JP2019202408A - Information processing device, robot work determination method, and robot work determination program - Google Patents

Abstract

To cause a robot to execute sensing work appropriately.SOLUTION: A success rate calculating part 13 acquires work information in which work for attaching an attachment component to a component to be attached is defined by a plurality of work element modules (including non-active sensing modules). The success rate calculating part 13 calculates a robot-process work success rate in the attachment work on the basis of information acquired from design information DB22 and equipment information DB23. A sensing module activation processing part 14 selects the work module in which the calculated robot work success rate is lowest, and determines whether or not the non-active sensing module included in the selected work module should be activated.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an information processing apparatus, a robot work determination method, and a robot work determination program.

  2. Description of the Related Art Conventionally, in work organization that assigns work to each process of an assembly line for assembling products, optimization is performed in consideration of compliance with the work order in each process and leveling of work. Since this optimization process is difficult by manual work, a technique for providing the operator with information on the points to be considered for work organization and a technique using various algorithms have been proposed.

  When an assembly line includes a process performed by a work robot, a technique for generating a robot program for teaching a work robot of an operation using a robot action template having a three-layer structure is known.

JP 2016-1332086 A JP 2014-104529 A

  While the robot motion template can be described by using the three-layered robot motion template, the robot work success rate may be lowered because the robot motion description alone cannot follow changes in the work situation. . For this reason, in an actual robot program, it is necessary to describe a sensing operation including a sensor input to the robot and a determination based on sensor information.

  However, the more sensing work is added, the longer the robot work time. For this reason, it is necessary to make the sensing work moderately so that the work time does not become too long and the work success rate is equal to or higher than the predetermined value, but adding such a sensing work is not easy and troublesome. Take it.

  In one aspect, an object of the present invention is to provide an information processing apparatus, a robot operation determination method, and a robot operation determination program that can cause a robot to appropriately perform a sensing operation.

  In one aspect, the information processing apparatus acquires the work information defined by a plurality of work elements including work elements related to sensing work for assembling an assembly part to an assembly destination part, the assembly part, and the assembly A calculation unit that calculates a success rate of the assembling work based on tolerance information of a pre-part, placement accuracy of the assembling destination part, and accuracy information of a robot that performs the assembling work, and a plurality of assembling of the robot A determination unit that identifies an assembly operation with the smallest success rate calculated by the calculation unit and determines to execute the operation element related to the sensing included in the identified assembly operation when performing the operation; I have.

  The robot can properly execute the sensing work.

It is a figure showing roughly the composition of the information processor concerning one embodiment. It is a functional block diagram of an information processor. It is a figure which shows an example of the work information stored in work information DB. 4A is a diagram illustrating an example of the data structure of the design information DB, and FIG. 4B is a diagram illustrating an example of the data structure of the facility information DB. It is a figure for demonstrating each information of Fig.4 (a) and FIG.4 (b). It is a flowchart which shows the process of a success rate calculation part and a sensing module activation process part. It is a figure showing the outline of operation 1 to operation 4. It is a figure which shows the load table | surface at the time of assigning the operation | work 1 and the operation | work 4 to the process 1, and allocating the operation | work 2 and the operation | work 3 to the robot process. It is a figure which shows the outline | summary of the operation | work 2 and the operation | work 3 allocated to the robot process. It is a figure for demonstrating step S13, S14. It is a figure which shows the load table | surface at the time of activating a sensing module.

  Hereinafter, an embodiment of an information processing apparatus will be described in detail with reference to FIGS.

  FIG. 1 shows a hardware configuration of an information processing apparatus 10 according to an embodiment. The information processing apparatus 10 of this embodiment is, for example, a PC (Personal Computer) or the like, and as shown in FIG. 1, a CPU (Central Processing Unit) 90, a ROM (Read Only Memory) 92, and a RAM (Random Access Memory) 94. , A storage unit (here, HDD (Hard Disk Drive)) 96, a network interface 97, a portable storage medium drive 99, a display unit 93, an input unit 95, and the like. The display unit 93 includes a liquid crystal display or the like, and the input unit 95 includes a keyboard, a mouse, a touch panel, or the like. Each component of the information processing apparatus 10 is connected to a bus 98. In the information processing apparatus 10, a program (including a robot work determination program) stored in the ROM 92 or the HDD 96, or a program (including a robot work determination program) read from the portable storage medium 91 by the portable storage medium drive 99. 2 is implemented by the CPU 90. 2 also shows a work information DB (database) 21, a design information DB 22, and a facility information DB 23 stored in the HDD 96 of the information processing apparatus 10. The portable storage medium 91 is, for example, a portable storage medium such as a CD-ROM, a DVD disk, or a USB (Universal Serial Bus) memory, or a semiconductor memory such as a flash memory.

  FIG. 2 is a functional block diagram of the information processing apparatus 10. In the information processing apparatus 10, when the CPU 90 executes the program, as shown in FIG. 2, an input unit 11, a process plan formulation unit 12, a success rate calculation unit 13 as an acquisition unit and a calculation unit, and a determination unit As a sensing module activation processing unit 14 and a robot program generation unit 15. 2 may be implemented by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA).

  The information processing apparatus 10 uses the data in the DBs 21, 22, and 23 when the assembly line (manufacturing line) is started up or when it is necessary to organize the assembly line due to production fluctuations or resource fluctuations. Allocate work to each process. In addition, the information processing apparatus 10 generates a robot program for causing the robot to execute the work assigned to the process in which the robot is arranged, and outputs the robot program to the robot.

  In the present embodiment, the assembly line conveys products from process to process by a belt conveyor (not shown) or the like. A person or a robot is arranged in each process of the assembly line. A person or robot arranged in each process manufactures a product by performing the work assigned by the process plan on the product conveyed in the assembly line. The number of people and robots is arbitrary. Accordingly, there may be one robot or a plurality of robots.

  Hereinafter, functions of each unit of the information processing apparatus 10 illustrated in FIG. 2 will be described.

  The input unit 11 receives input from the administrator, reads work information from the work information DB 21 based on the input, and transmits the work information to the process plan formulation unit 12. Here, it is assumed that work information as shown in FIG. 3 is stored in the work information DB 21. FIG. 3 is a diagram illustrating assembly work information as an example of work information. In the example of FIG. 3, the assembly work information includes assembly part information, assembly destination part information, information about work contents when the work subject is a person, and information about work details when the work subject is a robot. And are included.

  The information on the assembled parts is information indicating what parts are assembled by a person or a robot in the assembly work. Further, the information on the assembly destination part is information indicating what the person or the robot is to assemble in the assembly operation.

  The information regarding the work content when the work subject is a person describes that the work “assembly work” includes the element work “gripping” and “fitting”. Further, it is described that it takes 2 seconds to perform each of the element operations “gripping” and “fitting”.

  The information about the work contents when the work subject is a robot includes the element module "Move", "Pick_sp", "TransferN", "Sense_image", "Place_sp", "MoveN" in the work module "Assembly". It is described that. Each element work module describes a time (work time MT) and an operation module. In addition, in the information regarding the work content when the work subject is a robot, information on the work subject robot is described (see the column of “facility”). In this embodiment, the work module has an element work module, and the element work module has an operation module. In addition, the information regarding the work content may include other information such as information on the tool to be used.

  Returning to FIG. 2, the process plan formulation unit 12 allocates each work to each process based on the work information received from the input unit 11. Specifically, the process plan formulation unit 12 considers a plurality of parameters such as parameters relating to workability of people and robots, and performs a local search method such as a tabu search or an annealing method, Assign work to the robot. The parameters include, for example, parameters such as time variations between processes and whether or not the same tool can be integrated into a specific process. The process plan formulation unit 12 transmits information on the work allocated to each process to the success rate calculation unit 13.

  The success rate calculation unit 13 acquires information on each work assigned to the robot, calculates a work success rate (robot work success rate) for each work, and also calculates a work success rate (robot for all processes) assigned to the robot. Process success rate). The success rate calculation unit 13 refers to the design information DB 22 and the facility information DB 23 when calculating.

  Here, as shown in FIG. 4A, the design information DB 22 includes variation information on the assembled components and variation information on the assembly destination components. Assembling parts variation information stores information of “assembling part name” and “outer tolerance” in association with each other. The assembly destination part variation information stores information of “assembly destination part name”, “installation position variation”, “assembly part dimensional tolerance”, and “assembly part shape tolerance”. For example, assuming that the assembled part is Parts_A as shown in FIG. 5, the outer tolerance “σa” of the assembled part Parts_A is stored in the variation information of the assembled part. The “outer tolerance” means a tolerance of dimensions in a predetermined direction (the width direction in FIG. 5) of the assembled part. Further, assuming that the assembly destination part is Parts_B as shown in FIG. 5, the assembly destination part variation information includes the installation position variation “σb” of the assembly destination part Parts_B and the assembly portion dimensional tolerance “σpbh”. ”And the shape tolerance“ σbh ”of the assembly portion are stored. The “installation position variation” means a variation in the position where the assembly destination component that is carried on the belt conveyor is installed. “Dimension tolerance of assembly part” means the tolerance of the distance between the outer edge of the part to be assembled and the center point of the part where the assembly part is assembled. “Shape tolerance of the assembly part” means the assembly part. Means the tolerance of the dimension in the width direction of the part to be assembled.

  In the equipment information DB 23, as shown in FIG. 4B, variation information of the robot is stored. As shown in FIG. 4B, the robot variation information includes information on “robot name”, “conveying position variation”, and “gripping deviation of assembled parts”. For example, assuming that a robot (Robot_A) as shown in FIG. 5 is used, as the robot variation information, as shown in FIG. 4B, the transfer position variation “σr” of Robot_A, The grip misalignment “σpr” is stored. The “conveyance position variation” means a variation from the target position when the robot conveys the assembled part. Further, “gripping deviation of assembled parts” means an amount of deviation of deviation between the center of the robot and the center of the assembled parts when the robot grips the assembled parts.

  A specific method for calculating the robot work success rate and the robot process work success rate by the success rate calculation unit 13 will be described later.

  Returning to FIG. 2, the sensing module activation processing unit 14 executes a process of activating the sensing module included in each work allocated to the robot from an inactive state. The sensing module activation processing unit 14 transmits the processing result to the robot program generation unit 15.

  The robot program generation unit 15 generates a robot program based on the processing result of the sensing module activation processing unit 14 and transmits it to the robot to which the work is allocated.

(About processing of the information processing apparatus 10)
Next, processes of the success rate calculation unit 13 and the sensing module activation processing unit 14 of the information processing apparatus 10 will be described in detail with reference to the other drawings along the flowchart of FIG.

  FIG. 6 is a flowchart showing the processes of the success rate calculation unit 13 and the sensing module activation processing unit 14.

  Assuming that the processing of FIG. 6 is executed, the assembly line performs the work 1, work 2, work 3, and work 4 shown in FIG. 7, and the process plan formulation unit 12 is stored in the work information DB 21. It is assumed that each work is assigned to each process based on the work information. As a result, as shown in FIG. 8, it is assumed that operations 1 and 4 are allocated to the process 1 in which a person performs the operations, and operations 2 and 3 are allocated to the process in which the robot performs the operations.

  FIG. 9 shows operations 2 and 3 performed in the robot process. The sensing module included in each operation is in an inactive state (a state where it is not performed) at the stage where the processing of FIG. 6 is started. The process of FIG. 6 is a process for appropriately activating the inactive sensing module so that the robot process work success rate satisfies a predetermined standard (becomes a target value or more).

  In the process of FIG. 6, first, in step S10, the success rate calculation unit 13 acquires information from the design information DB 22 and the facility information DB 23, and calculates the robot work success rate of each work belonging to the robot process. Further, the success rate calculation unit 13 calculates the success rate of the entire robot process (robot process work success rate) using the calculated robot work success rate of each work. Hereinafter, a method for calculating the robot work success rate will be described.

(How to calculate the robot work success rate)
First, the success rate calculation unit 13 identifies an assembly part, an assembly destination part, and a robot. In the example of operation 2 in FIG. 9, suppose that Parts_A is specified as an assembly part, Parts_B is specified as an assembly destination part, and Robot_A is specified as a robot.

  Next, the success rate calculation unit 13 acquires the external tolerance “σa” of Parts_A as information on the assembled part (Parts_A) from the design information DB 22 (FIG. 4A), and as information on the assembly destination part (Parts_B). The installation position variation “σb” of Parts_B, the dimensional tolerance “σpbh” of the assembly part, and the shape tolerance “σbh” of the assembly part are acquired. In addition, the success rate calculation unit 13 acquires the conveyance position variation “σr” and the assembly component gripping variation variation “σpr” as information on the robot (Robot_A) from the equipment information DB 23 (FIG. 4B).

  In this case, since the total variation amount “σ” when Parts_A is assembled to Parts_B is the above-described tolerance and the sum of squares of each variation amount, the success rate calculation unit 13 calculates σ based on the following equation (1). calculate.

Here, as shown in FIG. 5, the gap T between Parts_A and Parts_B when Parts_A is assembled at the center of Parts_B is Wa in the dimension in the width direction of Parts_A, and the dimension in the width direction of the assembly part of Parts_B. Is represented by the following equation (2).
T = (Wbh−Wa) / 2 (2)

Therefore, assuming that the total variation amount σ is a normal distribution, the random variable z is expressed by the following equation (3).
z = 3T / σ (3)

  For this reason, the success rate calculation unit 13 calculates the probability that Parts_A will fit in the assembly part (gap T) of Parts_B, that is, the robot work success rate yield from the following equation (4) based on the standard normal cumulative distribution formula.

  As described above, after the success rate calculation unit 13 calculates the robot work success rate for each work (work 2, 3) assigned to the robot process, the robot work success rate (90%) of the work 2 The product (69.3%) of the robot work success rate (77%) of the work 3 is calculated to obtain the robot process work success rate. Thereafter, the process proceeds to step S11.

  In step S11, the sensing module activation processing unit 14 compares the robot process work success rate calculated in step S10 with a predetermined target value.

  Next, in step S12, the sensing module activation processing unit 14 determines whether or not the robot process work success rate is smaller than the target value. If the determination here is negative, the entire process of FIG. 6 is terminated. If the determination is positive, the process proceeds to step S13.

  In step S13, the sensing module activation processing unit 14 selects a work module having the lowest robot work success rate from work modules including inactive sensing modules. For example, if the robot work success rate of the work 2 is 90% and the robot work success rate of the work 3 is 72%, the work 3 is selected as the work module having the lowest robot work success rate (one point in FIG. 10). (See chain line).

  Next, in step S14, the sensing module activation processing unit 14 selects a sensing module having the minimum MT (working time) from the selected sensing modules. For example, among the two sensing modules included in operation 3, when the sensing module displayed on the left side has a smaller MT, the left sensing module is selected (see the broken line frame in FIG. 10).

  Next, in step S16, the sensing module activation processing unit 14 adds the work time (MT) of the selected sensing module to the total robot work time (ΣMT) of the selected work module.

  Next, in step S18, the sensing module activation processing unit 14 adds the work success contribution rate of the selected sensing module to the robot work success rate of the selected work module. For example, if the work success contribution rate of the selected sensing module is 5%, the sensing module activation processing unit 14 adds the robot work success rate of 77% to the robot work success rate of the selected work module. %.

  Next, in step S20, the sensing module activation processing unit 14 recalculates the work time (MCT) of the entire robot process and the robot process work success rate. In other words, the sensing module activation processing unit 14 calculates the sum of the total robot operation time (ΣMT) of the operation 2 and the total robot operation time (ΣMT) of the operation 3 calculated in step S16, and performs the entire robot process. Working time (MCT). The sensing module activation processing unit 14 also calculates the product (69.3%) of the robot work success rate (90%) of the work 2 and the robot work success rate (77%) of the work 3 calculated in step S18. Is the robot process work success rate.

  Next, in step S22, the sensing module activation processing unit 14 compares the work time (MCT) of the entire robot process with the longest work time (cycle time: CT) of processes performed by a person. In this case, as shown in FIG. 11, the MCT in the case where the MT of the sensing module is added to the operation 3 in FIG. 8 is compared with the CT.

  Next, in step S24, the sensing module activation processing unit 14 determines whether or not MCT is smaller than CT. If the determination in step S24 is negative, that is, if the MCT is larger than the CT, the human hands are free and unsuitable, so the entire process of FIG. 6 ends. In this case, the sensing module activation processing unit 14 may output the fact to the display unit 93 or the like, or causes the process plan formulation unit 12 to redo the process plan formulation (allocation of work to each process). Also good. On the other hand, if the determination in step S24 is affirmed, the process proceeds to step S26.

  In step S26, the sensing module activation processing unit 14 activates the selected sensing module, and updates the ΣMT and the robot work success rate.

  Next, in step S28, the sensing module activation processing unit 14 updates the MCT of the entire robot process and the robot process work success rate. Thereafter, the process returns to step S11.

  Returning to step S11, the sensing module activation processing unit 14 compares the robot process work success rate updated in step S28 with a predetermined target value.

  Next, in step S12, the sensing module activation processing unit 14 determines whether or not the robot process work success rate is smaller than the target value. If the determination here is negative, the sensing module activation processing unit 14 ends all the processes in FIG. 6 because it is not necessary to activate the sensing module any more. In this case, the sensing module activation processing unit 14 transmits information on the work module assigned to the robot process, including information on the activated sensing module, to the robot program generation unit 15. The robot program generation unit 15 generates a robot program based on the received information, and transmits the generated robot program to the robot that executes the robot process.

  On the other hand, if the determination in step S12 is affirmed, the process proceeds to step S13. Thereafter, the sensing module activation processing unit 14 repeats the processes and determinations in steps S11 to S28 until the determination in step S24 is denied or until the determination in step S12 is denied. That is, the work module having the lowest robot work success rate is selected from the work modules including the inactive sensing module, and the inactive sensing module with the minimum MT included in the selected work module is set as the activation target. Then, when the sensing module to be activated is activated, if the MCT does not exceed the CT and the robot process work success rate exceeds the target value, the determination in step S12 is denied, and all the processes in FIG. 6 are completed. To do. In this case, the robot program generation unit 15 generates a robot program based on the information received from the sensing module activation processing unit 14 and transmits it to the robot. On the other hand, if the MCT exceeds CT before the robot process work success rate reaches the target value, the sensing module cannot be activated so that the robot process work success rate satisfies the target value. After the negative determination, the entire process of FIG. 6 ends. In this case, the sensing module activation processing unit 14 outputs the fact to the display unit 93 or the like, or causes the process plan formulation unit 12 to re-determine a process plan (allocation of work to each process).

  As described above, by activating the inactive sensing module, the sensing module can be activated to a degree necessary and sufficient to make the robot process work success rate equal to or higher than the target value.

  As described above in detail, according to the present embodiment, the success rate calculation unit 13 defines the work for assembling the assembly part to the assembly destination part using a plurality of work element modules (including inactive sensing modules). Get work information. And the success rate calculation part 13 calculates the success rate (robot work success rate) of each operation | work assembled | attached based on the information acquired from design information DB22 and equipment information DB23. In addition, the sensing module activation processing unit 14 selects a work module with the lowest calculated robot work success rate, and determines whether to activate an inactive sensing module included in the selected work module. Thereby, in this embodiment, since the sensing module of the operation | work with the lowest robot work success rate is activated, the sensing module suitable for raising a robot process work success rate can be activated.

  Further, according to the present embodiment, the sensing module activation processing unit 14 activates a sensing module that has the smallest increase (MT) in time (MCT) required for assembly work when the sensing module is activated. (S14). Thereby, an appropriate sensing module that does not increase MCT so much can be activated.

  Further, according to the present embodiment, the sensing module activation processing unit 14 performs processing until the success rate of the entire robot process work (robot process work success rate) satisfies the target value within a range in which the MCT does not exceed CT. Repeat (add more sensing modules that are gradually activated). Thereby, a sensing module can be activated moderately.

  In the above-described embodiment, the case has been described where, in step S14, the sensing module that is inactive and has the smallest MT among the selected work modules is to be activated. However, the present invention is not limited to this. For example, a sensing module that is inactive and has the largest work success contribution ratio among the selected work modules may be set as an activation target.

  In the above embodiment, the case has been described in which the entire process of FIG. 6 is terminated when the robot process work success rate is equal to or higher than the target value. However, the present invention is not limited to this. For example, while MCT is less than CT, the processing after step S13 may be repeated so as to increase the number of sensing modules to be activated as much as possible.

  In the above embodiment, the case where the process for activating the sensing module is executed when the robot process work success rate is not equal to or higher than the target value has been described. However, the present invention is not limited to this. For example, when there is a work whose robot work success rate has not reached a predetermined reference value, any of the sensing modules included in the work may be activated.

  The above processing functions can be realized by a computer. In that case, a program describing the processing contents of the functions that the processing apparatus should have is provided. By executing the program on a computer, the above processing functions are realized on the computer. The program describing the processing contents can be recorded on a computer-readable storage medium (excluding a carrier wave).

  When distributing the program, for example, the program is sold in the form of a portable storage medium such as a DVD (Digital Versatile Disc) or a CD-ROM (Compact Disc Read Only Memory) on which the program is recorded. It is also possible to store the program in a storage device of a server computer and transfer the program from the server computer to another computer via a network.

  The computer that executes the program stores, for example, the program recorded in the portable storage medium or the program transferred from the server computer in its own storage device. Then, the computer reads the program from its own storage device and executes processing according to the program. The computer can also read the program directly from the portable storage medium and execute processing according to the program. Further, each time the program is transferred from the server computer, the computer can sequentially execute processing according to the received program.

  The above-described embodiment is an example of a preferred embodiment of the present invention. However, the present invention is not limited to this, and various modifications can be made without departing from the scope of the present invention.

In addition, the following additional remarks are disclosed regarding description of the above embodiment.
(Additional remark 1) The acquisition part which acquires the operation | work information which defined the operation | work which assembles | assembles an assembly | attachment part with respect to an assembly | attachment destination part with the some work element containing the work element regarding sensing,
A calculation unit for calculating a success rate of the assembling work based on tolerance information of the assembling part and the assembling destination part, placement accuracy of the assembling destination part, and accuracy information of a robot that performs the assembling work;
When the robot performs a plurality of assembling operations, the assembling operation with the minimum success rate calculated by the calculation unit is identified, and the robot is caused to execute a working element related to the sensing included in the identified assembling operation. A decision unit that decides,
An information processing apparatus comprising:
(Additional remark 2) The said determination part performs the work element regarding the said sensing to be performed based on the time required in order to perform the work element regarding each sensing, when the specified said assembly | attachment operation | work contains two or more work elements regarding the said sensing The information processing apparatus according to appendix 1, wherein:
(Additional remark 3) The said determination part is made to perform based on the contribution with respect to the increase in the said success rate at the time of performing the work element regarding each sensing, when the specified said assembly | attachment operation | work contains multiple work elements regarding the said sensing The information processing apparatus according to appendix 1, wherein work elements relating to the sensing are determined.
(Additional remark 4) The said determination part repeats the process to determine until the success rate of the whole some said assembly | attachment work satisfy | fills a predetermined reference | standard, or while the required time of the said some assembly | attachment work is less than predetermined time, The information processing apparatus according to any one of appendices 1 to 3, which is characterized.
(Supplementary Note 5) Acquire information that defines the work of assembling the assembly part to the assembly part with multiple work elements including work elements related to sensing,
Calculating the success rate of the assembling work based on tolerance information of the assembling part and the assembling destination part, placement accuracy of the assembling destination part, and accuracy information of the robot that performs the assembling work;
When the robot performs a plurality of assembly operations, the assembly operation with the minimum calculated success rate is identified, and it is determined to cause the robot to perform a work element related to the sensing included in the identified assembly operation. ,
A robot work determination method, characterized in that a computer executes processing.
(Supplementary Note 6) In the determining process, when the specified assembly work includes a plurality of work elements related to sensing, the work related to sensing to be executed based on the time required to execute the work elements related to each sensing. The robot work determination method according to appendix 5, wherein an element is determined.
(Supplementary Note 7) In the determination process, when the identified assembly work includes a plurality of work elements related to sensing, execution is performed based on the contribution to the increase in the success rate when each work element related to sensing is executed. The robot work determination method according to appendix 5, wherein a work element related to the sensing is determined.
(Supplementary Note 8) In the determining process, the determining process is repeated until the success rate of the plurality of assembly works as a whole satisfies a predetermined standard, or the time required for the plurality of assembly works is less than a predetermined time. The robot work determination method according to any one of appendices 5 to 7, characterized by:
(Supplementary Note 9) Acquire information that defines the work of assembling the assembly part to the assembly destination part with a plurality of work elements including work elements related to sensing,
Calculating the success rate of the assembling work based on tolerance information of the assembling part and the assembling destination part, placement accuracy of the assembling destination part, and accuracy information of the robot that performs the assembling work;
When the robot performs a plurality of assembly operations, the assembly operation with the minimum calculated success rate is identified, and it is determined to cause the robot to perform a work element related to the sensing included in the identified assembly operation. ,
A robot operation determination program for causing a computer to execute processing.

10 Information processing device 13 Success rate calculation unit (acquisition unit, calculation unit)
14 Sensing module activation processing unit (decision unit)

Claims (6)

An acquisition unit that acquires work information defined by a plurality of work elements including work elements related to sensing work for assembling an assembly part to an assembly destination part;
A calculation unit for calculating a success rate of the assembling work based on tolerance information of the assembling part and the assembling destination part, placement accuracy of the assembling destination part, and accuracy information of a robot that performs the assembling work;
When the robot performs a plurality of assembling operations, the assembling operation with the minimum success rate calculated by the calculation unit is identified, and the robot is caused to execute a working element related to the sensing included in the identified assembling operation. A decision unit that decides,
An information processing apparatus comprising:   The determining unit determines the work element related to the sensing to be executed based on a time required to execute the work element related to each sensing when the identified assembling work includes a plurality of work elements related to the sensing; The information processing apparatus according to claim 1.   The determination unit performs the sensing work to be executed based on a contribution to the increase in the success rate when the working element related to sensing is executed when the identified assembling work includes a plurality of work elements related to sensing. The information processing apparatus according to claim 1, wherein an element is determined.   The determination unit repeats the determining process until a success rate of the plurality of assembly operations as a whole satisfies a predetermined criterion, or while a time required for the plurality of assembly operations is less than a predetermined time. Item 4. The information processing device according to any one of Items 1 to 3. Acquire the information that defines the work to assemble the assembly part to the assembly destination part with multiple work elements including work elements related to sensing,
Calculating the success rate of the assembling work based on tolerance information of the assembling part and the assembling destination part, placement accuracy of the assembling destination part, and accuracy information of the robot that performs the assembling work;
When the robot performs a plurality of assembly operations, the assembly operation with the minimum calculated success rate is identified, and it is determined to cause the robot to perform a work element related to the sensing included in the identified assembly operation. ,
A robot work determination method, characterized in that a computer executes processing. Acquire the information that defines the work of assembling the assembly part to the assembly destination part with multiple work elements including work elements related to sensing,
Calculating the success rate of the assembling work based on tolerance information of the assembling part and the assembling destination part, placement accuracy of the assembling destination part, and accuracy information of the robot that performs the assembling work;
When the robot performs a plurality of assembly operations, the assembly operation with the minimum calculated success rate is identified, and it is determined to cause the robot to perform a work element related to the sensing included in the identified assembly operation. ,
A robot operation determination program for causing a computer to execute processing.

Images