Humanoid robot motion efficiency evaluation method and system, storage medium and device

Abstract

The human-shaped robot motion efficiency evaluation method, system, storage medium and equipment belong to the technical field of robot evaluation, in order to solve the problem that the existing robot motion efficiency evaluation is complicated and inaccurate. The present application first calculates the reference dynamic power DPoS index P according to the vector length of the i-th joint connecting rod to the DH parameter coordinate origin o, the rotational angular velocity of the i-th joint connecting rod, and the rotational inertia of the i-th joint connecting rod relative to the rotation axis at the coordinate origin. d Then, the ratio of the actual power of the human-shaped robot to the reference dynamic power is taken as the reference dynamic efficiency, and the motion efficiency of the human-shaped robot is evaluated according to the reference dynamic efficiency.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of robot evaluation, and particularly relates to a robot motion efficiency evaluation method, system, storage medium and equipment. BACKGROUND

[0002] Once, humanoid robots as images in film and television works give people unlimited imagination. In today's world of rapid development of science and technology, such imagination is gradually becoming a reality. In today's world, countries are actively conducting research on humanoid robot technology. At present, humanoid robot technology has achieved many gratifying research results, but there are still many problems in the field of humanoid robots that need to be solved.

[0003] Humanoid robots have high adaptability to human working environment due to their similarity to human appearance and structure. Therefore, from the perspective of reducing human work burden, humanoid robots have great potential. This puts forward requirements for the anthropomorphism, environmental adaptability, work reliability and work sustainability of humanoid robots. In order to realize the popularization of humanoid robots, the endurance capability is an important evaluation index, but the efficiency of the humanoid robot system is currently paid less attention to, and there is a lack of appropriate evaluation method. The commonly used evaluation index is to calculate the energy efficiency of each joint and then sum up or calculate the parameter: CoT for transportation for a specific task such as movement to evaluate and compare. These evaluation methods have problems such as complex operation, complicated calculation, inaccurate evaluation, etc. SUMMARY

[0004] The present application solves the problems of complicated calculation and inaccurate evaluation in the existing robot motion efficiency evaluation.

[0005] A humanoid robot motion efficiency evaluation method, comprising:

[0006] First, the reference dynamic power DPoS index P is calculated d :

[0007]

[0008] Wherein, m is the mass of the whole robot, g is the acceleration of gravity, v is the mass center motion speed, r io is the vector length of the i-th joint connecting rod to the DH parameter coordinate origin o, ω i is the rotation angular velocity of the i-th joint connecting rod, I io is the moment of inertia of the i-th joint connecting rod relative to the rotation axis at the coordinate origin;

[0009] Then, the reference dynamic efficiency KEoS is calculated according to P A and P d :

[0010]

[0011] Among them, P A The actual power of humanoid robots;

[0012] Evaluation of humanoid robot motion efficiency based on reference kinetic efficiency (KEoS).

[0013] Furthermore, the actual power P of the humanoid robot A The input power is obtained by the battery management system or power monitoring system, or the real-time voltage U and real-time output current I of the power supply are obtained, and the real-time output current I is obtained according to P A =UI calculates the actual power of the entire humanoid robot system.

[0014] Furthermore, the moment of inertia of the i-th joint link relative to the rotation axis at the coordinate origin is I io By using the parallel axis theorem:

[0015]

[0016] Among them, I imain is the moment of inertia of the i-th joint link relative to its own rotation axis, l io is the distance from the i-th joint rotation axis to the DH parameter coordinate origin o; m i is the mass of the i-th connecting rod.

[0017] Furthermore, when evaluating the motion efficiency of a humanoid robot based on the reference kinetic efficiency (KEoS), the humanoid robot must meet the following constraints:

[0018]

[0019] Among them, Δzoc and Δxoc are the vertical deviation and horizontal deviation between the center of mass position and the origin of the DH parameter coordinate, and L is the leg length of the humanoid robot.

[0020] A humanoid robot motion efficiency evaluation system, comprising:

[0021] DPoS indicator calculation unit: calculate the reference power DPoS indicator P d :

[0022]

[0023] Among them, m is the mass of the entire robot, g is the acceleration of gravity, v is the velocity of the center of mass, r io is the radial length from the i-th joint link to the origin o of the DH parameter coordinate, ω i is the angular velocity of the i-th joint link, I iois the moment of inertia of the ith joint link relative to the rotation axis at the coordinate origin;

[0024] The reference motion efficiency calculation unit calculates the reference motion efficiency KEoS according to P A and P d The reference motion efficiency KEoS is calculated according to P

[0025]

[0026] wherein P A is the actual power of the humanoid robot;

[0027] The motion efficiency evaluation unit evaluates the motion efficiency of the humanoid robot based on the reference motion efficiency KEoS.

[0028] Further, the system further comprises an actual power acquisition unit, which is configured to acquire or calculate the actual power P A of the humanoid robot. A The actual power P A of the humanoid robot is obtained by the input power obtained by the battery management system or the power supply monitoring system, or the real-time voltage U and the real-time output current I of the power supply are acquired, and the actual power of the whole humanoid robot system is calculated according to P

[0029] Further, the moment of inertia I io of the ith joint link relative to the rotation axis at the coordinate origin is obtained by the parallel axis theorem.

[0030]

[0031] wherein I imain is the moment of inertia of the ith joint link relative to the rotation axis of itself, l io is the distance from the ith joint rotation axis to the DH parameter coordinate origin o; and m i is the mass of the ith link.

[0032] Further, when evaluating the motion efficiency of the humanoid robot based on the reference motion efficiency KEoS, the humanoid robot needs to satisfy the following restriction conditions:

[0033]

[0034] wherein Δzoc and Δxoc are the vertical and horizontal deviations of the center of mass position from the DH parameter coordinate origin, and L is the leg length of the humanoid robot.

[0035] A computer storage medium, wherein the storage medium stores at least one instruction, and the at least one instruction is loaded and run by a processor to implement the humanoid robot motion efficiency evaluation system.

[0036] A humanoid robot motion efficiency evaluation device, the device comprises a processor and a memory, at least one instruction is stored in the memory, the at least one instruction is loaded and run by the processor, and the one kind humanoid robot motion efficiency evaluation system.

[0037] Compared with monitoring experimental data and calculating efficiency and sum separately, the application is more concise and fast, and ensures the accuracy of the motion efficiency calculation of the whole system. The application is simple and fast, can monitor and calculate the key parameter value in real time, so as to realize real-time motion efficiency evaluation. The index reference motion efficiency KEoS can evaluate the motion efficiency of the humanoid robot in performing various tasks in real time, and has universality.

[0038] Compared with the commonly used energy consumption index transportation cost CoT, the new index used in the application can more accurately evaluate the motion efficiency of the humanoid robot system, especially when the centroid motion speed of the whole humanoid robot system is very small, but the limbs have large motion, the transportation cost CoT cannot truly reflect the motion efficiency of the humanoid robot, and the application can still accurately evaluate the motion efficiency of the humanoid robot system when the centroid motion speed is very small but the limbs have large motion. BRIEF DESCRIPTION OF DRAWINGS

[0039] Figure 1 is the evaluation method flow chart described in the application;

[0040] Figure 2 is the humanoid robot walking test simulation schematic diagram of the evaluation method described in the application;

[0041] Figure 3 is the KEoS curve diagram of the humanoid robot calculated by the evaluation method described in the application;

[0042] Figure 4 is the comparison diagram of 1 / CoT and KEoS calculated when the humanoid robot designed by the application is tested for walking. DETAILED DESCRIPTION

[0043] The purpose of the present application is to solve the problem that there is no simple, fast and accurate evaluation method for the motion efficiency of humanoid robots at present. The present application can first divide the motion of a humanoid robot into two categories: whole body motion and fine work of the upper body. The whole body motion refers to the motion in which the whole body of the humanoid robot is involved. The motion generally has a large amplitude and a large change in the position of the center of mass, such as walking, running and jumping. The fine work of the upper body refers to the motion in which the lower body of the humanoid robot is stationary and acts as a base. The motion generally has a small amplitude and a small change in the position of the center of mass, and the hands are generally involved, such as playing a musical instrument and screwing. The present application proposes a reference dynamic efficiency (KEoS) for evaluation. During the motion of the humanoid robot, the reference dynamic efficiency can be calculated in real time to evaluate the motion efficiency of the humanoid robot at that moment. The determination process of KEoS requires the use of another parameter index: reference dynamic power (DPoS), which can evaluate the energy power consumed by the humanoid robot due to motion at that moment.

[0044] In order to evaluate the design of the system, the reference dynamic power of the robot under the same motion task needs to be calculated, and the average value is calculated for evaluation and comparison. The present application will be described in conjunction with the specific embodiments. Specific embodiment one:

[0046] In order to evaluate more comprehensively, more representative motion tasks are selected for evaluation. If the design results of the motion efficiency of any two humanoid robots are to be evaluated, the KEoS needs to be calculated based on the control of the task to compare the size. Since the target task performed by the humanoid robot can be divided into two categories: whole body mobility task with the participation of hands and feet, and fine work of the upper body. The reasons for choosing walking and grabbing heavy objects are that first of all, the two tasks are typical tasks in the two categories: the main function of the whole body motion of the human body is to move the human body, and the main way of human body movement is walking; the fine work of the upper body is mainly the change of the position and attitude of small objects by the hands of the human body; on the other hand, the research on these two tasks in the field of humanoid robots is relatively mature, and there is a lot of knowledge accumulation, so it can be more convenient to realize and explain. Therefore, this embodiment lists typical tasks: walking, grabbing heavy objects and lifting, and this embodiment takes these tasks as examples for explanation. In fact, the present application can also be applied to other tasks.

[0047] The test and calculation process of the whole system is as follows:

[0048] The humanoid robot moves according to the designed task, and in this process, the same control method is used, and the KEoS is calculated in real time during the motion:

[0049] 1. Calculate the actual power P A:Use the battery management system BMS or other power monitoring system to obtain the input power of the entire humanoid robot system in real time, or obtain the real-time voltage U and real-time output current I of the power supply, according to the formula: P A =UI calculates the actual power of the entire humanoid robot system.

[0050] 2. Calculate the reference dynamic power DPoS index P d :

[0051]

[0052] Among them, m is the mass of the entire robot, g is the acceleration of gravity, v is the velocity of the center of mass, r io is the radial length from the i-th joint link to the origin o of the DH parameter coordinate, ω i is the angular velocity of the i-th joint link (the angular velocity of the i-th link relative to its own axis of rotation), I io is the moment of inertia of the i-th joint link relative to the rotation axis at the coordinate origin;

[0053] I io It can be obtained by the parallel axis theorem:

[0054]

[0055] Among them, I imain is the moment of inertia of the i-th joint link relative to its own rotation axis, l io is the distance from the i-th joint rotation axis to the DH parameter coordinate origin o; m i is the mass of the i-th connecting rod.

[0056] The reference kinetic power is a simplified calculation form of the kinetic energy of the entire system. Considering that the center of mass of a humanoid robot is generally close to the hip, and the DH parameter coordinate origin of the entire humanoid robot is generally set at the hip joint, the kinetic energy of the rigid system is determined as follows:

[0057]

[0058] Among them, E represents the total kinetic energy of the rigid system. The entire rigid system is composed of many sub-rigid bodies. For the humanoid robot system, the entire robot can be regarded as a complex rigid system, and each connecting rod can be regarded as a sub-rigid body. m is the mass of the entire robot, v is the speed of the center of mass of the entire robot, Ii is the moment of inertia of each sub-rigid body relative to the center of mass, ω io is the angular velocity of each sub-rigid body relative to the center of mass, It is the relative kinetic energy of the rigid system. In the humanoid robot system, it can be approximated as the kinetic energy relative to the DH parameter coordinate origin o. Then, it is simplified by analogy with the form of transportation cost CoT to obtain the reference kinetic power DPoS.

[0059] Therefore, this evaluation method needs to introduce restrictions when used:

[0060]

[0061] Among them, Δzoc and Δxoc are the vertical deviation and horizontal deviation between the center of mass position and the origin of the DH parameter coordinate, and L is the leg length of the humanoid robot.

[0062] P d The parameter v in the expression is the input quantity during planning, ω i It can be obtained by real-time monitoring of the position sensors of each joint, io and l io The calculation can be done based on the kinematic parameters (these two parameters can be obtained by simply transforming the Jacobian matrix based on the actual joint motion angles of the robot and the robot kinematics). Therefore, the parameters in the entire DPoS can be easily calculated in real time. At the same time, due to their high similarity to the system kinetic energy derivative, they can be guaranteed to reasonably represent the instantaneous kinetic efficiency of the system.

[0063] It should be noted that the starting point of the present invention is to start from the perspective of the entire humanoid robot, which is a rigid system. First, the most accurate expression of its motion efficiency is written, which is the ratio of the power of real-time kinetic energy to the real-time input power. The kinetic energy of the rigid system can be written as the kinetic energy of the center of mass relative to the center of mass of other rigid bodies. However, since the center of mass position of the humanoid robot changes relative to the whole body at all times during the movement, it is difficult to calculate. In addition, the result of humanoid robot design is generally that the center of mass is located at the torso or hip joint. This paper makes an assumption on this formula and proposes a preliminary Simplification, that is, coinciding the center of mass position with the position of the DH coordinate origin o, makes it easier to calculate the relative kinetic energy of the second part; and when differentiating the kinetic energy to obtain power, the present invention can find that there will be an additional acceleration term in the formula, and for each sub-rigid body, it is extremely difficult to calculate the relative acceleration. Therefore, the present invention further simplifies this formula. Inspired by the use of gravitational acceleration g in the CoT definition to complete the representation of the acceleration dimension, the present invention uses expressions such as g and g / rio, so that all parameters in the formula of the present invention can be more conveniently obtained.

[0064] The new indicator used in this invention is compared with the commonly used energy consumption indicator transportation cost The motion efficiency of the humanoid robot system can be evaluated more accurately, especially when the center of mass motion speed of the entire humanoid robot system is very small, but the limbs have large motions, the transportation cost CoT is large, and it cannot truly reflect the motion efficiency of the humanoid robot.

[0065] 3. Calculate the reference kinetic efficiency KEoS:

[0066]

[0067] wherein P A is the actual power.

[0068] The reference kinetic efficiency is calculated in real time, and is used to evaluate the motion efficiency of the humanoid robot at the moment.

[0069] The evaluation method has the advantages that the calculation process is relatively simple, the calculation can be performed simultaneously with the motion of the system, the calculation can be performed for all motions of the system, and the evaluation method is universal.

[0070] The entire evaluation method calculation and test flow is shown in Figure 1 The typical motion of the humanoid robot is selected as walking at a uniform speed of 0.2 m / s for 10 m, and then lifting an apple on a table by 20 cm. Figure 2 The walking process simulation diagram is shown in Figure 3 The actual power of the system is calculated through the power management system during the entire motion process, the fixed parameters such as mgv and I are calculated according to the upper computer planning and the robot model, the joint motion parameters are calculated in real time according to the motion monitoring system, and then the remaining parameters required for calculating the kinetic power of the system are obtained, and finally, the kinetic efficiency of the system is calculated by taking the ratio of the two, and the kinetic efficiency curve is shown in The motion efficiency of the humanoid robot system can be evaluated in real time according to the kinetic efficiency curve.

[0071] Figure 4 The comparison diagram of 1 / CoT (the reason for selecting 1 / CoT is that it can ensure that the polarity of 1 / CoT and KEoS is the same, that is, the larger the number is, the higher the motion efficiency of the robot is) and KEoS calculated when the humanoid robot designed by the present application is tested is shown in Figure 4 It can be seen from that the values of the two change obviously in the red box area, and this area is the position where the humanoid robot adjusts the posture to step forward according to the ZMP algorithm, and the center of mass speed can be approximately ignored at this time, so that 1 / CoT is close to 0, while KEoS has an actual value, and the efficiency of the robot at this time is obviously not 0 in the real situation, so it can be seen that the description effect of KEoS of the present application is obviously better. Specific implementation method two:

[0073] The present embodiment is a humanoid robot motion efficiency evaluation system, comprising:

[0074] An actual power acquisition unit: acquiring or calculating the actual power P A of the humanoid robot. AThe input power obtained by the battery management system or the power supply monitoring system, or the real-time voltage U of the power supply and the real-time output current I are obtained, and the actual power of the whole humanoid robot system is calculated according to P A = UI.

[0075] The DPoS index calculation unit calculates the reference dynamic power DPoS index P d :

[0076]

[0077] Wherein, m is the mass of the whole robot, g is the acceleration of gravity, v is the mass center motion speed, r io is the vector length of the i-th joint connecting rod to the DH parameter coordinate origin o, ω i is the rotation angular velocity of the i-th joint, I io is the moment of inertia of the i-th joint connecting rod relative to the rotation axis at the coordinate origin.

[0078] The moment of inertia I uo of the i-th joint connecting rod relative to the rotation axis at the coordinate origin is obtained by the parallel axis theorem:

[0079]

[0080] Wherein, I imain is the moment of inertia of the i-th joint connecting rod relative to its own rotation axis, l io is the distance from the i-th joint rotation axis to the DH parameter coordinate origin o; m i is the mass of the i-th connecting rod.

[0081] The reference dynamic efficiency calculation unit calculates the reference dynamic efficiency KEoS according to P A and P d .

[0082]

[0083] Wherein, P A is the actual power of the humanoid robot.

[0084] The motion efficiency evaluation unit evaluates the motion efficiency of the humanoid robot based on the reference dynamic efficiency KEoS.

[0085] When evaluating the motion efficiency of the humanoid robot based on the reference dynamic efficiency KEoS, the humanoid robot needs to meet the following restriction conditions:

[0086]

[0087] Wherein, Δzoc and Δxoc are the vertical and horizontal deviations of the mass center position and the DH parameter coordinate origin, and L is the leg length of the humanoid robot. Specific implementation three:

[0089] The embodiment is a computer storage medium, and the storage medium stores at least one instruction. The at least one instruction is loaded by a processor and runs a humanoid robot motion efficiency evaluation system.

[0090] It should be understood that the instructions include a computer program product, software or computerized method corresponding to any method described in the present application; the instructions can be used to program a computer system or other electronic device. The computer storage medium can include a readable medium having instructions stored thereon, and can include but is not limited to a magnetic storage medium, an optical storage medium, a magneto-optical storage medium, a read-only memory (ROM), a random access memory (RAM), an erasable programmable memory (for example, an EPROM and an EEPROM), and a flash memory layer, or other types of media suitable for storing electronic instructions. Specific implementation four:

[0092] The embodiment is a humanoid robot motion efficiency evaluation device, and the device includes a processor and a memory. It should be understood that the device includes any device described in the present application, including a processor and a memory. The device can also include other units, modules, etc. that display, interact, process, control, etc. through signals or instructions, and other functions;

[0093] The storage stores at least one instruction, and the at least one instruction is loaded by the processor and runs a humanoid robot motion efficiency evaluation system.

[0094] Those skilled in the art should understand that the stored at least one instruction is a computer program product corresponding to the method or system. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product in the form of one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, such as object-oriented programming language Java and interpreted scripting language JavaScript.

[0095] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0096] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0097] The computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart block or blocks. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof. Figure 1 one or more flowcharts and / or blocks in the flowcharts and / or combination thereof.

[0098] While the preferred embodiments of the application have been described, additional variations and modifications can be employed by those skilled in the art. Therefore, the appended claims intend to cover all such modifications and variations as fall within the true spirit and scope of the application.

[0099] It is apparent that a person having ordinary skill in the art can make alterations and modifications to this application without deviating from the spirit and scope of the application. Therefore, it is intended that all such alterations and modifications be included within the scope of the application.

[0100] The above calculation examples of the present application are only used to illustrate the calculation model and calculation process of the present application, and are not used to limit the embodiments of the present application. Based on the above description, other different forms of changes or variations can be made by those skilled in the art, and all the embodiments cannot be exhausted here. Any obvious changes or variations derived from the technical solutions of the present application are still within the protection scope of the present application.

Claims

1. A method for evaluating the motion efficiency of a humanoid robot, characterized in that: include: First, calculate the reference dynamic power DPoS index P d : Among them, m is the mass of the entire robot, g is the acceleration of gravity, v is the velocity of the center of mass, r io is the radial length from the i-th joint link to the origin o of the DH parameter coordinate, ω i is the angular velocity of the i-th joint link, I io is the moment of inertia of the i-th joint link relative to the rotation axis at the coordinate origin; Then according to P A and P d Calculate the reference kinetic efficiency KEoS: Among them, P A The actual power of humanoid robots; The motion efficiency of a humanoid robot is evaluated based on the reference kinetic efficiency (KEoS). When evaluating the motion efficiency of a humanoid robot based on the reference kinetic efficiency (KEoS), the humanoid robot must meet the following constraints: Among them, Δzoc and Δxoc are the vertical deviation and horizontal deviation between the center of mass position and the origin of the DH parameter coordinate, and L is the leg length of the humanoid robot.

2. A method for evaluating the motion efficiency of a humanoid robot according to claim 1, characterized in that: The actual power P of the humanoid robot A The input power is obtained by the battery management system or power monitoring system, or the real-time voltage U and real-time output current I of the power supply are obtained, and the P A =UI calculates the actual power of the entire humanoid robot system.

3. A method for evaluating the motion efficiency of a humanoid robot according to claim 1 or 2, characterized in that: The moment of inertia of the i-th joint link relative to the rotation axis at the coordinate origin is I io By using the parallel axis theorem: Among them, I imain is the moment of inertia of the i-th joint link relative to its own rotation axis, l io is the distance from the i-th joint rotation axis to the DH parameter coordinate origin o; m i is the mass of the i-th connecting rod.

4. A humanoid robot motion efficiency evaluation system, characterized in that: include: DPoS indicator calculation unit: calculate the reference power DPoS indicator P d : Among them, m is the mass of the entire robot, g is the acceleration of gravity, v is the velocity of the center of mass, r io is the radial length from the i-th joint link to the origin o of the DH parameter coordinate, ω i is the angular velocity of the i-th joint link, I io is the moment of inertia of the i-th joint link relative to the rotation axis at the coordinate origin; Reference dynamic efficiency calculation unit: According to P A and P d Calculate the reference kinetic efficiency KEoS: Among them, P A The actual power of humanoid robots; Motion efficiency evaluation unit: Evaluates the motion efficiency of a humanoid robot based on the reference motion efficiency (KEoS). When evaluating the motion efficiency of a humanoid robot based on the reference motion efficiency (KEoS), the humanoid robot must meet the following constraints: Among them, Δzoc and Δxoc are the vertical deviation and horizontal deviation between the center of mass position and the origin of the DH parameter coordinate, and L is the leg length of the humanoid robot.

5. The humanoid robot motion efficiency evaluation system according to claim 4, characterized in that: The system further comprises an actual power acquisition unit, which is used to acquire or calculate the actual power P of the humanoid robot. A ; Actual power P of the humanoid robot A The input power is obtained by the battery management system or power monitoring system, or the real-time voltage U and real-time output current I of the power supply are obtained, and the P A =UI calculates the actual power of the entire humanoid robot system.

6. A humanoid robot motion efficiency evaluation system according to claim 4 or 5, characterized in that: The moment of inertia of the i-th joint link relative to the rotation axis at the coordinate origin is I io By using the parallel axis theorem: Among them, I imain is the moment of inertia of the i-th joint link relative to its own rotation axis, l io is the distance from the i-th joint rotation axis to the DH parameter coordinate origin o; m i is the mass of the i-th connecting rod.

7. A computer storage medium, characterized in that The storage medium stores at least one instruction, and the processor loads and runs the humanoid robot motion efficiency evaluation system according to any one of claims 4 to 6.

8. A humanoid robot motion efficiency evaluation device, characterized in that: The device includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to execute the humanoid robot motion efficiency evaluation system according to any one of claims 4 to 6.

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