data conversion unit 112 converts the shape data (3D CAD data) of the robot (or surrounding obstacles) into point cloud data of the robot (or point cloud data of surrounding obstacles within the specified range set in step S3).

[0035] In step S25, the genetic point cloud data division unit 113 randomly generates k combinations of (n-1) cut planes that divide the point cloud data of the robot (or surrounding obstacles) converted in step S24 into the number n of rectangular parallelepipeds input by the user via the input unit 11. The genetic point cloud data division unit 113 calculates the total volume of the set of rectangular parallelepipeds of the robot (or surrounding obstacles) divided by the (n-1) cut planes in each of the k combinations as an evaluation value for each combination of (n-1) cut planes.

[0036] In step S26, the genetic point cloud data division unit 113 recalculates the evaluation values ​​of the (n-1) cut planes for each of the k combinations newly generated by the genetic operation based on the genetic algorithm.

[0037] In step S27, the genetic point cloud data division unit 113 judges whether or not m candidates of point cloud sets have been obtained by repeating the maximum number of times m. If m candidates of point cloud sets have been obtained, the process proceeds to step S28. On the other hand, if m candidates of point cloud sets have not been obtained, the process returns to step S26.

[0038] In step S28, the minimum total volume search unit 114 searches for the (n-1) cut planes having the highest evaluation value among the evaluation values ​​of the (n-1) cut planes for each of the k combinations, that is, the (n-1) cut planes having the smallest total volume of the set of rectangular parallelepipeds in the 3D model of the robot (or surrounding obstacles), not shown, as optimal cut planes. The minimum total volume search unit 114 selects the set of rectangular parallelepipeds divided by the optimal (n-1) cut planes as the 3D model of the robot (or surrounding obstacles), not shown.

[0039] In step S29, the margin setting unit 115 sets a margin for the three-dimensional model of the set of rectangular parallelepipeds of the robot (or surrounding obstacles) selected in step S28.

[0040] As described above, the interference check device 1 according to one embodiment converts the robot and surrounding obstacles into a 3D model of a collection of rectangular parallelepipeds based on the shape data (3D CAD data) of the robot and surrounding obstacles. This enables the interference check device 1 to model the shapes of the robot and surrounding obstacles with a small amount of data, while improving the accuracy of the interference check. Furthermore, the interference checking device 1 uses a three-dimensional model of a collection of rectangular parallelepipeds, making it possible to reduce the calculation cost of the interference check and to perform the interference check at high speed.

[0041] Although one embodiment has been described above, the interference checking device 1 is not limited to the above-described embodiment, and may include modifications and improvements within the scope of achieving the object.

[0042] <Variation 1> In the embodiment described above, the interference check device 1 is a device separate from the robot control device (not shown), but is not limited to this. For example, the interference check device 1 may be included in the robot control device (not shown).

[0043] <Variation 2> Also, for example, in the above embodiment, the enclosing rectangular parallelepiped set conversion unit 101 converts the shape data (3D CAD data) of the robot (or surrounding obstacles) stored in the shape data storage unit 132 into point cloud data, divides the point cloud data into n pieces of point cloud data based on a genetic algorithm, and converts it into a 3D model of a set of rectangular parallelepipeds of the robot (or surrounding obstacles), but is not limited to this. For example, the enclosing rectangular parallelepiped set conversion unit 101 may convert the robot (or surrounding obstacles) into a 3D model of a set of rectangular parallelepipeds based on the number of rectangular parallelepipeds, the position of each rectangular parallelepiped, the size of each rectangular parallelepiped, etc. specified by the user based on the shape data (3D CAD data).

[0044] Each function included in the interference check device 1 in one embodiment can be realized by hardware, software, or a combination of these. Here, being realized by software means being realized by a computer reading and executing a program.

[0045] The program can be stored and provided to the computer using various types of non-transitory computer readable media. The non-transitory computer readable media includes various types of tangible storage media. Examples of the non-transitory computer readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs). The program may also be provided to the computer by various types of transitory computer readable media. Examples of the transitory computer readable media include electrical signals, optical signals, and electromagnetic waves. The transitory computer readable media can provide the program to the computer via wired communication paths such as electric wires and optical fibers, or wireless communication paths.

[0046] In addition, the steps of writing a program to be recorded on a recording medium include not only processes that are performed chronologically according to the order, but also processes that are not necessarily performed chronologically but are executed in parallel or individually.

[0047] In other words, the interference checking device of the present disclosure can take various forms having the following configurations.

[0048] (1) The interference checking device 1 disclosed herein is an interference checking device that performs interference checking between a robot and surrounding obstacles, and includes an enclosing rectangular parallelepiped set conversion unit 101 that converts each of the robot and surrounding obstacles into a 3D model that is a set of rectangular parallelepipeds, and an interference determination unit 122 that determines whether or not there is interference between the 3D model of the robot and the 3D model of the surrounding obstacles by simulating the operation of the 3D models of the robot and the surrounding obstacles based on an operating program. According to this interference check device 1, it is possible to improve the accuracy of interference check while modeling the shapes of the robot and surrounding obstacles with a small amount of data.

[0049] (2) The interference check device 1 described in (1) may include an input unit 11 for inputting the number of cuboids in the collection of cuboids, and the containing cuboid collection conversion unit 101 may include a point cloud data conversion unit 112 for converting the point cloud data of the robot and surrounding obstacles into point cloud data of the robot and surrounding obstacles based on their shape data, a genetic point cloud data division unit 113 for calculating an evaluation value for each combination of multiple cut planes that divide the point cloud data of the robot and surrounding obstacles into the number of cuboids input to the input unit 11 and recalculating the evaluation value for each combination of multiple cut planes that are newly generated based on a genetic algorithm, and a minimum total volume search unit 114 for searching for multiple cut planes with the highest evaluation value among the evaluation values ​​for each combination of multiple cut planes for the robot and surrounding obstacles. By doing so, the interference check device 1 can model each of the robot and surrounding obstacles as a collection of most fitting rectangular parallelepipeds.

[0050] (3) In the interference checking device 1 described in (1) or (2), the enclosing rectangular parallelepiped set conversion unit 101 may include a simplified range setting unit 111 that sets a range of the shape data of surrounding obstacles to be used in the simulation, and a margin setting unit 115 that sets a margin for the three-dimensional model of the robot and the set of rectangular parallelepipeds of the surrounding obstacles. In this way, the interference check device 1 can reduce the memory capacity required for the simulation by modeling only those parts of the surrounding obstacles that are required for the interference check.

[0051] (4) In the interference check device described in (2), the genetic point cloud data division unit 113 may recalculate the evaluation value for each combination of the multiple cutting planes a preset number of times. By doing so, the interference check device 1 can generate a three-dimensional model of an optimal set of rectangular parallelepipeds for each of the robot and surrounding obstacles. [Explanation of symbols]

[0052] 1. Interference check device 10 Control section 101 Containing Rectangular Parallelepiped Set Conversion Unit 111 Simplified range setting section 112 Point cloud data conversion section 113 Genetic point cloud data division part 114 Minimum total volume search section 115 Margin setting section 102 Simulation Execution Department 121 Coordinate system conversion section 122 Interference detection section 11 Input section 12 Display section 13 Storage section 131 Operation log memory unit 132 Shape data storage unit

Claims

1. An interference check device that checks for interference between a robot and surrounding obstacles, a rectangular parallelepiped set conversion unit that converts the robot and the surrounding obstacles into a three-dimensional model of a set of rectangular parallelepipeds; an interference determination unit that determines whether or not the three-dimensional model of the robot and the three-dimensional model of the peripheral obstacle interfere with each other by simulating the operation of the three-dimensional model of the robot and the peripheral obstacle based on an operation program; an input unit for inputting the number of rectangular parallelepipeds in the set of rectangular parallelepipeds, The containing rectangular parallelepiped set conversion unit is a point cloud data conversion unit that converts the shape data of the robot and the peripheral obstacle into point cloud data of the robot and the peripheral obstacle, respectively, based on the shape data of the robot and the peripheral obstacle; a point cloud data division unit that divides point cloud data of each of the robot and the surrounding obstacles into the number of the rectangular parallelepipeds input to the input unit, calculates an evaluation value for each combination of a plurality of cut surfaces obtained by dividing the point cloud data of each of the robot and the surrounding obstacles into the number of the rectangular parallelepipeds, and recalculates the evaluation value for each combination of the plurality of cut surfaces that are newly generated based on a genetic algorithm; and a minimum total volume search unit that searches for a plurality of cut surfaces that have the highest evaluation values ​​among the evaluation values ​​for each combination of the plurality of cut surfaces for the robot and each of the surrounding obstacles.

2. The containing rectangular parallelepiped set conversion unit is a simplified range setting unit that sets a range to be used in the simulation from among the shape data of the surrounding obstacles; 2. The interference check device according to claim 1, further comprising: a margin setting unit that sets a margin for a three-dimensional model of the set of rectangular parallelepipeds of the robot and the surrounding obstacles.

3. The interference check device according to claim 1 , wherein the point cloud data division unit recalculates the evaluation value for each combination of the plurality of cut surfaces a preset number of times.

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