CN112486170A - Robot control method, device, computer readable storage medium and robot - Google Patents

Robot control method, device, computer readable storage medium and robot Download PDF

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Publication number
CN112486170A
CN112486170A CN202011319782.7A CN202011319782A CN112486170A CN 112486170 A CN112486170 A CN 112486170A CN 202011319782 A CN202011319782 A CN 202011319782A CN 112486170 A CN112486170 A CN 112486170A
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Prior art keywords
robot
moment point
zero moment
axis
mass center
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Inventor
陈春玉
刘益彰
葛利刚
谢铮
熊友军
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Ubtech Robotics Corp
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Ubtech Robotics Corp
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Priority to CN202011319782.7A priority Critical patent/CN112486170A/en
Priority to PCT/CN2020/140433 priority patent/WO2022105023A1/en
Publication of CN112486170A publication Critical patent/CN112486170A/en
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • 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

Abstract

The present application relates to the field of robotics, and in particular, to a robot control method, apparatus, computer-readable storage medium, and robot. The method comprises the steps of obtaining left foot stress information and right foot stress information of a robot; calculating a zero moment point of the body mass center of the robot according to the left foot stress information and the right foot stress information; updating the motion trail of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position; performing inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot; and controlling the robot to move according to each joint angle. Through this application, can be based on linear inverted pendulum model, adjust the joint angle of motion in real time according to the atress information of robot, even meet the interference of various external environment power or under the circumstances of ground unevenness, still can stably walk.

Description

Robot control method, device, computer readable storage medium and robot
Technical Field
The present application relates to the field of robotics, and in particular, to a robot control method, apparatus, computer-readable storage medium, and robot.
Background
In the prior art, a biped robot usually adopts a pure position planning gait walking method, and under the condition of meeting various external environment force interferences or uneven ground, the system stability is poor, stable walking is difficult, and even toppling may occur.
Disclosure of Invention
In view of this, embodiments of the present application provide a robot control method, an apparatus, a computer-readable storage medium, and a robot, so as to solve the problem that the system stability of the existing biped robot is poor when encountering interference of various external environmental forces or uneven ground.
A first aspect of an embodiment of the present application provides a robot control method, which may include:
acquiring left foot stress information and right foot stress information of the robot;
calculating a zero moment point of the body mass center of the robot according to the left foot stress information and the right foot stress information;
updating the motion trail of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position;
performing inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot;
and controlling the robot to move according to each joint angle.
Further, the motion trajectory of the robot is updated according to the zero moment point of the body centroid, so as to obtain an updated body centroid position, including:
acquiring an actual position, an expected position, an actual speed, an expected speed and an expected zero moment point of the mass center of the body;
calculating the compliance control acceleration of the robot according to the actual position, the expected position, the actual speed, the expected speed, the zero moment point and the expected zero moment point of the mass center of the body;
and updating the motion trail of the robot according to the compliant control acceleration to obtain the updated mass center position of the body.
Further, the calculating the compliance control acceleration of the robot according to the actual position, the expected position, the actual speed, the expected speed, the zero moment point and the expected zero moment point of the center of mass of the body comprises:
calculating the compliance control acceleration according to:
Figure BDA0002792505510000021
wherein x isdIs the desired position, xmIn order to be said actual position,
Figure BDA0002792505510000022
in order for the desired speed to be said,
Figure BDA0002792505510000023
is said actual speed, pbxdFor the desired zero moment point, pbxIs the zero moment point, kbpxIs a preset coefficient of proportionality term, kbpvFor a predetermined damping term coefficient, kbzmpxIs a preset zero moment point coefficient, abControlling acceleration for the compliance.
Further, the updating the motion trajectory of the robot according to the compliant control acceleration to obtain the updated body centroid position includes:
updating the motion trail of the robot according to the following formula:
x(0)＝ab
Figure BDA0002792505510000024
Figure BDA0002792505510000025
Figure BDA0002792505510000026
wherein, abFor the compliance control acceleration, k is the number of iterations, x (k) is the body centroid position for the kth iteration,
Figure BDA0002792505510000027
and the body mass center speed of the kth iteration is obtained, T is a time variable, and T is the gait cycle of the robot.
Further, the calculating a zero moment point of a body centroid of the robot according to the left foot stress information and the right foot stress information includes:
calculating a left foot zero moment point of the robot according to the left foot stress information;
calculating a right foot zero moment point of the robot according to the right foot stress information;
and calculating the zero moment point of the mass center of the body according to the left foot zero moment point and the right foot zero moment point.
Further, the calculating a left foot zero moment point of the robot according to the left foot stress information includes:
calculating the left foot zero moment point according to the following formula:
plx＝(-τly-flxd)/flz
ply＝(-τlx-flyd)/flz
pl＝[plx ply 0]T
wherein d is the distance from the preset sensor to the sole, olxIs the coordinate of the left foot zero moment point on the x axis, olyIs the coordinate of the left foot zero moment point on the y axis, flxIs the component of the force of the left foot force information on the x-axis, flyIs that it isForce component of left foot force information on y-axis, flzIs the component of the force of the left foot force information in the z-axis, taulxIs the moment component of the left foot stress information on the x axis, taulyIs the moment component of the left foot stress information on the y axis, plIs the left foot zero moment point;
the calculating the right foot zero moment point of the robot according to the right foot stress information comprises the following steps:
calculating the right foot zero moment point according to the following formula:
prx＝(-τry-frxd)/frz
pry＝(-τrx-fryd)/frz
pr＝[prx pry 0]T
wherein p isrxIs the coordinate of the right foot zero moment point on the x axis, pryIs the coordinate of the right foot zero moment point on the y axis, frxIs the component of the force of the right foot force information on the x-axis, fryIs the force component of the force information of the right foot on the y-axis, frzIs the component of the force information of the right foot in the z-axis, taurxIs the moment component of the force information of the right foot on the x axis, tauryIs the moment component of the force information of the right foot on the y axis, prIs the right foot zero moment point.
Further, the calculating the zero moment point of the center of mass of the body according to the left foot zero moment point and the right foot zero moment point comprises:
calculating the zero moment point of the mass center of the body according to the following formula:
Figure BDA0002792505510000041
Figure BDA0002792505510000042
pb＝[pbx pby 0]T
wherein lxIs the distance between the mass center of the body and the sensor on the x-axis,/yIs the distance between the centroid of the body and the sensor on the x-axis, pbxIs the coordinate of the zero moment point of the mass center of the body on the x axis, pbyIs a coordinate on the y-axis of the zero moment point of the body centroid, pbIs the zero moment point of the mass center of the body.
A second aspect of embodiments of the present application provides a robot control device, which may include:
the stress information acquisition module is used for acquiring the left foot stress information and the right foot stress information of the robot;
the zero moment point calculating module is used for calculating a zero moment point of the mass center of the body of the robot according to the left foot stress information and the right foot stress information;
the motion trail updating module is used for updating the motion trail of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position;
the inverse kinematics analysis module is used for carrying out inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot;
and the motion control module is used for controlling the robot to move according to each joint angle.
Further, the motion trail updating module may include:
the parameter acquisition unit is used for acquiring the actual position, the expected position, the actual speed, the expected speed and the expected zero moment point of the mass center of the body;
the acceleration calculation unit is used for calculating the compliance control acceleration of the robot according to the actual position, the expected position, the actual speed, the expected speed, the zero moment point and the expected zero moment point of the mass center of the body;
and the motion trail updating unit is used for updating the motion trail of the robot according to the compliant control acceleration to obtain the updated mass center position of the body.
Further, the acceleration calculation unit is specifically configured to calculate the compliance control acceleration according to the following formula:
Figure BDA0002792505510000051
wherein x isdIs the desired position, xmIn order to be said actual position,
Figure BDA0002792505510000052
in order for the desired speed to be said,
Figure BDA0002792505510000053
is said actual speed, pbxdFor the desired zero moment point, pbxIs the zero moment point, kbpxIs a preset coefficient of proportionality term, kbpvFor a predetermined damping term coefficient, kbzmpxIs a preset zero moment point coefficient, abControlling acceleration for the compliance.
Further, the motion trail updating unit is specifically configured to update the motion trail of the robot according to the following formula:
x(0)＝ab
Figure BDA0002792505510000054
Figure BDA0002792505510000055
Figure BDA0002792505510000056
wherein, abFor the compliance control acceleration, k is the number of iterations, x (k) is the body centroid position for the kth iteration,
Figure BDA0002792505510000057
and the body mass center speed of the kth iteration is obtained, T is a time variable, and T is the gait cycle of the robot.
Further, the zero moment point calculation module may include:
the left foot zero moment point calculating unit is used for calculating a left foot zero moment point of the robot according to the left foot stress information;
the right foot zero moment point calculating unit is used for calculating a right foot zero moment point of the robot according to the right foot stress information;
and the mass center zero moment point calculating unit is used for calculating the zero moment point of the mass center of the body according to the left foot zero moment point and the right foot zero moment point.
Further, the left foot zero moment point calculating unit is specifically configured to calculate the left foot zero moment point according to the following formula:
plx＝(-τly-flxd)/flz
ply＝(-τlx-flyd)/flz
pl＝[plx ply 0]T
wherein d is the preset distance from the sensor to the sole, plxIs the coordinate of the left foot zero moment point on the x axis, plyIs the coordinate of the left foot zero moment point on the y axis, flxIs the component of the force of the left foot force information on the x-axis, flyIs the force component of the left foot force information on the y-axis, flzIs the component of the force of the left foot force information in the z-axis, taulxIs the moment component of the left foot stress information on the x axis, taulyIs the moment component of the left foot stress information on the y axis, plIs the left foot zero moment point;
further, the right foot zero moment point calculating unit is specifically configured to calculate the right foot zero moment point according to the following formula:
prx＝(-τry-frxd)/frz
pry＝(-τrx-fryd)/frz
pr＝[prx pry 0]T
wherein o isrxIs the coordinate of the right foot zero moment point on the x axis, pryIs the coordinate of the right foot zero moment point on the y axis, frxIs the component of the force of the right foot force information on the x-axis, fryIs the force component of the force information of the right foot on the y-axis, frzIs the component of the force information of the right foot in the z-axis, taurxIs the moment component of the force information of the right foot on the x axis, tauryIs the moment component of the force information of the right foot on the y axis, prIs the right foot zero moment point.
Further, the centroid zero moment point calculation unit is specifically configured to calculate a zero moment point of the body centroid according to the following formula:
Figure BDA0002792505510000061
Figure BDA0002792505510000062
pb＝[pbx pby 0]T
wherein lxIs the distance between the mass center of the body and the sensor on the x-axis,/yIs the distance between the centroid of the body and the sensor on the x-axis, pbxIs the coordinate of the zero moment point of the mass center of the body on the x axis, pbyIs a coordinate on the y-axis of the zero moment point of the body centroid, pbIs the zero moment point of the mass center of the body.
A third aspect of embodiments of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the robot control methods described above.
A fourth aspect of the embodiments of the present application provides a robot, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of any one of the robot control methods when executing the computer program.
A fifth aspect of embodiments of the present application provides a computer program product, which, when run on a robot, causes 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 advantages that: according to the embodiment of the application, the left foot stress information and the right foot stress information of the robot are obtained; calculating a zero moment point of the body mass center of the robot according to the left foot stress information and the right foot stress information; updating the motion trail of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position; performing inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot; and controlling the robot to move according to each joint angle. Through this application embodiment, can be based on linear inverted pendulum model, adjust the joint angle of motion in real time according to the atress information of robot, be favorable to improving the stability of robot walking in-process, even meet under the interference of various external environment power or the circumstances of ground unevenness, still can stably walk, greatly promoted the performance of robot.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed for the embodiments or the prior art descriptions 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 it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flowchart illustrating an embodiment of a robot balancing control method according to an embodiment of the present disclosure;
FIG. 2 is a schematic view of a sensor arrangement;
FIG. 3 is a schematic diagram of left foot force information and right foot force information;
FIG. 4 is a diagram of a specific force situation of a six-dimensional force sensor;
FIG. 5 is a schematic flow chart of calculating the zero moment point of the body centroid of the robot from the left foot force information and the right foot force information;
FIG. 6 is a schematic diagram of a linear inverted pendulum model;
FIG. 7 is a schematic flow chart of updating the motion trajectory of the robot according to the zero moment point of the center of mass of the body;
FIG. 8 is a block diagram of one embodiment of a robot controller according to an embodiment of the present disclosure;
fig. 9 is a schematic block diagram of a robot in an embodiment of the present application.
Detailed Description
In order to make the objects, features and advantages of the present invention more apparent and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the embodiments described below are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It will 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 present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application 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 this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
In addition, in the description of the present application, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, an embodiment of a robot control method in an embodiment of the present application may include:
and S101, acquiring left foot stress information and right foot stress information of the robot.
In the embodiment of the present application, as shown in fig. 2, sensors may be respectively disposed at positions where both feet and legs of the robot are connected, so as to acquire left foot stress information and right foot stress information of the robot.
Preferably, the sensor may be a six-dimensional force sensor, and can simultaneously detect the left foot stress information and the right foot stress information in the three-dimensional space in the plantar coordinate system shown in fig. 3, and the specific stress situation is shown in fig. 4. The left foot force information includes force components and moment components in the directions of three coordinate axes (i.e., x-axis, y-axis, and z-axis shown in fig. 3), and the right foot force information also includes force components and moment components in the directions of the three coordinate axes.
Here, the left foot force information is recorded as:
Fl＝[flx fly flz τlx τly τlz]T
wherein f islxIs the component of the force of the left foot force information on the x-axis, flyIs the force component of the left foot force information on the y-axis, flzIs the component of the force of the left foot force information in the z-axis, taulxIs the moment component of the left foot stress information on the x axis, taulyIs the moment component of the left foot stress information on the y axis, taulzMoment components of the left foot stress information on the z-axis are obtained.
Recording the right foot stress information as:
Fr＝[frx fry frz τrx τry τrz]T
wherein f isrxIs the component of the force of the right foot force information on the x-axis, fryIs the force component of the force information of the right foot on the y-axis, frzIs the component of the force information of the right foot in the z-axis, taurxIs the moment component of the force information of the right foot on the x axis, tauryIs the moment component of the force information of the right foot on the y axis, taurzMoment components of the right foot stress information on the z-axis.
And S102, calculating a zero moment point of the body mass center of the robot according to the left foot stress information and the right foot stress information.
As shown in fig. 5, step S102 may specifically include the following steps:
and S1021, calculating a Zero Moment Point (ZMP) of the left foot of the robot according to the left foot stress information.
Specifically, the left foot zero moment point may be calculated according to the following equation:
plx＝(-τly-flxd)/fllz
ply＝(-τlx-flyd)/flz
pl＝[plx ply 0]T
wherein d is the distance from the sensor to the sole of the foot, plxIs the coordinate of the left foot zero moment point on the x axis, plyIs the coordinate of the left foot zero moment point on the y axis, plIs the left foot zero moment point.
And S1022, calculating a right foot zero moment point of the robot according to the right foot stress information.
Specifically, the right foot zero moment point may be calculated according to the following equation:
prx＝(-τry-frxd)/frz
pry＝(-τrx-fryd)/frz
pr＝[orx ory 0]T
wherein o isrxIs the coordinate of the right foot zero moment point on the x axis, pryIs the coordinate of the right foot zero moment point on the y axis, prIs the right foot zero moment point.
And S1023, calculating a zero moment point of the mass center of the body according to the left foot zero moment point and the right foot zero moment point.
Specifically, the zero moment point of the centroid of the body can be calculated according to the following formula:
Figure BDA0002792505510000111
Figure BDA0002792505510000112
pb＝[pbx pby 0]T
wherein lxIs the distance between the mass center of the body and the sensor on the x-axis,/yIs the distance between the centroid of the body and the sensor on the x-axis, pbxIs the coordinate of the zero moment point of the mass center of the body on the x axis, pbyIs a coordinate on the y-axis of the zero moment point of the body centroid, pbIs the zero moment point of the mass center of the body.
And S103, updating the motion track of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position.
In order to enable the robot to better adapt to different external interferences, a compliance control algorithm based on a linear inverted pendulum model is adopted in the embodiment of the application, namely, a spring mass block model is designed on the mass module part based on the motion law of the linear inverted pendulum model shown in fig. 6, so that compliance control over the body is realized.
The stress analysis of the linear inverted pendulum model is as follows:
F＝k(0-x)
wherein x is the deformation amount of the spring, k is the elastic coefficient of the spring, 0 means that the deformation amount of the spring should be 0 under the normal motion condition of the linear inverted pendulum model, and F is the acting force borne by the linear inverted pendulum model.
To better implement the method in a robot, the force can be represented by a zero moment point. Step S103 may specifically include the steps shown in fig. 7:
and step S1031, acquiring the actual position, the expected position, the actual speed, the expected speed and the expected zero moment point of the mass center of the body.
And step S1032, calculating the compliance control acceleration of the robot according to the actual position, the expected position, the actual speed, the expected speed, the zero moment point and the expected zero moment point of the mass center of the body.
Specifically, the compliant control acceleration may be calculated according to:
Figure BDA0002792505510000113
wherein x isdIs the desired position, xmIn order to be said actual position,
Figure BDA0002792505510000121
in order for the desired speed to be said,
Figure BDA0002792505510000122
is said actual speed, pbxdFor the desired zero moment point, pbxIs the zero moment point, kbpxIs a preset coefficient of proportionality term, kbpvFor a predetermined damping term coefficient, kbzmpxIs a preset zero moment point coefficient, abControlling acceleration for the compliance. It should be noted that, since the control process on the x-axis is similar to the control process on the y-axis, in the embodiment of the present application, only the control process on the x-axis is taken as an example for description, so that the physical quantities in the previous formula and the subsequent formula are both components on the x-axis, the control process on the y-axis may refer to the control process on the x-axis, and only the corresponding physical quantities need to be replaced by the components on the y-axis.
And S1033, updating the motion trail of the robot according to the compliant control acceleration to obtain the updated mass center position of the body.
Specifically, the motion trajectory of the robot may be updated according to the following formula:
x(0)＝ab
Figure BDA0002792505510000123
Figure BDA0002792505510000124
Figure BDA0002792505510000125
wherein k is the number of iterations, x (k) is the location of the ontology centroid for the kth iteration,
Figure BDA0002792505510000126
and the body mass center speed of the kth iteration is obtained, T is a time variable, and T is the gait cycle of the robot.
And S104, performing inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot.
The inverse kinematics analysis is an analysis method commonly used in the field of existing robot technologies, and specifically, reference may be made to any inverse kinematics analysis process in the prior art, which is not described in detail herein for the embodiments of the present application.
Each joint angle of the left leg comprises six joint angles, namely a left leg hip joint pitch angle, a left leg hip joint yaw angle, a left leg hip joint roll angle, a left leg knee joint pitch angle, a left leg ankle joint pitch angle and a left leg ankle joint roll angle, and the six joint angles are recorded as follows: thetal＝[θl1 θl2 θl3 θl4 θl5 θl6]T。
Each joint angle of the right leg comprises six joint angles, namely a right leg hip joint pitch angle, a right leg hip joint yaw angle, a right leg hip joint roll angle, a right leg knee joint pitch angle, a right leg ankle joint pitch angle and a right leg ankle joint roll angle, and the six joint angles are recorded as follows: thetar＝[θr1 θr2 θr3 θr4 θr5 θr6]T。
And S105, controlling the robot to move according to each joint angle.
After the joint angles of the left leg and the right leg of the robot are obtained through calculation, the robot can be controlled to move according to the joint angles, and therefore the flexible control of the robot body is achieved.
In summary, the embodiment of the application acquires the left foot stress information and the right foot stress information of the robot; calculating a zero moment point of the body mass center of the robot according to the left foot stress information and the right foot stress information; updating the motion trail of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position; performing inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot; and controlling the robot to move according to each joint angle. Through this application embodiment, can be based on linear inverted pendulum model, adjust the joint angle of motion in real time according to the atress information of robot, be favorable to improving the stability of robot walking in-process, even meet under the interference of various external environment power or the circumstances of ground unevenness, still can stably walk, greatly promoted the performance of robot.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.
Fig. 8 is a block diagram of an embodiment of a robot control apparatus according to an embodiment of the present application, which corresponds to a robot control method according to the foregoing embodiment.
In this embodiment, a robot control apparatus may include:
a stress information acquiring module 801, configured to acquire left foot stress information and right foot stress information of the robot;
a zero moment point calculation module 802, configured to calculate a zero moment point of a body centroid of the robot according to the left foot stress information and the right foot stress information;
a motion trajectory updating module 803, configured to update the motion trajectory of the robot according to the zero moment point of the body centroid based on a preset linear inverted pendulum model, so as to obtain an updated body centroid position;
an inverse kinematics analysis module 804, configured to perform inverse kinematics analysis on the updated body centroid position to obtain each joint angle of the left leg and the right leg of the robot;
and a motion control module 805 for controlling the robot to move according to the joint angles.
Further, the motion trail updating module may include:
the parameter acquisition unit is used for acquiring the actual position, the expected position, the actual speed, the expected speed and the expected zero moment point of the mass center of the body;
the acceleration calculation unit is used for calculating the compliance control acceleration of the robot according to the actual position, the expected position, the actual speed, the expected speed, the zero moment point and the expected zero moment point of the mass center of the body;
and the motion trail updating unit is used for updating the motion trail of the robot according to the compliant control acceleration to obtain the updated mass center position of the body.
Further, the acceleration calculation unit is specifically configured to calculate the compliance control acceleration according to the following formula:
Figure BDA0002792505510000141
wherein x isdIs the desired position, xmIn order to be said actual position,
Figure BDA0002792505510000142
in order for the desired speed to be said,
Figure BDA0002792505510000143
is said actual speed, pbxdFor the desired zero moment point, pbxIs the zero moment point, kbpxIs a preset coefficient of proportionality term, kbpvFor a predetermined damping term coefficient, kbzmpxIs a preset zero moment point coefficient, abControlling acceleration for the compliance.
Further, the motion trail updating unit is specifically configured to update the motion trail of the robot according to the following formula:
x(0)＝ab
Figure BDA0002792505510000144
Figure BDA0002792505510000145
Figure BDA0002792505510000146
wherein, abFor the compliance control acceleration, k is the number of iterations, x (k) is the body centroid position for the kth iteration,
Figure BDA0002792505510000147
and the body mass center speed of the kth iteration is obtained, T is a time variable, and T is the gait cycle of the robot.
Further, the zero moment point calculation module may include:
the left foot zero moment point calculating unit is used for calculating a left foot zero moment point of the robot according to the left foot stress information;
the right foot zero moment point calculating unit is used for calculating a right foot zero moment point of the robot according to the right foot stress information;
and the mass center zero moment point calculating unit is used for calculating the zero moment point of the mass center of the body according to the left foot zero moment point and the right foot zero moment point.
Further, the left foot zero moment point calculating unit is specifically configured to calculate the left foot zero moment point according to the following formula:
plx＝(-τly-flxd)/flz
ply＝(-τlx-flyd)/flz
pl＝[plx ply 0]T
wherein d is the preset distance from the sensor to the sole, plxIs the coordinate of the left foot zero moment point on the x axis, plyIs the coordinate of the left foot zero moment point on the y axis, flxIs the component of the force of the left foot force information on the x-axis, flyIs the force component of the left foot force information on the y-axis, flzIs the component of the force of the left foot force information in the z-axis, taulxIs the moment component of the left foot stress information on the x axis, taulyIs the moment component of the left foot stress information on the y axis, plIs the left foot zero moment point;
further, the right foot zero moment point calculating unit is specifically configured to calculate the right foot zero moment point according to the following formula:
prx＝(-τry-frxd)/frz
pry＝(-τrx-fryd)/frz
pr＝[prx pry 0]T
wherein p isrxIs the coordinate of the right foot zero moment point on the x axis, pryIs the coordinate of the right foot zero moment point on the y axis, frxIs the component of the force of the right foot force information on the x-axis, fryIs the force component of the force information of the right foot on the y-axis, frzIs the component of the force information of the right foot in the z-axis, taurxIs the moment component of the force information of the right foot on the x axis, tauryIs the moment component of the force information of the right foot on the y axis, prIs the right foot zero moment point.
Further, the centroid zero moment point calculation unit is specifically configured to calculate a zero moment point of the body centroid according to the following formula:
Figure BDA0002792505510000161
Figure BDA0002792505510000162
pb＝[pbx pby 0]T
wherein lxIs the distance between the mass center of the body and the sensor on the x-axis,/yIs the distance between the centroid of the body and the sensor on the x-axis, pbxIs the coordinate of the zero moment point of the mass center of the body on the x axis, pbyIs a coordinate on the y-axis of the zero moment point of the body centroid, pbIs the zero moment point of the mass center of the body.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses, modules and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Fig. 9 shows a schematic block diagram of a robot provided in an embodiment of the present application, and only a part related to the embodiment of the present application is shown for convenience of explanation.
As shown in fig. 9, the robot 9 of this embodiment includes: a processor 90, a memory 91 and a computer program 92 stored in said memory 91 and executable on said processor 90. The processor 90, when executing the computer program 92, implements the steps in the various robot control method embodiments described above, such as steps S101 to S105 shown in fig. 1. Alternatively, the processor 90, when executing the computer program 92, implements the functions of each module/unit in the above-described device embodiments, such as the functions of the modules 801 to 805 shown in fig. 8.
Illustratively, the computer program 92 may be partitioned into one or more modules/units that are stored in the memory 91 and executed by the processor 90 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 92 in the robot 9.
Those skilled in the art will appreciate that fig. 9 is merely an example of a robot 9 and does not constitute a limitation of the robot 9 and may include more or fewer components than shown, or some components in combination, or different components, for example, the robot 9 may also include input and output devices, network access devices, buses, etc.
The Processor 90 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 91 may be an internal storage unit of the robot 9, such as a hard disk or a memory of the robot 9. The memory 91 may also be an external storage device of the robot 9, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like provided on the robot 9. Further, the memory 91 may also include both an internal storage unit and an external storage device of the robot 9. The memory 91 is used for storing the computer program and other programs and data required by the robot 9. The memory 91 may also be used to temporarily store 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-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
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 implementation. 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 above-described embodiments of the apparatus/robot are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the embodiments described above can be realized by a computer program, which can be stored in a computer-readable storage medium and can realize the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an 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, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable storage medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable storage media that does not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims (10)

1. A robot control method, comprising:
acquiring left foot stress information and right foot stress information of the robot;
calculating a zero moment point of the body mass center of the robot according to the left foot stress information and the right foot stress information;
updating the motion trail of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position;
performing inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot;
and controlling the robot to move according to each joint angle.
2. The robot control method according to claim 1, wherein the updating the motion trajectory of the robot according to the zero moment point of the body centroid to obtain an updated body centroid position comprises:
acquiring an actual position, an expected position, an actual speed, an expected speed and an expected zero moment point of the mass center of the body;
calculating the compliance control acceleration of the robot according to the actual position, the expected position, the actual speed, the expected speed, the zero moment point and the expected zero moment point of the mass center of the body;
and updating the motion trail of the robot according to the compliant control acceleration to obtain the updated mass center position of the body.
3. A robot control method according to claim 2, wherein said calculating a compliance control acceleration of the robot from the actual position of the body centre of mass, the desired position, the actual velocity, the desired velocity, the zero moment point and the desired zero moment point comprises:
calculating the compliance control acceleration according to:
Figure FDA0002792505500000011
wherein x isdIs the desired position, xmIn order to be said actual position,
Figure FDA0002792505500000012
in order for the desired speed to be said,
Figure FDA0002792505500000013
is said actual speed, pbxdFor the desired zero moment point, pbxIs the zero moment point, kbpxIs a preset coefficient of proportionality term, kbpvFor a predetermined damping term coefficient, kbzmpxIs a preset zero moment point coefficient, abControlling acceleration for the compliance.
4. The robot control method of claim 2, wherein the updating the motion trajectory of the robot according to the compliant control acceleration to obtain the updated body centroid position comprises:
updating the motion trail of the robot according to the following formula:
x(0)＝ab
Figure FDA0002792505500000021
Figure FDA0002792505500000022
Figure FDA0002792505500000023
wherein, abFor the compliance control acceleration, k is the number of iterations, x (k) is the body centroid position for the kth iteration,
Figure FDA0002792505500000024
and the body mass center speed of the kth iteration is obtained, T is a time variable, and T is the gait cycle of the robot.
5. The robot control method according to any one of claims 1 to 4, wherein the calculating a zero moment point of a body centroid of the robot from the left foot force information and the right foot force information includes:
calculating a left foot zero moment point of the robot according to the left foot stress information;
calculating a right foot zero moment point of the robot according to the right foot stress information;
and calculating the zero moment point of the mass center of the body according to the left foot zero moment point and the right foot zero moment point.
6. The robot control method of claim 5, wherein the calculating a left foot zero moment point of the robot from the left foot force information comprises:
calculating the left foot zero moment point according to the following formula:
plx＝(-τly-flxd)/flz
ply＝(-τlx-flyd)/flz
pl＝[plx ply 0]T
wherein d is the preset distance from the sensor to the sole, plxIs a stand forThe coordinate of the left foot zero moment point on the x axis, plyIs the coordinate of the left foot zero moment point on the y axis, flxIs the component of the force of the left foot force information on the x-axis, flyIs the force component of the left foot force information on the y-axis, flzIs the component of the force of the left foot force information in the z-axis, taulxIs the moment component of the left foot stress information on the x axis, taulyIs the moment component of the left foot stress information on the y axis, plIs the left foot zero moment point;
the right foot zero moment point of the robot is calculated according to the right foot stress information, and the method comprises the following steps:
calculating the right foot zero moment point according to the following formula:
prx＝(-τry-frxd)/frz
pry＝(-τrx-fryd)/frz
pr＝[prx pry 0]T
wherein p isrxIs the coordinate of the right foot zero moment point on the x axis, pryIs the coordinate of the right foot zero moment point on the y axis, frxIs the component of the force of the right foot force information on the x-axis, fryIs the force component of the force information of the right foot on the y-axis, frzIs the component of the force information of the right foot in the z-axis, taurxIs the moment component of the force information of the right foot on the x axis, tauryIs the moment component of the force information of the right foot on the y axis, prIs the right foot zero moment point.
7. The robot control method of claim 6, wherein said calculating a zero moment point of the center of mass of the body from the left foot zero moment point and the right foot zero moment point comprises:
calculating the zero moment point of the mass center of the body according to the following formula:
Figure FDA0002792505500000031
Figure FDA0002792505500000032
pb＝[pbx pby 0]T
wherein lxIs the distance between the mass center of the body and the sensor on the x-axis,/yIs the distance between the centroid of the body and the sensor on the x-axis, pbxIs the coordinate of the zero moment point of the mass center of the body on the x axis, pbyIs a coordinate on the y-axis of the zero moment point of the body centroid, pbIs the zero moment point of the mass center of the body.
8. A robot control apparatus, comprising:
the stress information acquisition module is used for acquiring the left foot stress information and the right foot stress information of the robot;
the zero moment point calculating module is used for calculating a zero moment point of the mass center of the body of the robot according to the left foot stress information and the right foot stress information;
the motion trail updating module is used for updating the motion trail of the robot according to the zero moment point of the body mass center based on a preset linear inverted pendulum model to obtain an updated body mass center position;
the inverse kinematics analysis module is used for carrying out inverse kinematics analysis on the updated body mass center position to obtain each joint angle of the left leg and the right leg of the robot;
and the motion control module is used for controlling the robot to move according to each joint angle.
9. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the robot control method according to any one of claims 1 to 7.
10. 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 realizes the steps of the robot control method according to any of claims 1 to 7 when executing the computer program.
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