A four-legged robot anti-sliding control method

Abstract

The present application relates to the field of robot technology, and discloses a kind of four-legged robot anti-sliding control method, including the sliding detector for estimating foot end contact condition, and the sliding compensation controller activated after identifying the occurrence of sliding;Sliding detector estimates the position and velocity of four-legged robot contact foot in world coordinate system to determine whether sliding occurs;The sliding compensation controller of four-legged robot is realized based on model predictive control, and the model predictive control problem is constructed according to the dynamics model of four-legged robot;Solve the model predictive control problem to obtain the optimal ground control force.The present application introduces the velocity and displacement error of end effector in the detection model, and the present application realizes the accurate detection of foot end sliding under different metachronal mode.At the same time, the hybrid controller proposed in the present application decomposes the control task of stabilizing sliding leg into horizontal plane position control and vertical force control.

Description

Technical Field

[0001] This invention relates to the field of robotics, and more specifically to an anti-slip control method for a quadruped robot. Background Technology

[0002] Quadruped robots, due to the flexibility and adaptability of their legged locomotion, have been widely used in challenging tasks across various terrains and conditions, such as mine exploration, industrial inspection, and rescue. Unlike wheeled robots, quadruped robots, as typical underactuated systems with floating bases, require external input forces for control through contact between their legs and the ground. Therefore, reliably estimating and executing contact forces is crucial for their motion strategy. However, when moving on slippery surfaces such as sand and snow, the lack of friction can cause the legs of legged robots to slip between themselves and the ground, leading to instability and falls. Therefore, developing anti-slip control algorithms for quadruped robots on slippery surfaces is of positive significance for improving their stability and safety.

[0003] Conventional quadruped robot control algorithms largely rely on the static contact assumption to derive and control foot contact forces, i.e., adding kinematic constraints where the contact point velocity and acceleration are zero. By substituting this constraint into the dynamics of a floating base, the contact force can be derived as a constraint force without additional force sensors. However, when slippage occurs, the static contact assumption no longer holds. The contact point of the supporting leg will deviate from its predetermined position, causing deformation of the supporting polygon, leading to the robot losing balance and falling. To improve the motion stability of the slipping surface, some existing algorithms actively switch to a slower quadrupedal control gait or directly switch from foot control to position control to suppress slippage. While these methods can prevent the robot from falling, they also significantly impair the robot's motion performance. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an anti-slip control method for quadruped robots to improve their stability on sliding surfaces. This method employs a slip detector designed to estimate foot contact conditions, accurately determining the occurrence of slippage. Simultaneously, a slip compensation controller activated upon slippage is designed, achieving hybrid control of contact force calculation and slip contact compensation position control through orthogonal decomposition and null space projection.

[0005] Slippery surfaces place high demands on the motion control algorithms of quadruped robots. Conventional leg control methods derive contact forces by assuming stationary foot contact, but this assumption no longer holds true under slippery conditions. This invention develops a slip detector that does not require any external sensors and proposes a novel slip recovery controller using orthogonal decomposition to stabilize slip contact and prevent robot falls. This method aims to solve the problems of inaccurate contact traction and foot slippage in quadruped robots on slippery surfaces, thereby improving their motion stability and safety.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0007] A method for anti-slip control of a quadruped robot includes a slip detector for estimating foot contact conditions and a slip compensation controller activated after slippage is detected; wherein:

[0008] The slip detector determines whether slippage has occurred by estimating the position and velocity of the quadruped robot's contact foot in the world coordinate system.

[0009] A sliding compensation controller for a quadruped robot is implemented based on model predictive control. The dynamic model of the quadruped robot is a single rigid body dynamic model that ignores the mass of the legs. A model predictive control problem is constructed based on the dynamic model of the quadruped robot. The optimal ground control force is obtained by solving the model predictive control problem.

[0010] Furthermore, the slip detector determines whether slippage has occurred by estimating the position and velocity of the quadruped robot's contact foot in the world coordinate system, specifically including:

[0011] Define the position error δd of the i-th contact foot. i and velocity error δv i for:

[0012] δd i =||x c,i -x c0,i ||;

[0013]

[0014] Where, x c,i Let x be the position of the robot's i-th contact foot in the world coordinate system. c0,i J is the position where the robot's i-th contact foot first contacts the ground in the world coordinate system. c,i is the Jacobian matrix corresponding to the i-th contact foot of the robot, and q represents the generalized coordinates of the robot;

[0015] Based on position error δd i and velocity error δv iEstimate the probability P of slipping on the i-th contact foot. slip,i :

[0016]

[0017] The expression for the erf function is: k p and k d This is the scaling factor for the sliding detector, used to adjust the detection sensitivity.

[0018] The criteria for judging the sliding detector are as follows:

[0019]

[0020] Where X slip,i This represents the sliding state of the i-th contacting foot, where True indicates slippage and False indicates no slippage.

[0021] Furthermore, the generalized coordinate q of the robot is given by the Kalman filter algorithm, and the input of the Kalman filter algorithm is the robot's body perception information, including foot contact sensors, inertial measurement units (IMUs) and joint angle encoders.

[0022] Furthermore, the sliding compensation controller for the quadruped robot based on model predictive control is described. The quadruped robot's dynamic model is a single rigid body dynamic model that ignores the mass of the legs. The model predictive control problem is constructed based on the quadruped robot's dynamic model, specifically including:

[0023] The dynamic model of the quadruped robot is as follows:

[0024]

[0025] Where m is the robot's mass, p is the position of the robot's center of mass in the world coordinate system, and λ is the distance between the robot's mass and the mass of the robot's body. i Let p be the contact force between the i-th contacting foot and the ground, g be the acceleration due to gravity, I be the moment of inertia of the robot's center of mass, ω be the angular velocity of the robot body, and p be the contact force between the i-th contacting foot and the ground. f,i Let i be the position of the i-th contacting foot in the world coordinate system;

[0026] Define the robot's state x and control variable u as follows:

[0027]

[0028] Where, Θ=[φ,θ,ψ] T It is the Euler angle representation of the robot's roll angle, pitch angle, and yaw angle, and the mapping from the angular velocity ω to this Euler angle change R(Θ) is:

[0029]

[0030] Combining equations (5) to (9), we obtain the linear state-space equations:

[0031]

[0032] in,

[0033]

[0034] Subsequently, a first-order hold is used to transform the state transition matrices A(t) and B(t) into discrete form A. k and B k This leads to the following linear model predictive control problem:

[0035]

[0036] Where N is the prediction step size, x k and Let R be the robot's current state and set state at time k; let R and Q be two positive definite weight matrices; x s This represents the robot's initial state; u min and u max These represent the maximum and minimum limits of the robot's control force, u. k Let C represent the control quantity at time k, and let C represent the constraint coefficient matrix.

[0037] constraint u min ≤Cu k ≤u max In addition to basic amplitude limiting, the content also includes friction cone limiting to prevent the robot from slipping:

[0038]

[0039] Where μ i λ is the coefficient of friction between the i-th contact foot and the ground, where c(i)∈{0,1} represents whether the i-th contact foot is suitable for ground contact; i,x ,λ i,y ,λ i,z Let λ be the components of the contact force between the i-th contacting foot and the ground in the x-axis, y-axis, and z-axis directions, respectively; max This represents the maximum permissible ground contact force in the z-direction.

[0040] Furthermore, solving the model predictive control problem to obtain the optimal ground control force specifically includes:

[0041] When the i-th contact foot slides against the ground, i.e., X slip,i When it is True, the corresponding μ iThis will be set to 0; this means that the sliding contact foot is only allowed to generate contact force in the perpendicular direction with the ground, thus preventing slippage.

[0042] Meanwhile, in order to keep the sliding contact foot in the correct position, the slip compensation controller will output a horizontal sliding restoring force.

[0043]

[0044] Where p s,i It is the position where the i-th contact foot, which is in a sliding state, begins to slide. and These are positive definite matrix parameters; sliding restoring force. Always parallel to the ground, used to pull the sliding contact foot toward and hold the correct contact point;

[0045] The motor control torque τ of the i-th leg of the robot i Obtained from the following formula:

[0046]

[0047] Among them, J i Let R be the Jacobian matrix in the fuselage coordinate system of the i-th leg, and R be the rotation transformation matrix from the fuselage to the world coordinate system.

[0048] Compared with the prior art, the beneficial technical effects of the present invention are:

[0049] This invention develops a slip detector that requires no external sensors and proposes a novel slip recovery controller using orthogonal decomposition to stabilize slip contact and prevent robot falls. This invention combines a hybrid position / force controller and integrates it into a model predictive control (MPC) motion strategy. By introducing velocity and displacement errors of the end effector into the detection model, this invention achieves accurate detection of foot slippage in different time-state modes. Simultaneously, the proposed hybrid controller decomposes the control task of stabilizing the sliding leg into horizontal plane position control and vertical force control.

[0050] Conventional quadruped robot control algorithms are mostly based on the static contact assumption to derive and control the contact force at the foot end. Therefore, they have poor adaptability to sliding and often struggle to react quickly to real-time dynamic changes, resulting in the robot's inability to adjust its posture or gait in time when encountering sliding or changes in ground friction. In contrast, the method proposed in this invention can solve the problems of inaccurate contact traction force and slippage of the contact foot on slippery surfaces, thereby improving the stability and safety of its movement. Attached Figure Description

[0051] Figure 1This is a system block diagram of the present invention.

[0052] Figure 2 This is a schematic diagram illustrating the application scenarios of the invention. Detailed Implementation

[0053] A preferred embodiment of the present invention will now be described in detail with reference to the accompanying drawings.

[0054] This invention designs an anti-slip control method for quadruped robots in slippery environments, and the system used is as follows: Figure 1 As shown, it mainly includes a slip detector that estimates the contact situation at the foot end, and a slip compensation controller that is activated after a slip is detected.

[0055] 1. Sliding detector

[0056] The slip detector determines whether slippage has occurred by estimating the position and velocity of the quadruped robot's contact foot in the world coordinate system. The specific technical process is as follows:

[0057] First, for each contact foot, define the positional error δd at the foot tip. i and velocity error δv i for:

[0058] δd i =||x c,i -x c0,i ||;

[0059]

[0060] Where, x c,i It is the position of the i-th contacting foot in the world coordinate system, x c0,i J is the position where the i-th contacting foot first contacts the ground in the world coordinate system. c,i is the Jacobian matrix corresponding to the i-th contact foot, and q corresponds to the robot's generalized coordinates.

[0061] The robot's generalized coordinates q are given by the Kalman filter algorithm, which takes into account the robot's body perception information, including foot contact sensors, inertial measurement units (IMUs), and joint angle encoders.

[0062] To suppress sensor noise, a low-pass filter is used to filter foot speed errors, thereby reducing the occurrence of slip misjudgments.

[0063] Based on the two errors mentioned above, the slip probability P of the i-th contact foot can be estimated. slip,i The specific calculation formula is as follows:

[0064]

[0065] The expression for the erf function is: k p and k d This is the scaling factor for the sliding detector, used to adjust the sensitivity of the detection.

[0066] Finally, the judgment criteria for the sliding detector are as follows:

[0067]

[0068] Where X slip,i This represents the sliding judgment state of the i-th contact foot.

[0069] 2. Sliding Compensation Controller

[0070] The quadruped robot and its sliding compensation controller are implemented based on MPC (Model Predictive Control), which will be described in detail below.

[0071] In MPC, the dynamics model of a quadruped robot is a single rigid body dynamics model that ignores the mass of its legs:

[0072]

[0073] Where m is the robot's mass, p is the position of the robot's center of mass in the world coordinate system, and λ is the distance between the robot's mass and the mass of the robot's body. i Let p be the contact force between the i-th contacting foot and the ground, g be the acceleration due to gravity, I be the moment of inertia of the robot's center of mass, ω be the angular velocity of the robot body, and p be the contact force between the i-th contacting foot and the ground. f,i Let be the position of the i-th contact foot in the world coordinate system.

[0074] Subsequently, the robot's state x and control variable u are defined as follows:

[0075]

[0076]

[0077] Where, Θ=[φ,θ,ψ] T This represents the Euler angles of the robot's roll, pitch, and yaw, and is a mapping from the angular velocity ω to the change in these Euler angles. for

[0078] Combining the dynamic equations, we obtain a linear state-space equation:

[0079]

[0080] in,

[0081]

[0082] Subsequently, a first-order hold is used to transform the state transition matrices A(t) and B(t) into discrete form A. k and B k .

[0083] Based on the above dynamics, the following linear MPC problem can be obtained:

[0084]

[0085] Where N is the prediction step size, x k and Let R and Q be the robot's current state and set state at time k. R and Q are two positive definite weight matrices. s This represents the robot's initial state.

[0086] constraint u min ≤Cu k ≤u max In addition to basic amplitude limiting, the content also includes friction cone limiting to prevent the robot from slipping:

[0087]

[0088] Where μ i is the friction coefficient between the i-th contact foot and the ground, and c(i)∈{0,1} is used to indicate whether the i-th contact foot is suitable for ground contact.

[0089] Solving this MPC problem yields the control quantity u required for tracking the trajectory, i.e., the optimal ground control force.

[0090] When the i-th contact foot slides against the ground, i.e., X slip,i When it is True, the corresponding μ i This will be set to 0. This means that the sliding leg is only allowed to generate contact force with the ground in the vertical direction, which will prevent slippage.

[0091] Meanwhile, in order to stabilize the sliding leg and keep it in the correct position, the sliding compensation controller will output a horizontal sliding restoring force.

[0092]

[0093] Where p s,i It is the position where the i-th contact foot, which is in a sliding state, begins to slide. and These are positive definite matrix parameters. Since the foot always slides in contact with the ground, the sliding restoring force... It also remains parallel to the ground. This restoring force will pull the sliding foot toward and hold its correct point of contact, thus preventing the foot from sliding.

[0094] Finally, the motor control torque τ of the i-th leg of the legged robot i Obtained from the following formula:

[0095]

[0096] Among them, J i Let R be the Jacobian matrix in the fuselage coordinate system of the i-th leg, and R be the rotation transformation matrix from the fuselage to the world coordinate system.

[0097] Figure 1 The left side corresponds to the generation of its reference state; the middle part is the control strategy, including the sliding compensator and the MPC controller; the right side is the sensing part, including the state estimator and the sliding estimator.

[0098] Figure 2 As an example of an application scenario for the invention: A standing quadruped robot slides its left foreleg from an initial contact position (blue) to its current position (red). A slip detector detects the slip by measuring the subsequent lateral velocity and displacement of the foot. Subsequently, an activated slip compensation controller generates the desired slip recovery force for position control to stabilize the sliding leg; simultaneously, it provides a vertical contact force to support the robot's torso.

[0099] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention, and no reference numerals in the claims should be construed as limiting the scope of the claims.

[0100] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A method for anti-slip control of a quadruped robot, characterized in that, This includes a slip detector that estimates foot contact conditions, and a slip compensation controller that is activated after a slip is detected; wherein: The slip detector determines whether slippage has occurred by estimating the position and velocity of the quadruped robot's contact foot in the world coordinate system. A sliding compensation controller for a quadruped robot is implemented based on model predictive control. The quadruped robot's dynamic model is a single rigid body dynamic model that neglects the mass of the legs. The model predictive control problem is constructed based on the quadruped robot's dynamic model, specifically including: The dynamic model of the quadruped robot is as follows: ； （5） ； （6） in, For robot quality, Let the position of the robot's center of mass in the world coordinate system be [the location of the robot's center of mass]. For the first The contact force between the foot and the ground. It is gravitational acceleration. It is the rotational inertia of the robot's center of mass. For the fuselage angular velocity, For the first The position of each contact foot in the world coordinate system; Define the robot's state and control quantity for: ； （7） ； （8） in, It is the Euler angle representation of the robot's roll angle, pitch angle, and yaw angle, while angular velocity... The change in Euler angles up to this point The mapping is: ；（9） Combining equations (5) to (9), we obtain the linear state-space equations: ； in, ； ； ； Subsequently, a first-order hold is used to convert the state transition matrix. and Transform into discrete form and This leads to the following linear model predictive control problem: ； in, It is the predicted step size. and It's a robot. The current state and the set state at any given moment; and These are two positive definite weight matrices; This represents the robot's initial state. and These represent the maximum and minimum limits of the robot's control force, respectively. Indicates the first The amount of control at any given moment Represents the constraint coefficient matrix; constraint In addition to basic amplitude limiting, the content also includes friction cone limiting to prevent the robot from slipping: ； in It is the first The coefficient of friction between the foot and the ground. Used to represent the first Is the contact foot suitable for ground contact? The first The components of the contact force between the contact foot and the ground in the x-axis, y-axis and z-axis directions; This represents the maximum permissible ground contact force in the z-direction; Solving the model predictive control problem to obtain the optimal ground control force specifically includes: When the The foot slips on the ground, that is... for At that time, the corresponding Will be set as This means that the sliding contact foot is only allowed to generate contact force in the perpendicular direction with the ground, which can prevent slippage from occurring. Meanwhile, in order to keep the sliding contact foot in the correct position, the slip compensation controller will output a horizontal sliding restoring force. : ； in It is the first one in the sliding state The position where the contact foot begins to slide. and These are positive definite matrix parameters; sliding restoring force. Always parallel to the ground, used to pull the sliding contact foot toward and hold the correct contact point; Robot Motor control torque for each leg Obtained from the following formula: ； in, For the first Jacobian matrix in single-leg fuselage coordinate system It is the rotation transformation matrix from the fuselage to the world coordinate system.

2. The method for anti-slip control of a quadruped robot according to claim 1, characterized in that, The slip detector determines whether slippage has occurred by estimating the position and velocity of the quadruped robot's contact foot in the world coordinate system, specifically including: Definition of the first Positional error of the contact foot and speed error for: ； ； in, It is the robot's first The position of a contact foot in the world coordinate system It is the robot's first The position where the first contact foot makes contact with the ground in the world coordinate system. It is the robot's first Jacobian matrix corresponding to each contact foot Represents the robot's generalized coordinates; Based on position error and speed error , estimate the first The probability of slippage on the foot. : ； in, The expression of the function is , and This is the scaling factor for the sliding detector, used to adjust the detection sensitivity. The criteria for judging the sliding detector are as follows: ； in For the first The sliding state of the contact foot. Indicates slipping. This indicates that the surface is not slippery.

3. The method for anti-slip control of a quadruped robot according to claim 2, characterized in that, The robot's generalized coordinates The Kalman filter algorithm is used as input to the robot's body perception information, including foot contact sensors, inertial measurement units (IMUs), and joint angle encoders.

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