Information processing system, information processing program and information processing method

Abstract

To solve the problem that track information cannot be generated, if a weld line is not defined as a line in three-dimensional data.SOLUTION: An information processing system includes at least one operation device which is configured to perform: master point group data generation processing (S3) of generating master point group data in which a surface shape of a work object is defined in a point group from three-dimensional model data of the work object; and first work information data generation processing (S5) of extracting a work object place of the work object from the master point group data, and generating work information data including at least an operation path of a work tool performing work on the extracted work object place.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to an information processing system, an information processing program, and an information processing method, and more particularly to an information processing system, an information processing program, and an information processing method for generating work information data used for controlling a robot. [Background technology]

[0002] In controlling a work robot that performs work such as welding, it is necessary to generate work information data that includes at least information on the trajectory of the arm movement. Therefore, a technology for generating trajectory information required for generating work information data is disclosed in Patent Document 1. Patent Document 1 shows a weld line selection method that quickly extracts weld lines based on three-dimensional CAD data. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2010-184278 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the technique described in Patent Document 1 has a problem in that unless the weld line is defined as a line in the three-dimensional model data, it is not possible to generate the weld line (for example, trajectory information). [Means for solving the problem]

[0005] One aspect of the present invention is an information processing system comprising at least one computing device configured to perform a master point cloud data generation process for generating master point cloud data that defines a surface shape of a work object as a point cloud from three-dimensional model data of the work object, and a first work information data generation process for extracting work target locations of the work object from the master point cloud data, and generating work information data including at least an operation path of a work tool that will perform work on the extracted work target locations.

[0006] One aspect of the present invention is an information processing program that causes a computing device to execute a master point cloud data generation process that generates master point cloud data that defines the surface shape of a work object as a point cloud from three-dimensional model data of the work object, and a first work information data generation process that extracts work target locations of the work object from the master point cloud data, and generates work information data that includes at least an operation path of a work tool that will perform work on the extracted work target locations.

[0007] One aspect of the present invention is an information processing method for generating work information data including at least a movement path of a work tool from three-dimensional model data using a computer, the information processing method comprising the steps of generating master point cloud data that defines a surface shape of a work object as a point cloud from the three-dimensional model data of the work object, extracting work target locations of the work object from the master point cloud data, and generating the work information data corresponding to the extracted work target locations.

[0008] One aspect of the present invention uses master point cloud data generated from three-dimensional model data to generate work information data including at least a motion path of a work tool that will perform work on a work target location. Effect of the Invention

[0009] According to one aspect of the present invention, it is possible to generate work information data that includes at least the movement path of a work tool that performs work on a location that is not defined as line data in three-dimensional model data. [Brief description of the drawings]

[0010] [Figure 1] 1 is a schematic diagram of a working robot system according to a first embodiment. [Diagram 2] FIG. 2 is a diagram illustrating an example of work using the working robot system according to the first embodiment. [Diagram 3] 4 is a flowchart illustrating an operation of the information processing system according to the first embodiment. [Figure 4] 11 is a flowchart illustrating a flow of a work information data generation process in the information processing system according to the first embodiment. [Diagram 5] 5 is a diagram for explaining a specific example of the operations from step S10 to step S13 in the flowchart shown in FIG. 4. [Figure 6] 11 is a flowchart illustrating the flow of a tool path determination process in the information processing system according to the first embodiment. [Figure 7] 7 is a diagram for explaining a specific example of the operations of steps S20, S22, and S24 in the flowchart shown in FIG. 6. [Figure 8] 11 is a flowchart illustrating an operation of the information processing system according to the second embodiment. [Figure 9] 13 is a flowchart illustrating an operation of the information processing system according to the third embodiment. [Figure 10] 13 is a flowchart illustrating the flow of a work information data correction process in the information system according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] In order to clarify the description, the following description and drawings are omitted and simplified as appropriate. In addition, each element shown in the drawings as a functional block performing various processes can be configured in hardware with a CPU (Central Processing Unit), memory, and other circuits, and in software, can be realized by a program loaded into memory. Therefore, it is understood by those skilled in the art that these functional blocks can be realized in various forms by hardware alone, software alone, or a combination thereof, and are not limited to any one of them. In addition, the same elements are given the same symbols in each drawing, and duplicated explanations are omitted as necessary.

[0012] Moreover, the above-mentioned program includes a set of instructions (or software code) for making the computer perform one or more functions described in the embodiment when the program is read into the computer. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or the tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray (registered trademark) disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or a communication medium. By way of example and not limitation, the transitory computer-readable medium or the communication medium includes electrical, optical, acoustic, or other forms of propagating signals.

[0013] First embodiment Hereinafter, embodiments of the present invention will be described with reference to the drawings. Fig. 1 is a schematic diagram of a working robot system according to the first embodiment. As shown in Fig. 1, the working robot system 1 according to the first embodiment includes a computer 10 and a working robot 20. The working robot 20 has a robot arm 21 mounted on a base, and a work tool 22 and a working sensor 23 attached to the tip of the working robot 20.

[0014] Computer 10 receives three-dimensional model data generated elsewhere, or generates three-dimensional model data. Computer 10 also generates work information data used in controlling working robot 20 using the three-dimensional model data. Here, the generation of the work data involves a number of processes, but these processes may be performed using at least one computer 10, and the number of computers 10 included in working robot system 1 is not limited to one. Computer 10 also transmits the generated work information data to working robot 20. In working robot system 1 according to the first embodiment, working robot 20 has a control unit (not shown) that controls robot arm 21, and controls robot arm 21 using the work information data received by the control unit.

[0015] The working robot 20 is capable of performing at least one of the following tasks: welding, painting, coating, cutting, polishing, grinding, and turning. The robot arm 21 moves the work tool 22 attached to the tip of the robot arm 21 and the working part sensor 23 along a trajectory defined by the work information data.

[0016] The work tool 22 varies depending on the work to be performed. For example, the work tool 22 is a welding torch, nozzle, welding rod, etc. when performing welding work, and a painting tool such as a painting gun when performing painting work. Other possible work tools include coating tools (e.g., coating spray), cutting tools (e.g., drills, end mills, milling cutters), polishing tools (e.g., polishing brushes), cutting tools (grindstones, cup brushes, diamond bars), turning tools (e.g., bits), etc.

[0017] Working sensor 23 is a sensor that scans the shape of a work target. Possible sensors of this type include LiDAR (Light Detection and Ranging), a line scanner, a three-dimensional scanner, etc. In working robot system 1 according to the first embodiment, working sensor 23 is used to recognize the shape of the work target before work is performed and to recognize the shape of the work target after work is performed.

[0018] Fig. 2 is a diagram illustrating an example of a task using the working robot system 1 according to the first embodiment. In the example shown in Fig. 2, non-welded members 31 are overlapped on a base material 30, and the non-welded members 31 are welded along a welding target line WL set at an end thereof, thereby joining the non-welded members 31 to the base material 30. In this case, in the working robot system 1 according to the first embodiment, the working robot 20 controls the robot arm 21 so that the tip of the work tool 22 moves along the welding target line WL at a predetermined speed and at a predetermined angle with respect to the base material 30.

[0019] In working robot system 1 according to the first embodiment, before production activities are carried out, work information data must be created for each task performed on a work target. Then, in working robot system 1 according to the first embodiment, computer 10 creates work information data from three-dimensional model data. In this way, by creating work information data from three-dimensional model data, working robot 20 is used to create work information data without using an actual object such as a prototype.

[0020] Here, the three-dimensional model data includes three-dimensional CAD (Computer Aided Design) data and attribute data described later. The CAD data may be data that has surface information indicating the shape of the work object. The data format of the CAD data is STEP (Standard for the Exchange of Product model data), IGES (Intial Graphics Exchange Specification), STL (STereoLithography), etc. The attribute data includes data such as part names, product numbers, materials, dimensions, work conditions, and contour shapes. As described later, the attribute data may include work object lines. The attribute data may be data included in the three-dimensional model data and configured in a computer-readable data format, or may be data of assemblies and parts described in drawings drawn on paper (e.g., ASSY (Assembly) data). The work information data includes shape data of the contour line of the work object, position data indicating the position of the contour line on the work object, and data related to work information such as dimensions of the work object, work position, work path, material and plate thickness for each part of the work object. For example, in the case of welding work, the attribute data may include at least one of data on welding conditions such as welding current, welding speed, and torch angle.

[0021] In working robot system 1 according to the first embodiment, a model-based work information data generation process is carried out on computer 10 to generate work information data from three-dimensional model data without using an actual object. This model-based work information data generation process is carried out by executing an information processing program stored in a storage device mounted on computer 10 using a calculation device such as a CPU.

[0022] The model-based work information data generation process will be described in detail below. The model-based work information data generation process includes a plurality of processes, which may be executed by one computer or a plurality of computers. Therefore, in the following description, the computer 10 will be referred to as an information processing system. For the sake of simplicity, the model-based work information data generation process will be described below using an example of generating work information data corresponding to welding work. However, the model-based work information data generation process according to the first embodiment can be applied to various works other than welding work.

[0023] FIG. 3 is a flowchart illustrating the operation of the information processing system according to the first embodiment.

[0024] As shown in FIG. 3, the information processing system described below includes at least one computing device configured to perform a master point cloud data generation process (steps S1 to S3) for generating master point cloud data that defines the surface shape of the work object as a point cloud from three-dimensional model data of the work object, and a first work information data generation process (step S5) for extracting work target locations of the work object from the master point cloud data, and generating work information data that includes at least the motion path of a work tool that will perform work on the extracted work target locations.

[0025] As shown in Fig. 3, in the model-based work information data generation process according to the first embodiment, first, a model data acquisition process is performed to acquire three-dimensional model data of a work object that has already been generated (step S1). Next, in the model-based work information data generation process according to the first embodiment, a three-dimensional mesh data generation process is performed to generate three-dimensional mesh data of the work object from the three-dimensional model data acquired in step S1 (step S2). These steps S1 and S2 may be collectively referred to as a data conversion process.

[0026] The 3D mesh data generated in step S2 represents the overall shape of the work object using unit meshes defined at a predetermined size. The 3D mesh data makes it possible to handle the shape of the work object as a set of faces.

[0027] Next, the model-based work information data generation process according to the first embodiment performs a master point cloud data generation process for generating master point cloud data that defines the surface shape of the work object as a point cloud from the three-dimensional model data of the work object (step S3). In the example shown in FIG. 2, the three-dimensional mesh data generated in step S2 is used as three-dimensional model data in step S3. In the master point cloud data generation process according to the first embodiment, for example, a virtual cube that covers the entire three-dimensional mesh data is defined, and when a measurement line perpendicular to one face of the virtual cube is extended to the three-dimensional mesh data, a point at which the measurement line intersects with the three-dimensional mesh data is taken as one of the master point cloud data. The master point cloud data includes a number of intersections between the measurement lines and the three-dimensional mesh data, and is a collection of countless point information. This point information is, for example, coordinate information. Here, for example, if one side of the virtual cube is considered to be a side on which the work object can be observed by the working unit sensor 23 when the work object is placed on the workbench, a correlation can be obtained with the actual point cloud data of the work object acquired by the working unit sensor 23 during actual work, thereby improving work efficiency.

[0028] Next, the model-based work information data generation process according to the first embodiment performs an attribute data extraction process to extract attribute data from the three-dimensional model data (step S4). The attribute data extracted in step S4 includes at least position information of the work target location defined by the dimensions of the work target, the work position, and the work path. The attribute data may also include position data indicating the position of the contour line of the work target, and data related to work information such as the material and plate thickness of each part of the work target. Here, in the model-based work information data generation process according to the first embodiment, as an example, the position information of the work target location is defined by the attribute data included in the three-dimensional model data.

[0029] Next, the model-based work information data generation process according to the first embodiment performs a first work information data generation process (e.g., work information data generation process of step S5) in which a work target portion of the work object is extracted from the master point cloud data, and work information data including at least an operation path (e.g., a tool path) of the work tool 22 that performs work on the extracted work target portion is generated. The work information data generation process of step S5 includes a plurality of processes, and therefore the work information data generation process of step S5 will be described in detail with reference to Figs. 4 and 5.

[0030] Fig. 4 is a flowchart for explaining the flow of work information data generation processing in the information processing system according to the first embodiment. Fig. 5 is a diagram for explaining a specific example of the operations from step S10 to step S13 of the flowchart shown in Fig. 4. In Fig. 5, the surface of the work object on which the point cloud is set is shown by hatching. Also, in Fig. 5, a work object material (e.g., non-welded member 31) is placed on the surface of base material 30, and a curved portion of the outer periphery of non-welded member 31 is to be welded. That is, in the first embodiment, an example of generating work information data corresponding to a work object line having a curve will be described.

[0031] As shown in Figure 4, the work information data generation process in step S5 includes a base material surface extraction process (steps S10, S11) that extracts the base material surface on which the work target line is set from the master point cloud data, a boundary line extraction process (step S12) that extracts a boundary line that defines the outer periphery of the base material surface on the master point cloud data, a continuous line data conversion process (step S13) that converts a line among the boundary lines that is specified as the work target line into continuous line data consisting of a series of approximation lines, and a tool path determination process (step S14) that determines a tool path that defines the movement trajectory of the work tool 22 attached to the robot arm 21 based on the continuous line data.

[0032] As shown in Fig. 4, in the work information data generation process in step S5, first, the master point cloud data generated in step S3 is acquired (step S10). The master point cloud data acquired in step S10 is, for example, the one shown in the diagram corresponding to step S10 in Fig. 5, in which non-welded members 31 are placed on the surface of base material 30. In the first embodiment, the portion of the outer periphery of non-welded members 31 that is composed of curved surfaces is to be welded.

[0033] Next, in the work information data generation process in step S5, a base material surface extraction process is performed to extract the base material surface on which the work target line is set from the master point cloud data (step S11). As shown in the diagram corresponding to step S11 in Fig. 5, in step S11, an area excluding the point cloud data of the portion corresponding to the non-welded member 31 is extracted from the master point cloud data as the base material surface.

[0034] Next, in the work information data generation process in step S5, a boundary extraction process is performed to extract a boundary line that defines the periphery of the base material surface on the master point cloud data (step S12). As shown in the diagram corresponding to step S12 in Fig. 5, in step S12, a boundary line 32 that defines the periphery of the base material surface is extracted from the master point cloud data.

[0035] Next, in the work information data generation process in step S5, a continuous line data conversion process is performed to convert the line designated as the work target line 33 among the boundary line 32 into continuous line data in which approximation lines are continuous (step S13). In the diagram corresponding to step S13 in FIG. 5, only the work target line 33 extracted in step S13 is shown. This work target line 33 is defined as continuous line data by a combination of multiple approximation lines, each of which is a straight line. The approximation line may also include a curved line. This work target line 33 may be designated by the attribute data extracted in step S4, or may be designated by the user while referring to the screen.

[0036] Next, in the work information data generation process in step S5, a tool path determination process is performed to determine a tool path that defines the movement trajectory of a tool (e.g., the work tool 22) attached to the robot arm based on the continuous line data (step S14). Here, the tool path determination process in step S14 is performed by a plurality of processes, so the tool path determination process will be described in detail with reference to Figs. 6 and 7.

[0037] Fig. 6 is a flowchart for explaining the flow of a tool path determination process in the information processing system according to the first embodiment. Fig. 7 is a diagram for explaining a specific example of the operations of steps S20, S22, and S24 of the flowchart shown in Fig. 6. Note that in Fig. 7 as well, the surface of the work object on which the point cloud is set is shown by hatching. Fig. 7 shows the same example as Fig. 5. Note that the continuous line data shown in Fig. 7 is schematic data having fewer approximation lines than the number of approximation lines constituting the actual continuous line data, for the sake of explanation.

[0038] As shown in FIG. 6, the tool path determination process in step S14 includes an end point extraction process (step S20) for extracting end points 34 of each approximation line included in the continuous line data, a normal calculation process (steps S22, S23) for calculating a normal 36 for each end point 34, a Cartesian coordinate system calculation process (step S24) for calculating Cartesian coordinate system data for each end point 34 by normalizing the Z-axis, the X-axis, and the Y-axis, with the normal 36 as the Z-axis, the direction toward the next end point 34 as the X-axis, and the cross product of the Z-axis and the X-axis as the Y-axis, and a data generation process (step S27) for generating work information data by connecting the Cartesian coordinate system data calculated for each end point 34 in order from the start point of the continuous line data toward the end point.

[0039] As shown in Fig. 6, in the tool path determination process in step S14, first, an end point extraction process is performed to extract end points of each approximation line included in the continuous line data obtained in step S13 (step S20). As shown in the diagram corresponding to step S20 in Fig. 7, a large number of end points 34 are set on the continuous line data by the end point extraction process. Note that, of the multiple end points 34, the start point of the continuous line data is numbered 0, and the end point is numbered Ne. Also, in Fig. 6, N is shown as a variable indicating the end point number.

[0040] Next, in the tool path determination process in step S14, N is initialized to 0 (step S21), and while N is incremented by one (step S26), the processes in steps S22 to S24 are repeated until the end point number N becomes the end point number Ne of the end point (step S25).

[0041] In the tool path determination process in step S14, a normal calculation process for calculating a normal for each end point is performed in steps S22 and S23. In step S22, point cloud data within a range of radius R centered on the end point of the processing target is extracted. As shown in the diagram corresponding to step S22 in FIG. 7, only point cloud data within a range of radius R centered on the end point 34 of the processing target is extracted in step S22. Then, in step S23, a normal at the end point 34 of the processing target is calculated using the point cloud data extracted in step S22. As shown in the diagram corresponding to step S23 in FIG. 7, in step S23, a normal 36 starting from the end point 34 of the processing target is calculated. This normal is calculated by analyzing the point cloud data within a range of radius R centered on the end point 34 using a method such as Principle Component Analysis (PCA).

[0042] Next, in the tool path determination process in step S14, a Cartesian coordinate system calculation process is performed for each end point, in which the normal line is the Z axis, the direction toward the next end point is the X axis, and the cross product of the Z axis and the X axis is the Y axis, and the Z, X, and Y axes are normalized to calculate Cartesian coordinate system data (step S24). In the diagram corresponding to step S24 shown in Fig. 7, the Z, X, and Y axes are defined for three end points 34, but in step S24, Cartesian coordinate system data in which the Z, X, and Y axes are normalized is calculated for all end points.

[0043] Next, in the tool path determination process in step S14, a data generation process is performed in which the orthogonal coordinate system data calculated for each end point calculated in step S24 of the repeated process of steps S22 to S26 is connected in order from the start point of the continuous line data toward the end point to generate work information data (tool path) (step S27). Also, in step S27, the generated work data is stored in a work information data storage unit, which is one of the storage units on the computer 10.

[0044] As described above, the information processing system according to the first embodiment generates work information data using master point cloud data generated from three-dimensional model data. In this way, by converting the three-dimensional model data into master point cloud data, it becomes possible to define a work target line 33 on the master point cloud data even if the work target location is not defined as line data on the three-dimensional model data. Then, by using this work target line 33, the information processing system according to the first embodiment becomes able to generate work information data applicable to the work robot 20.

[0045] Furthermore, by using the information processing system according to the first embodiment to generate work information data without using an actual object, there is no need to generate work information data using the working robot 20 and a prototype, so that work information data can be generated regardless of, for example, the location of the working robot 20. In other words, with the working robot system 1 according to the first embodiment, work information data can be created without operating the working robot 20 in advance, which makes it possible to improve business efficiency.

[0046] Furthermore, when work information data is created using an actual work object and working robot 20, variations in how the work object is placed can adversely affect the accuracy of the work information data. However, with working robot system 1 according to the first embodiment, work information data is generated from three-dimensional model data that is free of variations, making it possible to generate highly accurate work information data that is unrelated to variations in how the work object is placed.

[0047] Embodiment 2 In the second embodiment, a description will be given of another mode of the model-based work information data generation process according to the first embodiment. Note that in the description of the second embodiment, the same reference numerals as those in the first embodiment will be used to denote the matters described in the first embodiment, and the description will be omitted.

[0048] Fig. 8 is a flowchart for explaining the operation of the information processing system according to the embodiment 2. As shown in Fig. 8, the model-based work information data generation process according to the embodiment 2 is obtained by adding the processes of steps S30 to S33 to the model-based work information data generation process according to the embodiment 1.

[0049] The information processing system of the second embodiment includes a data conversion process (steps S1, S2) of acquiring three-dimensional model data of a work object and generating three-dimensional mesh data of the work object, a shape determination process (step S30) of determining whether or not the work object is defined as line data on the three-dimensional model data, a primitive shape data extraction process (step S31) of extracting a primitive shape from the three-dimensional mesh data and generating primitive shape data if the work object is defined as line data on the three-dimensional model data in the shape determination process (step S30), and a second work information data generation process (steps S32, S33) of generating work information data according to the line data on the primitive shape data, and if the work object is defined as line data on the three-dimensional model data in the shape determination process (step S30), a master point cloud data generation process (step S3) and a first work information data generation process (step S5) are performed.

[0050] In the model-based work information data generation process according to the second embodiment, following the three-dimensional mesh data generation process (step S2), a shape determination process is carried out to determine whether the work target area is defined as line data on the three-dimensional model data (step S30).

[0051] In the three-dimensional model data, the lines that define the shape of the components are defined as line data. Therefore, when joining end faces, the line data that defines the periphery of the end faces of the components is defined in the three-dimensional model data, and the work information data can be generated using this line data as the work target line. On the other hand, for example, when performing processing such as overlapping one component on the surface of another component, no line data is defined on the surface of the one component, and it is necessary to perform the work information data generation process (step S5) using the master point cloud data (step S3) described in the first embodiment.

[0052] In the model-based work information data generation process according to the second embodiment, if the work target area is not defined as line data on the three-dimensional model data in the shape determination process of step S30, the processes of steps S3 to S5 described in the first embodiment are carried out.

[0053] On the other hand, in the model-based work information data generation process according to the second embodiment, if the work target area is defined as line data on the three-dimensional model data in the shape determination process of step S30, a primitive shape data extraction process is performed to extract a primitive shape from the three-dimensional mesh data and generate primitive shape data (step S31).

[0054] Here, a primitive shape is a relatively simple shape that is determined in advance, such as a cube, a rectangular solid, a sphere, a cylinder, a cone, etc. Data having information on the lines and faces of such shapes is called primitive shape data. In the primitive shape data extraction process in step S31, the work object is replaced with model data that combines primitive shapes.

[0055] Next, in the model-based work information data generation process according to the second embodiment, an attribute data extraction process is performed to extract attribute data from the three-dimensional model data in the same manner as in step S4 (step S32). After that, in the model-based work information data generation process according to the second embodiment, a second work information data generation process (for example, work information data generation process (step S33)) is performed to generate work information data according to the line data on the primitive shape data.

[0056] Replacing model data using primitive shape data can reduce the calculation load compared to creating master point cloud data. Therefore, by using the model-based work information data generation process according to the second embodiment, the amount of calculation of the information processing system can be appropriately reduced depending on the complexity of the work object and the work content. In other words, by using the model-based work information data generation process according to the second embodiment, it is possible to reduce the time required to generate work information data.

[0057] Third embodiment In the third embodiment, a description will be given of another mode of the model-based work information data generation process according to the first embodiment. Note that in the description of the third embodiment, the same reference numerals as those in the first embodiment will be used to denote the matters described in the first embodiment, and the description thereof will be omitted.

[0058] Fig. 9 is a flowchart illustrating the operation of the information processing system according to the third embodiment. Fig. 10 is a flowchart illustrating the flow of the work information data correction process in the information system according to the third embodiment.

[0059] As shown in Figures 9 and 10, the model-based work information data generation process according to the third embodiment includes an actual point cloud data acquisition process (step S40) for acquiring actual point cloud data from a work object using the working unit sensor 23, and a work information data correction process (step S41) for generating corrected work information data by correcting the work information data based on the actual point cloud data. The work information data correction process (step S41) includes a transformation matrix calculation process (steps S50, S51) for calculating a transformation matrix for transforming the master point cloud data so that the positions of pre-specified characteristic points between the master point cloud data and the actual point cloud data match, and a data correction process (step S52) for applying the inverse matrix of the transformation matrix to the work information data to generate corrected work information data.

[0060] 9, the model-based work information data generation process according to the third embodiment is obtained by adding steps S40 and S41 to the model-based work information data generation process according to the first embodiment. Specifically, the model-based work information data generation process according to the third embodiment corrects the work information data generated in step S5 in accordance with the state of the work target (actual object) placed on the workbench in steps S40 and S41.

[0061] Therefore, in the model-based work information data generation process of the third embodiment, after the work information data generation process of step S5, an actual point cloud data acquisition process is performed to acquire actual point cloud data from the work object using a sensor (e.g., working unit sensor 23) (step S40).

[0062] Next, in the model-based work information data generation process according to the third embodiment, a work information data correction process is performed to generate corrected work information data by correcting the work information data based on the actual point cloud data (step S41). Here, the work information data correction process in step S41 performs a plurality of processes, which will be described with reference to FIG.

[0063] 10, in the work information data correction process in step S41, a feature portion extraction process is performed (step S50) to extract feature portions that are geometric features from both the master point cloud data created in step S3 and the actual point cloud data acquired in step S40. These feature portions can be, for example, notches, holes, and normals to specific locations on the work object.

[0064] Next, in the work information data correction process in step S41, a transformation matrix calculation process is performed to calculate a transformation matrix for transforming the master point cloud data so that the positions of pre-specified characteristic points (e.g., characteristic parts extracted in step S50) between the actual point cloud data and the master point cloud data match (step S51).

[0065] Next, in the work information data correction process in step S41, the inverse matrix of the transformation matrix is ​​applied to the work information data generated in step S5 to generate corrected work information data (step S52). By the data correction process in step S52, corrected work information data is generated by offsetting the work information data generated in step S5 by an offset amount corresponding to the deviation amount of the actual point cloud data from the master point cloud data.

[0066] As described above, in the model-based work information data generation process according to the third embodiment, even if an actual object is placed on the work table at a position or angle that is deviated from the shape defined by the master point cloud data, it is possible to operate the work robot 20 based on work information data that has been corrected to accommodate the deviation. By generating such work information data, it is possible to improve the accuracy of work performed by the work robot 20.

[0067] The actual point cloud data acquisition process (step S40) and the work information data correction process (step S41) of the model-based work information data generation process according to the third embodiment may be performed by the computer 10, or may be performed by a computer placed near the work robot 20, or by a processor in a control unit built into the work robot 20.

[0068] The present invention is not limited to the above-described embodiments, and can be modified as appropriate without departing from the spirit and scope of the present invention. For example, a person skilled in the art can easily conceive of implementing the present invention by appropriately combining the features described in each embodiment.

[0069] Finally, the embodiment of the present invention will be summarized with reference to the drawings etc. As shown in Figs. 1 to 10, the embodiment of the present invention will be described as follows.

[0070] (Appendix 1) A master point cloud data generation process (S1 to S3) for generating master point cloud data that defines a surface shape of a work object by a point cloud from three-dimensional model data of the work object; A first work information data generation process (S5) for extracting a work target location of the work object from the master point cloud data and generating work information data including at least an operation path of a work tool that performs work on the extracted work target location; An information processing system comprising at least one computing device configured to perform the steps of:

[0071] (Appendix 2) The first work information data generation process (S5) includes: A base material surface extraction process (S10, S11) for extracting a base material surface on which a work target line is set from the master point cloud data; A boundary line extraction process (S12) for extracting a boundary line defining an outer periphery of the base material surface on the master point cloud data; a continuous line data conversion process (S13) for converting the line designated as the work target line among the boundary lines into continuous line data including a continuous approximation line; a tool path determination process (S14) for determining a tool path that defines a movement trajectory of a tool attached to a robot arm based on the continuous line data; 2. An information processing system as described in claim 1, comprising:

[0072] (Appendix 3) An end point extraction process (S20) for extracting end points of each approximation line included in the continuous line data; A normal calculation process (S22, S23) for calculating a normal for each of the end points; a Cartesian coordinate system calculation process (S24) for calculating Cartesian coordinate system data by normalizing the Z axis, the X axis, and the Y axis, with the normal line being the Z axis, the direction toward the next endpoint being the X axis, and the cross product of the Z axis and the X axis being the Y axis; a data generation process (S27) for generating the work information data by sequentially connecting the orthogonal coordinate system data calculated for each of the end points from the start point of the continuous line data toward the end points; 3. The information processing system of claim 2, comprising:

[0073] (Appendix 4) 4. The information processing system according to claim 3, wherein the position information of the work target area is defined by attribute data included in the three-dimensional model data.

[0074] (Appendix 5) A data conversion process (S1, S2) for acquiring three-dimensional model data of the work object and generating three-dimensional mesh data of the work object; a shape determination process (S30) for determining whether or not the work target area on the three-dimensional mesh data is defined as line data on the three-dimensional model data; a primitive shape data extraction process (S31) for extracting a primitive shape from the three-dimensional mesh data and generating primitive shape data when the operation target portion is defined as line data on the three-dimensional model data in the shape determination process; A second work information data generation process (S32, S33) for generating the work information data along the line data on the primitive shape data, An information processing system according to any one of appendices 1 to 4, wherein, in the shape determination process (S30), when the work target area is defined as line data on the three-dimensional model data, the master point cloud data generation process (S3) and the first work information data generation process (S5) are performed.

[0075] (Appendix 6) An actual point cloud data acquisition process (S40) for acquiring actual point cloud data from the work object using a sensor; A work information data correction process (S41) for generating corrected work information data by correcting the work information data based on the actual point cloud data, The work information data correction process (S41) A transformation matrix calculation process (S50, S51) for calculating a transformation matrix for transforming the master point cloud data so that positions of pre-specified characteristic points in the master point cloud data and the actual point cloud data coincide with each other; A data correction process (S52) for applying an inverse matrix of the transformation matrix to the work information data to generate the corrected work information data; 6. The information processing system according to claim 1,

[0076] (Appendix 7) A master point cloud data generation process (S1 to S3) for generating master point cloud data that defines a surface shape of a work object by a point cloud from three-dimensional model data of the work object; A first work information data generation process (S5) for extracting a work target location of the work object from the master point cloud data and generating work information data including at least an operation path of a work tool that performs work on the extracted work target location; An information processing program that causes a computing device to execute the above.

[0077] (Appendix 8) An information processing method for generating work information data including at least a motion path of a work tool from three-dimensional model data using a computer, comprising: generating master point cloud data that defines a surface shape of the work object by a point cloud from the three-dimensional model data of the work object (S1 to S3); A work target portion of the work object is extracted from the master point cloud data, and the work information data corresponding to the extracted work target portion is generated (S5). Information processing methods. [Explanation of symbols]

[0078] 1. Working robot system 10. Computers 20 Working Robot 21 Robot Arm 22 Work tools 23 Working part sensor 30 Base material 31 Non-welded components WL Welding target line

Claims

1. A master point cloud data generation process for generating master point cloud data that defines a surface shape of a work object using a point cloud from three-dimensional model data of the work object; a first work information data generation process for extracting a work target location of the work object from the master point cloud data, and generating work information data including at least an operation path of a work tool that performs work on the extracted work target location; An information processing system comprising at least one computing device configured to perform the steps of:

2. The first work information data generation process includes: A base material surface extraction process for extracting a base material surface on which a work target line is set from the master point cloud data; A boundary line extraction process for extracting a boundary line defining an outer periphery of the base material surface on the master point cloud data; a continuous line data conversion process for converting the line designated as the work target line among the boundary lines into continuous line data including a continuous approximation line; a tool path determination process for determining a tool path that defines a movement trajectory of a tool attached to a robot arm based on the continuous line data; The information processing system according to claim 1 .

3. an end point extraction process for extracting end points of each approximation line included in the continuous line data; A normal calculation process for calculating a normal for each of the end points; a Cartesian coordinate system calculation process for calculating Cartesian coordinate system data by normalizing the Z axis, the X axis, and the Y axis for each of the end points, with the normal line as the Z axis, the direction toward the next end point as the X axis, and the cross product of the Z axis and the X axis as the Y axis; a data generation process in which the orthogonal coordinate system data calculated for each of the end points is sequentially connected from the start point of the continuous line data toward the end points to generate the work information data; The information processing system according to claim 2 .

4. The information processing system according to claim 1 , wherein the position information of the work target location is defined by attribute data included in the three-dimensional model data.

5. A data conversion process for acquiring three-dimensional model data of the work object and generating three-dimensional mesh data of the work object; a shape determination process for determining whether or not the work target area on the three-dimensional mesh data is defined as line data on the three-dimensional model data; a primitive shape data extraction process for extracting a primitive shape from the three-dimensional mesh data and generating primitive shape data when the operation target portion is defined as line data on the three-dimensional model data in the shape determination process; a second work information data generation process for generating the work information data along the line data on the primitive shape data; The information processing system according to claim 1, wherein, in the shape determination process, when the work target area is defined as line data on the three-dimensional model data, the master point cloud data generation process and the first work information data generation process are performed.

6. An actual point cloud data acquisition process for acquiring actual point cloud data from the work object using a sensor; A work information data correction process for generating corrected work information data by correcting the work information data based on the actual point cloud data, The work information data correction process includes: a transformation matrix calculation process for calculating a transformation matrix for transforming the master point cloud data so that positions of pre-specified characteristic points in the master point cloud data and the actual point cloud data coincide with each other; a data correction process for applying an inverse matrix of the transformation matrix to the work information data to generate the corrected work information data; The information processing system according to claim 1 , further comprising:

7. A master point cloud data generation process for generating master point cloud data that defines a surface shape of a work object using a point cloud from three-dimensional model data of the work object; a first work information data generation process for extracting a work target location of the work object from the master point cloud data, and generating work information data including at least an operation path of a work tool that performs work on the extracted work target location; An information processing program that causes a computing device to execute the above.

8. An information processing method for generating work information data including at least a motion path of a work tool from three-dimensional model data using a computer, comprising: generating master point cloud data that defines a surface shape of the work object by a point cloud from the three-dimensional model data of the work object; extracting a work target portion of the work object from the master point cloud data, and generating the work information data corresponding to the extracted work target portion; Information processing methods.

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