Simulation baby robot for training, examination and teaching and examination and evaluation system

Abstract

The invention discloses a simulation baby robot for training, examination and teaching and an examination and evaluation system, and relates to the technical field of training, examination and teaching aids, the simulation baby robot comprises a robot body and a posture monitoring mechanism, and the examination and evaluation system comprises a data storage unit, a data acquisition unit, an image analysis unit and a comprehensive evaluation unit; according to the invention, the posture monitoring mechanisms arranged at all positions of the robot body are used for acquiring the posture data of the robot in the assessment process, and the behavior analysis and judgment node is used for judging the assessed posture data in the assessment process, so that the image acquisition signal is generated; after an image acquisition signal is received, multiple groups of continuous video screenshots are intercepted from the operation video to serve as to-be-analyzed images, the to-be-analyzed images and standard action images are subjected to feature comparison, action approval evaluation results are generated, the action approval evaluation results are graded according to difference values, and the action approval evaluation results are obtained. And the assessment result is notified through the voice prompter, so that the assessment result is objective and fair.

Description

Technical Field

[0001] The present invention relates to the technical field of training, assessment and teaching tools, and in particular to a simulated infant robot for training, assessment and teaching and an assessment and evaluation system. Background Art

[0002] As the quality of life improves, more people begin to pay attention to the care of infants. Infants do not have language and body expression skills, and because of their fragile bodies, caregivers need to invest more patience and more delicate operations to care for them. Nursing staff engaged in infant care generally need professional training, and they need to be evaluated after the training. The performance appraisal of nursing staff is the top priority of every hospital management work. A reasonable performance appraisal system can enhance the enthusiasm, initiative and creativity of nursing staff. Therefore, it is very necessary to conduct scientific and reasonable, qualitative and quantitative appraisal and evaluation of hospital nursing staff. However, the existing relevant appraisal system is generally based on the managers' own experience, and the direct leaders conduct the appraisal and evaluation. Therefore, there are many and complex appraisal branches, and the appraisal is time-consuming and labor-intensive. The evaluation factors of the appraised personnel are single and subjective. It is impossible to make a comprehensive, timely and fair appraisal and evaluation of the work of nursing staff. In view of the above-mentioned technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to generate action approval evaluation results by comparing the features of the image to be analyzed with the standard action image, grade the action approval evaluation results according to the difference values, obtain the assessment results and notify the assessment results through a voice prompt to ensure that the assessment results are objective and fair.

[0004] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a simulated baby robot for training, assessment and teaching, comprising a robot body and a posture monitoring mechanism, the robot body comprising a head, a neck, a trunk and four limbs, the head is fixedly provided with a camera and a voice prompter, the outer surfaces of the trunk and the four limbs are evenly distributed with a plurality of positioning grooves, the posture monitoring mechanism is movably connected to the inner wall of the positioning groove, and the outer surface of the trunk is fixedly provided with a touch screen; The height, weight and human proportions of the robot body refer to the relevant data of real babies; The posture monitoring mechanism includes a positioning seat and a sensor group. The outer surface of the positioning seat is fixedly provided with a plug-in iron block, the outer surface of the positioning seat is provided with a component groove, the outer surface of the component groove is fixedly provided with an adsorption ring, and the sensor group is fixedly provided on the inner wall of the component groove. The sensor group includes a height sensor, a displacement sensor, an acceleration sensor, an inclination sensor and a pressure sensor.

[0005] Furthermore, an extension groove corresponding to the magnetic attraction block is arranged inside the positioning groove, and a magnetic attraction block which is adapted to the plug-in iron block is fixed on the inner wall of the extension groove.

[0006] The present invention also provides an assessment and evaluation system for a simulated infant robot for training, assessment and teaching, comprising a data storage unit, a data acquisition unit, an image analysis unit and a comprehensive evaluation unit; The data storage unit includes an assessment rules storage module and an evaluation standard storage module. The assessment rules storage module is used to store assessable nursing items and pre-assessment operation rules corresponding to the nursing items, and the evaluation standard storage module is used to store assessment operation standards corresponding to the assessable nursing items.

[0007] The data acquisition unit is used to acquire the robot posture data during the assessment process through the posture monitoring mechanism set at various locations of the robot body, and to search for the preset behavior analysis judgment node in the self-assessment standard storage module, and to judge the evaluable posture data during the assessment process through the behavior analysis judgment node to generate an image acquisition signal and send it to the image analysis unit, and at the same time calculate the difference value between the robot posture data and the assessment operation standard to output it to the comprehensive assessment unit; The image analysis unit includes an image acquisition module and an image analysis module. The image acquisition module is used to record the operation video of the nursing staff during the assessment process through a camera, and after receiving the image acquisition signal, multiple groups of continuous video screenshots are intercepted from the operation video as images to be analyzed and sent to the image analysis unit; The image analysis module is used to obtain and process the image to be analyzed, extract features from the image to be analyzed, obtain the assessment operation standard from the assessment standard storage module, the assessment operation standard also includes a standard action image, compare the features of the image to be analyzed with the standard action image, generate an action approval assessment result and send it to the comprehensive assessment unit; The comprehensive evaluation unit is used to obtain the action approval evaluation results and the difference value, grade the action approval evaluation results according to the difference value, obtain the assessment results and notify the assessment results through the voice prompter.

[0008] Furthermore, it also includes an assessment requirement acquisition unit, which is used to obtain assessment requirements through the touch screen. The assessment requirements include the nursing items to be assessed and the assessment time, and search the data storage unit for the pre-assessment operation details corresponding to the nursing items based on the nursing items to be assessed, and display them through the touch screen to guide nursing staff to make pre-assessment preparations.

[0009] Furthermore, the specific process of generating the image acquisition signal is as follows: S101, obtaining the robot posture data during the assessment process through the posture monitoring mechanism set at various locations of the robot body, wherein the robot posture data includes height data Hi, displacement data Xi, acceleration data ai, inclination data θi and pressure data Fi; S102, obtaining the assessment requirements and then obtaining the assessment time, wherein the assessment time includes the assessment start time and the assessment end time, establishing a time axis according to the assessment time, searching for a preset behavior analysis and judgment node in the self-assessment standard storage module, and defining a number of continuous monitoring time points on the time axis according to the distribution of the analysis and judgment nodes in the assessment cycle; S103, marking the robot posture data at the monitoring time point on the time axis one by one, and judging the corresponding assessment operation standards at the nodes according to the behavior analysis, namely, the standard height range (Hmin, Hmax), standard displacement range (Xmin, Xmax), standard acceleration range (amin, amax), standard inclination range (θmin, θmax) and standard pressure range (Fmin, Fmax); S104. If the robot posture data at the behavior analysis judgment node all meet the assessment operation standards, an image acquisition signal is generated.

[0010] Furthermore, the specific process of calculating the difference between the robot posture data and the assessment operation standard is as follows: The difference value Uk is calculated according to the following formula: , where e1, e2, e3, e4 and e5 are preset proportional coefficients, It is a dimensionless coefficient, and the difference value is used to reflect the gap between the robot posture data and the assessment operation standard.

[0011] Furthermore, the specific process of generating the action approval evaluation result is as follows: S201, acquiring an image to be analyzed, wherein the image to be analyzed takes the time when an image acquisition signal is received as the starting point t0, takes multiple video screenshots with t0+T as the image acquisition period, and establishes a time-series image set; S202, extracting the contour of each image to be analyzed in the time series image set, and establishing an action joint distribution mark; S203, obtaining the assessment operation standard from the evaluation standard storage module, wherein the standard action image is distributed with identification mark points, establishing an image mapping between the image to be analyzed and the standard action image, and marking the action joint distribution mark to the standard action image according to the mapping; S204, after performing contour extraction on the standard action image, obtaining the distance between the recognition mark point and the action joint distribution mark, and superimposing and calculating the distance to obtain the total distance deviation value Si; S205, obtaining a preset deviation judgment interval (Smin, Smax), if the total distance deviation value Si is less than or equal to Smin, the action approval evaluation result is excellent; If the total distance deviation value Si is less than Smax and greater than Smin, the action approval evaluation result is good; If the total distance deviation value Si is greater than or equal to Smin, the action approval evaluation result is unqualified.

[0012] Furthermore, the specific process of obtaining the assessment results is as follows: Get the action approval evaluation result and the corresponding difference value Uk: Get the preset difference judgment interval (Umin, Umax). If Uk is less than or equal to Umin, the action approval evaluation result is: Outstanding performance was further evaluated as Outstanding+; Good was further evaluated as good+; Unqualified is further evaluated as good-; If Uk is less than Umax and greater than Umin, the action approval evaluation result is: Outstanding performance was further evaluated as excellent; Good was further evaluated as fair to moderate; Failure remains failure; If Uk is greater than or equal to Umax, the action approval evaluation result is: Outstanding performance was further assessed as Excellent-; Good was further assessed as good-; A failure remains a failure.

[0013] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: The simulated infant robot and assessment and evaluation system for training, assessment and teaching obtains the robot's posture data during the assessment process through posture monitoring mechanisms arranged at various locations on the robot body, and judges the evaluable posture data during the assessment process through behavior analysis judgment nodes to generate an image acquisition signal. After receiving the image acquisition signal, multiple groups of continuous video screenshots are captured from the operation video as images to be analyzed, and features of the images to be analyzed are compared with standard action images to generate action approval and evaluation results. The action approval and evaluation results are graded according to the difference values, and the assessment results are obtained and notified through a voice prompter to ensure that the assessment results are objective and fair. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 The overall external structure schematic diagram of the present invention is shown; Figure 2 Another schematic diagram of the overall external structure of the present invention is shown; Figure 3 A schematic diagram of the structure of the posture monitoring mechanism of the present invention is shown; Figure 4 A schematic diagram of the structure of the assessment and evaluation system of the present invention is shown; Legend: 1. Robot body; 101. Head; 102. Neck; 103. Torso; 104. Limbs; 2. Positioning slot; 3. Touch screen; 4. Camera; 5. Voice prompter; 6. Positioning seat; 7. Plug-in iron block; 8. Component slot; 9. Adsorption ring; 10. Sensor group; 11. Magnetic block. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] Embodiment 1: like Figure 1-3 As shown, a simulated baby robot for training, assessment and teaching includes a robot body 1 and a posture monitoring mechanism. The robot body 1 includes a head 101, a neck 102, a trunk 103, and limbs 104. The head 101 is fixedly provided with a camera 4 and a voice prompter 5. The outer surfaces of the trunk 103 and the limbs 104 are evenly distributed with a plurality of positioning grooves 2. The posture monitoring mechanism is movably connected to the inner wall of the positioning groove 2. The outer surface of the trunk 103 is fixedly provided with a touch screen 3. The height, weight, and human proportions of the robot body 1 refer to the relevant data of real babies; The posture monitoring mechanism includes a positioning seat 6 and a sensor group 10. An inserting iron block 7 is fixedly provided on the outer surface of the positioning seat 6. An element groove 8 is opened on the outer surface of the positioning seat 6. An adsorption ring 9 is fixedly provided on the outer surface of the element groove 8. The sensor group 10 is fixedly provided on the inner wall of the element groove 8. The sensor group 10 includes a height sensor, a displacement sensor, an acceleration sensor, an inclination sensor and a pressure sensor.

[0017] An extension groove corresponding to the magnetic attraction block 11 is arranged inside the positioning groove 2 , and a magnetic attraction block 11 which is adapted to the plug-in iron block 7 is fixed on the inner wall of the extension groove.

[0018] The working principle is as follows: before conducting the assessment, the assessment requirements are obtained through the touch screen 3. The assessment points can be known according to the pre-assessment operation details corresponding to the nursing project, and the posture monitoring mechanisms are installed one by one at the assessment points, that is, the positioning seats 6 are inserted into the corresponding positioning slots 2 one by one, and the plug-in iron block and the magnetic suction block 11 fit each other. Under the action of magnetic attraction, the positioning seat 6 is fixed in the positioning slot 2, and the positioning seat 6 is fit with the robot body 1 through the adsorption ring 9. Since the positioning seat 6 and the positioning slot 2 are provided with power connection posts at the corresponding positions, the sensor group 10 is connected to the power supply provided inside the robot body 1, and then the robot posture data during the assessment process is obtained through the sensor group 10 for assessment evaluation. The sampling and detachable posture monitoring mechanism facilitates its application to different assessment items, avoids multiple sensor groups 10 working at the same time to collect unnecessary data, and affects the efficiency and accuracy of data processing. At the same time, it can also deepen the learning impression of the operator before the assessment.

[0019] Embodiment 2: like Figure 4 As shown, an assessment and evaluation system for a simulated infant robot for training, assessment and teaching includes a data storage unit, a data acquisition unit, an image analysis unit and a comprehensive evaluation unit; The data storage unit includes an assessment rules storage module and an evaluation standard storage module. The assessment rules storage module is used to store assessable nursing items and pre-assessment operation rules corresponding to the nursing items. The evaluation standard storage module is used to store the assessment operation standards corresponding to the assessable nursing items.

[0020] The data acquisition unit is used to acquire the robot posture data during the assessment process through the posture monitoring mechanism set at various locations of the robot body 1, and to search for the preset behavior analysis judgment node in the self-assessment standard storage module, and to judge the evaluable posture data during the assessment process through the behavior analysis judgment node to generate an image acquisition signal and send it to the image analysis unit, and at the same time calculate the difference value between the robot posture data and the assessment operation standard to output it to the comprehensive assessment unit; The specific process of generating the image acquisition signal is as follows: S101, obtaining the robot posture data during the assessment process through the posture monitoring mechanism set at various locations of the robot body 1, the robot posture data including height data Hi, displacement data Xi, acceleration data ai, inclination data θi and pressure data Fi; S102, obtaining the assessment requirements and then obtaining the assessment time, the assessment time includes the assessment start time and the assessment end time, establishing a time axis according to the assessment time, searching for a preset behavior analysis and judgment node in the self-assessment standard storage module, and defining a number of continuous monitoring time points on the time axis according to the distribution of the analysis and judgment nodes in the assessment cycle; S103, marking the robot posture data at the monitoring time point on the time axis one by one, and judging the corresponding assessment operation standards at the nodes according to the behavior analysis, namely, the standard height range (Hmin, Hmax), standard displacement range (Xmin, Xmax), standard acceleration range (amin, amax), standard inclination range (θmin, θmax) and standard pressure range (Fmin, Fmax); S104. If the robot posture data at the behavior analysis judgment node all meet the assessment operation standards, an image acquisition signal is generated.

[0021] The specific process of calculating the difference between the robot posture data and the assessment operation standard is as follows: The difference value Uk is calculated according to the following formula: , where e1, e2, e3, e4 and e5 are preset proportional coefficients, It is a dimensionless coefficient, and the difference value is used to reflect the gap between the robot posture data and the assessment operation standard.

[0022] The image analysis unit includes an image acquisition module and an image analysis module. The image acquisition module is used to record the operation video of the nursing staff during the assessment process through a camera, and after receiving the image acquisition signal, multiple groups of continuous video screenshots are intercepted from the operation video as images to be analyzed and sent to the image analysis unit; The image analysis module is used to obtain and process the image to be analyzed, extract features from the image to be analyzed, obtain the assessment operation standard from the assessment standard storage module, the assessment operation standard also includes the standard action image, compare the features of the image to be analyzed with the standard action image, generate the action approval assessment result and send it to the comprehensive assessment unit; The specific process of generating action approval evaluation results is as follows: S201, acquiring an image to be analyzed, wherein the image to be analyzed takes the time when an image acquisition signal is received as the starting point t0, takes multiple video screenshots with t0+T as the image acquisition period, and establishes a time-series image set; S202, extracting the contour of each image to be analyzed in the time series image set, and establishing an action joint distribution mark; S203, obtaining the assessment operation standard from the self-assessment standard storage module, the standard action image is distributed with identification mark points, an image mapping is established between the image to be analyzed and the standard action image, and the action joint distribution mark is annotated to the standard action image according to the mapping; S204, after performing contour extraction on the standard action image, obtaining the distance between the recognition mark point and the action joint distribution mark, and superimposing and calculating the distance to obtain the total distance deviation value Si; S205, obtaining a preset deviation judgment interval (Smin, Smax), if the total distance deviation value Si is less than or equal to Smin, the action approval evaluation result is excellent; If the total distance deviation value Si is less than Smax and greater than Smin, the action approval evaluation result is good; If the total distance deviation value Si is greater than or equal to Smin, the action approval evaluation result is unqualified.

[0023] The comprehensive evaluation unit is used to obtain the action approval evaluation results and the difference value, grade the action approval evaluation results according to the difference value, obtain the assessment results and notify the assessment results through the voice prompter.

[0024] Get the action approval evaluation result and the corresponding difference value Uk: Get the preset difference judgment interval (Umin, Umax). If Uk is less than or equal to Umin, the action approval evaluation result is: Outstanding performance was further evaluated as Outstanding+; Good was further evaluated as good+; Unqualified is further evaluated as good-; If Uk is less than Umax and greater than Umin, the action approval evaluation result is: Outstanding performance was further evaluated as excellent; Good was further evaluated as fair to moderate; Failure remains failure; If Uk is greater than or equal to Umax, the action approval evaluation result is: Outstanding performance was further assessed as Excellent-; Good was further assessed as good-; A failure remains a failure.

[0025] It also includes an assessment requirement acquisition unit for acquiring assessment requirements through the touch screen 3. The assessment requirements include the nursing items to be assessed and the assessment time. The pre-assessment operation details corresponding to the nursing items are searched from the data storage unit according to the nursing items to be assessed, and displayed through the touch screen 3 to guide nursing staff to make pre-assessment preparations.

[0026] The present invention obtains the robot posture data during the assessment process through the posture monitoring mechanism arranged at various locations of the robot body 1, and judges the evaluable posture data during the assessment process through the behavior analysis judgment node to generate an image acquisition signal. After receiving the image acquisition signal, multiple groups of continuous video screenshots are captured from the operation video as images to be analyzed, and the features of the images to be analyzed are compared with the standard action images to generate action approval evaluation results. The action approval evaluation results are graded according to the difference values, and the assessment results are obtained and notified through a voice prompter to ensure that the assessment results are objective and fair.

[0027] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0028] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. In the two embodiments provided in the present application, it should be understood that the disclosed devices and systems can be implemented in other ways; for example, the device embodiments described above are only schematic, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed; another point, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, the indirect coupling or communication connection of devices or modules can be electrical, mechanical or other forms; The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A simulated infant robot for training, assessment and teaching, comprising a robot body (1) and a posture monitoring mechanism, characterized in that: The robot body (1) comprises a head (101), a neck (102), a trunk (103), and four limbs (104); the head (101) is fixedly provided with a camera (4) and a voice prompter (5); the outer surfaces of the trunk (103) and the four limbs (104) are evenly distributed with a plurality of positioning grooves (2); the posture monitoring mechanism is movably connected to the inner wall of the positioning groove (2); and the outer surface of the trunk (103) is fixedly provided with a touch screen (3); The posture monitoring mechanism comprises a positioning seat (6) and a sensor group (10); an inserting iron block (7) is fixedly provided on the outer surface of the positioning seat (6); an element groove (8) is opened on the outer surface of the positioning seat (6); an adsorption ring (9) is fixedly provided on the outer surface of the element groove (8); the sensor group (10) is fixedly provided on the inner wall of the element groove (8); the sensor group (10) comprises a height sensor, a displacement sensor, an acceleration sensor, an inclination sensor and a pressure sensor.

2. The simulation baby robot for training, assessment and teaching according to claim 1, characterized in that: An extension groove corresponding to the magnetic attraction block (11) is provided inside the positioning groove (2), and a magnetic attraction block (11) adapted to the plug-in iron block (7) is fixedly provided on the inner wall of the extension groove.

3. An assessment and evaluation system for a simulated infant robot for training, assessment and teaching, characterized in that: It includes a data storage unit, a data acquisition unit, an image analysis unit and a comprehensive evaluation unit; The data storage unit includes an assessment rule storage module and an evaluation standard storage module, wherein the assessment rule storage module is used to store assessable nursing items and pre-assessment operation rules corresponding to the nursing items, and the evaluation standard storage module is used to store assessment operation standards corresponding to the assessable nursing items; The data acquisition unit is used to acquire the robot posture data during the assessment process through posture monitoring mechanisms arranged at various locations of the robot body (1), and to search for a preset behavior analysis judgment node in the self-assessment standard storage module, and to judge the evaluable posture data during the assessment process through the behavior analysis judgment node, so as to generate an image acquisition signal and send it to the image analysis unit, and at the same time calculate the difference value between the robot posture data and the assessment operation standard to output it to the comprehensive assessment unit; The image analysis unit includes an image acquisition module and an image analysis module. The image acquisition module is used to record the operation video of the nursing staff during the assessment process through a camera, and after receiving the image acquisition signal, multiple groups of continuous video screenshots are intercepted from the operation video as images to be analyzed and sent to the image analysis unit; The image analysis module is used to obtain and process the image to be analyzed, extract features from the image to be analyzed, obtain the assessment operation standard from the assessment standard storage module, the assessment operation standard also includes a standard action image, compare the features of the image to be analyzed with the standard action image, generate an action approval assessment result and send it to the comprehensive assessment unit; The comprehensive evaluation unit is used to obtain the action approval evaluation results and the difference value, grade the action approval evaluation results according to the difference value, obtain the assessment results and notify the assessment results through the voice prompter.

4. The assessment and evaluation system of the simulated infant robot for training, assessment and teaching according to claim 3, characterized in that: It also includes an assessment requirement acquisition unit for acquiring assessment requirements through the touch screen (3), wherein the assessment requirements include the nursing items to be assessed and the assessment time, and searching the data storage unit for the pre-assessment operation details corresponding to the nursing items to be assessed, and displaying them through the touch screen (3) to guide nursing staff to make pre-assessment preparations.

5. The assessment and evaluation system of the simulated infant robot for training, assessment and teaching according to claim 3, characterized in that: The specific process of generating the image acquisition signal is as follows: S101, obtaining the robot posture data during the assessment process through posture monitoring mechanisms arranged at various locations of the robot body (1), wherein the robot posture data includes height data Hi, displacement data Xi, acceleration data ai, inclination data θi and pressure data Fi; S102, obtaining the assessment requirements and then obtaining the assessment time, wherein the assessment time includes the assessment start time and the assessment end time, establishing a time axis according to the assessment time, searching for a preset behavior analysis and judgment node in the self-assessment standard storage module, and defining a number of continuous monitoring time points on the time axis according to the distribution of the analysis and judgment nodes in the assessment cycle; S103, marking the robot posture data at the monitoring time point on the time axis one by one, and judging the corresponding assessment operation standards at the nodes according to the behavior analysis, namely, the standard height range (Hmin, Hmax), standard displacement range (Xmin, Xmax), standard acceleration range (amin, amax), standard inclination range (θmin, θmax) and standard pressure range (Fmin, Fmax); S104. If the robot posture data at the behavior analysis judgment node all meet the assessment operation standards, an image acquisition signal is generated.

6. The assessment and evaluation system of the simulated infant robot for training, assessment and teaching according to claim 3, characterized in that: The specific process of calculating the difference between the robot posture data and the assessment operation standard is as follows: The difference value Uk is calculated according to the following formula: , where e1, e2, e3, e4 and e5 are preset proportional coefficients, It is a dimensionless coefficient, and the difference value is used to reflect the gap between the robot posture data and the assessment operation standard.

7. The assessment and evaluation system of the simulated infant robot for training, assessment and teaching according to claim 3, characterized in that: The specific process of generating action approval evaluation results is as follows: S201, acquiring an image to be analyzed, wherein the image to be analyzed takes the time when an image acquisition signal is received as the starting point t0, takes multiple video screenshots with t0+T as the image acquisition period, and establishes a time-series image set; S202, extracting the contour of each image to be analyzed in the time series image set, and establishing an action joint distribution mark; S203, obtaining the assessment operation standard from the evaluation standard storage module, wherein the standard action image is distributed with identification mark points, establishing an image mapping between the image to be analyzed and the standard action image, and marking the action joint distribution mark to the standard action image according to the mapping; S204, after performing contour extraction on the standard action image, obtaining the distance between the recognition mark point and the action joint distribution mark, and superimposing and calculating the distance to obtain the total distance deviation value Si; S205, obtaining a preset deviation judgment interval (Smin, Smax), if the total distance deviation value Si is less than or equal to Smin, the action approval evaluation result is excellent; If the total distance deviation value Si is less than Smax and greater than Smin, the action approval evaluation result is good; If the total distance deviation value Si is greater than or equal to Smin, the action approval evaluation result is unqualified.

8. The assessment and evaluation system of the simulated infant robot for training, assessment and teaching according to claim 3, characterized in that: The specific process of obtaining the assessment results is as follows: Get the action approval evaluation result and the corresponding difference value Uk: Get the preset difference judgment interval (Umin, Umax). If Uk is less than or equal to Umin, the action approval evaluation result is: Outstanding performance was further evaluated as Outstanding+; Good was further evaluated as good+; Unqualified is further evaluated as good-; If Uk is less than Umax and greater than Umin, the action approval evaluation result is: Outstanding performance was further evaluated as excellent; Good was further evaluated as fair to moderate; Failure remains failure; If Uk is greater than or equal to Umax, the action approval evaluation result is: Outstanding performance was further assessed as Excellent-; Good was further assessed as good-; A failure remains a failure.

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