A motion mode adjustment method and device for detecting device

Abstract

The present invention proposes a motion mode adjustment method and device for a detection device. The method constructs a motion adjustment model for the detection device, and according to the real-time motion mode of the detection device, adjusts the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model, and / or the energy consumption level mathematical model in the motion adjustment model to adjust the motion mode of the detection device. Through the present invention, the driving mode and the center of mass position of the spherical structure detection device facing different task requirements can be accurately adjusted, so that the working performance of the spherical structure detection device is optimized, and the work efficiency and user experience are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of device performance improvement, and in particular to a motion mode adjustment method, device, computer equipment and storage medium for detecting a device. Background Art

[0002] The detection equipment with spherical structure has the ability of anti-overturning and self-protection due to its special shape and movement mode, and also has the advantages of high movement efficiency and low energy consumption. The spherical detection equipment based on the pendulum eccentric torque drive mechanism has low complexity and high drive efficiency, and is the preferred target for the current research on spherical detection equipment; the spherical detection equipment based on the pendulum eccentric torque drive mechanism increases the range of motion of the pendulum inside the spherical shell, so that the pendulum has the ability to move circumferentially and radially at the same time, which can not only enable the spherical detection equipment to realize the traditional pendulum drive mode, but also realize the new inverted pendulum drive mode, and the radial movement of the pendulum under the two different drive modes can make the motion state of the spherical detection equipment present different characteristics.

[0003] When facing unstructured task environments, the inverted pendulum drive mode and the radial change of the center of mass can greatly promote the enrichment of the drive mode of the spherical detection equipment and improve the practicality of the spherical detection equipment. However, the inverted pendulum drive and the radial change of the center of mass can affect the motion characteristics of the spherical detection equipment in terms of motion ability, control performance and energy consumption level. Integrating the motion characteristics of different drive modes and different radial positions of the center of mass into the actual use requirements of the spherical detection equipment is of great significance to improving the practicality of the spherical detection equipment. Summary of the invention

[0004] The present invention provides a motion mode adjustment method, device, computer equipment and storage medium for detection equipment, aiming to provide a basis for selecting the driving mode and center of mass position of a spherical detection equipment with radially variable center of mass capability for different task requirements.

[0005] To this end, a first object of the present invention is to provide a motion mode adjustment method for a detection device, comprising:

[0006] Constructing a motion regulation model of the detection device; wherein the motion regulation model includes a motion capability mathematical model, a control performance mathematical model and an energy consumption level mathematical model;

[0007] According to the real-time motion mode of the detection device, the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model and / or the energy consumption level mathematical model in the motion adjustment model are adjusted to adjust the motion mode of the detection device.

[0008] Among them, the detection device is a spherical structure, which is driven by a driving pendulum; the driving pendulum is divided into a heavy pendulum and an inverted pendulum.

[0009] The motion ability mathematical model in the motion regulation model is determined by the climbing ability and steering ability of the detection equipment; the motion ability mathematical model formula is expressed as:

[0010]

[0011] in, Indicates the climbing slope angle, A represents the driving pendulum length of the spherical structure detection device; Norm (L) represents the gradeability, which is related to the drive pendulum length; B Norm (L,γ) represents the steering ability, which is related to the drive pendulum length and the climbing slope angle; Norm is the normalization operation.

[0012] Among them, the control performance mathematical model in the motion regulation model is determined by the control system convergence speed, control overshoot, control stability and control system response speed; the control performance mathematical model formula is expressed as:

[0013]

[0014] in, Indicates the speed of movement, It represents the convergence speed of the control system, which is related to the drive pendulum length and the climbing slope angle; Indicates the control overshoot, which is related to the movement speed, drive pendulum length and climbing slope angle; Indicates control stability, which is related to movement speed, drive pendulum length and climbing slope angle; It indicates the response speed of the control system and is related to the movement speed, drive pendulum length and climbing slope angle.

[0015] Among them, the mathematical model of energy consumption level in the motion regulation model is determined by the average output power of the sampling period; the mathematical model formula of energy consumption level is expressed as:

[0016]

[0017] in, It represents the average output power during the sampling period, which is related to the movement speed, drive pendulum length and climbing slope angle.

[0018] Among them, the motion adjustment model formula of the detection device is expressed as:

[0019]

[0020]

[0021] Among them, n1, n2, and n3 are weight parameters set according to the actual requirements for motion capability, control performance, and energy consumption level during the execution of the detection equipment task, and n1+n2+n3=1.

[0022] Among them, the climbing ability, steering ability, control system convergence speed, control overshoot, control stability, control system response speed and cycle average output power are all obtained through data fitting.

[0023] A second object of the present invention is to provide a motion mode adjustment device for detecting a device, comprising:

[0024] A model building module is used to build a motion regulation model of the detection device; wherein the motion regulation model includes a motion capability mathematical model, a control performance mathematical model and an energy consumption level mathematical model;

[0025] The motion mode adjustment module is used to adjust the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model and / or the energy consumption level mathematical model in the motion adjustment model according to the real-time motion mode of the detection device, so as to adjust the motion mode of the detection device.

[0026] The third object of the present invention is to provide a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method of the aforementioned technical solution is implemented.

[0027] The fourth object of the present invention is to provide a non-temporary computer-readable storage medium having a computer program stored thereon, which implements the method of the aforementioned technical solution when the computer program is executed by a processor.

[0028] Different from the prior art, the motion mode adjustment method for the detection device provided by the present invention constructs a motion adjustment model for the detection device, and adjusts the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model, and / or the energy consumption level mathematical model in the motion adjustment model according to the real-time motion mode of the detection device, so as to adjust the motion mode of the detection device. Through the present invention, the driving mode and the center of mass position of the spherical structure detection device can be accurately adjusted for different task requirements, so as to optimize the working performance of the spherical structure detection device and improve work efficiency and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The present invention and / or additional aspects and advantages will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0030] Figure 1 It is a flow chart of a motion mode adjustment method for detecting equipment provided by the present invention.

[0031] Figure 2 It is a trend diagram of the convergence time changing with the pendulum length and the expected speed in a motion mode adjustment method for a detection device provided by the present invention.

[0032] Figure 3 It is a trend diagram of the convergence time changing with the pendulum length and the slope angle in a motion mode adjustment method for a detection device provided by the present invention.

[0033] Figure 4 It is another trend diagram of the convergence time changing with the pendulum length and the slope angle in the motion mode adjustment method for detecting equipment provided by the present invention.

[0034] Figure 5 The present invention provides a trend diagram of the maximum absolute value of the position error when the motion does not converge in a motion mode adjustment method for a detection device as the pendulum length and the expected speed change.

[0035] Figure 6 The present invention provides a trend diagram of the maximum absolute value of the position error when the motion does not converge in a motion mode adjustment method for a detection device as the pendulum length and the slope angle change.

[0036] Figure 7 The present invention provides a trend diagram of the root mean square error of the position error when the motion does not converge in a motion mode adjustment method for a detection device as the pendulum length and the expected speed change.

[0037] Figure 8 The present invention provides a trend diagram of the root mean square error of the position error when the motion does not converge in a motion mode adjustment method for a detection device as the pendulum length and the slope angle change.

[0038] Fig. 9 It is a trend diagram of the maximum torque generation time changing with the pendulum length and the expected speed in a motion mode adjustment method for detecting equipment provided by the present invention.

[0039] Fig.10 It is a trend diagram of the maximum torque generation time changing with the pendulum length and the slope angle in a motion mode adjustment method for detecting equipment provided by the present invention.

[0040] Fig.11 It is a slope angle diagram corresponding to the climbing ability under different pendulum lengths in a motion mode adjustment method for detecting equipment provided by the present invention.

[0041] Fig.12 The present invention provides a trend diagram of the maximum distance between the motion path and the line connecting the initial and target positions changing with the pendulum length and the slope angle in a motion mode adjustment method for detecting equipment.

[0042] Fig.13 The present invention provides a trend diagram of average output power changing with pendulum length and expected speed in a motion mode adjustment method for detecting equipment.

[0043] Fig.14 The present invention provides a trend diagram of average output power changing with pendulum length and slope angle in a motion mode adjustment method for detecting equipment.

[0044] Fig.15 It is another trend diagram of the convergence time changing with the pendulum length and the slope angle in the motion mode adjustment method for detecting equipment provided by the present invention.

[0045] Fig.16 It is a structural schematic diagram of a motion mode adjustment device for detecting equipment provided by the present invention.

[0046] Fig.17 It is a structural schematic diagram of a non-temporary computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0047] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0048] Figure 1 A flow chart of a method for adjusting the motion mode of a detection device provided by an embodiment of the present invention. The method comprises the following steps:

[0049] Step 101, constructing a motion regulation model of the detection device; wherein the motion regulation model includes a motion capability mathematical model, a control performance mathematical model and an energy consumption level mathematical model.

[0050] The detection device involved in the present invention has a spherical appearance and is actually a spherical robot. It performs mobile detection based on a pendulum-type eccentric force driving mechanism, has low structural complexity and high driving efficiency.

[0051] A motion regulation model is constructed for the detection device of the spherical structure. There are two driving modes of the detection device of the spherical robot, namely, heavy pendulum drive and inverted pendulum drive.

[0052] The performance parameters of the detection device provided with a spherical structure of the present invention are shown in Table 1:

[0053]

[0054] Table 1 Performance parameters of detection equipment

[0055] The control performance mathematical model in the motion regulation model is determined by the control system convergence speed, control overshoot, control stability and control system response speed; the control performance mathematical model formula is expressed as:

[0056]

[0057] in, Indicates the speed of movement, It represents the convergence speed of the control system, which is related to the drive pendulum length and the climbing slope angle; Indicates the control overshoot, which is related to the movement speed, drive pendulum length and climbing slope angle; Indicates control stability, which is related to movement speed, drive pendulum length and climbing slope angle; It indicates the response speed of the control system and is related to the movement speed, drive pendulum length and climbing slope angle.

[0058] Specifically, by adjusting the pendulum length L, slope angle γ and expected speed v during the operation of the detection device of the spherical mechanism, it can be seen that in terms of controlling the convergence speed of the detection device, the change trend of the inverted pendulum drive mode is the same as that of the heavy pendulum drive mode, which becomes worse with the increase of the task slope or movement speed, and becomes better with the increase of the center of mass-center distance. Compared with the heavy pendulum drive mode, the inverted pendulum drive mode has a disadvantage in terms of the control system convergence speed, which can increase with the increase of the task slope or movement speed, and when the detection device of the spherical structure is in a horizontal plane motion state, the above disadvantage can remain relatively stable with the increase of the center of mass-center distance, and when the detection device of the spherical structure is in a slope motion state, the above disadvantage can be reduced with the increase of the center of mass-center distance.

[0059] Based on the above discussion, in the heavy pendulum driving mode and the inverted pendulum driving mode, the convergence speed level is expressed by the following formula:

[0060]

[0061] i is the driving mode number, i=1 is the heavy pendulum driving mode, and i=2 is the inverted pendulum driving mode.

[0062] (1) For different pendulum lengths L and desired speeds v d Combined, the convergence time t in two different modes r1 With t r2 The changing trend of Figure 2 As shown:

[0063] The pendulum length L and expected speed v of the spherical robot under two driving modes d When both remain consistent, 0.48s≤t r2 -t r1≤6.03s, that is, the inverted pendulum drive mode is inferior to the heavy pendulum drive mode in terms of convergence speed. d When the pendulum length L changes from 0.04m to 0.12m, the convergence speed of the two driving modes gradually accelerates. For further analysis, When v d When the speed is 0.2m / s, It changes randomly in a small range, with an average value of 111.50%; when v d Gradually increase from 0.2m / s to 1.6m / s, Changes randomly in a small range, with v d The average value of the change gradually increases to 129.38% compared with 0.2m / s, that is, in terms of convergence speed, the disadvantage of the inverted pendulum drive mode relative to the heavy pendulum drive mode remains relatively stable as the pendulum length L increases, and as the expected speed v d Increase and gradually increase.

[0064] Using the least squares method Figure 2 The experimental data shown in the figure are fitted by formula, and the decimal place of the coefficient to be determined is 2. Then the convergence time tri, the pendulum length L and the expected speed v d The mathematical model is shown in the following formula:

[0065]

[0066]

[0067] According to the theoretical error analysis method, the fitting accuracy is judged by the following formula:

[0068]

[0069] The fitting accuracy of the experimental data was judged according to the formula, and the fitting accuracy was 0.171s and 0.136s respectively, which did not affect the fitting accuracy of the experimental data.

[0070] (2) Combining different pendulum lengths L and slope angles γ, the convergence time t in two different modes r1 With t r2 The changing trend of Figure 3 As shown:

[0071] When the pendulum length L of the spherical robot and the slope angle γ are consistent in the two driving modes, 0.61s≤t r2 -t r1≤6.30s, that is, the inverted pendulum drive mode is inferior to the heavy pendulum drive mode in terms of convergence speed. When the slope angle γ is constant and the pendulum length L gradually changes from 0.04m to 0.12m, the convergence speeds of the two drive modes gradually increase. Further analysis shows that when γ is 1°, It gradually decreases, and its average value is 127.13%; when γ is 3°, gradually decreases, and its average value is 132.69%; as γ increases from 0° to 10°, The changing average value gradually increases from 120.40% to 142.71%, that is, in terms of convergence speed, the disadvantage of the inverted pendulum driving mode relative to the heavy pendulum driving mode gradually decreases with the increase of the pendulum length L, and gradually increases with the increase of the slope angle γ.

[0072] Using the least squares method Figure 3 The experimental data shown in the figure are fitted by formula, and the decimal place of the undetermined coefficient is 2. The mathematical model of the convergence time tri, the pendulum length L and the slope angle γ is as follows:

[0073]

[0074]

[0075] The fitting accuracy of the experimental data was judged according to the formula, and the fitting accuracy was 0.127s and 0.155s respectively, which did not affect the fitting accuracy of the experimental data.

[0076] (3) Combining different pendulum lengths L and slope angles γ, the convergence time t in two different modes r1 With t r2 The changing trend of Figure 4 As shown:

[0077] Through similar analysis as above, the least square method is used to Figure 4 The experimental data shown in the figure are fitted by formula, and the mathematical model of convergence time tri, pendulum length L and slope angle γ is as follows:

[0078]

[0079]

[0080] The fitting accuracy of the experimental data was judged according to the formula, and the fitting accuracy was 0.162s and 0.141s respectively, which did not affect the fitting accuracy of the experimental data.

[0081] Furthermore, by normalizing the above three sets of fitting formulas, we can get the formula for the convergence speed level. In the formula, given the pendulum length L and the expected speed vd And the actual value of the slope angle γ, we can get the control system convergence speed level in the two modes. The pendulum length L ranges from [0.04, 0.12]; v d The value range is [0.2,1.6]; the value range of γ corresponding to L is [0,10]. The range of variation is [0,1], and The smaller the value, the faster the convergence speed.

[0082] In terms of controlling overshoot, the changing trend of the inverted pendulum drive mode is the same as that of the heavy pendulum drive mode, that is, it becomes worse with the increase of the task slope or movement speed, and becomes better with the increase of the center of mass-center distance. Compared with the heavy pendulum drive mode, the inverted pendulum drive mode has an advantage in controlling overshoot, which can increase with the increase of the task slope or movement speed, and when the detection device is in a horizontal plane motion state, the above advantages can remain relatively stable with the increase of the center of mass-center distance, and when the detection device is in a slope motion state, the above advantages can decrease with the increase of the center of mass-center distance.

[0083] Based on the above discussion, in the heavy pendulum driving mode and the inverted pendulum driving mode, the control overshoot level is expressed by the following formula:

[0084]

[0085] (1) For different pendulum lengths L and desired speeds v d Combined, the maximum absolute value of the spherical shell motion position error in two different modes |e x | max1 and |e x | max2 , and the maximum absolute value of the swing position error |e x | max1 With |e x | max 2 , the changing trend is as follows Figure 5 As shown;

[0086] The pendulum length L and expected speed v of the spherical robot under two driving modes d When all remain consistent, 0.031m≤|e x | max1 -|e x | max2 ≤0.249m, 0.038rad≤|e α | max1 -|e α | max2 ≤0.195rad, that is, in terms of controlling overshoot, the inverted pendulum drive mode has an advantage over the heavy pendulum drive mode. dWhen the pendulum length L changes from 0.04m to 0.12m, the control overshoot of the two driving modes gradually decreases. Further analysis: When v d When it is 0.2m / s, It changes randomly in a small range, with an average value of 81.24%; when v d Gradually increase from 0.2m / s to 1.6m / s, Changes randomly in a small range, with v d The average value of the change gradually decreases to 67.35% compared with 0.2m / s, that is, in terms of controlling overshoot, the advantage of the inverted pendulum drive mode over the heavy pendulum drive mode remains relatively stable as the pendulum length L increases, and gradually increases as the desired speed vd increases.

[0087] Using the least squares method Figure 5 The experimental data is fitted by formula to obtain the maximum absolute value of the spherical shell motion position error when the motion does not converge |e x | max , pendulum length L and desired velocity v d Mathematical model and the maximum absolute value of the position error of the re-swing when the motion has not converged |e α | max , pendulum length L and desired velocity v d Mathematical model As shown below:

[0088]

[0089]

[0090]

[0091]

[0092] The fitting accuracy of the experimental data was judged to be 0.0124m, 0.0089m, 0.0103rad, and 0.0117rad, respectively. This fitting accuracy does not affect the trend judgment of the experimental data.

[0093] (2) For different combinations of pendulum length L and slope angle γ, the maximum absolute value of the spherical shell motion position error in two different modes |e x | max1 and |e x | max2 , and the maximum absolute value of the swing position error |e x | max1 With |e x |max 2 , the changing trend is as follows Figure 6 As shown;

[0094] When the pendulum length L of the spherical robot and the slope angle γ are consistent in the two driving modes, 0.023m≤e x | max1 -|e x | max2 ≤0.142m, 0.022rad≤|e α | max1 -|e α | max2 ≤0.235rad, that is, in terms of controlling overshoot, the inverted pendulum drive mode has an advantage over the heavy pendulum drive mode.

[0095] When the slope angle γ is constant and the pendulum length L gradually changes from 0.04m to 0.12m, the control overshoot of the two driving modes gradually decreases. Further analysis: When γ is 1°, gradually increases, and its average value is 77.30%; when γ is 3°, As γ increases from 0° to 10°, The changing average value gradually decreases from 84.71% to 64.39%, that is, in terms of controlling overshoot, the advantage of the inverted pendulum driving mode over the heavy pendulum driving mode gradually decreases with the increase of the pendulum length L, and gradually increases with the increase of the slope angle γ.

[0096] Using the least squares method Figure 6 The experimental data is fitted by formula to obtain the maximum absolute value of the spherical shell motion position error when the motion does not converge |e x | max , mathematical model of pendulum length L and slope angle γ and the maximum absolute value of the position error of the re-swing when the motion has not converged |e α | max , mathematical model of pendulum length L and slope angle γ As shown below:

[0097]

[0098]

[0099]

[0100]

[0101] The fitting accuracy of the experimental data was judged to be 0.0072m, 0.0101m, 0.0137rad, and 0.0105rad, respectively. This fitting accuracy does not affect the trend judgment of the experimental data.

[0102] Furthermore, by normalizing the above two sets of fitting formulas, we can get the formula for controlling overshoot. In the formula, given the pendulum length L and the desired speed v d And the actual value of the slope angle γ, the control overshoot level in the two modes can be obtained. The pendulum length L ranges from [0.04, 0.12]; v d The value range is [0.2,1.6]; the value range of γ corresponding to L is [0,10]. The range of variation is [0,1], and The smaller the value, the faster the convergence speed.

[0103] Based on the above discussion, in the heavy pendulum driving mode and the inverted pendulum driving mode, the control stability level is expressed by the following formula:

[0104]

[0105] (1) For different pendulum lengths L and desired speeds v d Combined, the root mean square error of the spherical shell motion position error in two different modes is e x-rmse1 and e x-rmse2 , and the root mean square error of the swing position error e α-rmse1 and e α-rmse2 The changing trend of Figure 7 shown.

[0106] The pendulum length L and expected speed v of the spherical robot under two driving modes d When all remain consistent, 0.109m≤e x-rmse2 -e x-rmse1 ≤1.721m, 0.026rad≤e α-rmse2 -e α-rmse1 ≤0.154rad, that is, in terms of the control stability of the spherical robot, the inverted pendulum drive mode is inferior to the heavy pendulum drive mode. d When the pendulum length L gradually changes from 0.04m to 0.12m, the control stability of the two driving modes gradually increases. Further analysis: When v d When it is 0.2m / s, It changes randomly in a small range, and the average value of the change is 118.17%; when vd gradually increases from 0.2m / s to 1.6m / s, Changes randomly in a small range, with vd Compared with 0.2 m / s, the average value of the change gradually increases to 154.97%, that is, in terms of the control stability of the spherical robot, the disadvantage of the inverted pendulum drive mode relative to the heavy pendulum drive mode can remain relatively stable as the pendulum length L increases, and as the expected speed v d gradually increases with the increase of .

[0107] Using the least squares method Figure 7 The experimental data is fitted by formula to obtain the root mean square error of the spherical shell motion position error when the motion does not converge. x-rmse , pendulum length L and desired velocity v d Mathematical model and the root mean square error of the swing position error when the motion has not converged e α-rmse , pendulum length L and desired velocity v d Mathematical model As shown below:

[0108]

[0109]

[0110]

[0111]

[0112] The fitting accuracy of the experimental data was judged to be 0.0207m, 0.0173m, 0.0054rad, and 0.0029rad, respectively. This fitting accuracy does not affect the trend judgment of the experimental data.

[0113] (2) The root mean square error of the spherical shell motion position error under two different modes is e for different combinations of pendulum length L and slope angle γ. x-rmse1 and e x-rmse2 , and the root mean square error of the swing position error e α-rmse1 and e α-rmse2 The changing trend of Figure 8 shown.

[0114] When the pendulum length L of the spherical robot and the slope angle γ are consistent in the two driving modes, 0.079m≤e x-rmse2 -e x-rmse1 ≤0.602m, 0.020rad≤e α-rmse2 -e α-rmse1 ≤0.149rad, that is, in terms of control stability, the inverted pendulum driving mode is inferior to the heavy pendulum driving mode. When the slope angle γ is constant and the pendulum length L gradually changes from 0.04m to 0.12m, the control stability of the two driving modes gradually decreases. Further analysis: When γ is 1°, It gradually decreases, and its average value is 129.47%; when γ is 3°, gradually decreases, and its average value is 138.28%; as γ increases from 0° to 10°, The changing average value gradually increases from 122.91% to 147.47%, that is, in terms of control stability, the disadvantage of the inverted pendulum driving mode relative to the heavy pendulum driving mode gradually decreases with the increase of the pendulum length L, and gradually increases with the increase of the slope angle γ.

[0115] Using the least squares method Figure 8 The experimental data is fitted by formula to obtain the root mean square error of the spherical shell motion position error when the motion does not converge. α-rmse , mathematical model of pendulum length L and slope angle γ and the root mean square error of the swing position error when the motion has not converged e α-rmse , mathematical model of pendulum length L and slope angle γ As shown below:

[0116]

[0117]

[0118]

[0119]

[0120] The fitting accuracy of the experimental data was judged to be 0.0236m, 0.0203m, 0.0091rad, and 0.0074rad, respectively. This fitting accuracy does not affect the trend judgment of the experimental data.

[0121] Furthermore, by normalizing the above two sets of fitting formulas, we can get the formula for control stability. In the formula, given the pendulum length L and the desired speed v d And the actual value of the slope angle γ, we can get the control stability level in the two modes. The pendulum length L ranges from [0.04, 0.12]; v d The value range is [0.2,1.6]; the value range of γ corresponding to L is [0,10]. The range of variation is [0,1], and The smaller the value, the faster the convergence speed.

[0122] Based on the above discussion, in the heavy pendulum driving mode and the inverted pendulum driving mode, the control system response speed level is expressed by the following formula:

[0123]

[0124] (1) For different pendulum lengths L and desired speeds v d Combined, the convergence time t in two different modes τ-max1 and t τ-max2 The changing trend of Fig. 9 shown.

[0125] The pendulum length L and expected speed v of the spherical robot under two driving modes d When all remain consistent, 0.10s≤t τ-max1 -t r-max2 ≤0.39s, that is, the inverted pendulum drive mode has an advantage over the heavy pendulum drive mode in terms of control system response speed. d When the pendulum length L gradually changes from 0.04m to 0.12m, the control system response speed of the two driving modes gradually decreases. Further analysis: different v d In case of In a small range of disordered changes, that is, in terms of control system response speed, the advantage of the inverted pendulum drive mode over the heavy pendulum drive mode increases with the pendulum length L and the desired speed v d Increased and remained relatively stable.

[0126] Using the least squares method Fig. 9 The experimental data is fitted by formula, and the decimal place of the coefficient to be determined is 2, then the maximum torque generation time t τ-maxi , pendulum length L and desired velocity v d Mathematical model As shown below:

[0127]

[0128]

[0129] The fitting accuracy of the experimental data was judged to be 0.0137s and 0.0106s respectively, which did not affect the trend judgment of the experimental data.

[0130] (2) Combining different pendulum lengths L and slope angles γ, the convergence time t in two different modes τ-max1 and t τ-max2 The changing trend of Fig.10 shown.

[0131] When the pendulum length L of the spherical robot and the slope angle γ are consistent in the two driving modes, 0.12s≤t τ-max1 -t τ-max2≤0.32s, that is, the inverted pendulum drive mode has an advantage over the heavy pendulum drive mode in terms of control system response speed. When the slope angle γ is constant and the pendulum length L gradually changes from 0.04m to 0.12m, the control system response speeds of the two drive modes gradually decrease. Further analysis: In a small range of disordered changes, that is, in terms of control system response speed, the advantage of the inverted pendulum drive mode over the heavy pendulum drive mode remains relatively stable as the pendulum length L and the slope angle γ increase.

[0132] Using the least squares method Fig.10 The experimental data is fitted by formula, and the decimal place of the coefficient to be determined is 2, then the maximum torque generation time t τ-maxi , mathematical model of pendulum length L and slope angle γ As shown below:

[0133]

[0134]

[0135] The fitting accuracy of the experimental data was judged to be 0.127s and 0.155s respectively, which did not affect the trend judgment of the experimental data.

[0136] Furthermore, by normalizing the above two sets of fitting formulas, we can get the formula for control stability. In the formula, given the pendulum length L and the desired speed v d And the actual value of the slope angle γ, we can get the control stability level in the two modes. The pendulum length L ranges from [0.04, 0.12]; v d The value range is [0.2,1.6]; the value range of γ corresponding to L is [0,10]. The range of variation is [0,1], and The smaller the value, the faster the convergence speed.

[0137] The mathematical model formula of sports ability is expressed as:

[0138]

[0139] in, Indicates the climbing slope angle, A represents the driving pendulum length of the spherical structure detection device; Norm (L) represents the gradeability, which is related to the drive pendulum length; B Norm (L, γ) represents the steering ability, which is related to the drive pendulum length and the climbing slope angle; Norm is the normalization operation.

[0140] The correspondence between the pendulum length L and the maximum slope angle γ is as follows: Fig.11 As shown in the figure, when the movement of the spherical structure detection device can converge, the climbing ability of the device in the inverted pendulum drive mode and the heavy pendulum drive mode is the same. As the pendulum length L gradually changes from 0.04m to 0.12m, the maximum climbing angle gradually increases from 3° to 10°.

[0141] Using the least squares method Fig.10 Perform a formula fitting, and the decimal place of the undetermined coefficient is 2, then the mathematical model fitting results of the pendulum length L and the maximum climbing angle γ are as follows:

[0142] γ=A(L)=-10416.67L 3 +2857.14L 2 -152.98L+5.20

[0143] It can be seen that in terms of climbing ability, the inverted pendulum driving mode is the same as the heavy pendulum driving mode, and the climbing ability increases with the increase of the distance between the center of mass and the center of the ball.

[0144] The climbing ability of the spherical structure detection device in the heavy pendulum driving mode and the inverted pendulum driving mode is expressed by the following formula:

[0145] A Norm (L) = Norm[1 / A(L)]

[0146] Combining different pendulum lengths L and slope angles γ, the maximum distance D between the motion path and the line connecting the initial and target positions in two different modes max1 With D max2 The changing trend of Fig.12 shown.

[0147] In the two driving modes, when the pendulum length L and the slope angle are consistent, 0.061m≤D max1 -D max2 ≤0.219m, that is, the inverted pendulum driving mode has an advantage over the heavy pendulum driving mode in terms of steering ability. When the slope angle γ is constant and the pendulum length L gradually changes from 0.04m to 0.12m, the steering ability of the two driving modes is gradually enhanced. Further analysis: When γ is 0°, It changes randomly in a small range, and the average value is 83.33%; when γ is 1°, gradually increases, and the average value is 80.55%; when γ is 3°, gradually increases, with an average value of 76.06%; as γ increases from 0° to 10°, The changing average value decreases from 83.33% to 73.34%, that is, in terms of steering ability, the advantage of the inverted pendulum driving mode over the heavy pendulum driving mode gradually decreases with the increase of the pendulum length L, and also gradually decreases with the increase of the slope angle γ.

[0148] Using the least squares method Fig.12 Perform a formula fitting, and the decimal place of the coefficient to be determined is 2, then the maximum distance D between the motion path and the line connecting the initial and target positions max The mathematical model fitting results of the pendulum length L and the maximum climbing angle γ are as follows:

[0149] B (1) =-224.59L 3 +0.01γ 3 +85.44L 2 +0.01γ 2 -14.92L-0.03γ+1.85L 2 γ-0.02Lγ 2 -0.05Lγ+1.37

[0150] B (2) =-156.89L 3 -0.01γ 3 +61.45L 2 +0.01γ 2 -11.72L-0.08γ+0.22L 2 γ-0.02Lγ 2 +0.45Lγ+1.19

[0151] Based on the above, it can be seen that in terms of steering ability, the change trend of the inverted pendulum drive mode is the same as that of the heavy pendulum drive mode, that is, it becomes better with the increase of the task slope and the distance between the center of mass and the center of the ball. Compared with the heavy pendulum drive mode, the inverted pendulum drive mode has an advantage in the control system convergence speed, which can increase with the increase of the task slope, and when the spherical structure detection device is in a horizontal plane motion state, the above advantages can remain relatively stable with the increase of the distance between the center of mass and the center of the ball. When the spherical robot is in a slope motion state, the above advantages can decrease with the increase of the distance between the center of mass and the center of the ball.

[0152] The steering capability of the spherical structure detection device in the heavy pendulum driving mode and the inverted pendulum driving mode is expressed by the following formula:

[0153]

[0154] Given the pendulum length L and the desired velocity v d And the actual value of the slope angle γ, the steering ability level in the two modes can be obtained. The swing length L ranges from [0.04, 0.12]; vd The value range is [0.2,1.6]; the value range of γ corresponding to L is [0,10]. The range of variation is [0,1], and The smaller the value, the faster the convergence speed.

[0155] The energy consumption level mathematical model is determined by the average output power during the sampling period; the energy consumption level mathematical model formula is expressed as:

[0156]

[0157] in, It represents the average output power during the sampling period, which is related to the movement speed, drive pendulum length and climbing slope angle.

[0158] The energy consumption level evaluation index is the average power Pi output by the driving motor in each sampling period under two different driving modes. Its changes are analyzed and a relevant mathematical model is established.

[0159] (1) For different pendulum lengths L and desired speeds v d The change trends of the average output power P1 and P2 of the drive motor in each sampling period under the two different modes are as follows: Fig.13 shown.

[0160] Using the least squares method Fig.13 The experimental data shown in the figure are fitted by formula, and the decimal place of the coefficient to be determined is 2. Then the average output power Pi, pendulum length L and expected speed v of the drive motor in each sampling period are d Mathematical model As shown below:

[0161]

[0162]

[0163] The fitting accuracy of the experimental data was judged to be 0.013W and 0.021W respectively, which does not affect the trend judgment of the experimental data.

[0164] (2) For different combinations of pendulum length L and slope angle γ, the variation trends of the average output power P1 and P2 of the drive motor in each sampling period under two different modes are as follows: Fig.14 shown.

[0165] When the pendulum length L and the slope angle γ of the spherical robot are consistent in the two driving modes, 0.052W≤P1-P2≤0.936W, that is, the inverted pendulum driving mode has an advantage over the heavy pendulum driving mode in terms of energy consumption level. When the slope angle remains constant and the pendulum length L gradually changes from 0.04m to 0.12m, the energy consumption of the two driving modes increases. Further analysis: When γ is 1°, gradually increases, and its average value is 81.35%; when γ is 3°, As γ increases from 0° to 10°, The changing average value gradually decreases from 87.13% to 69.35%, that is, in terms of energy consumption level, the advantage of the inverted pendulum driving mode over the heavy pendulum driving mode gradually decreases with the increase of the pendulum length L, and gradually increases with the increase of the slope angle γ.

[0166] Using the least squares method Fig.14 The experimental data shown in the figure are fitted by formula, and the decimal place of the coefficient to be determined is 2. Then the mathematical model of the average output power Pi, pendulum length L and slope angle γ of the drive motor in each sampling period is As shown below:

[0167]

[0168]

[0169] The fitting accuracy of the experimental data was judged to be 0.024W and 0.018W respectively, which did not affect the trend judgment of the experimental data.

[0170] (3) For different combinations of pendulum length L and slope angle γ, the variation trends of the average output power P1 and P2 of the drive motor in each sampling period under two different modes are as follows: Fig.15 shown.

[0171] When the pendulum length L and the slope angle γ of the spherical robot are consistent in the two driving modes, 0.035W≤P1-P2≤1.482W, that is, the inverted pendulum driving mode has an advantage over the heavy pendulum driving mode in terms of energy consumption level. When the slope angle γ is constant and the pendulum length L gradually changes from 0.04m to 0.12m, the energy consumption of the two driving modes increases. Further analysis: When γ is 1°, gradually increases, and its average value is 86.04%; when γ is 3°, As γ increases from 0° to 10°, The changing average value gradually decreases from 91.35% to 73.33%, that is, in terms of energy consumption level, the advantage of the inverted pendulum driving mode over the heavy pendulum driving mode gradually decreases with the increase of the pendulum length L, and gradually increases with the increase of the slope angle γ.

[0172] Using the least squares method Fig.15 The experimental data shown in the figure are fitted by formula, and the decimal place of the coefficient to be determined is 2. Then the mathematical model of the average output power Pi, pendulum length L and slope angle γ of the drive motor in each sampling period is As shown below:

[0173]

[0174]

[0175] The energy consumption level of the inverted pendulum drive mode has the same trend as that of the heavy pendulum drive mode, that is, it increases with the increase of the task slope or movement speed and the increase of the distance between the center of mass and the center of the sphere. Compared with the heavy pendulum drive mode, the inverted pendulum drive mode has an advantage in energy consumption level, which can increase with the increase of the task slope or movement speed, and when the detection device is in a horizontal plane motion state, the above advantages can remain relatively stable with the increase of the distance between the center of mass and the center of the sphere, and when the detection device is in a slope motion state, the above advantages can decrease with the increase of the distance between the center of mass and the center of the sphere.

[0176] The energy consumption level of the spherical structure detection equipment in the heavy pendulum driving mode and the inverted pendulum driving mode is expressed by the following formula:

[0177]

[0178] Given the pendulum length L and the desired velocity v d And the actual value of the slope angle γ, the steering ability level in the two modes can be obtained. The swing length L ranges from [0.04, 0.12]; v d The value range is [0.2,1.6]; the value range of γ corresponding to L is [0,10]. The range of variation is [0,1], and The smaller the value, the faster the convergence speed.

[0179] The motion adjustment model formula of the detection device is expressed as:

[0180]

[0181]

[0182] Among them, n1, n2, and n3 are weight parameters set according to the actual requirements for motion capability, control performance, and energy consumption level during the execution of the detection equipment task, and n1+n2+n3=1.

[0183] Assuming that the maximum climbing ability of the prototype of the detection equipment used is 10° and the maximum movement speed is 4m / s, the corresponding relationship between the climbing ability of the detection equipment and the climbing ability γ of the actual spherical robot is: The corresponding relationship between the movement speed and the actual movement speed v of the spherical robot is: The maximum pendulum length and the minimum pendulum length are 0.12m and 0.04m respectively. n1, n2, and n3 are weight parameters set according to the actual requirements for motion capability, control performance, and energy consumption level during the execution of the detection equipment task. The larger the parameter value, the more important the related performance, and n1+n2+n3=1.

[0184] For a given The corresponding pendulum length value can be calculated by the model formula to obtain the optimal The optimal pendulum length of the spherical robot in actual use can be obtained by converting the following formula:

[0185]

[0186] Therefore, in the mission preparation stage, the detection equipment with a spherical structure with a radially variable center of mass can select the driving mode according to the motion characteristics of the two driving modes and the actual requirements of the mission, and during the mission execution, the optimal pendulum length L can be determined and adjusted according to the mission's requirements for motion characteristics, the slope γ that needs to be faced, and the required motion speed v, so that the practicality of the spherical structure detection equipment in the face of unstructured mission environments is greatly improved.

[0187] Step 102, according to the real-time motion mode of the detection device, adjust the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model and / or the energy consumption level mathematical model in the motion adjustment model to adjust the motion mode of the detection device.

[0188] In the embodiment of the present invention, the current slope angle γ is set to 0°, and the expected speed v d Set to 1m / s.

[0189] Task 1: If the spherical detection equipment needs to have the best energy consumption performance during the task execution, adjust n1, n2, and n3 in the motion regulation model formula according to the task requirements, set the motion ability weight parameter n1 to 0.1, the control performance weight parameter n2 to 0.2, and the energy consumption level weight parameter n3 to 0.7.

[0190] Task 2: If the spherical robot needs to have a small control overshoot and at the same time ensure optimal control performance while taking into account energy consumption level performance, adjust n1, n2, and n3 in the motion regulation model formula according to task requirements, set the motion ability weight parameter n1 to 0.1, the control performance weight parameter n2 to 0.6, and the energy consumption level weight parameter n3 to 0.3.

[0191] According to the characteristics of the heavy pendulum drive and the inverted pendulum drive, compared with the heavy pendulum drive mode, the inverted pendulum drive mode has advantages in energy consumption level and control system overshoot. Therefore, the drive mode parameter in the model formula is set to 2 in both Task 1 and Task 2. Further calculation shows that the optimal pendulum length of Task 1 is L = 0.053m, and the optimal pendulum length of Task 2 is L = 0.098m.

[0192] Task 1 requires optimal energy consumption performance. The average output power of the drive motor in each sampling period is compared. Compared with the pendulum length L=0.12m in the heavy pendulum drive mode, the power reduction of the detection equipment in the heavy pendulum drive mode is 54.67% when the pendulum length is L=0.053m, and the power reduction in the inverted pendulum drive mode is 67.03%. It can be seen that the energy consumption performance is greatly improved.

[0193] Task 2 requires a small overshoot and a balanced energy consumption while ensuring optimal control performance. Therefore, the convergence time t r , the maximum absolute value of the position error when the motion does not converge |e x | max With |e α | max , the root mean square error of the position error when the motion does not converge e x-rmse With e α-rmse , the time when the maximum torque is generated during the movement τ-max The four types of control performance indicators and the average output power P of the drive motor in each sampling period are compared. Compared with the pendulum length L = 0.12m in the heavy swing drive mode, when the pendulum length is L = 0.098m, the detection device is in the heavy swing drive mode, and the average improvement of the four types of control performance indicators is 40.75%, while the indicator P decreases by 19.35%; when it is in the inverted pendulum drive mode, the average improvement of the four types of control performance indicators is 40.60%, while the indicator P decreases by 40.28%. The above data show that compared with the pendulum length L = 0.12m in the heavy swing drive mode, when the detection device is in the inverted pendulum drive mode and the pendulum length L = 0.098m, the control performance decreases but the energy consumption performance is improved.

[0194] In order to implement the embodiment, the present invention also proposes a motion mode adjustment device for detecting a device, such as Fig.16 As shown, including:

[0195] The model building module 310 is used to build a motion regulation model of the detection device; wherein the motion regulation model includes a motion capability mathematical model, a control performance mathematical model and an energy consumption level mathematical model;

[0196] The motion mode adjustment module 320 is used to adjust the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model and / or the energy consumption level mathematical model in the motion adjustment model according to the real-time motion mode of the detection device, so as to adjust the motion mode of the detection device.

[0197] In order to implement the embodiment, the present invention also proposes another computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the motion mode adjustment for the detection device as in the embodiment of the present invention is implemented.

[0198] like Fig.17 As shown, the non-transitory computer-readable storage medium includes a memory 810 of instructions, an interface 830, and the instructions can be executed by a processor 820 for adjusting the device according to the motion pattern of the detection device to complete the method. Optionally, the storage medium can be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a tape, a floppy disk, and an optical data storage device, etc.

[0199] In order to implement the embodiment, the present invention further proposes a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the motion mode adjustment for the detection device as in the embodiment of the present invention.

[0200] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0201] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0202] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present invention belong.

[0203] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0204] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the described embodiment, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0205] A person skilled in the art may understand that all or part of the steps of implementing the method of the embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0206] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0207] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the embodiments are exemplary and cannot be construed as limiting the present invention. A person of ordinary skill in the art may change, modify, replace and modify the embodiments within the scope of the present invention.

Claims

1. A method for adjusting a motion mode of a detection device, characterized in that: include: Constructing a motion regulation model of the detection device; wherein the motion regulation model includes a motion capability mathematical model, a control performance mathematical model and an energy consumption level mathematical model; According to the real-time motion mode of the detection device, the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model and / or the energy consumption level mathematical model in the motion adjustment model are adjusted to adjust the motion mode of the detection device; the detection device is a spherical structure and is driven by a driving pendulum; the driving pendulum is divided into a heavy pendulum and an inverted pendulum; The motion capability mathematical model in the motion regulation model is determined by the climbing capability and steering capability of the detection device; the motion capability mathematical model formula is expressed as: in, Indicates the climbing slope angle, The driving pendulum length of the detection device representing the spherical structure; Indicates gradeability, which is related to the drive pendulum length; Indicates the steering ability, which is related to the driving pendulum length and the climbing slope angle; Norm is the normalization operation, i is the driving mode index, i=1 is the heavy pendulum driving mode, i=2 is the inverted pendulum driving mode; The control performance mathematical model in the motion regulation model is determined by the control system convergence speed, control overshoot, control stability and control system response speed; the control performance mathematical model formula is expressed as: in, Indicates the speed of movement, It represents the convergence speed of the control system, which is related to the drive pendulum length and the climbing slope angle; Indicates the control overshoot, which is related to the movement speed, drive pendulum length and climbing slope angle; Indicates control stability, which is related to movement speed, drive pendulum length and climbing slope angle; Indicates the response speed of the control system, which is related to the movement speed, drive pendulum length and climbing slope angle; The energy consumption level mathematical model in the motion regulation model is determined by the average output power of the sampling period; the energy consumption level mathematical model formula is expressed as: in, It represents the average output power during the sampling period, which is related to the movement speed, drive pendulum length and climbing slope angle; The motion adjustment model formula of the detection device is expressed as: Among them, n1, n2, and n3 are weight parameters set according to the actual requirements of the motion capability, control performance, and energy consumption level of the detection equipment during the task execution, and n1+n2+n3=1. For a given The corresponding pendulum length value.

2. The motion mode adjustment method for detecting equipment according to claim 1, characterized in that: The gradeability, steering capability, control system convergence speed, control overshoot, control stability, control system response speed and cycle average output power are all obtained through data fitting.

3. A motion mode adjustment device for detecting equipment, characterized in that: include: A model building module, used to build a motion regulation model of the detection device; wherein the motion regulation model includes a motion capability mathematical model, a control performance mathematical model and an energy consumption level mathematical model; A motion mode adjustment module, used to adjust the weight parameters corresponding to the motion ability mathematical model, the control performance mathematical model and / or the energy consumption level mathematical model in the motion adjustment model according to the real-time motion mode of the detection device, so as to adjust the motion mode of the detection device; Wherein, the detection device is a spherical structure, and is driven by a driving pendulum; the driving pendulum is divided into a heavy pendulum and an inverted pendulum; The motion capability mathematical model in the motion regulation model is determined by the climbing capability and steering capability of the detection device; the motion capability mathematical model formula is expressed as: in, Indicates the climbing slope angle, The driving pendulum length of the detection device representing the spherical structure; Indicates gradeability, which is related to the drive pendulum length; Indicates the steering ability, which is related to the driving pendulum length and the climbing slope angle; Norm is the normalization operation, i is the driving mode index, i=1 is the heavy pendulum driving mode, i=2 is the inverted pendulum driving mode; The control performance mathematical model in the motion regulation model is determined by the control system convergence speed, control overshoot, control stability and control system response speed; the control performance mathematical model formula is expressed as: in, Indicates the speed of movement, It represents the convergence speed of the control system, which is related to the drive pendulum length and the climbing slope angle; Indicates the control overshoot, which is related to the movement speed, drive pendulum length and climbing slope angle; Indicates control stability, which is related to movement speed, drive pendulum length and climbing slope angle; Indicates the response speed of the control system, which is related to the movement speed, drive pendulum length and climbing slope angle; The energy consumption level mathematical model in the motion regulation model is determined by the average output power of the sampling period; the energy consumption level mathematical model formula is expressed as: in, It represents the average output power during the sampling period, which is related to the movement speed, drive pendulum length and climbing slope angle; The motion adjustment model formula of the detection device is expressed as: Among them, n1, n2, and n3 are weight parameters set according to the actual requirements of the motion capability, control performance, and energy consumption level of the detection equipment during the task execution, and n1+n2+n3=1. For a given The corresponding pendulum length value.

4. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method according to any one of claims 1 to 2 is implemented.

5. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 2 is implemented.

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