Information processing device, evaluation method, and evaluation program

Abstract

This information processing device (100) comprises: an acquisition unit (120) that acquires information representing the trajectory of movements of a user who is polishing an object; and an evaluation unit (150) that, on the basis of the trajectory, evaluates an application ability which is the ability to polish the object adaptively.

Description

Information processing device, evaluation method, and evaluation program

[0001] This disclosure relates to an information processing device, an evaluation method, and an evaluation program.

[0002] Many workers are employed in factories and other workplaces. Among these workers are skilled workers. Skilled workers in the manufacturing industry possess both basic and applied skills. Basic skills refer to the ability to perform prescribed actions. Applied skills refer to the ability to perform actions flexibly and adaptably. Training to become skilled workers is desired. To become a skilled worker, support for skill acquisition is necessary. Therefore, for example, technologies to support skill acquisition have been proposed (see Patent Document 1).

[0003] Japanese Patent Publication No. 2023-156177

[0004] The technology described in Patent Document 1 can evaluate basic abilities. However, the technology described in Patent Document 1 cannot evaluate applied abilities. Therefore, the question is how to evaluate applied abilities.

[0005] The purpose of this disclosure is to evaluate the application capabilities.

[0006] An information processing device according to one aspect of the present disclosure is provided. The information processing device includes an acquisition unit that acquires information indicating the trajectory of a user's actions in polishing an object, and an evaluation unit that evaluates the application ability, which is the ability to polish the object flexibly based on the trajectory.

[0007] According to this disclosure, application capabilities can be evaluated.

[0008] This is a diagram showing the hardware of the information processing device of Embodiment 1. This is a block diagram showing the functions of the information processing device of Embodiment 1. This is a diagram showing a specific example of the trajectory detection process of Embodiment 1. This is a diagram showing a specific example of the evaluation of basic capabilities of Embodiment 1. (A) to (C) are diagrams showing a specific example (1) of the evaluation process of applied capabilities of Embodiment 1. This is a diagram showing a specific example (2) of the evaluation process of Embodiment 1. This is a diagram showing a specific example (3) of the evaluation process of Embodiment 1. This is a diagram showing a specific example of the gradient image generation process of Embodiment 1. (A) and (B) show specific examples of the output process of Embodiment 1. This is a flowchart showing an example of the process executed by the information processing device of Embodiment 1. This is a block diagram showing the functions of the information processing device of Embodiment 2. (A) and (B) are diagrams showing specific examples of the trajectory output of Embodiment 2. This is a flowchart showing an example of the process executed by the information processing device of Embodiment 2. This is a diagram showing an example of the output of the improvement order of Embodiment 3. This is a flowchart showing an example of the process executed by the information processing device of Embodiment 3.

[0009] The embodiments will be described below with reference to the drawings.

[0010] Embodiment 1.

[0011] Figure 1 shows the hardware of the information processing device of Embodiment 1. The information processing device 100 is also called a computer. The information processing device 100 is a device that executes an evaluation method. The information processing device 100 has a processor 101, a volatile storage device 102, and a non-volatile storage device 103.

[0012] The processor 101 controls the entire information processing device 100. For example, the processor 101 may be a CPU (Central Processing Unit), an FPGA (Field Programmable Gate Array), etc. The processor 101 may also be a multiprocessor. The information processing device 100 may also have processing circuits.

[0013] The volatile storage device 102 is the main memory of the information processing device 100. For example, the volatile storage device 102 is RAM (Random Access Memory). The non-volatile storage device 103 is the auxiliary storage of the information processing device 100. For example, the non-volatile storage device 103 is an HDD (Hard Disk Drive) or an SSD (Solid State Drive). The information processing device 100 also communicates with the camera 200 and the display 300. The camera 200 and the display 300 may be included in the information processing device 100.

[0014] Next, the functions of the information processing device 100 will be described. Figure 2 is a block diagram showing the functions of the information processing device in the first embodiment. The information processing device 100 includes a storage unit 110, an acquisition unit 120, an extraction unit 130, a trajectory detection unit 140, an evaluation unit 150, an image generation unit 160, and an output unit 170.

[0015] The storage unit 110 may be implemented as a storage area reserved in a volatile storage device 102 or a non-volatile storage device 103. The storage unit 110 may also be called a memory. Some or all of the acquisition unit 120, extraction unit 130, trajectory detection unit 140, evaluation unit 150, image generation unit 160, and output unit 170 may be implemented by processing circuits. In addition, some or all of the acquisition unit 120, extraction unit 130, trajectory detection unit 140, evaluation unit 150, image generation unit 160, and output unit 170 may be implemented as modules of a program executed by the processor 101. For example, the program executed by the processor 101 is also called an evaluation program or an evaluation program product. For example, the evaluation program is recorded on a recording medium.

[0016] The memory unit 110 stores various types of information.

[0017] The acquisition unit 120 acquires multiple images. For example, the acquisition unit 120 acquires multiple images from the storage unit 110. Alternatively, for example, the acquisition unit 120 acquires multiple images from an external device. The external device is a device located outside the information processing device 100. For example, the external device may be a cloud server or external memory. The diagram of the external device is omitted. The acquisition unit 120 may also acquire multiple images from the camera 200. The multiple images are described below. The multiple images are images showing the user's work. The user is a worker in a factory or similar location.

[0018] The extraction unit 130 extracts multiple images showing the user polishing an object from among multiple images acquired by the acquisition unit 120. For example, the extraction unit 130 uses a trained model based on CNN (Convolutional Neural Network) to extract multiple images showing the user polishing an object. Note that the above "polishing" can also be expressed as "scraping". Also, for example, the object is a mold. In the following explanation, the object will be a mold.

[0019] The trajectory detection unit 140 detects the trajectory of the user's action of polishing an object based on multiple images extracted by the extraction unit 130. The trajectory detection process will be explained using a specific example.

[0020] Figure 3 shows a specific example of the trajectory detection process of Embodiment 1. Figure 3 shows an example of multiple images extracted by the extraction unit 130. These multiple images are images 10_1, 10_2, etc. Figure 3 also shows a mold 10a. Furthermore, Figure 3 shows a tool 10b equipped with a blade 10c. Images 10_1, 10_2, etc. show the user polishing the mold 10a using the tool 10b.

[0021] The trajectory detection unit 140 detects a predetermined object. For example, the object is the blade 10c or the user's fingernail. In the following description, the object will be the blade 10c. The trajectory detection unit 140 uses equations (1) and (2) to determine the centroid coordinate (x) of the region of the blade 10c. ｇ , y ｇ Calculate the result.

[0022]

[0023]

[0024] Note, x ｉ y is the x-coordinate of pixel i within the region of blade 10c. ｉ is the y-coordinate of pixel i within the region of blade 10c. N is the number of pixels in the region of blade 10c.

[0025] Figure 3 shows the centroid coordinates 10d_1. Similarly, the trajectory detection unit 140 calculates the centroid coordinates (x) for each image. ｇ , y ｇ The centroid coordinates (x) are calculated for each image. ｇ , y ｇ Based on this, the trajectory can be obtained. Figure 3 shows information 11 indicating the trajectory. In this way, information indicating the trajectory of the user's actions as they polish the object can be obtained. The acquisition unit 120 acquires this information from the trajectory detection unit 140. In addition, at least one of the above processes performed by the acquisition unit 120, the extraction unit 130, and the trajectory detection unit 140 may be performed by an external device. For example, if an external device performs the process performed by the trajectory detection unit 140, the acquisition unit 120 acquires information indicating the trajectory of the user's actions as they polish the object from the external device.

[0026] The evaluation unit 150 evaluates basic abilities and applied abilities based on the trajectory. The evaluation of basic abilities and applied abilities will be explained below.

[0027] <Evaluation of Basic Capabilities> In the evaluation of basic capabilities, the evaluation unit 150 evaluates whether the user is performing the specified actions. The evaluation items are stroke length and movement width. The evaluation process will be explained using a specific example.

[0028] Figure 4 is a diagram showing a specific example of the evaluation of the basic ability in Embodiment 1. Figure 4 shows information 11 indicating a locus. The evaluation unit 150 evaluates the stroke length and the movement width using the information 11 indicating the locus. Specifically, the evaluation unit 150 calculates the difference between the minimum value and the maximum value on the vertical axis as the stroke length. The evaluation unit 150 calculates the movement amount on the horizontal axis as the movement width.

[0029] The evaluation unit 150 identifies the score corresponding to the calculated stroke length based on the information indicating the correspondence between the stroke length and the score. Note that the information is stored in the storage unit 110 or an external device. The information is acquired by the acquisition unit 120. In this way, the stroke length is evaluated.

[0030] Further, the evaluation unit 150 identifies the score corresponding to the calculated movement width based on the information indicating the correspondence between the movement width and the score. Note that the information is stored in the storage unit 110 or an external device. The information is acquired by the acquisition unit 120. In this way, the movement width is evaluated.

[0031] The information processing device 100 may evaluate basic abilities other than the stroke length and the movement width. For example, the information processing device 100 evaluates the polishing range. Specifically, the information processing device 100 evaluates whether a narrow range is polished. The information processing device 100 evaluates whether a wide range is polished. The information processing device 100 can evaluate the evaluation items based on an image. Also, for example, the information processing device 10 is evaluate whether polishing is done with force. The information processing device 100 can evaluate the evaluation items based on the acceleration in the traveling direction and the mass of the tool.

[0032] <Evaluation of application ability> Next, the evaluation of the application ability will be described. The application ability is the ability to polish an object flexibly. In the evaluation of the application ability, the evaluation unit 150 evaluates whether the user is operating flexibly. Specifically, the evaluation unit 150 evaluates two evaluation items.

[0033] Describe the first evaluation item. An expert determines (i.e., situation judgment) the polished areas and unpolished areas, and polishes the unpolished areas. Therefore, the evaluation unit 150 determines the polished areas and unpolished areas of the user and evaluates whether the user is polishing the unpolished areas.

[0034] Describe the second evaluation item. An expert determines (i.e., situation judgment) the areas to be polished and polishes the areas to be polished. Therefore, the evaluation unit 150 determines the areas to be polished by the user and evaluates whether the user is polishing the areas to be polished.

[0035] <First evaluation item> Explain the evaluation process of the first evaluation item using a specific example. FIGS. 5(A) to 5(C) are diagrams showing a specific example (Part 1) of the evaluation process of the application ability in the first embodiment. The acquisition unit 120 acquires information indicating the trajectory at the first time. Let the first time be time T １ ~T ｍ Let it be. FIG. 5(A) shows the information indicating the trajectory from time T １ ~T ｍ . For example, the information is information generated by the trajectory detection unit 140. Note that m is a positive integer.

[0036] The evaluation unit 150 divides the information indicating the trajectory at the first time into a grid. FIG. 5(B) shows a state in which the information indicating the trajectory is divided into a grid. The evaluation unit 150 generates a two-dimensional histogram indicating the number of hand passes based on the divided information indicating the trajectory. FIG. 5(C) shows the two-dimensional histogram. Based on the two-dimensional histogram, from time T １ ~T ｍA portion that has not been polished at (i.e., the first time) is identified. That is, the unpolished portion is a portion where the number of passes is 0. For example, the unpolished portion is represented by coordinates. Thus, information indicating the unpolished portion, identified based on the trajectory at the first time, is obtained. The acquisition unit 120 acquires the information from the evaluation unit 150. Also, at least one of the above processes executed by the acquisition unit 120 and the evaluation unit 150 may be executed by an external device. For example, when the external device executes the process executed by the evaluation unit 150, the acquisition unit 120 acquires information indicating the unpolished portion, identified based on the trajectory at the first time, from the external device.

[0037] The acquisition unit 120 acquires information indicating the trajectory at the second time. For example, the information is information generated by the trajectory detection unit 140. The second time is a time after the first time. Let the second time be time T ｍ＋１ to T ｎ . n is a positive integer. The evaluation unit 150 divides the information indicating the trajectory at the second time into a grid. The evaluation unit 150 generates a two-dimensional histogram indicating the number of hand passes based on the information indicating the divided trajectory. Thereby, a two-dimensional histogram as shown in FIG. 5(C) is obtained. Thus, a two-dimensional histogram generated based on the trajectory at the second time is obtained. The acquisition unit 120 acquires the two-dimensional histogram from the evaluation unit 150. Also, at least one of the above processes executed by the acquisition unit 120 and the evaluation unit 150 may be executed by an external device. For example, when the external device executes the process executed by the evaluation unit 150, the acquisition unit 120 acquires the two-dimensional histogram generated based on the trajectory at the second time from the external device.

[0038] The evaluation unit 150 evaluates whether the unpolished portion is being polished using the information indicating the unpolished portion and the two-dimensional histogram. Specifically, the evaluation process is shown. FIG. 6 is a diagram showing a specific example (part 2) of the evaluation process of Embodiment 1. FIG. 6 shows time T １ to T ｍFigure 6 shows the area 20 that was not polished at time T. ｍ This shows the subsequent trajectory (i.e., the trajectory in the second time period). For example, time T ｍ Subsequent trajectories are identified based on the number of times the two-dimensional histogram is passed over in the second time period. The evaluation unit 150 calculates the degree of agreement between the unpolished area in the first time period and the trajectory in the second time period every second. For example, the evaluation unit 150 compares area 20a and time T ｍ＋１ The degree of agreement with the trajectory is calculated. Also, for example, the evaluation unit 150 compares location 20b and time T ｍ＋２ Calculate the degree of agreement with the trajectory.

[0039] Figure 7 shows a specific example (part 3) of the evaluation process of Embodiment 1. The upper part of Figure 7 shows an example of the agreement score result. The evaluation unit 150 calculates a representative value of the agreement score based on the agreement score result. The representative value may be the mean, mode, or median. The evaluation unit 150 may calculate the minimum value instead of the representative value. The evaluation unit 150 identifies the score corresponding to the calculated representative value based on information showing the correspondence between the representative value and the score. This information is stored in the storage unit 110 or an external device. This information is acquired by the acquisition unit 120.

[0040] The evaluation unit 150 may also calculate a score based on the ratio of areas (i.e., areas) that were polished in the second time period to areas (i.e., areas) that were not polished in the first time period. For example, the evaluation unit 150 may calculate the score using formula (3).

[0041]

[0042] In this way, the evaluation unit 150 determines which areas have been polished and which have not, and evaluates whether or not the user has polished the areas that have not been polished.

[0043] <Second Evaluation Item> Next, the evaluation process for the second evaluation item will be explained in detail. The acquisition unit 120 acquires information showing the trajectory at the third time. For example, this information is generated by the trajectory detection unit 140. The third time may be the same as or different from the first time. The evaluation unit 150 divides the information showing the trajectory at the third time into a grid based on the information showing the trajectory at the third time. Based on the divided trajectory information, the evaluation unit 150 generates a two-dimensional histogram showing the number of times the hand passes over the grid. This results in a two-dimensional histogram like the one shown in Figure 5(C).

[0044] The image generation unit 160 smooths the generated two-dimensional histogram. The image generation unit 160 subtracts the generated two-dimensional histogram from the smoothed two-dimensional histogram to generate a gradient image. The gradient image is an image that shows the gradient. Areas that need polishing are identified based on the gradient image. For example, areas where the gradient degree shown in the gradient image is negative are areas that need polishing. Therefore, the gradient image may also be described as an image that can identify areas that need polishing. An example of a gradient image will be shown later. The acquisition unit 120 acquires information indicating areas that need polishing through the processing of the image generation unit 160. For example, areas that need polishing are represented by coordinates. In addition, at least one of the above processes performed by the acquisition unit 120, the evaluation unit 150, and the image generation unit 160 may be performed by an external device. For example, if an external device performs the process performed by the image generation unit 160, the acquisition unit 120 acquires information indicating areas that need polishing, identified based on the trajectory at a third time, from the external device.

[0045] Next, the generation of a gradient image in the fourth time period will be explained using a specific example. Note that the fourth time period is a time period after the third time period. The fourth time period may be the same as or different from the second time period. Figure 8 is a diagram showing a specific example of the gradient image generation process of Embodiment 1. The acquisition unit 120 acquires information indicating the trajectory in the fourth time period. For example, this information is information generated by the trajectory detection unit 140. The evaluation unit 150 divides the information indicating the trajectory in the fourth time period into a grid based on the information indicating the trajectory in the fourth time period. Based on the divided trajectory information, the evaluation unit 150 generates a two-dimensional histogram showing the number of times the hand passes over the grid. Figure 8 shows an example of the generated two-dimensional histogram.

[0046] The image generation unit 160 smooths the generated two-dimensional histogram. Figure 8 shows an example of a smoothed two-dimensional histogram. The image generation unit 160 subtracts the generated two-dimensional histogram from the smoothed two-dimensional histogram to generate a gradient image. Figure 8 shows an example of a gradient image. This gradient image is an image generated based on the trajectory in the fourth time and is an image that shows the degree of gradient. Based on the degree of gradient, polished areas are identified. For example, areas with a positive gradient are polished areas. In this way, a gradient image is generated. Furthermore, at least one of the above processes performed by the acquisition unit 120, the evaluation unit 150, and the image generation unit 160 may be performed by an external device. For example, if an external device performs the process performed by the image generation unit 160, the acquisition unit 120 acquires a gradient image from the external device that is an image generated based on the trajectory in the fourth time and shows the degree of gradient.

[0047] The evaluation unit 150 uses information indicating the areas to be polished and the gradient image at the fourth time step to evaluate whether the areas to be polished have been polished. Specifically, if the gradient of the area to be polished is positive, the evaluation unit 150 evaluates that the area to be polished has been polished. For example, Figure 8 shows the area to be polished 30. If the gradient of the area to be polished 30 is positive, the evaluation unit 150 evaluates that the area to be polished 30 has been polished. Also, for example, the evaluation unit 150 calculates a score using formula (4). In formula (4), "area to be polished" and "polished area" refer to the area of ​​the "area to be polished" and the area of ​​the "polished area".

[0048]

[0049] In this way, the evaluation unit 150 determines which areas the user should polish and evaluates whether or not the user has polished those areas.

[0050] The evaluation unit 150 may perform the following processing. First, the acquisition unit 120 acquires a two-dimensional histogram generated based on the trajectory at the fourth time from the evaluation unit 150. If the two-dimensional histogram is generated by an external device, the acquisition unit 120 acquires the two-dimensional histogram from the external device. The evaluation unit 150 uses the information indicating the areas to be polished and the two-dimensional histogram to evaluate whether the areas to be polished have been polished. Specifically, if the number of times the areas to be polished are passed through in the two-dimensional histogram is 1 or more, the evaluation unit 150 evaluates that the areas to be polished have been polished.

[0051] The evaluation unit 150 may also compare the area polished by the user with the surrounding area and evaluate whether or not there is a step. Specifically, if the degree of gradient decreases from the area polished by the user towards the surrounding area, the evaluation unit 150 will evaluate that there is no step. The evaluation unit 150 may also calculate a score using formula (5). The “surrounding area” in formula (5) is predetermined. For example, the “surrounding area” is 10 pixels. Therefore, “polished area + surrounding area” is a range of 10 pixels centered on the “polished area”.

[0052]

[0053] This allows the information processing device 100 to evaluate whether or not the mold has been smoothly machined.

[0054] The output unit 170 outputs scores for basic ability and applied ability. For example, the output unit 170 outputs the scores for basic ability and applied ability to the display 300. Alternatively, for example, the output unit 170 outputs the scores for basic ability and applied ability to the storage unit 110 or an external device. A specific example of the output processing is shown below.

[0055] Figures 9(A) and 9(B) show specific examples of the output processing of Embodiment 1. The score may be represented in a table. Figure 9(A) shows an evaluation table 40. For example, the output unit 170 outputs the evaluation table 40 to the display 300. The score may also be represented in a graph. Figure 9(B) shows a graph 41. For example, the output unit 170 outputs the graph 41 to the display 300. By looking at the score, the user can grasp their own ability. In other words, the information processing device 100 can provide learning support by presenting the score to the user. The output unit 170 may output only the score for applied ability. The score may also be expressed as an evaluation value.

[0056] Next, the processes performed by the information processing device 100 will be explained using a flowchart. Figure 10 is a flowchart of an example of the processes performed by the information processing device of Embodiment 1. (Step S11) The acquisition unit 120 acquires multiple images. (Step S12) The extraction unit 130 extracts multiple images showing the user polishing the mold from the multiple images acquired by the acquisition unit 120. (Step S13) The trajectory detection unit 140 detects the trajectory of the user polishing the mold based on the multiple images extracted by the extraction unit 130. (Step S14) The evaluation unit 150 evaluates the basic ability using the trajectory. (Step S15) The evaluation unit 150 evaluates the applied ability using the trajectory. (Step S16) The output unit 170 outputs the scores for the basic ability and applied ability.

[0057] As described above, the information processing device 100 evaluates application capabilities. Therefore, according to Embodiment 1, the information processing device 100 can evaluate application capabilities.

[0058] The above describes cases in which both basic and applied abilities are evaluated. The information processing device 100 may evaluate only applied abilities.

[0059] Embodiment 2. Next, Embodiment 2 will be described. Embodiment 2 will mainly describe the differences from Embodiment 1. In Embodiment 2, the explanation of matters common to Embodiment 1 will be omitted.

[0060] Figure 11 is a block diagram showing the functions of the information processing device of Embodiment 2. The information processing device 100 further includes a trajectory generation unit 180. Part or all of the trajectory generation unit 180 may be implemented by a processing circuit. Alternatively, part or all of the trajectory generation unit 180 may be implemented as a module of a program executed by the processor 101. Details of the functions of the trajectory generation unit 180 will be described later.

[0061] The acquisition unit 120 identifies evaluation items from the basic ability evaluation items that are below a predetermined threshold. The acquisition unit 120 acquires reference trajectories for the identified evaluation items from the storage unit 110 or an external device. The reference trajectory is a trajectory with a score of "100". The acquisition unit 120 identifies evaluation items from the applied ability evaluation items whose scores are below a predetermined threshold. The acquisition unit 120 acquires reference trajectories for the identified evaluation items from the storage unit 110 or an external device. When the acquisition unit 120 acquires reference trajectories from the storage unit 110 or an external device, it may use the dominant hand or tool as a search key. The output unit 170 outputs the reference trajectory. For example, the output unit 170 outputs the reference trajectory to the display 300. The acquisition unit 120 may acquire examples of trajectories with low scores from the storage unit 110 or an external device. The output unit 170 may output the acquired trajectory.

[0062] The trajectory generation unit 180 identifies evaluation items from the basic ability evaluation items that are below a predetermined threshold. The trajectory generation unit 180 uses the trajectory of the identified evaluation item to generate a trajectory that improves the score of that trajectory. Specifically, the trajectory generation unit 180 generates a trajectory that shows how to modify the trajectory of the identified evaluation item to improve the score. The trajectory generation unit 180 identifies evaluation items from the applied ability evaluation items whose scores are below a predetermined threshold. The trajectory generation unit 180 uses the trajectory of the identified evaluation item to generate a trajectory that improves the score of that trajectory. Specifically, the trajectory generation unit 180 generates a trajectory that shows how to modify the trajectory of the identified evaluation item to improve the score. The output unit 170 outputs the modified trajectory, which is the generated trajectory. For example, the output unit 170 outputs the modified trajectory to the display 300. The modified trajectory may also be called an edited trajectory.

[0063] Specific examples of reference trajectories and corrected trajectories are shown. Figures 12(A) and (B) show specific examples of trajectories output in Embodiment 2. Figure 12(A) shows the case where the stroke length score is below a threshold. Also, Figure 12(A) shows the state in which the reference trajectory is displayed on the display 300. This reference trajectory is acquired from the storage unit 110 by the acquisition unit 120. The user can recognize the trajectory with a score of "100" by visually inspecting the reference trajectory. Therefore, the user's time to acquire the skill is shortened. The output unit 170 may output both the actual trajectory and the reference trajectory to the display 300. By outputting the two trajectories, the user can make a comparison.

[0064] Figure 12(B) shows the case where the score of the unpolished area is below a threshold. Figure 12(B) also shows the state where the corrected trajectory is displayed on the display 300. By visually confirming the corrected trajectory, the user can recognize what action should have been taken. Therefore, the user's time to acquire the skill is shortened. The output unit 170 may output both the actual trajectory and the corrected trajectory to the display 300. By outputting two trajectories, the user can compare them.

[0065] Next, the processes performed by the information processing device 100 will be explained using a flowchart. Figure 13 is a flowchart of an example of the processes performed by the information processing device of Embodiment 2. The processes in Figure 13 differ from those in Figure 10 in that step S16a is performed. Therefore, step S16a will be explained in Figure 13. The explanation of processes other than step S16a will be omitted. (Step S16a) The output unit 170 outputs the reference trajectory and the corrected trajectory.

[0066] According to Embodiment 2, the information processing device 100 can provide support to shorten the user's time required to acquire the necessary skills.

[0067] Embodiment 3. Next, Embodiment 3 will be described. Embodiment 3 will mainly describe the differences from Embodiment 1. In Embodiment 3, the explanation of matters common to Embodiment 1 will be omitted. Embodiment 1 described the case where a score is output. Embodiment 3 will describe the case where both the score and the improvement ranking are output. A specific example will be given.

[0068] Figure 14 shows an example of the output of the improvement ranking for Embodiment 3. Figure 14 shows the evaluation table 40. The evaluation table 40 further includes an improvement ranking item. The improvement ranking is determined by the following conditions: Basic ability evaluation items are ranked higher than applied ability evaluation items. Within the basic ability evaluation items, the ranking is determined by the ease of improvement. Evaluation items for areas that have not been polished are ranked higher than evaluation items for areas that need polishing.

[0069] The output unit 170 outputs an improvement ranking based on the scores for basic ability and applied ability. For example, the output unit 170 outputs an evaluation table 40, including the scores and improvement rankings, to the display 300. This allows the user to recognize the improvement ranking. As a result, the user can acquire skills efficiently.

[0070] Next, the processes performed by the information processing device 100 will be explained using a flowchart. Figure 15 is a flowchart of an example of the processes performed by the information processing device of Embodiment 3. The processes in Figure 15 differ from those in Figure 10 in that step S16b is performed. Therefore, step S16b will be explained in Figure 15. The explanation of processes other than step S16b will be omitted. (Step S16b) The output unit 170 outputs the score and the improvement ranking.

[0071] According to Embodiment 3, the information processing device 100 can provide support to shorten the user's time required to acquire the necessary skills.

[0072] Embodiments 1 to 3 describe cases where the system is implemented using a single device. Embodiments 1 to 3 may also be implemented using multiple devices.

[0073] Each embodiment is merely illustrative, and various modifications are possible within the scope of this disclosure. Furthermore, the features of each embodiment can be combined with each other as appropriate.

[0074] 10_1, 10_2 Images, 10a Mold, 10b Tool, 10c Blade, 10d_1, 10d_2 Centroid coordinates, 11 Information showing the trajectory, 20 Unpolished areas, 20a-20q Areas, 30 Areas to be polished, 40 Evaluation sheet, 41 Graph, 100 Information processing device, 101 Processor, 102 Volatile memory device, 103 Non-volatile memory device, 110 Storage unit, 120 Acquisition unit, 130 Extraction unit, 140 Trajectory detection unit, 150 Evaluation unit, 160 Image generation unit, 170 Output unit, 180 Trajectory generation unit, 200 Camera, 300 Display.

Claims

1. An information processing device comprising: an acquisition unit that acquires information indicating the trajectory of a user's actions while polishing an object; and an evaluation unit that evaluates the application ability, which is the ability to polish the object flexibly based on the trajectory.

2. The information processing apparatus according to claim 1, wherein the acquisition unit acquires information indicating unpolished areas identified based on the trajectory at a first time, acquires a two-dimensional histogram generated based on the trajectory at a second time which is a time after the first time, and the evaluation unit uses the information indicating the unpolished areas and the two-dimensional histogram to evaluate whether or not the unpolished areas have been polished.

3. The information processing apparatus according to claim 1, wherein the acquisition unit acquires information indicating areas to be polished, which has been identified based on the trajectory in a third time period, and acquires a gradient image which is an image generated based on the trajectory in a fourth time period which is a time after the third time period and indicates the degree of gradient, or a two-dimensional histogram which is generated based on the trajectory in the fourth time period, and the evaluation unit uses the information indicating areas to be polished and the gradient image or the two-dimensional histogram to evaluate whether or not the areas to be polished have been polished.

4. The information processing apparatus according to claim 3, wherein the evaluation unit compares the area polished by the user with the area around the area polished by the user and evaluates whether or not there is a step or unevenness.

5. The information processing apparatus according to any one of claims 1 to 4, further comprising an output unit that outputs an evaluation value of the application capability.

6. An information processing apparatus according to any one of claims 1 to 4, further comprising an output unit, wherein the acquisition unit acquires reference trajectories of evaluation items among the application ability evaluation items whose evaluation values ​​are less than or equal to a predetermined threshold, and the output unit outputs the reference trajectories.

7. An information processing apparatus according to any one of claims 1 to 4, further comprising: a trajectory generation unit that generates a trajectory to improve the evaluation value of the trajectory using the trajectory of an evaluation item among the evaluation items of the applied ability whose evaluation value is below a predetermined threshold; and an output unit that outputs a corrected trajectory which is the generated trajectory.

8. An information processing apparatus according to any one of claims 1 to 4, further comprising an output unit, wherein the evaluation unit evaluates a basic ability which is the ability to perform a defined operation based on the trajectory, and the output unit outputs an improvement ranking based on the evaluation value of the basic ability and the evaluation value of the applied ability.

9. An evaluation method comprising an information processing device acquiring information indicating the trajectory of a user's actions while polishing an object, and evaluating the user's ability to polish the object flexibly based on the trajectory.

10. An evaluation program that causes an information processing device to acquire information showing the trajectory of a user's actions while polishing an object, and to execute a process that evaluates the user's applied ability, which is the ability to polish the object flexibly based on the trajectory.

Images