CN109910873B - Sliding mode-based automatic parking torque control method for unmanned vehicle - Google Patents
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Abstract
The invention belongs to the technical field of automatic parking of unmanned vehicles, in particular to an automatic parking torque control method of an unmanned vehicle based on a sliding mode, which solves the control problems of visual blind areas and the like existing in the traditional unmanned vehicle parking technical means which excessively depends on a visual sensor. The method of the invention is that the system modeling is carried out, the torque controller design is carried out by utilizing the global feedback information, firstly, the system modeling is carried out, the description of the target parking area and the surrounding obstacles is realized, and then, the torque controller design is carried out according to the model information, thereby greatly reducing the serious dependence on the automatic parking visual sensor. Therefore, parking errors caused by visual blind areas are avoided, the parking accuracy is improved through the method, the deep revolution of an automatic parking technology is promoted, the manufacturing and development industries of new-generation information technologies and high-end equipment are further promoted, and the method has good application value.
Description
Technical Field
The invention belongs to the technical field of automatic parking of unmanned vehicles, and relates to a torque control method based on the dynamics and kinematics characteristics of the unmanned vehicles, in particular to an automatic parking torque control method of the unmanned vehicles based on a sliding mode.
Background
At present, with the rapid advance of scientific technology, sensors such as vision sensors, laser range finders, balance gyroscopes, ultrasonic radars and photoelectric codes, and positioning control technologies such as GPS are becoming mature and perfect. Particularly, the control technologies are deeply integrated with control theories such as current unmanned driving and the like, and the unmanned control technologies (including the automatic parking technology) become one of the hot problems of the current automatic control theories and scientific practical application. However, the existing unmanned control technology mainly relies on the traditional trajectory tracking control strategy, and the automatic parking control technology often relies on the vision sensor too much, so that once a vision blind area occurs in the driving process of a vehicle or the vision sensor fails, irrecoverable loss is caused, and the application value of the vehicle is seriously influenced. Therefore, a new parking control technical means is needed to be invented to overcome the defects of the traditional parking control technical means.
Disclosure of Invention
The invention aims to solve the control problems of visual blind areas and the like existing in the traditional unmanned vehicle parking technical means which excessively depend on a visual sensor, and provides an unmanned vehicle automatic parking torque control method based on a sliding mode.
The technical scheme for solving the technical problem is as follows: an automatic parking torque control method for an unmanned vehicle based on a sliding mode comprises the following steps:
firstly, recognizing, positioning and ranging the unmanned vehicle, the target parking area and the obstacle in the target parking area through a GPS to obtain the position information x of the unmanned vehicle and the position information u of the obstacle0Reference point x of target parking area under ith constraint condition0i;
Modeling according to the position information of the unmanned vehicle, the obstacle and the target parking area obtained in the step I and the shape of the target parking area through mathematical software, constructing an area potential function P for the target parking area, and constructing an obstacle avoidance potential function U for the identified obstacle, wherein the method specifically comprises the following steps:
wherein k isiIs the gain of the target parking area under the adjustable ith constraint condition; n is the number of target parking area constraints; f. ofΔi(Δxi0 is a function with a continuous smooth scalar, fΔi(Δxi) Indicates the target parking area under the ith constraint condition, Δ xi=x-x0iReference to a target parking area under an ith constraintPoint x0iThe central point of the target parking area under the ith constraint condition is obtained; i x-u0The distance between the unmanned vehicle and the obstacle is represented by | |, R is the radius of a maximum sensing area with the center of the unmanned vehicle as the center of a circle, R is the radius of the minimum safe distance between the center of the unmanned vehicle and the obstacle, and R and R are values set manually according to actual requirements;
thirdly, designing a torque controller for controlling the unmanned vehicle to enter a target parking area according to the area potential function P and the obstacle avoidance potential function U established in the second step, wherein the torque controller specifically comprises the following steps:
wherein q is a vector in a two-dimensional plane formed by the linear velocity and the angular velocity; theta is a course angle of the unmanned vehicle; k is an adjustable gain matrix, K is set according to actual requirements,in order to estimate the parameters of the system,adaptive rate by system parametersDerived, inter alia, the adaptation rate of the system parameterss is a sliding mode variable, and s is q-qr,Y is a regression matrix known to be associated with unmanned vehicle dynamics, the specific expression of Y is different for different types of dynamic structures,are known as input transformation matrices, corresponding to different types of dynamic structuresThe specific expression of (a) is different,is the gradient of the target parking area,is the barrier gradient; the dynamics and power model of the unmanned vehicle is as follows:
Fourthly, gain k of the target parking area under the ith constraint condition is adjustediAnd the gain matrix K is used for carrying out stability analysis on the automatic parking torque controller of the unmanned vehicle.
The method comprises the steps that firstly, the unmanned vehicle, the target parking area and the barrier in the target parking area are positioned through the GPS, and the position information x of the unmanned vehicle and the position information u of the barrier are obtained0Reference point x of target parking area under ith constraint condition0iIdentifying and analyzing a target parking area through a GPS and measuring the distance between the unmanned vehicle and the obstacle; secondly, modeling the identified obstacles and the target parking area by using mathematical software, wherein the function principle of the area potential function P is that the potential energy in the target parking area is the lowest, the potential energy outside the target parking area is higher, and the unmanned vehicle can move from high potential energy to low potential energy along the gradient direction and finally enters the target parking area by artificially constructing a gravitational field near the target parking areaA vehicle area. The action principle of the obstacle avoidance potential function U is that potential energy near the obstacle is the highest, the potential energy outside the obstacle is lower, a repulsive force field near the obstacle is artificially constructed, and once the unmanned vehicle enters the repulsive force field, the unmanned vehicle can move from high potential energy to low potential energy along the gradient direction and finally is separated from the obstacle environment. In the obstacle avoidance potential function U, R is the radius of the maximum sensing area with the center of the unmanned vehicle as the center of a circle, R is the radius of the minimum safe distance between the center of the unmanned vehicle and the obstacle, if the distance between the obstacle and the unmanned vehicle is greater than R, the unmanned vehicle cannot sense the obstacle, if the distance between the unmanned vehicle and the obstacle is between R and R, the unmanned vehicle can sense the obstacle, and therefore the step of adjusting the torque value of the unmanned vehicle to change the course obstacle avoidance is carried out, and R and R are values set manually according to actual requirements, so that the method is more convenient and humanized to use, can be changed in different ways according to the conditions of different target parking areas, and has higher practicability. The action principle of the torque controller in the third step is as follows: in fact, the dynamic behavior of the unmanned vehicle is not only related to the kinematic relative position of the unmanned vehicle, but also to the structural form, mass distribution, position of the actuators, transmission, etc. of the unmanned vehicle. The dynamic performance of the unmanned vehicle is described by a dynamic equation, and the dynamics is to study the dynamic relation between the motion and the moment of the unmanned vehicle by considering the factors. By a modern control theory method and applying a stability analysis theory, a closed-loop control system formed by the controller is gradually stable, namely, unmanned vehicles can finally enter a target parking area to be invariable and concentrated, and the gradient of the target parking area is gradually increasedThe automatic parking of the unmanned vehicle can be realized. And step three, the direct torque controller is adopted, namely the invention adjusts the rotation speed ratio of two wheels of the vehicle according to the torque controller, controls the steering of the wheels through the rotation speed ratio and further controls the direction of the unmanned vehicle to realize automatic obstacle avoidance and parking. The distance between the unmanned vehicle and the obstacle in the target parking area can be ensured through the control of the step threeGreater than r. The dynamics and dynamics model of the unmanned vehicle in step (iii) is the prior art and is well known to those skilled in the art, and will not be described in detail in the present invention. In the fourth step, the gain k of the target parking area under the ith constraint condition of the area potential function P needs to be continuously adjustediAnd a gain matrix K of the torque controller tau ensures that the stability of the whole system can be ensured by ensuring the stability of the region potential function P and the torque controller tau. The method of the invention is that the system modeling is carried out, the torque controller design is carried out by utilizing the global feedback information, firstly, the system modeling is carried out, the description of the target parking area and the surrounding obstacles is realized, and then, the torque controller design is carried out according to the model information, thereby greatly reducing the serious dependence on the automatic parking visual sensor.
Preferably, after the moment controller in the step (iii) regulates that the unmanned vehicle enters the target parking area, the attitude of the unmanned vehicle in the target parking area is regulated by the attitude regulator, and the attitude controller is: ω ═ α tanh (θ - θ)d) Alpha is an attitude adjustment rate adjustable parameter, thetadIs a desired attitude, θ, of the unmanned vehicle in the target parking areadIs a value set manually according to actual requirements. The action principle of the attitude controller is that a modern control theory method and a stability analysis theory are applied, a closed-loop control system formed by the attitude controller is also gradually stable, and theta-thetadAnd (5) adjusting any posture when the posture is 0.
Preferably, the stability analysis in the step (iv) adopts Lyapunov theory and Barbalt's theorem. In the stability analysis process, the Lyapunov theory and the Barbalt theorem are used simultaneously, and the two theories meet the requirement of the invention on the stability analysis of the whole system.
Preferably, the shape of the target parking area can be recognized through the visual sensor, the distance between the unmanned vehicle and the obstacle of the target parking area can be measured through the distance measuring device, and the required information can be obtained conveniently and directly by directly using the visual sensor and the distance measuring device.
Compared with the prior art, the invention has the beneficial effects that: the method does not need a real-time vision processing technology, greatly reduces the serious dependence on the automatic parking vision sensor, avoids parking errors caused by the vision blind area, is further suitable for automatic parking under the conditions of the vision blind area and the failure of the vision sensor, improves the parking accuracy through the method, enables the automatic parking technology to obtain better adaptability and integrity, promotes the deep revolution of the automatic parking technology, further promotes the manufacturing and developing industries of new-generation information technology and high-end equipment, and has good application value.
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Fig. 1 is a schematic diagram of automated parking according to the present invention.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the technical solutions of the present invention will be described in detail below. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the examples given herein without any inventive step, are within the scope of the present invention.
Referring to fig. 1, a method for controlling an automatic parking torque of an unmanned vehicle based on a sliding mode according to the present invention will now be described.
An automatic parking torque control method for an unmanned vehicle based on a sliding mode comprises the following steps:
firstly, recognizing, positioning and ranging the unmanned vehicle, the target parking area and the obstacle in the target parking area through a GPS to obtain the position information x of the unmanned vehicle and the position information u of the obstacle0Reference point x of target parking area under ith constraint condition0i;
Modeling according to the position information of the unmanned vehicle, the obstacle and the target parking area obtained in the step I and the shape of the target parking area through mathematical software, constructing an area potential function P for the target parking area, and constructing an obstacle avoidance potential function U for the identified obstacle, wherein the method specifically comprises the following steps:
wherein k isiIs the gain of the target parking area under the adjustable ith constraint condition; n is the number of the constraint conditions of the target parking area, the target parking area is not in a regular shape generally, but is formed by the intersection of a plurality of areas, and as can be seen by a potential function P, the target parking area is the intersection of n areas, so n is the number of the constraint conditions of the target parking area; f. ofΔi(Δxi) Is a function with a continuous smooth scalar fΔi(Δxi) Indicates the target parking area under the ith constraint condition, Δ xi=x-x0iReference point x of target parking area under ith constraint condition0iThe central point of the target parking area under the ith constraint condition is obtained; i x-u0The distance between the unmanned vehicle and the obstacle is represented by | |, R is the radius of a maximum sensing area with the center of the unmanned vehicle as the center of a circle, R is the radius of the minimum safe distance between the center of the unmanned vehicle and the obstacle, and R and R are values set manually according to actual requirements; for example, if the target parking area is simply a circular area, then n is 1, i.e., the number of constraints for the target parking area is 1, and this timeΔx=x-x0Where x0 represents a reference point of the target parking area under a single constraint condition, that is, the center of a circular area, and if the radius of the circular area is 1, f isΔ(Δx)=Δx2-1<0,fΔ(Δ x) represents a circular area with a radius of 1 and a center of x 0;
thirdly, designing a torque controller for controlling the unmanned vehicle to enter a target parking area according to the area potential function P and the obstacle avoidance potential function U established in the second step, wherein the torque controller specifically comprises the following steps:
wherein q is a vector in a two-dimensional plane formed by the linear velocity and the angular velocity; theta is a course angle of the unmanned vehicle; k is an adjustable gain matrix, K is set according to actual requirements,in order to estimate the parameters of the system,adaptive rate by system parametersDerived, inter alia, the adaptation rate of the system parameterss is a sliding mode variable, and s is q-qr,Y is a regression matrix known to be associated with unmanned vehicle dynamics, the specific expression of Y is different for different types of dynamic structures,are known as input transformation matrices, corresponding to different types of dynamic structuresThe specific expression of (a) is different,is the gradient of the target parking area,is the barrier gradient; whereinThe dynamics and power model of the unmanned vehicle is as follows:
Fourthly, gain k of the target parking area under the ith constraint condition is adjustediAnd the gain matrix K is used for carrying out stability analysis on the automatic parking torque controller of the unmanned vehicle.
The method comprises the steps that firstly, the unmanned vehicle, the target parking area and the barrier in the target parking area are positioned through the GPS, and the position information x of the unmanned vehicle and the position information u of the barrier are obtained0Reference point x of target parking area under ith constraint condition0iIdentifying and analyzing a target parking area through a GPS and measuring the distance between the unmanned vehicle and the obstacle; secondly, modeling the identified obstacles and the target parking area by using mathematical software, wherein the function principle of the area potential function P is that the potential energy in the target parking area is the lowest, the potential energy outside the target parking area is higher, and the unmanned vehicle can move from high potential energy to low potential energy along the gradient direction and finally enters the target parking area by artificially constructing a gravitational field near the target parking area. The action principle of the obstacle avoidance potential function U is that potential energy near the obstacle is the highest, the potential energy outside the obstacle is lower, a repulsive force field near the obstacle is artificially constructed, and once the unmanned vehicle enters the repulsive force field, the unmanned vehicle can move from high potential energy to low potential energy along the gradient direction and finally is separated from the obstacle environment. In the obstacle avoidance function U, R is the radius of the maximum sensing area with the center of the unmanned vehicle as the center of circle, and R is the radius of the minimum safe distance between the center of the unmanned vehicle and the obstacleIf the distance between the obstacle and the unmanned vehicle is larger than R, the unmanned vehicle cannot sense the obstacle, and if the distance between the unmanned vehicle and the obstacle is between R and R, the unmanned vehicle can sense the obstacle, so that the step of adjusting the torque value by the unmanned vehicle to change the course to avoid the obstacle is carried out, and R and R are values set manually according to actual requirements, so that the method is more convenient and more humanized to use, can make different changes according to the conditions of different target parking areas, and has higher practicability. The action principle of the torque controller in the third step is as follows: in fact, the dynamic behavior of the unmanned vehicle is not only related to the kinematic relative position of the unmanned vehicle, but also to the structural form, mass distribution, position of the actuators, transmission, etc. of the unmanned vehicle. The dynamic performance of the unmanned vehicle is described by a dynamic equation, and the dynamics is to study the dynamic relation between the motion and the moment of the unmanned vehicle by considering the factors. By a modern control theory method and applying a stability analysis theory, a closed-loop control system formed by the controller is gradually stable, namely, unmanned vehicles can finally enter a target parking area to be invariable and concentrated, and the gradient of the target parking area is gradually increasedThe automatic parking of the unmanned vehicle can be realized. And step three, the direct torque controller is adopted, namely the invention adjusts the rotation speed ratio of two wheels of the vehicle according to the torque controller, controls the steering of the wheels through the rotation speed ratio and further controls the direction of the unmanned vehicle to realize automatic obstacle avoidance and parking. And c, controlling to ensure that the distance between the unmanned vehicle and the obstacle in the target parking area is greater than r. The dynamics and dynamics model of the unmanned vehicle in step (iii) is the prior art and is well known to those skilled in the art, and will not be described in detail in the present invention. In the fourth step, the gain k of the target parking area under the ith constraint condition of the area potential function P needs to be continuously adjustediAnd a gain matrix K of the torque controller tau ensures that the stability of the whole system can be ensured by ensuring the stability of the region potential function P and the torque controller tau. The method of the invention utilizes the whole situation through system modelingThe torque controller design based on the feedback information is characterized in that firstly, system modeling is carried out, description of a target parking area and surrounding obstacles is realized, and then the torque controller is designed according to model information, so that the serious dependence on an automatic parking visual sensor is greatly reduced.
Further, as a specific embodiment of the sliding-mode-based unmanned vehicle automatic parking torque control method of the present invention, after the torque controller in step (iii) adjusts that the unmanned vehicle enters the target parking area, the attitude of the unmanned vehicle in the target parking area is adjusted by the attitude adjuster, and the attitude controller is: omega is alpha tanh (theta-theta d), alpha is an adjustable parameter of the attitude adjustment rate, and theta isdIs a desired attitude, θ, of the unmanned vehicle in the target parking areadIs a value set manually according to actual requirements. The action principle of the attitude controller is that a modern control theory method and a stability analysis theory are applied, a closed-loop control system formed by the attitude controller is also gradually stable, and theta-thetadAnd (5) adjusting any posture when the posture is 0.
Further, as a specific implementation manner of the sliding-mode-based unmanned vehicle automatic parking torque control method, the stability analysis in the step (iv) adopts the Lyapunov theory and the barbalt theorem. In the stability analysis process, the Lyapunov theory and the Barbalt theorem are used simultaneously, and the two theories meet the requirement of the invention on the stability analysis of the whole system.
Further, as a specific implementation manner of the sliding-mode-based unmanned vehicle automatic parking torque control method, the shape of the target parking area can be identified through a visual sensor, the distance between the unmanned vehicle and an obstacle in the target parking area can be measured through a distance measuring device, and the required information can be obtained more conveniently and directly by directly using the visual sensor and the distance measuring device.
Further, as a specific embodiment of the sliding mode-based unmanned vehicle automatic parking torque control method, the vision sensor and the infrared distance sensor are mounted on the unmanned vehicle. The shape of the target parking area and the distance between the unmanned vehicle and the obstacle can be obtained more conveniently by installing the vision sensor and the infrared distance sensor on the unmanned vehicle.
Further, as a specific implementation manner of the sliding-mode-based unmanned vehicle automatic parking torque control method, mathematical software in the step two is Matlab, Mathematics or Python. The method mainly depends on mathematical software to carry out simulation, and the mathematical software can meet the requirements.
Further, in a specific embodiment, the method of the present invention is numerically simulated by using Matlab, so that automated parking of the unmanned vehicle can be realized, and specifically, an ode45 algorithm in Matlab is adopted, and an initial value is randomly selected, so that numerical verification is performed on a model and a torque controller of the entire system.
The embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (8)
1. An automatic parking torque control method for an unmanned vehicle based on a sliding mode is characterized by comprising the following steps:
firstly, recognizing, positioning and ranging the unmanned vehicle, the target parking area and the obstacle in the target parking area through a GPS to obtain the position information x of the unmanned vehicle and the position information u of the obstacle0Reference point x of target parking area under ith constraint condition0i;
Modeling according to the position information of the unmanned vehicle, the obstacle and the target parking area obtained in the step I and the shape of the target parking area through mathematical software, constructing an area potential function P for the target parking area, and constructing an obstacle avoidance potential function U for the identified obstacle, wherein the method specifically comprises the following steps:
wherein k isiIs the gain of the target parking area under the adjustable ith constraint condition; n is the number of target parking area constraints; f. ofΔi(Δxi) Is a function with a continuous smooth scalar fΔi(Δxi) Indicates the target parking area under the ith constraint condition, Δ xi=x-x0iReference point x of target parking area under ith constraint condition0iThe central point of the target parking area under the ith constraint condition is obtained; i x-u0The distance between the unmanned vehicle and the obstacle is represented by | |, R is the radius of a maximum sensing area with the center of the unmanned vehicle as the center of a circle, R is the radius of the minimum safe distance between the center of the unmanned vehicle and the obstacle, and R and R are values set manually according to actual requirements;
thirdly, designing a torque controller for controlling the unmanned vehicle to enter a target parking area according to the area potential function P and the obstacle avoidance potential function U established in the second step, wherein the torque controller specifically comprises the following steps:
wherein q is a vector in a two-dimensional plane formed by the linear velocity and the angular velocity; theta is a course angle of the unmanned vehicle; k is an adjustable gain matrix, K is set according to actual requirements,in order to estimate the parameters of the system,adaptive rate by system parametersDerived, inter alia, the adaptation rate of the system parameterss is a sliding mode variable, and s is q-qr,Y is a regression matrix known to be associated with unmanned vehicle dynamics, the specific expression of Y is different for different types of dynamic structures,are known as input transformation matrices, corresponding to different types of dynamic structuresThe specific expression of (a) is different,is the gradient of the target parking area,is the barrier gradient; the dynamics and power model of the unmanned vehicle is as follows:
Fourthly, adjusting the target poise under the ith constraint conditionGain k of the vehicle zoneiAnd the gain matrix K is used for carrying out stability analysis on the automatic parking torque controller of the unmanned vehicle.
2. The sliding-mode-based unmanned vehicle automatic parking torque control method according to claim 1, characterized in that: after the moment controller in the third step regulates the unmanned vehicle to enter the target parking area, the posture of the unmanned vehicle in the target parking area is regulated through the posture regulator, and the posture controller is as follows: ω ═ α tanh (θ - θ)d) Alpha is an attitude adjustment rate adjustable parameter, thetadIs a desired attitude, θ, of the unmanned vehicle in the target parking areadIs a value set manually according to actual requirements.
3. The sliding-mode-based automatic parking torque control method for the unmanned vehicle, according to claim 1 or 2, is characterized in that: and (4) adopting Lyapunov theory and Barbalt theorem for stability analysis in the step (IV).
4. The sliding-mode-based unmanned vehicle automatic parking torque control method according to claim 3, characterized in that: and the step I can also identify the shape of the target parking area through a visual sensor.
5. The sliding-mode-based unmanned vehicle automatic parking torque control method according to claim 4, characterized in that: and the step I can also measure the distance between the unmanned vehicle and the obstacle in the target parking area through the distance measuring device.
6. The sliding-mode-based unmanned vehicle automatic parking torque control method according to claim 5, characterized in that: the distance measuring device is an infrared distance sensor.
7. The sliding-mode-based unmanned vehicle automatic parking torque control method according to claim 6, characterized in that: the vision sensor and the infrared distance sensor are installed on the unmanned vehicle.
8. The sliding-mode-based unmanned vehicle automatic parking torque control method according to claim 7, characterized in that: and the mathematical software in the step two is Matlab, Mathemetics or Python.
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Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1506862A (en) * | 2002-12-11 | 2004-06-23 | 中国科学院自动化研究所 | Autonomous mobile robot platform based on multi-DSP parallel processing |
CN105955268A (en) * | 2016-05-12 | 2016-09-21 | 哈尔滨工程大学 | Local obstacle avoidance considering UUV moving object sliding mode tracking control method |
CN107544500A (en) * | 2017-09-18 | 2018-01-05 | 哈尔滨工程大学 | A kind of unmanned boat berthing action trail planing method for considering constraint |
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Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1506862A (en) * | 2002-12-11 | 2004-06-23 | 中国科学院自动化研究所 | Autonomous mobile robot platform based on multi-DSP parallel processing |
CN105955268A (en) * | 2016-05-12 | 2016-09-21 | 哈尔滨工程大学 | Local obstacle avoidance considering UUV moving object sliding mode tracking control method |
CN107544500A (en) * | 2017-09-18 | 2018-01-05 | 哈尔滨工程大学 | A kind of unmanned boat berthing action trail planing method for considering constraint |
Non-Patent Citations (1)
Title |
---|
智能车辆局部避障路径规划及横向运动控制研究;陈东;《中国优秀硕士学位论文全文数据库(电子期刊)工程科技II辑》;20170215;C035-291 * |
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