WO2018223776A1 - Procédé, appareil et système de commande destinés à un robot, et support d'informations lisible par ordinateur - Google Patents

Procédé, appareil et système de commande destinés à un robot, et support d'informations lisible par ordinateur Download PDF

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Publication number
WO2018223776A1
WO2018223776A1 PCT/CN2018/083351 CN2018083351W WO2018223776A1 WO 2018223776 A1 WO2018223776 A1 WO 2018223776A1 CN 2018083351 W CN2018083351 W CN 2018083351W WO 2018223776 A1 WO2018223776 A1 WO 2018223776A1
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Prior art keywords
deviation
domain
robot
correction amount
motion correction
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PCT/CN2018/083351
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English (en)
Chinese (zh)
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霍峰
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北京京东尚科信息技术有限公司
北京京东世纪贸易有限公司
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Publication of WO2018223776A1 publication Critical patent/WO2018223776A1/fr

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions

Definitions

  • the present disclosure relates to the field of control technologies, and in particular, to a control method of a robot, a control device of the robot, a control system of the robot, and a computer readable storage medium.
  • the related technology generally controls each driving wheel of the robot according to the calculation result of the path planning method, thereby achieving the purpose of correcting the motion track.
  • the inventors of the present disclosure have found that the above related art has the following problems: the traditional path planning method needs to perform a complex solution according to the current position and speed of the robot to pre-plan the correcting path, resulting in a slow control response, and for the environment, the road surface, and the like.
  • the adaptive ability of the influence caused by external factors is poor.
  • the present disclosure proposes a control technology scheme for a robot, which can improve the adaptive ability and response speed of the robot motion control.
  • a method of controlling a robot comprising: blurring the traveling angle deviation and the position deviation in a range of a traveling angle deviation and a position deviation of a current moment of the robot, respectively Obtaining a fuzzy value of the deviation of the traveling angle and a fuzzy value of the positional deviation; performing fuzzy inference on the fuzzy value of the traveling angle deviation and the fuzzy value of the positional deviation to obtain a fuzzy value of the motion correction amount of the robot; In the domain of the motion correction amount, the blur correction value of the motion correction amount is subjected to deblurring processing to obtain the motion correction amount; wherein the control method further includes the travel angle deviation and the position according to the current time Deviation, real-time adjustment of the domain of the travel angle deviation and the domain of the positional deviation.
  • the domain of the motion correction amount is adjusted in real time according to the traveling speed of the current moment of the robot.
  • the domain of the deviation of the angle of travel of the previous moment and the domain of the positional deviation are [-P, P] and [-E, E], respectively, and the deviation of the traveling angle and the positional deviation of the current time are ⁇ and y, respectively.
  • a first domain scaling factor ⁇ ; a domain of the deviation of the traveling angle at the current time and a domain of the positional deviation Adjusted to [- ⁇ P, ⁇ P] and [- ⁇ E, ⁇ E], respectively.
  • the first domain scaling factor ⁇ max ⁇ (
  • the constant between ⁇ is a constant between [0.08, 0.12].
  • determining a second universe scaling factor ⁇ according to a traveling speed v of the current moment of the robot wherein ⁇ determined in a case where v is greater than or equal to a threshold is greater than ⁇ determined in a case where v is less than a threshold;
  • the domain of the motion correction amount at the current time is adjusted from the field of motion correction amount [-T, T] of the previous moment to [- ⁇ T, ⁇ T].
  • the second domain scaling factor :
  • ⁇ t is a constant between (0, 1) and v t is a preset crawling speed.
  • the predetermined creep speed v t is a constant between [32, 48] mm/s.
  • the blur value is at least one of a large deviation in the positive direction, a deviation in the positive direction, a small deviation in the positive direction, no deviation, a large deviation in the reverse direction, a deviation in the reverse direction, or a small deviation in the reverse direction.
  • a control apparatus for a robot comprising: a blurring processing component, for the deviation of the traveling angle and the position of the traveling angle deviation and the position deviation of the current moment of the robot respectively Obscuring the positional deviation to obtain a fuzzy value of the deviation of the traveling angle and a fuzzy value of the positional deviation;
  • the fuzzy inference component is configured to perform fuzzy inference on the fuzzy value of the traveling angle deviation and the fuzzy value of the positional deviation, a fuzzy value of the motion correction amount of the robot;
  • the defuzzification processing component is configured to perform a blurring process on the blur value of the motion correction amount in the domain of the motion correction amount to obtain the motion correction amount;
  • the fuzzification processing component is further configured to perform real-time adjustment on the domain of the traveling angle deviation and the domain of the position deviation according to the traveling angle deviation and the position deviation of the current time.
  • the deblurring processing component is further configured to perform real-time adjustment of the domain of the motion correction amount according to a traveling speed of the current moment of the robot.
  • the fuzzification processing component is configured to perform the following steps: the domain of the deviation of the traveling angle deviation and the domain of the position deviation at the previous moment are [-P, P] and [-E, E], respectively.
  • the traveling angle deviation and the positional deviation of the time are ⁇ and y, respectively, and the first domain scaling factor ⁇ is determined according to the ratio of
  • the domain of the angular deviation and the domain of the positional deviation are adjusted to [- ⁇ P, ⁇ P] and [- ⁇ E, ⁇ E], respectively.
  • the first domain scaling factor ⁇ max ⁇ (
  • the constant between ⁇ is a constant between [0.08, 0.12].
  • the deblurring processing component is configured to perform the step of: determining a second universe scaling factor ⁇ according to a traveling speed v of the current moment of the robot, wherein ⁇ determined in a case where v is greater than or equal to a threshold, It is larger than ⁇ determined when v is smaller than the threshold value; the domain of the motion correction amount at the current time is adjusted from the domain [-T, T] of the motion correction amount at the previous time to [- ⁇ T, ⁇ T].
  • the second domain scaling factor :
  • ⁇ t is a constant between (0, 1) and v t is a preset crawling speed.
  • the predetermined creep speed v t is a constant between [32, 48] mm/s.
  • the blur value is at least one of a large deviation in the positive direction, a deviation in the positive direction, a small deviation in the positive direction, no deviation, a large deviation in the reverse direction, a deviation in the reverse direction, and a small deviation in the reverse direction.
  • a control apparatus for a robot comprising: a memory and a processor coupled to the memory, the processor being configured to execute based on an instruction stored in the memory device One or several steps in the control method of the robot described in any of the above embodiments.
  • a control system for a robot includes: a position sensor for acquiring a real-time position and a traveling direction of the robot; and a processor for performing the method described in any of the above embodiments One or several steps in the robot's control method.
  • a computer readable storage medium having stored thereon a computer program, the program being executed by a processor to implement one or more of the control methods of the robot described in any of the above embodiments Steps.
  • FIG. 1 illustrates an exemplary flowchart of a method of controlling a robot in accordance with some embodiments of the present disclosure
  • FIG. 2 illustrates a schematic diagram of a method of controlling a robot in accordance with some embodiments of the present disclosure
  • FIG. 3 illustrates an exemplary block diagram of a control device of a robot, in accordance with some embodiments of the present disclosure
  • FIG. 4 illustrates an exemplary block diagram of a control device of a robot according to further embodiments of the present disclosure
  • FIG. 5 illustrates an exemplary block diagram of a control device of a robot in accordance with further embodiments of the present disclosure
  • FIG. 6 illustrates an exemplary block diagram of a control system of a robot, in accordance with some embodiments of the present disclosure.
  • FIG. 1 illustrates an exemplary flow chart of a method of controlling a robot in accordance with some embodiments of the present disclosure.
  • the method includes: step 101, adjusting a field of angular deviation and position deviation in real time; step 102, determining a fuzzy value of the angular deviation and the position deviation; and step 103, determining a fuzzy value of the motion correction amount; and the step 104. Determine a motion correction amount.
  • step 101 the domain of the deviation of the traveling angle and the field of the positional deviation are adjusted in real time based on the deviation of the traveling angle and the positional deviation at the current time.
  • robot motion can be controlled according to the schematic in FIG.
  • FIG. 2 shows a schematic diagram of a method of controlling a robot in accordance with some embodiments of the present disclosure.
  • the ideal traveling direction of the robot 20 is the X axis
  • the position coordinate of the robot 20 in the vertical direction of the X axis is the Y axis.
  • the actual position of the robot 20 at the moment is the point M(x, y), and the ideal position should be the coordinate system origin O(0, 0), and the angle v between the speed v of the robot 20 and the X axis is ⁇ , where the ideal moment is
  • the position can be determined by scanning the markings laid on the ground by a scanning device on the robot 20, which can be a two-dimensional code with a spacing of 1 meter. Therefore, at the current time, the displacement deviation of the robot 20 is y, and the deviation of the traveling angle is ⁇ , and the angular deviation can be set clockwise to be positive and counterclockwise to be negative.
  • the domain of the deviation of the angle of travel of the previous moment and the domain of the positional deviation are [-P, P] and [-E, E], respectively, and the deviation of the traveling angle and the positional deviation at the current time are respectively ⁇ .
  • the first domain scaling factor ⁇ can be determined from the ratio of
  • ⁇ is to ensure that the adjusted domain does not infinitely close to 0, can be set to a constant between [0.08, 0.12], or according to the actual The situation is set to a relatively small number such as 0.15, 0.2, etc. that is not zero.
  • the domains of the travel angle deviation and positional deviation at the previous moment [-P, P] and [-E, E] are respectively adjusted to [- ⁇ P, ⁇ P] and [- ⁇ E, ⁇ E].
  • the initial domain of the deviation of the travel angle can be set to [-1°, 1°]
  • the initial domain of positional deviation is [- 20mm, 20mm]
  • the initial domain can be adjusted according to the scaling factor calculated at the first moment.
  • step 102 the travel angle deviation and the position deviation are blurred in the field of the travel angle deviation and the position deviation of the current time of the robot, respectively, and the blur value of the travel angle deviation and the blur value of the position deviation are obtained.
  • the fuzzy value may be set to a positive direction large deviation PB, a positive direction deviation PM, a positive direction small deviation PS, an unbiased ZE, a reverse large deviation NB, a reverse direction deviation NM, or a reverse small deviation NS.
  • the membership function can be set for each fuzzy value according to the actual situation.
  • the membership function is preferably a triangle membership function, and a trapezoid membership function can also be used. Taking ⁇ and y into each of the above membership functions, respectively, calculating the membership degree corresponding to each fuzzy value, and then determining which fuzzy ⁇ and y should be blurred by comparing the degree of membership of ⁇ and y for each fuzzy value. value.
  • step 103 fuzzy inference is performed on the blur value of the travel angle deviation and the blur value of the position deviation to obtain a blur value of the motion correction amount of the robot.
  • the robot 20 has two drive wheels 21 and 22, and the motion correction amounts of the drive wheel 21 and the drive wheel 22 can be set to be opposite to each other, for example, the motion correction of the drive wheel 21.
  • the amount is z
  • the motion correction amount of the drive wheel 22 is -z.
  • the two drive wheels 21 and 22 are simultaneously controlled in accordance with the respective correction amounts.
  • the correspondence between the motion correction amount z of the drive wheel 21 and the fuzzy inference of ⁇ and y can be as shown in the following table:
  • the fuzzy reasoning correspondence can be adjusted according to the actual situation.
  • step 104 in the domain of the motion correction amount, the blur value of the motion correction amount is subjected to deblurring processing to obtain a motion correction amount.
  • the domain of the motion correction amount is adjusted in real time based on the travel speed v of the current time of the robot.
  • the second universe scaling factor ⁇ may be determined according to the traveling speed v of the current moment of the robot, and it is ensured that ⁇ determined in the case where v is greater than or equal to the threshold is greater than ⁇ determined in the case where v is less than the threshold.
  • determining the second domain scaling factor according to the traveling speed v of the current moment of the robot is
  • ⁇ t is a constant between (0, 1)
  • v t is the preset crawling speed
  • the domain of the motion correction amount of the current time is from the field of motion correction of the previous moment [-T, T] Adjust to [- ⁇ T, ⁇ T].
  • the crawling speed v t is a preset slower robot traveling speed when the robot approaches the target position, so as to prevent the robot from coming over the brake or adjusting to exceed the target position.
  • the creep speed can be a constant between [32, 48] mm/s.
  • the initial domain of the motion correction amount can be set to [-30 mm/s, 30 mm/s], which is operated by the robot.
  • the initial domain can be adjusted by scaling factor ⁇ .
  • the response speed to the robot control is improved by the fuzzy control; the fuzzy set theory field of the fuzzy control input and the output quantity is adjusted in real time, and the correcting ability for the robot trajectory is improved; the opposite of the same control amount is adopted.
  • the number of the two driving wheels of the robot is controlled at the same time, which overcomes the control error caused by the uncoordinated control of each driving wheel.
  • FIG. 3 illustrates an exemplary block diagram of a control device of a robot, in accordance with some embodiments of the present disclosure.
  • the apparatus includes: a fuzzification processing component 31, a fuzzy inference component 32, and a defuzzification processing component 33.
  • the blurring processing unit 31 blurs the traveling angle deviation and the position deviation in the field of the traveling angle deviation and the position deviation of the current time of the robot, respectively, and obtains the blur value of the traveling angle deviation and the blur value of the position deviation.
  • the fuzzification processing component 31 can also adjust the domain of the deviation of the traveling angle deviation and the position deviation in real time according to the deviation of the traveling angle and the position deviation at the current time.
  • the fuzzification processing component 31 can acquire real-time position information of the robot through a position sensor mounted on the robot.
  • the position sensor may be a motor optical code disc
  • the blurring processing component 31 calculates the real-time position and the traveling direction of the robot by the motor optical code discs of the two driving wheels of the robot, thereby determining the traveling angle deviation and the position deviation.
  • the fuzzification processing component 31 is configured to perform the steps of: the domain of the deviation of the angle of travel of the previous moment and the domain of the positional deviation are [-P, P] and [-E, E], respectively.
  • the traveling angle deviation and the position deviation of the current time are ⁇ and y, respectively, and the first domain expansion factor ⁇ is determined according to the ratio of
  • the domain of the deviation and the field of positional deviation are adjusted to [- ⁇ P, ⁇ P] and [- ⁇ E, ⁇ E], respectively.
  • the fuzzy inference component 32 performs fuzzy inference on the blur value of the travel angle deviation and the blur value of the position deviation to obtain a blur value of the motion correction amount of the robot.
  • the deblurring processing component 33 deblurs the blurring value of the motion correction amount in the domain of the motion correction amount to obtain a motion correction amount.
  • the robot 20 has two drive wheels 21 and 22 that are respectively driven by two motors.
  • the driving wheels 21 and 22 can be driven by differential driving, that is, when the two motors rotate at the same speed in the same direction, the robot advances and retreats in a straight line, and when the two motors rotate in the same direction at the same speed, the robot turns in place.
  • the motion correction amounts of the drive wheels 21 and 22 are opposite to each other.
  • the deblurring processing component 33 adjusts the universe of motion corrections in real time based on the speed of travel of the robot at the current time.
  • the deblurring processing component 33 is configured to perform the steps of: determining the second universe scaling factor ⁇ according to the traveling speed v of the current moment of the robot, and being able to ensure that ⁇ determined in the case where v is greater than or equal to the threshold, is greater than less than v. ⁇ determined in the case of the threshold; the domain of the motion correction amount at the current time is adjusted from the field of motion correction [-T, T] of the previous moment to [- ⁇ T, ⁇ T].
  • the deblurring processing component 33 determines that the second domain scaling factor is based on the traveling speed v of the current moment of the robot.
  • ⁇ t is a constant between (0, 1), v t is the preset crawling speed, and the domain of the motion correction amount at the current time is from the field of motion correction of the previous moment [-T, T] Adjust to [- ⁇ T, ⁇ T].
  • the fuzzification processing component and the defuzzification processing component can adjust the fuzzy set theory domain in real time according to actual conditions, and can correct the robot under different working conditions such as load change and road surface condition change, thereby enhancing the adaptive capability. Increases the accuracy of the control and reduces the control response time.
  • FIG. 4 illustrates an exemplary block diagram of a control device of a robot in accordance with further embodiments of the present disclosure.
  • the apparatus 40 of this embodiment includes a memory 41 and a processor 42 coupled to the memory 41, the processor 42 being configured to perform any of the implementations of the present disclosure based on instructions stored in the memory 41.
  • the processor 42 being configured to perform any of the implementations of the present disclosure based on instructions stored in the memory 41.
  • the memory 41 may include, for example, a system memory, a fixed non-volatile storage medium, or the like.
  • the system memory stores, for example, an operating system, an application, a boot loader, a database, and other programs.
  • FIG. 5 illustrates an exemplary block diagram of a control device of a robot in accordance with further embodiments of the present disclosure.
  • the processor 520 is coupled to the memory 510 via the BUS bus 530.
  • Display device 50 may also be coupled to external storage device 550 via storage interface 560 for invoking external data, and may also be coupled to a network or another computer system (not shown) via network interface 560. It will not be described in detail here.
  • control methods of any of the foregoing embodiments can be implemented by storing data instructions through memory 510 and processing the instructions by processor 520.
  • FIG. 6 illustrates an exemplary block diagram of a control system of a robot, in accordance with some embodiments of the present disclosure.
  • the control system 6 includes a position sensor 61 and a processor 62.
  • the position sensor 61 is used to acquire the real-time position and traveling direction of the robot.
  • the processor 62 is operative to perform one or more of the robotic control methods of any of the above embodiments.
  • a computer readable storage medium having stored thereon a computer program that, when executed by a processor, implements one or more of the steps of controlling a robot in any of the above embodiments.
  • the computer readable storage medium is a non-transitory computer readable storage medium.
  • the methods and systems of the present disclosure may be implemented in a number of ways.
  • the methods and systems of the present disclosure may be implemented in software, hardware, firmware, or any combination of software, hardware, or firmware.
  • the above-described sequence of steps for the method is for illustrative purposes only, and the steps of the method of the present disclosure are not limited to the order specifically described above unless otherwise specifically stated.
  • the present disclosure may also be embodied as programs recorded in a recording medium, the programs including machine readable instructions for implementing a method in accordance with the present disclosure.
  • the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.

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  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

La présente invention concerne un procédé et un appareil de commande destinés à un robot. Le procédé consiste : à effectuer respectivement, dans l'univers de déroulement d'un écart angulaire en cours et d'un écart de positionnement d'un robot à un moment actuel, une modification logique floue sur l'écart angulaire en cours et sur l'écart de positionnement afin d'obtenir une valeur floue de l'écart angulaire en cours et une valeur floue de l'écart positionnel (102); à effectuer un raisonnement flou sur la valeur floue de l'écart angulaire en cours et sur la valeur floue de l'écart positionnel afin d'obtenir une valeur floue d'une quantité de correction de mouvement du robot (103); et à effectuer, dans l'univers de déroulement de la quantité de correction de mouvement, un traitement de clarification sur la valeur floue de la quantité de correction de mouvement afin d'obtenir le degré de correction de mouvement (104); et le procédé consiste en outre à régler l'univers de déroulement de l'écart angulaire en cours et l'univers de déroulement de l'écart positionnel en temps réel en fonction de l'écart angulaire en cours et de l'écart positionnel au moment actuel (101). Le procédé et l'appareil peuvent améliorer la capacité d'auto-adaptation et la vitesse de réponse d'une commande de mouvement de robot.
PCT/CN2018/083351 2017-06-07 2018-04-17 Procédé, appareil et système de commande destinés à un robot, et support d'informations lisible par ordinateur WO2018223776A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113885514A (zh) * 2021-10-25 2022-01-04 上海影谱科技有限公司 基于模糊控制和几何追踪的agv路径跟踪方法及系统

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111562780A (zh) * 2019-02-13 2020-08-21 北京京东尚科信息技术有限公司 一种搬运设备运行轨迹设置方法和装置

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013003845A (ja) * 2011-06-16 2013-01-07 Institute Of National Colleges Of Technology Japan 組み込み知能コントローラ、制御システム、制御プログラム、記録媒体、及び制御方法
CN103345153A (zh) * 2013-06-16 2013-10-09 北京联合大学 通用网络化预测模糊控制方法
CN104898665A (zh) * 2015-04-16 2015-09-09 山东建筑大学 巡检机器人轨迹规划的方法和装置
CN105867377A (zh) * 2016-04-13 2016-08-17 浙江理工大学 一种农业机械自动导航控制方法

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0566803A (ja) * 1991-09-06 1993-03-19 Nippon Telegr & Teleph Corp <Ntt> 小口径トンネルロボツトのニユーラル型最適フアジイ集合代表値オートチユーニング方法
CN102645893A (zh) * 2012-04-19 2012-08-22 哈尔滨工程大学 船舶航向变论域模糊控制方法
CN104199461B (zh) * 2014-08-29 2017-02-08 山东科技大学 机器人鸟自主导航系统及导航方法
CN106444357B (zh) * 2016-05-17 2019-10-01 长春工业大学 一种变论域模糊pid双液压缸电液伺服同步控制方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013003845A (ja) * 2011-06-16 2013-01-07 Institute Of National Colleges Of Technology Japan 組み込み知能コントローラ、制御システム、制御プログラム、記録媒体、及び制御方法
CN103345153A (zh) * 2013-06-16 2013-10-09 北京联合大学 通用网络化预测模糊控制方法
CN104898665A (zh) * 2015-04-16 2015-09-09 山东建筑大学 巡检机器人轨迹规划的方法和装置
CN105867377A (zh) * 2016-04-13 2016-08-17 浙江理工大学 一种农业机械自动导航控制方法

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113885514A (zh) * 2021-10-25 2022-01-04 上海影谱科技有限公司 基于模糊控制和几何追踪的agv路径跟踪方法及系统
CN113885514B (zh) * 2021-10-25 2024-05-07 上海影谱科技有限公司 基于模糊控制和几何追踪的agv路径跟踪方法及系统

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