CN115690909A - Transformer substation constructor autonomous positioning method and device - Google Patents

Abstract

The application discloses a transformer substation constructor autonomous positioning method and device. Wherein, the method comprises the following steps: collecting the motion data of the feet of the transformer substation constructor; respectively resolving position data of the feet based on the motion data of the feet, and determining the relative positions of the feet; carrying out inequality constraint on the relative position to obtain the corrected relative position; and calculating the pose of the transformer substation constructor based on the corrected relative position so as to autonomously position the transformer substation constructor. The technical problem that positioning of transformer substation constructors is inaccurate is solved.

Description

Transformer substation constructor autonomous positioning method and device

Technical Field

The application relates to the field of artificial intelligence, in particular to a transformer substation constructor autonomous positioning method and device.

Background

The conventional transformer substation constructor positioning needs to establish a human motion sensor model, and inertia autonomous positioning and orientation data are generated by utilizing a motion inertia autonomous positioning and orientation method so as to protect the safety of constructors. The conventional foot-bound inertial sensor pedestrian positioning system does not depend on external information, is slightly influenced by the environment, and is indispensable in navigation positioning of transformer substation construction.

However, the single inertial sensor pedestrian positioning system has the problems of navigation error divergence and the like, and the single-foot positioning method often has the problems of error accumulation and course drift during the use of a navigation inertial device, so that although the short-time positioning accuracy is higher, the accuracy requirement of long-time navigation is difficult to meet.

In view of the above problems, no effective solution has been proposed.

Disclosure of Invention

The embodiment of the application provides a transformer substation constructor autonomous positioning method and device, and the technical problem that positioning of transformer substation constructors is inaccurate is at least solved.

According to an aspect of an embodiment of the present application, there is provided a transformer substation constructor autonomous positioning method, including: collecting the motion data of both feet of the transformer substation constructor; respectively resolving position data of the feet based on the motion data of the feet, and determining the relative positions of the feet; performing inequality constraint on the relative position to obtain the corrected relative position; and calculating the pose of the transformer substation constructor based on the corrected relative position so as to autonomously position the transformer substation constructor.

According to another aspect of the embodiments of the present application, there is also provided a transformer substation constructor autonomous positioning device, including: the acquisition module is used for acquiring the motion data of the feet of the transformer substation constructor; the determining module is used for respectively calculating the position data of the feet based on the motion data of the feet and determining the relative positions of the feet; the constraint module is used for carrying out inequality constraint on the relative position to obtain the corrected relative position; and the positioning module is used for resolving the pose of the transformer substation constructor based on the corrected relative position so as to autonomously position the transformer substation constructor.

In the embodiment of the application, the inequality constraint condition is constructed according to the maximum step length of the pedestrian, the calculated position data is brought into the constraint condition, when the relative position between the two feet does not meet the constraint condition, the relative position between the two feet is constrained, the technical problem that the positioning of the transformer substation constructors is inaccurate is solved, and the technical effect of accurately positioning the constructors is achieved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 is a flowchart of a method for autonomously positioning a transformer substation constructor according to an embodiment of the present application;

FIG. 2 is a flow chart of another method for autonomous substation builder location according to an embodiment of the present application;

FIG. 3 is a schematic gait diagram according to an embodiment of the application;

FIG. 4 is a flow chart of yet another method for autonomous substation builder location according to an embodiment of the present application;

FIG. 5 is a schematic structural diagram of yet another substation builder autonomous positioning device according to an embodiment of the present application;

fig. 6 is a schematic diagram of a transformer substation constructor wearing a navigation shoe according to an embodiment of the application.

Detailed Description

In order to make the technical solutions of the present application better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only some embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

According to the embodiment of the application, a transformer substation constructor autonomous positioning method is provided, as shown in fig. 1, the method comprises the following steps:

step S102, collecting motion data of both feet of the transformer substation constructor;

and step S104, respectively calculating the position data of the feet based on the motion data of the feet, and determining the relative positions of the feet.

For example, based on the motion data of the feet, posture calculation is respectively carried out to obtain posture data of the feet; judging the motion states of the feet by adopting a zero-speed detection method based on the posture data of the feet; determining a relative position between the feet based on the state of motion of the feet.

When the zero-speed detection method is adopted to judge the motion state, the gait cycle can be separated by adopting the zero-speed detection method based on the motion data of the double feet; and then, based on the length of the zero-speed interval, each separated gait cycle is restrained, and the interference of misjudgment on the gait in each gait cycle is filtered through the pseudo zero-speed interval so as to judge the motion state of the feet.

In one example, determining the relative position between the feet may first estimate the length of travel in each gait cycle based on the motion state of the feet using the correlation of the stride length in that gait cycle to the acceleration in the vertical direction. Here, the vertical direction refers to a direction orthogonal to the stepping direction, i.e., a human body standing direction. Then, based on the length of travel, a relative position between the feet is determined. The stepping length is a spatial relative distance calculated by an inertia device when the feet land simultaneously, and the advancing length refers to an estimated actual step length.

And S106, carrying out inequality constraint on the relative position to obtain the corrected relative position.

First, constraints (also called constraint models) are constructed.

Acquiring a state vector and a state vector of an inertial navigation system through the inertial navigation system respectively arranged on the two feet; and determining a state parameter coefficient matrix of the inertial navigation system based on the state vector and the state vector of the inertial navigation system. For example, based on the state vector and the state vector of the inertial navigation system, determining a joint state vector and an attitude error vector of the biped at the current moment; determining a state parameter coefficient matrix of the inertial navigation system based on the joint state vector and the attitude error vector.

Then, based on the state parameter coefficient matrix, determining a constraint condition equation for constraining the relative position; and converting the optimization problem of the constraint condition equation and the objective function into a function extremum value by utilizing a Lagrange multiplier method so as to determine a circle with the radius r as a preset constraint condition.

And after the constraint condition is constructed, judging whether the relative position meets the preset constraint condition. And if not, carrying out inequality constraint on the relative position to obtain the corrected relative position. If yes, directly carrying out the next operation.

And S108, resolving the pose of the transformer substation constructor based on the corrected relative position so as to autonomously position the transformer substation constructor.

Obtaining acceleration data and angular velocity data of an inertial navigation system based on the corrected relative position; obtaining pose data in an inertial navigation system based on the acceleration data and the angular velocity data; and compensating the pose data in the inertial navigation system to obtain the pose of the transformer substation constructor.

For example, an extended kalman filter is triggered through a zero-speed detection algorithm, and the error of the state quantity of the inertial navigation system is estimated by using the extended kalman filter; and selecting components corresponding to the speed and the position in the error of the state quantity of the inertial navigation system, and compensating the speed and the position in the pose data in the navigation system to obtain the pose of the transformer substation constructor.

In one example, after compensating for velocity and position in pose data in the inertial navigation system, the method further comprises: estimating an attitude error of the inertial navigation system by utilizing the extended Kalman filtering; the estimated attitude error is used to correct the direction cosine matrix from the transform for the coordinate system.

The embodiment of the application provides a self-adaptive zero-speed detection method for positioning, so that the positioning is more accurate. In addition, from the perspective of improving positioning safety, an inequality constraint track fusion method of the biped gait self-adaptive fixed connection inertial device is provided, the interval of zero-speed correction is shortened, the observed quantity is increased, the biped performs autonomous positioning respectively, and inequality constraint is constructed through physical constraint during walking, so that the positioning precision is improved.

Example 2

According to the embodiment of the application, the method for automatically positioning the transformer substation constructors is provided. In the embodiment, firstly, inertia calculation is performed through original acceleration and angular velocity data; substituting the calculated position data into a constraint model, and performing ellipsoid constraint when the relative position between the two feet is greater than the step length; and thirdly, when the gait of the pedestrian is in the support interval, correcting the speed through Kalman filtering.

Fig. 2 is a flowchart of a method for autonomously positioning a transformer substation constructor according to an embodiment of the present application, and as shown in fig. 2, the method includes:

step S202, self-gait statistic analysis.

The motion state of the foot of the pedestrian is called gait, and each gait cycle can be divided into 4 stages, namely a touchdown stage, a starting stage, a suspension stage and a drop-foot stage. As shown in fig. 3, the duration of these four phases typically accounts for 24.8%,20.5%,38.0% and 16.7% of the entire gait cycle, respectively.

A touchdown stage: this phase is the stance phase of the pedestrian, with the feet bearing the entire body weight. During this time the pedestrian's foot position and stance remains unchanged and the velocity is theoretically zero.

A starting stage: the stage is a stage of the foot of the pedestrian about to leave the ground, namely the whole process from heel leaving the ground to toe leaving the ground, and at the moment, the pose information of the pedestrian is changed.

A suspension stage: the stage is a stage of completely lifting off the ground by feet of the pedestrian, and most of pose changes occur in the stage in the motion process of the pedestrian.

Landing stage: the stage is the stage of the foot of the pedestrian transitioning from the suspension state to the touchdown state, namely the whole process from heel landing to toe landing.

The sampling frequency of the foot-mounted inertial sensor was set to 100Hz, and the data length = standing time × sampling frequency.

And step S204, self-adaptive step size identification.

The zero-speed detection method is a sliding window detection method with fixed window length, and the motion state of the pedestrian is judged by using data with fixed length. When the pedestrian moves rapidly or in variable speed, the zero-speed detection method cannot effectively detect the zero-speed interval of the foot of the pedestrian, and further the accuracy of a pedestrian positioning system is influenced. Separating gait cycles according to the results of the biped MIMU zero-speed detection, calculating the step length by using a nonlinear model in each cycle, and updating the step length in the biped inequality constraint model in real time so as to realize the self-adaptive change of the constraint model.

The length of the step is often changed under the influence of factors such as walking speed, step frequency, physical state of the pedestrian and the like, and is not a fixed value. Generally speaking, the law of change is that the faster the walking speed, the higher the step frequency, and the larger the step size accordingly. Separating gait cycles according to the results of the biped MIMU zero-speed detection, calculating the step length by using a nonlinear model in each cycle, and updating the step length in the biped inequality constraint model in real time so as to realize the self-adaptive change of the constraint model.

The process that the foot undergoes between landing one landing and the next is called a gait cycle. The foot-bound pedestrian inertial navigation system usually utilizes the characteristic of a zero-speed interval and adopts a ZUPT algorithm to correct the accumulated error of an inertial sensor. According to the pedestrian walking rule, under the normal walking state, the ratio of the zero-speed interval in one gait cycle is about 30-40%. Let the gait cycle be T, T ₀ The length of the zero-speed interval in the period is the following for any step in the whole walking process:

setting window filtering aiming at false detection caused by foot landing shake

The false zero speed interval of the gait detection method eliminates the interference of misjudgment on the gait detection. The step length refers to the length between the left foot and the right foot when the pedestrian takes one step, namely the distance between the heel landing points of the opposite sides, and is called as a single step, and the step length aimed at by the step length constraint method is developed on the basis of the single step.

The step length (step) estimation algorithm based on a nonlinear model Weinberg is adopted, and estimation is carried out by utilizing the correlation of the stepping length in one gait cycle and the acceleration in the vertical direction. The estimation formula is as follows:

where K is a non-linear estimation coefficient, a _max Represents the maximum value of the vertical acceleration, a, over k gait cycles _min The representation indicates the minimum value of acceleration in the vertical direction. The estimated step length is the length of the pedestrian advancing in the k gait cycle, namely the distance between the heel landing point positions on the same side, and is composed of two continuous single steps, which is called a multi-step. Analyzing the relation between the single step and the step recovery to obtain a corresponding single step calculation formula:

d is the distance difference between the two feet, and the value is properly taken according to the installation position of the MIMU sensor of the left foot and the right foot in the actual measurement process.

In step S206, inertia is calculated.

In the embodiment of the application, an inertial solution model is adopted for navigation solution. The inertia calculation model is constructed by the following steps:

(1) And (6) data acquisition.

First obtaining corrected acceleration data

And angular velocity data

(2) The attitude of the sensor is updated.

By solving the direction cosine matrix of the transformation from the carrier system to the navigation system

And (3) adopting a quaternion attitude updating algorithm to realize the rotation transformation and updating of the attitude, wherein an updating formula of the direction cosine matrix is as follows:

wherein, Δ t is the time interval of data sampling; delta omega _k To tie the angular velocity from the carrier

The formed oblique symmetrical array is formed by the following steps,

representing a directional cosine matrix, f representing a mapping function,

denotes angular velocity, I _3X3 The identity matrix is represented by the following formula:

in the inertial navigation system, a carrier system is a coordinate system of an inertial device carried on feet of a constructor, a navigation system is a reference coordinate system used for determining navigation parameters of the carrier, and a geographical coordinate system is usually selected.

(3) Position coordinates in a navigation system are acquired. In order to acquire coordinates under a navigation system, acceleration of the IMU under a carrier system is required

Acceleration of transition to navigation system

Meanwhile, the influence of the local gravity acceleration g is eliminated, and the formula is as follows:

(4) And acquiring the speed and the position under the navigation system. According to Newton's second law applicable to moving object, the acceleration under navigation system is determined

Integrating to obtain the velocity v under the navigation system _k，k-1 The velocity v is calculated _k，k-1 Integration is performed to obtain the position p under the navigation system _k，k-1 。

p _k，k-1 ＝p _k-1，k-1 +v _k，k-1 ·Δt

Wherein p is _k，k-1 The obtained position under the navigation system is shown.

(5) The solved speed and position are compensated. Triggering and expanding Kalman filtering EKF through zero-speed detection algorithm to estimate error delta x of state quantity of inertial navigation system _k Selecting a component δ v corresponding to the velocity _k And the component δ p of the sum position _k Compensation is performed, and the formula is as follows:

v _k，k ＝v _k，k-1 -δv _k

p _k，k ＝p _k，k-1 -δp _k

(6) And correcting the direction cosine matrix. Error of attitude (roll angle, pitch angle, and heading angle) estimated by Kalman filtering

Bonding of

For correcting k-direction cosine matrix

The correction formula is as follows:

wherein is delta J _k Comprises the following steps:

wherein, I _3*3 Representing an identity matrix.

And step S208, constraint of an inequality.

The two inertia devices are fixedly connected to heels of the feet respectively, and the distance between the feet is not more than a certain threshold value by researching the motion state of the feet in the walking or running process of a person. That is, when one foot is in the stance phase, the position of the other foot in motion cannot exceed a threshold, which is defined as the maximum spatial limit. In order to fuse the information of the two inertial navigation systems, a constraint model is constructed according to the maximum step length of the pedestrian, the calculated position data is brought into the constraint model, and when the relative position between the two feet exceeds the condition that the constraint is not met, the constraint is carried out.

The constraint of the biped inertial device is defined at the time t, and the state vectors of the left-foot MIMU inertial navigation system and the right-foot MIMU inertial navigation system are respectively

The state vector contains position, velocity, attitude information of the three axes, namely:

defining a biped MIMU combined state vector and an attitude error vector at the moment t:

wherein x is _t Representing the state vector at time t, def representing the definition,

representing the attitude error vector at time t,

representing the left and right foot attitude error vectors.

A state parameter coefficient matrix:

the maximum stepping length is recorded as r, and the distance difference between the left foot MIMU and the right foot MIMU on the horizontal plane is recorded as delta d. Then at any time during walking, the inequality deltad is not more than gamma must be satisfied due to the restriction of the stepping length deltad.

Δ d represents the distance between the left and right feet.

The Lagrange multiplier method is to convert the optimization problem of constraint condition equation and objective function into the problem of solving function extremum, and it uses the method:

wherein λ represents a parameter (the process of which is explained below), p _t Which represents the position information at the time t,

the error vector of the attitude is represented by,

the end result is an extremum of the function under the constraint equation. Namely:

obtaining by solution:

wherein, I ₆ Representing an identity matrix and L a state parameter coefficient matrix.

Then, to obtain the parameter λ, first note that:

from the above formula, one can obtain:

solving until lambda is more than or equal to 0:

wherein:

the prediction covariance equation of the left and right foot postures can be obtained by the following steps:

wherein the content of the first and second substances,

the position vector representing the left hand inertial navigation,

indicating that the right inertial navigation is a position vector,

representing the subsystem range error vector, gamma representing a process parameter,

representing the left foot attitude error vector,

representing the right foot attitude error vector.

And step S210, pose resolving.

Obtaining acceleration data and angular velocity data of an inertial navigation system based on the corrected relative position; obtaining pose data in an inertial navigation system based on the acceleration data and the angular velocity data; and compensating the pose data in the inertial navigation system to obtain the pose of the transformer substation constructor. The specific pose calculation process is similar to the calculation in step S206, and is not described here again.

The embodiment of the application acquires IMU data of pedestrian slow, fast and variable speed movement; according to the collected walking data, dividing the data into a bottoming stage, a starting stage, a suspension stage and a foot falling stage, counting the time length of each stage, carrying out gait analysis and statistics in different motion states, and carrying out key statistics on the time length of the foot falling stage; moreover, a self-adaptive step length adjustment algorithm based on a nonlinear model is provided, and the applicability of the zero-speed correction algorithm is improved; in addition, based on zero-speed correction, according to the left-right foot state inequality constraint condition, the pedestrian track fusion algorithm is designed by fusing left-right foot track information through inequality Kalman filtering, and therefore the positioning accuracy is improved.

It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.

Through the description of the foregoing embodiments, it is clear to those skilled in the art that the method according to the foregoing embodiments may be implemented by software plus a necessary general hardware platform, and certainly may also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present application.

Example 3

According to an embodiment of the present application, there is also provided a method for autonomously positioning a transformer substation constructor, as shown in fig. 4, the method includes:

and step S402, collecting the motion state data of the feet.

And collecting the motion state data of the feet of the constructors by using an inertial sensing device.

And S404, attitude calculation and zero speed correction.

The attitude calculation is performed based on the bipedal motion state data, and the specific calculation method is as described in embodiment 2, which is not described herein again.

After the attitude is resolved, zero-speed correction is performed on the resolved attitude data.

In step S406, navigation is performed.

And carrying out navigation calculation based on the corrected attitude data.

And step S408, carrying out inequality constraint.

And carrying out inequality constraint on the data obtained by the navigation solution. The specific inequality constraint method is as described in embodiment 2, and is not described herein again.

And S410, outputting the pose.

And outputting the pose based on the data after the inequality constraint.

The method provides the constraint condition of the navigation state of the constructor under the biped motion form, constructs the biped inequality constraint through physical constraint between walking, thereby solving the problem that the position and course information is not observable, effectively improving the positioning precision of the constructor, and being suitable for the autonomous positioning of the quick motion or variable speed motion of the constructor of the transformer substation and being free from the interference of the external environment.

Example 4

According to the embodiment of the application, still provide a transformer substation constructor is from dynamic positioning device, as shown in fig. 5, include: an acquisition module 42, a determination module 44, a constraint module 46, and a location module 48.

The acquisition module 42 is used for acquiring the motion data of the feet of the transformer substation constructor;

and the determining module 44 is used for respectively calculating the position data of the feet based on the motion data of the feet and determining the relative positions of the feet.

For example, the determining module 44 performs posture calculation based on the motion data of the feet, respectively, to obtain posture data of the feet; judging the motion states of the feet by adopting a zero-speed detection method based on the posture data of the feet; determining a relative position between the feet based on the state of motion of the feet.

When the determining module 44 determines the motion state by using a zero-speed detection method, it may first separate the gait cycle by using a zero-speed detection method based on the motion data of the feet; and then, based on the length of the zero-speed interval, each separated gait cycle is constrained, and through the pseudo zero-speed interval, the interference of misjudgment on the gait in each gait cycle is filtered out, so as to judge the motion state of the feet.

The determining module 44, when determining the relative position between the feet, may first estimate the length of travel in each gait cycle based on the motion state of the feet by using the correlation between the step length and the vertical acceleration in the gait cycle; then, based on the length of travel, a relative position between the feet is determined.

And a constraint module 46, configured to perform inequality constraint on the relative position when the relative position does not meet a preset constraint condition, to obtain the corrected relative position.

Constraint module 46 first constructs constraints.

Acquiring a state vector and a state vector of an inertial navigation system through inertial devices of the inertial navigation system respectively arranged on the two feet; and determining a state parameter coefficient matrix of the inertial navigation system based on the state vector and the state vector of the inertial navigation system. Determining a joint state vector and an attitude error vector of the biped at the current moment, for example, based on a state vector and a state vector of the inertial navigation system; determining a state parameter coefficient matrix of the inertial navigation system based on the joint state vector and the attitude error vector.

Then, based on the state parameter coefficient matrix, determining a constraint condition equation for constraining the relative position; and converting the optimization problem of the constraint condition equation and the objective function into a function extremum by using a Lagrange multiplier method, and determining a circle with the radius r as the preset constraint condition.

After the constraint condition is constructed, the constraint module 46 determines whether the relative position satisfies a predetermined constraint condition. If not, inequality constraint is carried out on the relative position to obtain the corrected relative position

And the positioning module 48 is used for calculating the pose of the transformer substation constructor based on the corrected relative position so as to autonomously position the transformer substation constructor.

The positioning module 48 obtains acceleration data and angular velocity data of the inertial navigation system based on the corrected relative position; obtaining pose data in an inertial navigation system based on the acceleration data and the angular velocity data; and compensating the pose data in the inertial navigation system to obtain the pose of the transformer substation constructor.

For example, an extended kalman filter is triggered through a zero-speed detection algorithm, and the error of the state quantity of the inertial navigation system is estimated by using the extended kalman filter; and selecting components corresponding to the speed and the position in the error of the state quantity of the inertial navigation system, and compensating the speed and the position in the pose data in the navigation system to obtain the pose of the transformer substation constructor.

In one example, a correction module may be further included that estimates an attitude error of the inertial navigation system using the extended kalman filter; the estimated attitude error is used to correct a direction cosine matrix transformed from the carrier system to the navigation system.

The positioning and orienting device for the foot-worn shoes is customized by constructing a human body kinematics model, physically establishing a walking biped space relation, and setting a variable speed motion touchdown state and other various models. The ZUPT accuracy during fast and slow speed and variable speed movement is realized by calculating the step length of variable speed movement by using a nonlinear function. In order to fuse the information of the left foot and the right foot, an inequality constraint model is constructed according to the maximum step length of the pedestrian, the calculated position data is brought into the constraint model, and when the relative position between the two feet exceeds the condition that the constraint is not met, the constraint is carried out, so that the positioning accuracy is improved.

Example 5

According to the embodiment of the application, the wearable equipment is further provided and comprises the transformer substation constructor autonomous positioning device. Fig. 6 shows that the substation constructor wears the wearable device 62, and the substation constructor is autonomously positioned by the substation constructor autonomous positioning device 622 on the wearable device 62. The specific implementation process is as described above, and is not described herein again.

Example 6

The embodiment of the invention also provides a storage medium. Alternatively, in the present embodiment, the storage medium may store a program that, when executed, enables a computer to execute the method in embodiments 1 to 3 described above.

Optionally, in this embodiment, the storage medium may include, but is not limited to: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.

Optionally, the specific examples in this embodiment may refer to the examples described in embodiments 1 to 6 above, and this embodiment is not described herein again.

The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.

The integrated unit in the above embodiments, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in the above computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing one or more computer devices (which may be personal computers, servers, network devices, etc.) to execute all or part of the steps of the method according to the embodiments of the present invention.

In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and amendments can be made without departing from the principle of the present invention, and these modifications and amendments should also be considered as the protection scope of the present invention.

Claims (10)

1. A transformer substation constructor autonomous positioning method is characterized by comprising the following steps:

collecting the motion data of the feet of the transformer substation constructor;

respectively resolving position data of the feet based on the motion data of the feet, and determining the relative positions of the feet;

carrying out inequality constraint on the relative position to obtain the corrected relative position;

and calculating the pose of the transformer substation constructor based on the corrected relative position so as to autonomously position the transformer substation constructor.

2. The method of claim 1, wherein separately resolving positional data of the feet based on the motion data of the feet and determining the relative position between the feet comprises:

respectively performing attitude calculation based on the motion data of the feet to obtain attitude data of the feet;

judging the motion states of the feet by adopting a zero-speed detection method based on the posture data of the feet;

determining a relative position between the feet based on the state of motion of the feet.

3. The method of claim 2, wherein determining the motion status of the feet by using a zero-velocity detection method comprises:

separating the posture data of the feet by adopting a zero-speed detection method to obtain a plurality of gait cycles;

and based on the length of the zero-speed interval, each gait cycle is constrained, and through a pseudo zero-speed interval, the interference of misjudgment on the gait in each gait cycle is filtered out so as to judge the motion state of the feet.

4. The method of claim 3, wherein determining the relative position between the feet based on the state of motion of the feet comprises:

estimating a length of travel in each of the gait cycles using the acceleration in that gait cycle based on the state of motion of the feet;

based on the length of travel, a relative position between the feet is determined.

5. The method of claim 1, wherein prior to inequality constraining the relative position, the method further comprises:

acquiring a state vector and a state vector of an inertial navigation system, and determining a state parameter coefficient matrix of the inertial navigation system based on the state vector and the state vector of the inertial navigation system;

determining a constraint condition equation for constraining the relative position based on the state parameter coefficient matrix;

and solving a function extremum value by utilizing a Lagrange multiplier method based on the constraint condition equation so as to determine the constraint condition of the inequality constraint.

6. The method of claim 5, wherein determining the state parameter coefficient matrix for the inertial navigation system based on the state vector and the state vector of the inertial navigation system comprises:

determining a joint state vector and an attitude error vector of the double feet at the current moment based on the state vector and the state vector of the inertial navigation system;

determining a state parameter coefficient matrix of the inertial navigation system based on the joint state vector and the attitude error vector.

7. The method of claim 1, wherein resolving the pose of the substation builder based on the revised relative position comprises:

obtaining acceleration data and angular velocity data of the transformer substation constructor based on the corrected relative position;

obtaining pose data of the transformer substation constructors based on the acceleration data and the angular velocity data;

and compensating the pose data of the transformer substation constructor to obtain the pose of the transformer substation constructor.

8. The method of claim 7, wherein compensating pose data of the substation constructor to obtain the pose of the substation constructor comprises:

triggering extended Kalman filtering through a zero-speed detection algorithm, and estimating the error of the state quantity of the inertial navigation system by utilizing the extended Kalman filtering;

and selecting components corresponding to the speed and the position in the error of the state quantity of the inertial navigation system, and compensating the speed and the position in the position and posture data of the transformer substation constructor to obtain the position and posture of the transformer substation constructor.

9. The utility model provides a transformer substation constructor is positioner independently which characterized in that includes:

the acquisition module is used for acquiring the motion data of the feet of the transformer substation constructor;

the determining module is used for respectively calculating the position data of the feet based on the motion data of the feet and determining the relative positions of the feet;

the constraint module is used for carrying out inequality constraint on the relative position to obtain the corrected relative position;

and the positioning module is used for resolving the pose of the transformer substation constructor based on the corrected relative position so as to autonomously position the transformer substation constructor.

10. A computer-readable storage medium, on which a program is stored, which, when executed, causes a computer to carry out the method according to any one of claims 1 to 8.

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