CN113359791B - Robot control method and device, computer readable storage medium and robot - Google Patents
Robot control method and device, computer readable storage medium and robot Download PDFInfo
- Publication number
- CN113359791B CN113359791B CN202110583417.5A CN202110583417A CN113359791B CN 113359791 B CN113359791 B CN 113359791B CN 202110583417 A CN202110583417 A CN 202110583417A CN 113359791 B CN113359791 B CN 113359791B
- Authority
- CN
- China
- Prior art keywords
- robot
- strategy
- interference
- zero moment
- moment point
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000005259 measurement Methods 0.000 claims abstract description 26
- 210000004394 hip joint Anatomy 0.000 claims description 64
- 230000001133 acceleration Effects 0.000 claims description 48
- 238000011217 control strategy Methods 0.000 claims description 23
- 238000004590 computer program Methods 0.000 claims description 22
- 210000001624 hip Anatomy 0.000 claims description 12
- 230000005484 gravity Effects 0.000 claims description 4
- 230000008569 process Effects 0.000 abstract description 12
- 238000010586 diagram Methods 0.000 description 8
- 230000006870 function Effects 0.000 description 6
- 210000002683 foot Anatomy 0.000 description 5
- 238000012545 processing Methods 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000013016 damping Methods 0.000 description 2
- 210000003423 ankle Anatomy 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- 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
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0891—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for land vehicles
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D57/00—Vehicles characterised by having other propulsion or other ground- engaging means than wheels or endless track, alone or in addition to wheels or endless track
- B62D57/02—Vehicles characterised by having other propulsion or other ground- engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members
- B62D57/032—Vehicles characterised by having other propulsion or other ground- engaging means than wheels or endless track, alone or in addition to wheels or endless track with ground-engaging propulsion means, e.g. walking members with alternately or sequentially lifted supporting base and legs; with alternately or sequentially lifted feet or skid
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Combustion & Propulsion (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Manipulator (AREA)
Abstract
The application belongs to the technical field of robots, and particularly relates to a robot control method and device, a computer readable storage medium and a robot. The method comprises the following steps: determining a zero moment point measurement of the robot; selecting a target anti-interference strategy subset corresponding to the zero moment point measured value from a preset anti-interference strategy set; and controlling the robot according to the target anti-interference strategy subset. According to the application, a plurality of different anti-interference strategies form an anti-interference strategy set, and in the walking process of the robot, the optimal anti-interference strategy subset can be selected from the anti-interference strategy subset according to the zero moment point measured value of the robot, and the robot is controlled according to the strategy subset, so that the robot can flexibly switch among various complex interference scenes.
Description
Technical Field
The application belongs to the technical field of robots, and particularly relates to a robot control method and device, a computer readable storage medium and a robot.
Background
When the biped robot steps or walks, the biped robot is easily interfered by external environment or human factors, so that the robot falls down. In the prior art, certain specific strategies can be used for resisting interference and recovering the robot to a stable state, but the strategies are usually only aimed at a single interference scene, and are difficult to be applied to other interference scenes, so that the flexibility is poor.
Disclosure of Invention
In view of the above, the embodiments of the present application provide a robot control method, a device, a computer readable storage medium, and a robot, so as to solve the problem of poor flexibility of the existing robot control method.
A first aspect of an embodiment of the present application provides a robot control method, which may include:
determining a zero moment point measurement of the robot;
Selecting a target anti-interference strategy subset corresponding to the zero moment point measured value from a preset anti-interference strategy set;
Controlling the robot according to the target anti-interference strategy subset, including: if the target anti-interference strategy subset comprises a stepping strategy, calculating the product of the length from the center of mass of the robot to a supporting point and the actual angle of the hip joint of the robot, and taking the opposite number of the ratio of the product to the preset circle frequency as the stepping step length of the robot; and controlling the robot to move according to the step length.
In a specific implementation manner of the first aspect, selecting a target anti-interference strategy subset corresponding to the zero moment point measurement value from a preset anti-interference strategy set may include:
If the zero moment point measured value is smaller than or equal to a preset first threshold value, selecting a centroid compliance strategy from the anti-interference strategy set as the target anti-interference strategy subset;
If the zero moment point measured value is larger than the first threshold value and smaller than a preset second threshold value, selecting a mass center compliance strategy and a hip joint control strategy from the anti-interference strategy set as the target anti-interference strategy subset;
and if the zero moment point measured value is larger than the second threshold value, selecting a centroid compliance strategy, a hip joint control strategy and a stepping strategy from the anti-interference strategy set as the target anti-interference strategy subset.
In a specific implementation manner of the first aspect, if the target anti-interference policy subset includes a centroid compliance policy, the controlling the robot according to the target anti-interference policy subset may include:
calculating a centroid acceleration of the robot according to the formula:
wherein x c is the actual position of the centroid of the robot, For the desired position of the centroid of the robot,/>For the actual speed of the centroid of the robot,/>For the desired speed of the centroid of the robot, p m is the zero moment point measurement,/>For the expected value of the zero moment point of the robot, K p1 is a preset position gain coefficient, K d1 is a preset speed gain coefficient, K z1 is a preset zero moment point gain coefficient,/>A centroid acceleration for the robot;
and controlling the robot to move according to the mass center acceleration.
In a specific implementation of the first aspect, if the target anti-interference policy subset includes a hip joint control policy, the controlling the robot according to the target anti-interference policy subset may include:
the hip angular acceleration of the robot is calculated according to the following formula:
Wherein, theta m is the actual angle of the hip joint of the robot, theta d is the expected angle of the hip joint of the robot, For the actual angular velocity of the hip joint of the robot,/>For the expected angular velocity of the hip joint of the robot, p m is the zero moment point measurement value, p' boundary is the zero moment point boundary value of the robot, K p2 is a preset angular gain coefficient, K d2 is a preset angular velocity gain coefficient, K z2 is a preset zero moment point gain coefficient,/>Hip angular acceleration for the robot;
and controlling the robot to move according to the hip joint angular acceleration.
In a specific implementation of the first aspect, the robot control method may further include:
Setting the first threshold and the second threshold according to:
Wherein, For the front sole distance of the robot, z is the mass center height of the robot, g is gravity acceleration, J is the upper body moment of inertia of the robot,/>Maximum angular acceleration of the hip joint of the robot, m being the mass of the robot,/>For the first threshold,/>Is the second threshold.
A second aspect of an embodiment of the present application provides a robot control device, which may include:
the zero moment point determining module is used for determining a zero moment point measured value of the robot;
The anti-interference strategy selection module is used for selecting a target anti-interference strategy subset corresponding to the zero moment point measured value from a preset anti-interference strategy set;
The robot control module is used for controlling the robot according to the target anti-interference strategy subset, and comprises the following steps: if the target anti-interference strategy subset comprises a stepping strategy, calculating the product of the length from the center of mass of the robot to a supporting point and the actual angle of the hip joint of the robot, and taking the opposite number of the ratio of the product to the preset circle frequency as the stepping step length of the robot; and controlling the robot to move according to the step length.
In a specific implementation manner of the second aspect, the anti-interference policy selection module may include:
A first strategy subset selecting unit, configured to select a centroid compliance strategy from the anti-interference strategy set as the target anti-interference strategy subset if the zero moment point measurement value is less than or equal to a preset first threshold value;
A second strategy subset selecting unit, configured to select a centroid compliance strategy and a hip joint control strategy from the anti-interference strategy set as the target anti-interference strategy subset if the zero moment point measurement value is greater than the first threshold and less than a preset second threshold;
and the third strategy subset selecting unit is used for selecting a centroid compliance strategy, a hip joint control strategy and a stepping strategy from the anti-interference strategy set as the target anti-interference strategy subset if the zero moment point measured value is larger than the second threshold value.
In a specific implementation of the second aspect, the robot control module may include:
The centroid compliance control unit is used for calculating centroid acceleration of the robot according to the following formula if the centroid compliance strategy is included in the target anti-interference strategy subset:
wherein x c is the actual position of the centroid of the robot, For the desired position of the centroid of the robot,/>For the actual speed of the centroid of the robot,/>For the desired speed of the centroid of the robot, p m is the zero moment point measurement,/>For the expected value of the zero moment point of the robot, K p1 is a preset position gain coefficient, K d1 is a preset speed gain coefficient, K z1 is a preset zero moment point gain coefficient,/>A centroid acceleration for the robot; and controlling the robot to move according to the mass center acceleration.
In a specific implementation of the second aspect, the robot control module may include:
The hip joint control unit is used for calculating the hip joint angular acceleration of the robot according to the following formula if the target anti-interference strategy subset comprises a hip joint control strategy:
Wherein, theta m is the actual angle of the hip joint of the robot, theta d is the expected angle of the hip joint of the robot, For the actual angular velocity of the hip joint of the robot,/>For the expected angular velocity of the hip joint of the robot, p m is the zero moment point measurement value, p ′ boundary is the zero moment point boundary value of the robot, K p2 is a preset angle gain coefficient, K d2 is a preset angular velocity gain coefficient, K z2 is a preset zero moment point gain coefficient,/>Hip angular acceleration for the robot; and controlling the robot to move according to the hip joint angular acceleration.
In a specific implementation of the second aspect, the robot control device may further include:
a threshold setting module, configured to set the first threshold and the second threshold according to the following formula:
Wherein, For the front sole distance of the robot, z is the mass center height of the robot, g is gravity acceleration, J is the upper body moment of inertia of the robot,/>Maximum angular acceleration of the hip joint of the robot, m being the mass of the robot,/>For the first threshold,/>Is the second threshold.
A third aspect of the embodiments of the present application provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of any one of the robot control methods described above.
A fourth aspect of the embodiments of the present application provides a robot comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of any one of the above-mentioned robot control methods when executing the computer program.
A fifth aspect of the embodiments of the present application provides a computer program product for, when run on a robot, causing the robot to perform the steps of any of the robot control methods described above.
Compared with the prior art, the embodiment of the application has the beneficial effects that: the method and the device for determining the zero moment point measurement value of the robot; selecting a target anti-interference strategy subset corresponding to the zero moment point measured value from a preset anti-interference strategy set; and controlling the robot according to the target anti-interference strategy subset. According to the embodiment of the application, a plurality of different anti-interference strategies form an anti-interference strategy set, an optimal anti-interference strategy subset (namely a target anti-interference strategy subset) can be selected from the anti-interference strategy subset according to the zero moment point measured value of the robot in the walking process of the robot, and the robot is controlled according to the strategy subset, so that the robot can flexibly switch among various complex interference scenes.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of one embodiment of a method for controlling a robot in accordance with an embodiment of the present application;
FIG. 2 is a schematic illustration of a spring damping model;
FIG. 3 is a schematic diagram of a robot before and after being disturbed by an external force;
Fig. 4 is a schematic diagram of a handover of each anti-interference strategy;
FIG. 5 is a block diagram of one embodiment of a robot control device according to an embodiment of the present application;
Fig. 6 is a schematic block diagram of a robot in an embodiment of the application.
Detailed Description
In order to make the objects, features and advantages of the present application more comprehensible, the technical solutions in the embodiments of the present application are described in detail below with reference to the accompanying drawings, and it is apparent that the embodiments described below are only some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application, the terms "first," "second," "third," etc. are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
When the robot is subjected to external disturbance force, the influence of the disturbance force needs to be counteracted by internal moment under the condition of not being completely unstable. The sole of the robot contacts with the ground in a stable state, and for small interference, only compensation torque is required to be applied to the ankle. However, as the disturbance increases, more body balance strategies must be considered, and bending the upper body creates additional torque to resist the effects of external disturbance. If the interference is too large, the overall state adjustment can be performed by stepping to keep stable.
In the embodiment of the application, corresponding anti-interference strategies are preset respectively for external force interference conditions of different degrees, so as to form an anti-interference strategy set. In the walking process of the robot, an optimal anti-interference strategy subset can be selected according to the actual external force interference condition, and the robot is controlled according to the strategy subset, so that the robot can flexibly switch among various complex interference scenes.
For convenience of description, in the embodiment of the present application, a world coordinate system may be pre-established, in which a forward direction of the robot is an x-axis, a lateral direction is a y-axis, and a longitudinal direction is a z-axis. It should be noted that, in the embodiments of the present application, the motion of the robot in the x-axis direction is analyzed, and, unless otherwise specified, the physical quantities such as zero moment point (Zero Moment Point, ZMP), position, velocity, and acceleration used in the following descriptions refer to the components of these physical quantities in the x-axis direction.
Referring to fig. 1, an embodiment of a robot control method according to an embodiment of the present application may include:
Step S101, determining a zero moment point measurement value of the robot.
The zero moment point measurement value can be measured by a force sensor and a moment sensor of the robot foot, and in the embodiment of the application, the zero moment point measurement value can be used as a measurement index of the interference of external force on the robot. The larger the zero moment point measured value is, the larger the external force interference to the robot is, otherwise, the smaller the zero moment point measured value is, the smaller the external force interference to the robot is
Step S102, selecting a target anti-interference strategy subset corresponding to the zero moment point measurement value from a preset anti-interference strategy set.
In an embodiment of the application, the anti-interference strategy set can comprise a centroid compliance strategy, a hip joint control strategy and a stepping strategy.
If the zero moment point measured value is smaller than or equal to a preset first threshold value, selecting a mass center compliant strategy from the anti-interference strategy set as a target anti-interference strategy subset;
If the zero moment point measured value is larger than the first threshold value and smaller than a preset second threshold value, selecting a centroid compliance strategy and a hip joint control strategy from the anti-interference strategy set as a target anti-interference strategy subset;
And if the zero moment point measured value is larger than a second threshold value, selecting a centroid compliance strategy, a hip joint control strategy and a stepping strategy from the anti-interference strategy set as a target anti-interference strategy subset.
And step S103, controlling the robot according to the target anti-interference strategy subset.
For a centroid compliance strategy, the control of the centroid is realized by a compliance controller, and when the centroid is disturbed by external force, the adjustment of centroid track is performed by the compliance controller to resist the disturbance. In the embodiment of the application, the relation between the expected position of the mass center of the robot and the actual position of the mass center can be equivalent to a spring damping model as shown in fig. 2.
Based on this model, taking the zero moment point as the contact force term, the centroid acceleration of the robot can be calculated according to the following equation:
wherein x c is the actual position of the centroid of the robot, For the desired position of the centroid of the robot,/>Is the actual speed of the mass center of the robot,/>For the desired speed of the centroid of the robot, p m is the zero moment point measurement,/>Is the expected value of zero moment point of the robot, x c and/>Can be obtained by measuring by a sensor,/>And/>Can be set according to actual conditions, K p1 is a preset position gain coefficient, K d1 is a preset speed gain coefficient, K z1 is a preset zero moment point gain coefficient, the specific values of the gain coefficients can be set according to actual conditions, and the gain coefficients are expressed as/>Is the mass center acceleration of the robot.
Due to the limitation of the size of the robot foot, under the centroid compliance strategy, the centroid acceleration should meet the following limitation conditions:
Wherein, p f is a preset zero moment forward boundary value, p b is a preset zero moment backward boundary value, g is a gravitational acceleration, and z is the mass center height of the robot.
After the mass center acceleration is calculated through the process, the robot can be controlled to move according to the mass center acceleration.
For the hip joint control strategy, the control of the hip joint is realized by controlling the attitude angle of the upper body of the robot, and the hip joint angular acceleration of the robot can be calculated according to the following formula:
Wherein, theta m is the actual angle of the hip joint of the robot, theta d is the expected angle of the hip joint of the robot, Is the actual angular velocity of the hip joint of the robot,/>For the desired angular velocity of the hip joint of the robot, p ′ boundary is the zero moment point boundary value of the robot, θ m and/>Can be measured by a sensor, and the expected posture of the upper body of the robot is vertical during walking, so that theta d and/>The specific values of p ′ boundary can be set according to the actual condition, K p2 is a preset angle gain coefficient, K d2 is a preset angular velocity gain coefficient, K z2 is a preset zero moment point gain coefficient, and the specific values of the gain coefficients can be set according to the actual conditionIs the angular acceleration of the hip joint of the robot. After the robot is interfered by the outside, the hip joint angular acceleration is generated through the process so as to resist the outside interference. After the external interference disappears, the expected angle of the hip joint is zero, so that the posture of the robot can be controlled to be corrected.
The hip angular acceleration is also limited by the foot size, and in embodiments of the present application, the scope of the hip control strategy may be defined according to the following equation:
wherein J is the moment of inertia of the upper body of the robot, The maximum angular acceleration of the hip joint of the robot is given, and m is the mass of the robot.
After the hip joint angular acceleration is calculated through the above process, the robot can be controlled to move according to the hip joint angular acceleration.
For a step strategy, a step size may be set based on a Capture Point (CP). Wherein the capture points satisfy the relationship shown in the following formula:
wherein ζ is the capture point, ω is the circular frequency, and
When ζ=0, then there are:
after being disturbed by external force, the above formula becomes:
Wherein, And/>The desired position of the centroid and the desired speed of the centroid after being disturbed by an external force are respectively.
Fig. 3 is a schematic diagram of a robot before and after disturbance by an external force, where the robot satisfies the following relationship:
Wherein, L ′ is the length from the center of mass of the robot to the supporting point after being disturbed by the external force, which can be approximately equal to the length from the center of mass of the robot to the supporting point (denoted as L) before being disturbed by the external force, θ m is generally smaller and is approximately 0, cos (θ m) is approximately 1, and the above formula can be simplified as:
at this time, the step size of the robot may be calculated according to the following formula:
wherein Deltax is the step length of the robot.
After the step length is calculated through the process, the robot can be controlled to move according to the step length.
In a specific implementation of the embodiment of the present application, specific values of the first threshold and the second threshold may also be set. For the same backward and forward boundary conditions (p f,pb), under the hip control strategy, the centroid acceleration of the robot has a larger variation range, while under the centroid compliance strategy, the centroid acceleration of the robot has a smaller variation range, and when the zero moment point of the robot exceeds the supporting range of the foot, the robot keeps stable by stepping.
Fig. 4 is a schematic diagram of the switching of each anti-interference strategy. Wherein,Is the distance between the front sole of the robot, i.e. the distance between the ankle joint center and the horizontal direction of the front edge of the foot,/>For a first threshold, i.e. demarcating centroid compliance strategy and hip control strategy,/>For the second threshold, i.e. the demarcation between the hip control strategy and the swing strategy, the specific values of the first threshold and the second threshold may be set according to the following formula:
When (when) When the robot is in use, the mass center compliant strategy is adopted only, so that the robot is suitable for small external force disturbance;
When (when) When the robot is used, a hip joint control strategy is added on the basis of a centroid compliance strategy, and external force disturbance is resisted by adding hip joint rotation;
When (when) And when the robot is used, a stepping strategy is added on the basis of a centroid compliance strategy and a hip joint control strategy to keep stable.
In summary, the embodiment of the application determines the zero moment point measurement value of the robot; selecting a target anti-interference strategy subset corresponding to the zero moment point measured value from a preset anti-interference strategy set; and controlling the robot according to the target anti-interference strategy subset. According to the embodiment of the application, a plurality of different anti-interference strategies form an anti-interference strategy set, an optimal anti-interference strategy subset (namely a target anti-interference strategy subset) can be selected from the anti-interference strategy subset according to the zero moment point measured value of the robot in the walking process of the robot, and the robot is controlled according to the strategy subset, so that the robot can flexibly switch among various complex interference scenes.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present application.
Corresponding to the robot control method described in the above embodiments, fig. 5 shows a block diagram of an embodiment of a robot control device according to an embodiment of the present application.
In this embodiment, a robot control device may include:
a zero moment point determination module 501 configured to determine a zero moment point measurement of the robot;
The anti-interference strategy selection module 502 is configured to select a target anti-interference strategy subset corresponding to the zero moment point measurement value from a preset anti-interference strategy set;
and a robot control module 503, configured to control the robot according to the target anti-interference policy subset.
In a specific implementation of the embodiment of the present application, the anti-interference policy selection module may include:
A first strategy subset selecting unit, configured to select a centroid compliance strategy from the anti-interference strategy set as the target anti-interference strategy subset if the zero moment point measurement value is less than or equal to a preset first threshold value;
A second strategy subset selecting unit, configured to select a centroid compliance strategy and a hip joint control strategy from the anti-interference strategy set as the target anti-interference strategy subset if the zero moment point measurement value is greater than the first threshold and less than a preset second threshold;
and the third strategy subset selecting unit is used for selecting a centroid compliance strategy, a hip joint control strategy and a stepping strategy from the anti-interference strategy set as the target anti-interference strategy subset if the zero moment point measured value is larger than the second threshold value.
In a specific implementation of the embodiment of the present application, the robot control module may include:
The centroid compliance control unit is used for calculating centroid acceleration of the robot according to the following formula if the centroid compliance strategy is included in the target anti-interference strategy subset:
wherein x c is the actual position of the centroid of the robot, For the desired position of the centroid of the robot,/>For the actual speed of the centroid of the robot,/>For the desired speed of the centroid of the robot, p m is the zero moment point measurement,/>For the expected value of the zero moment point of the robot, K p1 is a preset position gain coefficient, K d1 is a preset speed gain coefficient, K z1 is a preset zero moment point gain coefficient,/>A centroid acceleration for the robot; and controlling the robot to move according to the mass center acceleration.
In a specific implementation of the embodiment of the present application, the robot control module may include:
The hip joint control unit is used for calculating the hip joint angular acceleration of the robot according to the following formula if the target anti-interference strategy subset comprises a hip joint control strategy:
Wherein, theta m is the actual angle of the hip joint of the robot, theta d is the expected angle of the hip joint of the robot, For the actual angular velocity of the hip joint of the robot,/>For the expected angular velocity of the hip joint of the robot, p m is the zero moment point measurement value, p ′ boundary is the zero moment point boundary value of the robot, K p2 is a preset angle gain coefficient, K d2 is a preset angular velocity gain coefficient, K z2 is a preset zero moment point gain coefficient,/>Hip angular acceleration for the robot; and controlling the robot to move according to the hip joint angular acceleration.
In a specific implementation of the embodiment of the present application, the robot control module may include:
and the step control unit is used for calculating the step length of the robot according to the following formula if the step strategy is included in the target anti-interference strategy subset:
wherein L is the length from the mass center of the robot to the supporting point, Omega is a preset circular frequency, and Deltax is a stepping step length of the robot; and controlling the robot to move according to the step length.
In a specific implementation of the embodiment of the present application, the robot control device may further include:
a threshold setting module, configured to set the first threshold and the second threshold according to the following formula:
Wherein, For the front sole distance of the robot, z is the mass center height of the robot, g is gravity acceleration, J is the upper body moment of inertia of the robot,/>Maximum angular acceleration of the hip joint of the robot, m being the mass of the robot,/>For the first threshold,/>Is the second threshold.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described apparatus, modules and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Fig. 6 shows a schematic block diagram of a robot provided in an embodiment of the present application, and only a portion related to the embodiment of the present application is shown for convenience of explanation.
As shown in fig. 6, the robot 6 of this embodiment includes: a processor 60, a memory 61 and a computer program 62 stored in said memory 61 and executable on said processor 60. The processor 60, when executing the computer program 62, implements the steps of the respective robot control method embodiments described above, for example, steps S101 to S103 shown in fig. 1. Or the processor 60, when executing the computer program 62, performs the functions of the modules/units of the apparatus embodiments described above, such as the functions of modules 501-503 shown in fig. 5.
Illustratively, the computer program 62 may be partitioned into one or more modules/units that are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 62 in the robot 6.
It will be appreciated by those skilled in the art that fig. 6 is merely an example of a robot 6 and is not meant to be limiting of the robot 6, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., the robot 6 may also include input and output devices, network access devices, buses, etc.
The Processor 60 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 61 may be an internal storage unit of the robot 6, such as a hard disk or a memory of the robot 6. The memory 61 may be an external storage device of the robot 6, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), or the like, which are provided on the robot 6. Further, the memory 61 may also include both an internal memory unit and an external memory device of the robot 6. The memory 61 is used for storing the computer program as well as other programs and data required by the robot 6. The memory 61 may also be used for temporarily storing data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/robot and method may be implemented in other ways. For example, the apparatus/robot embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical function division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated modules/units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable storage medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable storage medium may include content that is subject to appropriate increases and decreases as required by jurisdictions and by jurisdictions in which such computer readable storage medium does not include electrical carrier signals and telecommunications signals.
The above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (7)
1. A robot control method, comprising:
determining a zero moment point measurement of the robot;
if the zero moment point measured value is smaller than or equal to a preset first threshold value, selecting a mass center compliance strategy from a preset anti-interference strategy set as a target anti-interference strategy subset; if the zero moment point measured value is larger than the first threshold value and smaller than a preset second threshold value, selecting a mass center compliance strategy and a hip joint control strategy from the anti-interference strategy set as the target anti-interference strategy subset; if the zero moment point measured value is larger than the second threshold value, selecting a centroid compliance strategy, a hip joint control strategy and a stepping strategy from the anti-interference strategy set as the target anti-interference strategy subset;
Controlling the robot according to the target anti-interference strategy subset, including: if the target anti-interference strategy subset comprises a stepping strategy, calculating the product of the length from the center of mass of the robot to a supporting point and the actual angle of the hip joint of the robot, and taking the opposite number of the ratio of the product to the preset circle frequency as the stepping step length of the robot; and controlling the robot to move according to the step length.
2. The method of claim 1, wherein if the target anti-interference strategy subset includes a centroid compliance strategy, the controlling the robot according to the target anti-interference strategy subset comprises:
calculating a centroid acceleration of the robot according to the formula:
wherein x c is the actual position of the centroid of the robot, For the desired position of the centroid of the robot,/>For the actual speed of the centroid of the robot,/>For the desired speed of the centroid of the robot, p m is the zero moment point measurement,/>For the expected value of the zero moment point of the robot, K p1 is a preset position gain coefficient, K d1 is a preset speed gain coefficient, K z1 is a preset zero moment point gain coefficient,/>A centroid acceleration for the robot;
and controlling the robot to move according to the mass center acceleration.
3. The method of claim 1, wherein if the target anti-interference strategy subset includes a hip control strategy, the controlling the robot according to the target anti-interference strategy subset includes:
the hip angular acceleration of the robot is calculated according to the following formula:
Wherein, theta m is the actual angle of the hip joint of the robot, theta d is the expected angle of the hip joint of the robot, For the actual angular velocity of the hip joint of the robot,/>For the expected angular velocity of the hip joint of the robot, p m is the zero moment point measurement value, p ′ boundary is the zero moment point boundary value of the robot, K p2 is a preset angle gain coefficient, K d2 is a preset angular velocity gain coefficient, K z2 is a preset zero moment point gain coefficient,/>Hip angular acceleration for the robot;
and controlling the robot to move according to the hip joint angular acceleration.
4. A robot control method according to any one of claims 1 to 3, further comprising:
Setting the first threshold and the second threshold according to:
Wherein, For the front sole distance of the robot, z is the mass center height of the robot, g is gravity acceleration, J is the upper body moment of inertia of the robot,/>Maximum angular acceleration of the hip joint of the robot, m being the mass of the robot,/>For the first threshold,/>Is the second threshold.
5. A robot control device, comprising:
the zero moment point determining module is used for determining a zero moment point measured value of the robot;
The anti-interference strategy selection module is used for selecting a mass center compliance strategy from a preset anti-interference strategy set as a target anti-interference strategy subset if the zero moment point measured value is smaller than or equal to a preset first threshold value; if the zero moment point measured value is larger than the first threshold value and smaller than a preset second threshold value, selecting a mass center compliance strategy and a hip joint control strategy from the anti-interference strategy set as the target anti-interference strategy subset; if the zero moment point measured value is larger than the second threshold value, selecting a centroid compliance strategy, a hip joint control strategy and a stepping strategy from the anti-interference strategy set as the target anti-interference strategy subset;
The robot control module is used for controlling the robot according to the target anti-interference strategy subset, and comprises the following steps: if the target anti-interference strategy subset comprises a stepping strategy, calculating the product of the length from the center of mass of the robot to a supporting point and the actual angle of the hip joint of the robot, and taking the opposite number of the ratio of the product to the preset circle frequency as the stepping step length of the robot; and controlling the robot to move according to the step length.
6. A computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps of the robot control method according to any one of claims 1 to 4.
7. A robot comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, realizes the steps of the robot control method according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110583417.5A CN113359791B (en) | 2021-05-27 | 2021-05-27 | Robot control method and device, computer readable storage medium and robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110583417.5A CN113359791B (en) | 2021-05-27 | 2021-05-27 | Robot control method and device, computer readable storage medium and robot |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113359791A CN113359791A (en) | 2021-09-07 |
| CN113359791B true CN113359791B (en) | 2024-06-18 |
Family
ID=77527838
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110583417.5A Active CN113359791B (en) | 2021-05-27 | 2021-05-27 | Robot control method and device, computer readable storage medium and robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113359791B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115933723B (en) * | 2023-01-04 | 2023-08-25 | 之江实验室 | Whole-body compliant control method applied to rapid walking of biped robot |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112276950A (en) * | 2020-10-21 | 2021-01-29 | 乐聚(深圳)机器人技术有限公司 | Anti-disturbance model training and control method, device, equipment, robot and medium |
| CN112486170A (en) * | 2020-11-23 | 2021-03-12 | 深圳市优必选科技股份有限公司 | Robot control method, device, computer readable storage medium and robot |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5355064A (en) * | 1992-03-04 | 1994-10-11 | Honda Giken Kogyo Kabushiki Kaisha | Control system for legged mobile robot |
| JP4905041B2 (en) * | 2006-10-06 | 2012-03-28 | 富士通株式会社 | Robot controller |
| WO2009067458A1 (en) * | 2007-11-21 | 2009-05-28 | Honda Motor Co., Ltd. | Learning capture points for humanoid push recovery |
| JP5071140B2 (en) * | 2008-02-14 | 2012-11-14 | トヨタ自動車株式会社 | Legged robot and control method thereof |
| US20120316682A1 (en) * | 2011-06-10 | 2012-12-13 | Samsung Electronics Co., Ltd. | Balance control apparatus of robot and control method thereof |
| CN110053684B (en) * | 2019-04-24 | 2021-06-01 | 哈尔滨理工大学 | Leg device and control of crawling robot suitable for slope road surface |
| CN111015653B (en) * | 2019-12-13 | 2021-06-04 | 深圳市优必选科技股份有限公司 | Robot control method, device, computer readable storage medium and robot |
| CN112051735B (en) * | 2020-08-19 | 2022-03-29 | 大连理工大学 | Humanoid robot walking control method |
-
2021
- 2021-05-27 CN CN202110583417.5A patent/CN113359791B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112276950A (en) * | 2020-10-21 | 2021-01-29 | 乐聚(深圳)机器人技术有限公司 | Anti-disturbance model training and control method, device, equipment, robot and medium |
| CN112486170A (en) * | 2020-11-23 | 2021-03-12 | 深圳市优必选科技股份有限公司 | Robot control method, device, computer readable storage medium and robot |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113359791A (en) | 2021-09-07 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111015653B (en) | Robot control method, device, computer readable storage medium and robot | |
| CN111377004B (en) | Biped robot gait control method and biped robot | |
| US12053885B2 (en) | Control method for robot, computer-readable storage medium and robot | |
| US20230271656A1 (en) | Robot state estimation method, computer-readable storage medium, and legged robot | |
| CN113253607B (en) | Gait planning method and device for ascending stairs, readable storage medium and robot | |
| CN113290559B (en) | Robot balance control method and device, robot control equipment and storage medium | |
| WO2009067458A1 (en) | Learning capture points for humanoid push recovery | |
| CA3086559C (en) | Method for predicting a motion of an object, method for calibrating a motion model, method for deriving a predefined quantity and method for generating a virtual reality view | |
| CN113050616A (en) | Control method for walking of biped robot and biped robot | |
| CN111208809B (en) | Robot gait planning method and terminal equipment | |
| CN113031579B (en) | Walking control method and device of biped robot and biped robot | |
| CN113064433A (en) | Robot stepping control method, robot stepping control device, robot control device, and storage medium | |
| CN113359791B (en) | Robot control method and device, computer readable storage medium and robot | |
| CN113146638A (en) | Centroid pose estimation method and device, computer readable storage medium and robot | |
| CN110986928A (en) | Real-time drift correction method for triaxial gyroscope of photoelectric pod | |
| CN112060078A (en) | Robot control method, device, computer readable storage medium and robot | |
| CN109866217B (en) | Robot mileage positioning method, device, terminal equipment and computer storage medium | |
| CN114489104B (en) | Robot stepping control method and device, robot control equipment and storage medium | |
| CN112486170B (en) | Robot control method and device, computer readable storage medium and robot | |
| CN112731951B (en) | Robot balance control method and device, readable storage medium and robot | |
| CN112597612B (en) | Robot optimization method, device, terminal equipment and computer readable storage medium | |
| CN112947398B (en) | Robot gait planning method and device, readable storage medium and robot | |
| CN111844013B (en) | Robot gait planning method and device, robot and storage medium | |
| CN114454981B (en) | Jumping motion control method and device of biped robot and biped robot | |
| CN113246124B (en) | Robot control method and device, computer readable storage medium and robot |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |