CN115857532A - Gait trajectory planning method, device and system - Google Patents
Gait trajectory planning method, device and system Download PDFInfo
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Abstract
The invention relates to the technical field of robot control, in particular to a gait track planning method, a device and a system, which are used for adjusting the gait track of a robot, and the method comprises the following steps: acquiring real-time sole pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle, and calculating ideal leg length variation by adopting a first preset algorithm according to the real-time sole pressure data and the ideal sole pressure data; then, according to the ideal leg length variation, the maximum distance value from the hip joint to the ankle joint of the robot, the calf length and the thigh length of the robot, an ideal adjusting angle is calculated by adopting a second preset algorithm; finally, the motion trail of the knee joint of the robot is adjusted in real time according to the ideal adjusting angle, so that the robot can realize flexible knee bending action of the leg after contacting the ground, the impact force of the foot and the ground is reduced, and the performances of stability, comfort and the like of equipment are improved.
Description
Technical Field
The invention relates to the technical field of robot control, in particular to a gait track planning method, device and system.
Background
The gait track planning of the existing foot type robot or exoskeleton robot mostly adopts the gait planning based on human body motion capture data, and the method collects the motion data of hip, knee and ankle joints when a normal person normally walks and applies the motion data to the joints of the robot directly or after fitting. For the exoskeleton robot, only the joint motion data of the hip and the knee are used, and the ankle joint is connected by a passive element and does not need to be actively driven. The method has the greatest advantage of simplifying the complexity of gait planning and enabling the robot to obtain the humanoid walking gait.
The collected gait track or the fitted humanoid track is directly adopted to control the lower limb exoskeleton to walk, when the swing foot touches the ground, the speed of the center of mass (CoM) of the human exoskeleton system can be reoriented and impact force acting on the sole of the foot is generated, as shown in figure 1. In the swing phase, the body mass center rotates around the ankle joint of the supporting leg (rear leg), in the moment of the swing leg (front leg) contacting the ground, the body mass center is converted into rotation around the ankle joint of the swing leg, the speed of the mass center changes suddenly, a large foot-ground collision impact force can be generated to act on the human body and the exoskeleton, at the moment, the lower limb joints of the exoskeleton still move according to a predefined track, the exoskeleton joints are rigid to the action of external force, a cushioning and damping knee bending action can not be generated to relieve the impact force, the patient can be uncomfortable or even injured due to the large and frequent impact force, and the equipment can also be damaged.
Disclosure of Invention
The invention aims to provide a gait track planning method, which can adjust the motion track of a knee joint at the moment of touchdown so as to realize flexible knee bending action of a leg and reduce the impact force applied to the body.
Another object of the present invention is to provide a gait path planning device, which can adjust the motion path of the knee joint at the moment of touchdown to realize the flexible knee bending motion of the leg, thereby reducing the impact force on the body.
Another objective of the present invention is to provide a gait path planning system, which can adjust the motion path of the knee joint at the moment of touchdown to realize the flexible knee bending motion of the leg, thereby reducing the impact force on the body.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides a gait trajectory planning method, where the method is used to adjust a gait trajectory of a robot, and the method includes: collecting real-time plantar pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle; calculating the ideal leg length variation by adopting a first preset algorithm according to the real-time sole pressure data and the ideal sole pressure data; calculating an ideal adjusting angle by adopting a second preset algorithm according to the ideal leg length variation, the maximum distance value from the center of mass of the robot to the ankle joint, the shank length and the thigh length of the robot; and adjusting the motion trail of the knee joint of the robot in real time according to the ideal adjusting angle.
In a second aspect, an embodiment of the present invention further provides a gait trajectory planning apparatus, where the apparatus is configured to adjust a gait trajectory of a robot, and the apparatus includes: the acquisition module is used for acquiring real-time plantar pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle; the first calculation module is used for calculating the ideal leg length variation by adopting a first preset algorithm according to the real-time sole pressure data and the ideal sole pressure data; the second calculation module is used for calculating an ideal adjusting angle by adopting a second preset algorithm according to the ideal leg length variation, the maximum distance value from the center of mass of the robot to the ankle joint, the shank length and the thigh length of the robot; and the adjusting module is used for adjusting the motion trail of the knee joint of the robot in real time according to the ideal adjusting angle.
In a third aspect, an embodiment of the present invention further provides a gait trajectory planning system, where the system is configured to adjust a gait trajectory of a robot, and the system includes: the pressure sensor is arranged on the sole of the robot and used for acquiring real-time sole pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle; the impedance controller is used for receiving the real-time plantar pressure data and calculating the ideal leg length variation by adopting a first preset algorithm according to the real-time plantar pressure data and the ideal plantar pressure data; the knee joint controller comprises an inverse kinematics resolver and a first PID (proportion integration differentiation) controller, wherein the inverse kinematics resolver is used for calculating an ideal adjusting angle according to the ideal leg length variation, the maximum distance value from the center of mass of the robot to the ankle joint, the shank length and the thigh length of the robot; the first PID controller is used for adjusting the motion trail of the knee joint of the robot in real time according to the ideal adjusting angle.
The embodiment of the invention provides a gait track planning method, a device and a system, which are used for adjusting the gait track of a robot, and the method comprises the following steps: acquiring real-time plantar pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle, and calculating the ideal leg length variation by adopting a first predetermined algorithm according to the real-time plantar pressure data and the ideal plantar pressure data; then, according to the ideal leg length variation, the maximum distance value from the center of mass of the robot to the ankle joint, the shank length and the thigh length of the robot, an ideal adjusting angle is calculated by adopting a second preset algorithm; and finally, adjusting the motion trail of the knee joint of the robot in real time according to the ideal adjusting angle, so that the flexible knee bending action of the leg part can be realized, and the impact damage to equipment or the body is avoided.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 shows a prior art scenario diagram.
Fig. 2 is a schematic structural diagram illustrating a gait trajectory planning system according to an embodiment of the present invention.
Fig. 3 shows a schematic diagram of a motion state of a robot provided by an embodiment of the present invention.
Fig. 4 is a schematic diagram illustrating an operation logic of an impedance controller according to an embodiment of the present invention.
Fig. 5 is a schematic diagram illustrating a control logic of a knee joint controller according to an embodiment of the present invention.
Fig. 6 is a schematic diagram illustrating a comparison between a predefined knee joint trajectory and an adjusted target trajectory of a knee joint according to an embodiment of the present invention.
Fig. 7 is a flowchart illustrating a gait trajectory planning method according to an embodiment of the present invention.
Fig. 8 is a schematic functional block diagram of a gait trajectory planning device according to an embodiment of the present invention.
The figure is as follows:
100-a gait trajectory planning system; 110-a pressure sensor; 120-an inertial sensor; 130-an impedance controller; 140-knee joint controller; 141-inverse kinematics solver; 142-a first PID controller; 150-a second PID controller; 200-a gait trajectory planning device; 210-an acquisition module; 220-a first calculation module; 230-a second calculation module; 240-adjustment module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Fig. 2 is a schematic structural diagram of a gait track planning system 100 according to an embodiment of the present invention, where the gait track planning system 100 is used to adjust a gait track of a robot, the robot includes a legged robot or an exoskeleton robot, and the gait track of the robot is adjusted to make a driving track of the robot smoother, so that neither the device itself nor a human body wearing the exoskeleton robot is injured by an impact force of a rigid motion.
The gait trajectory planning system 100 is mounted on a robot and includes a pressure sensor 110, an inertial sensor 120, an impedance controller 130, a knee joint controller 140, and a second PID controller 150, wherein the knee joint controller 140 includes an inverse kinematics resolver 141 and a first PID controller 142. The first PID controller 142 and the second PID controller 150 are used to control the movement locus of different joint portions of the robot, respectively. Further, a PID controller (Proportion-Integration-differentiation controller) is composed of a proportional unit P, an integral unit I and a differentiation unit D, and is mainly suitable for a system whose basic linearity and dynamic characteristics do not change with time through setting three parameters of Kp, ki and Kd.
Referring to fig. 3, which is a schematic view illustrating a motion state of a robot according to an embodiment of the present invention, the pressure sensor 110 is disposed at a sole position of a legged robot or an exoskeleton robot, and is configured to collect real-time sole pressure data f (t) after a swing leg of the robot touches the ground in a current gait cycle, and feed the real-time sole pressure data back to the impedance controller 130 in time.
As can be seen from fig. 3, when the swing leg of the robot touches the ground, the distance between the hip joint and the ankle joint of the swing leg is defined as x, and the angle θ between the connection line and the vertical direction is defined as 1 The angle theta 1 Can be measured by the inertial sensor 120 arranged in the lower-limb exoskeleton robot or the foot type robot, and further can obtain the included angle theta through measurement 1 Calculating ideal plantar pressure data f r The calculation method is as follows:
mu is the ratio of the gravity borne by the swing leg in the stepping posture to the integral gravity of the human-exoskeleton system, and can be directly measured in a static state when the human-computer system steps one step or obtained by estimating body mass distribution; m is the total mass of the human-exoskeleton; and due to ideal plantar pressure data f r Is a constant value, so that the angle theta is measured 1 And is also an ideal value, i.e. the angle at which the body is not subjected to impact forces.
Further, the impedance controller 130 calculates the ideal variation of the leg length by using a first predetermined algorithm according to the real-time sole pressure data and the ideal sole pressure data. The ideal leg length variation, which is the variation distance from the hip joint to the ankle joint of the robot, makes the corresponding change, i.e., does not generate a large impact force. Fig. 4 is a schematic diagram of the operation logic of the impedance controller 130 according to an embodiment of the present invention, wherein the real-time plantar pressure data f (t) and the ideal plantar pressure data f (t) r For input, m is the weight of the human machine system, k and c represent the predefined stiffness and damping coefficients, respectively, s is the complex frequency, and the output of the impedance controller Δ x (t) is the ideal leg length variation.
Further, when the ideal leg length variation is output from the impedance controller 130, the ideal leg length variation is timely transmitted to the inverse kinematics resolver 141 of the knee joint controller 140, and the inverse kinematics resolver 141 is used for calculating the maximum distance value x from the hip joint to the ankle joint of the robot according to the ideal leg length variation and the ideal leg length variation 0 Length l of robot shank c And thigh length l t Calculating an ideal adjustment angleMeanwhile, fig. 5 is a schematic diagram of a control logic of the knee joint controller 140 according to an embodiment of the present invention. The specific algorithm is as follows:
x(t)＝x 0 -Δx(t)
where Δ x (t) is the ideal leg length variation, x 0 Is the maximum distance value from the hip joint to the ankle joint of the robot, l c The length of the lower leg of the robot, l t Is the thigh length of the robot, [ theta ] r [ (S) ] t ) The angle is adjusted ideally.
Furthermore, the first PID controller 142 of the knee joint controller 140 adjusts the motion trajectory of the knee joint of the robot in real time according to the calculated ideal adjustment angle, so as to realize the flexible knee bending action of the leg of the robot, thereby reducing the impact force applied to the human body.
It should be noted that, when the swing leg of the robot is not in the ground contact stage, that is, when no impact force is generated to cause impact force damage to the robot or the human body, the first PID controller 142 adjusts the knee joint motion of the robot according to a predefined knee joint trajectory, which is a predefined human-like joint trajectory that can be derived from the human motion capture data and the fitting data thereof, and specifically includes the time series data of the motion angle of the knee joint in one gait cycle. When the swing leg of the robot touches the ground, the motion angle of the knee joint of the robot is adjusted, so that the damage to equipment or a human body caused by large impact force generated when the swing leg touches the ground is well avoided.
The motion of the hip joint is controlled by the second PID controller 150, and whether the swing leg of the robot is in the touchdown or touchless stage, the second PID controller 150 adjusts the motion of the hip joint of the robot according to a predefined hip joint track, wherein the predefined hip joint track comprises time sequence data of the motion angle of the hip joint in one gait cycle.
Fig. 6 is a schematic diagram illustrating a comparison between a predefined knee joint trajectory and an adjusted target trajectory of a knee joint according to an embodiment of the present invention, and it can be seen from the diagram that the predefined knee joint trajectory can be directly adopted for the trajectory planning of the swing leg of the robot, as shown by a solid line. A typical knee joint trajectory diagram obtained by the trajectory planning method provided by the present solution is shown by a dotted line. The idea of the trajectory planning method provided by the scheme is that the impedance controller is added at the position of the knee joint of the robot, so that flexible buffering and shock absorption are realized. Specifically, the flexible knee bending action of the leg can be realized by controlling the motion track of the knee joint so as to reduce the impact force to the human body.
Fig. 7 is a schematic flow chart of a gait trajectory planning method according to an embodiment of the present invention, the method is used for adjusting a gait trajectory of a robot, and the method includes:
and S110, acquiring real-time sole pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle.
Specifically, the pressure sensor 110 disposed at the sole position of the foot-type robot or exoskeleton robot collects real-time sole pressure data f (t) after the swing leg of the robot touches the ground in the current gait cycle, and feeds back the real-time sole pressure data to the impedance controller 130 in time.
And S120, calculating the ideal leg length variation by adopting a first preset algorithm according to the real-time sole pressure data and the ideal sole pressure data.
Specifically, as can be seen from fig. 3, when the swing leg of the robot touches the ground, the distance between the hip joint and the ankle joint of the swing leg can be defined as x, and the angle between the line and the vertical direction is θ 1 The angle theta 1 Can be measured by the inertial sensor 120 arranged in the lower-limb exoskeleton robot or the foot type robot, and further can obtain the included angle theta through measurement 1 Calculating ideal plantar pressure data f r The calculation method is as follows:
mu is the ratio of the gravity borne by the swing leg in the stepping posture to the integral gravity of the human-exoskeleton system, and can be directly measured in a static state when the human-computer system steps one step or obtained by estimating body mass distribution; m is the total mass of the human-exoskeleton; and due to ideal plantar pressure data f r Is a constant value, so that the angle theta is measured 1 And is also an ideal value, i.e. the angle at which the body is not subjected to impact forces.
Further, the impedance controller 130 calculates the ideal leg length variation according to the real-time sole pressure data and the ideal sole pressure data by using a first predetermined algorithm. The ideal leg length variation, i.e., the leg of the robot, makes the corresponding change, i.e., no large impact force is generated. Fig. 4 is a schematic diagram of the operation logic of the impedance controller 130 according to an embodiment of the present invention, wherein the real-time plantar pressure data f (t) and the ideal plantar pressure data f (t) r For input, m is the weight of the human machine system, k and c represent the predefined stiffness and damping coefficients, respectively, s is the complex frequency, and the output of the impedance controller Δ x (t) is the ideal leg length variation.
And S130, calculating an ideal adjusting angle by adopting a second preset algorithm according to the ideal leg length variation, the maximum distance value from the hip joint to the ankle joint of the robot, the calf length and the thigh length of the robot.
Specifically, the inverse kinematics solver 141 of the knee joint controller 140 will be used to calculate the maximum distance value x from the robot hip to the ankle based on the ideal leg length variation 0 Length l of robot shank c And thigh length l t The ideal adjustment angle is calculated, and fig. 5 is a schematic control logic diagram of the knee joint controller 140 according to the embodiment of the present invention. The specific algorithm is as follows:
x(t)=x 0 -Δx(t)
where Δ x (t) is the ideal leg length variation, x 0 Is the maximum distance value from the center of mass of the robot to the ankle joint, l c The length of the lower leg of the robot, l t Is the thigh length of the robot, theta r And (t) is an ideal adjusting angle.
And S140, adjusting the motion track of the knee joint of the robot in real time according to the ideal adjusting angle.
Specifically, the first PID controller 142 of the knee joint controller 140 adjusts the motion trajectory of the knee joint of the robot in real time according to the calculated ideal adjustment angle, so as to realize the flexible knee bending action of the leg of the robot, thereby reducing the impact force applied to the human body.
Referring to fig. 8, a schematic structural diagram of a gait trajectory planning apparatus 200 according to an embodiment of the present invention is shown, the apparatus including:
the collecting module 210 is configured to collect real-time plantar pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle.
In an embodiment of the present invention, S110 may be performed by the acquisition module 210.
The first calculating module 220 is configured to calculate an ideal leg length variation by using a first predetermined algorithm according to the real-time sole pressure data and the ideal sole pressure data.
In an embodiment of the present invention, S120 may be performed by the first calculation module 220.
And a second calculating module 230, configured to calculate an ideal adjustment angle by using a second predetermined algorithm according to the ideal leg length variation, the maximum distance value from the center of mass of the robot to the ankle joint, the calf length of the robot, and the thigh length of the robot.
In an embodiment of the present invention, S130 may be performed by the second calculation module 230.
And the adjusting module 240 is used for adjusting the motion track of the knee joint of the robot in real time according to the ideal adjusting angle.
In an embodiment of the present invention, S140 may be performed by the adjusting module 240.
Since the detailed description is already given in the gait trajectory planning method section, the detailed description is omitted here.
In summary, the gait track planning method, apparatus and system provided in the embodiments of the present invention are used for adjusting the gait track of a robot, and the method includes: acquiring real-time sole pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle, and calculating ideal leg length variation by adopting a first preset algorithm according to the real-time sole pressure data and the ideal sole pressure data; then, according to the ideal leg length variation, the maximum distance value from the center of mass of the robot to the ankle joint, the shank length and the thigh length of the robot, an ideal adjusting angle is calculated by adopting a second preset algorithm; and finally, the motion trail of the knee joint of the robot is adjusted in real time according to the ideal adjusting angle, so that the flexible knee bending action of the leg can be realized, and the impact damage to equipment or a body is avoided.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A gait trajectory planning method for planning a gait trajectory of a robot, the method comprising:
collecting real-time plantar pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle;
calculating the ideal leg length variation by adopting a first preset algorithm according to the real-time sole pressure data and the ideal sole pressure data;
calculating an ideal adjusting angle by adopting a second preset algorithm according to the ideal leg length variation, the maximum distance value from the hip joint to the ankle joint of the robot, the shank length and the thigh length of the robot;
and adjusting the motion trail of the knee joint of the robot in real time according to the ideal adjusting angle.
2. The method of claim 1, wherein the method further comprises:
adjusting hip joint motion of the robot according to a predefined hip joint trajectory, the predefined hip joint trajectory including time series data of motion angles of a hip joint within one gait cycle.
3. The method of claim 1, wherein the method further comprises:
adjusting the knee joint movement of the robot according to a predefined knee joint track in the non-touchdown stage of the swing leg of the robot, wherein the predefined knee joint track comprises time sequence data of the movement angle of the knee joint in one gait cycle.
4. The method of claim 1, wherein the second predetermined algorithm is:
x(t)=x 0 -Δx(t)
where Δ x (t) is the ideal leg length variation, x 0 Is the maximum distance value from the hip joint to the ankle joint of the robot, l c The length of the lower leg of the robot, l t Is the thigh length of the robot, theta r And (t) is an ideal adjusting angle.
5. A gait trajectory planning apparatus for planning a gait trajectory of a robot, the apparatus comprising:
the acquisition module is used for acquiring real-time plantar pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle;
the first calculation module is used for calculating the ideal leg length variation by adopting a first preset algorithm according to the real-time sole pressure data and the ideal sole pressure data;
the second calculation module is used for calculating an ideal adjusting angle by adopting a second preset algorithm according to the ideal leg length variation, the maximum distance value from the hip joint to the ankle joint of the robot, the shank length and the thigh length of the robot;
and the adjusting module is used for adjusting the motion trail of the knee joint of the robot in real time according to the ideal adjusting angle.
6. The apparatus of claim 5, wherein the adjustment module is further to:
adjusting hip joint motion of the robot according to a predefined hip joint trajectory, the predefined hip joint trajectory including time series data of motion angles of a hip joint within one gait cycle.
7. The apparatus of claim 5, wherein the adjustment module is further to:
and adjusting the knee joint movement of the robot according to a predefined knee joint track in the non-contact stage of the swing leg of the robot, wherein the predefined knee joint track comprises time series data of the movement angle of the knee joint in one gait cycle.
8. A gait trajectory planning system for planning a gait trajectory of a robot, the system comprising:
the pressure sensor is arranged on the sole of the robot and used for acquiring real-time sole pressure data of the robot after the swing leg of the robot touches the ground in the current gait cycle;
the impedance controller is used for receiving the real-time plantar pressure data and calculating the ideal leg length variation by adopting a first preset algorithm according to the real-time plantar pressure data and the ideal plantar pressure data;
the knee joint controller comprises an inverse kinematics resolver and a first PID (proportion integration differentiation) controller, wherein the inverse kinematics resolver is used for calculating an ideal adjusting angle according to the ideal leg length variation, the maximum distance value from the hip joint to the ankle joint of the robot, the shank length and the thigh length of the robot;
the first PID controller is used for adjusting the motion trail of the knee joint of the robot in real time according to the ideal adjusting angle.
9. The system of claim 8, further comprising a second PID controller for adjusting the hip joint movement of the robot according to a predefined hip joint trajectory comprising time series data of the movement angle of the hip joint within one gait cycle
And in the stage that the swing leg of the robot is not in touch with the ground, the first PID controller is used for adjusting the knee joint movement of the robot according to a predefined knee joint track, and the predefined knee joint track comprises time sequence data of the movement angle of the knee joint in one gait cycle.
10. The system of claim 8, further comprising an inertial sensor disposed on the lower limb of the robot,
the inertial sensor is used for measuring an included angle between a connecting line from the hip joint to the ankle joint of the robot and the vertical direction, and the included angle is used for calculating the ideal plantar pressure data.
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