Heavy-load quadruped robot anti-skid stability control method on wet and slippery road

Abstract

The application discloses a heavy-load quadruped robot wet and slippery road anti-skid stability control method and belongs to the technical field of robot motion control. The application sets controllable negative pressure adhesion foot end assembly at the end of the leg unit, in the control method, firstly, the robot state, the foot end contact state and the road friction coefficient are acquired, and the reference state sequence in the prediction time domain is generated; the discrete AP-MPC control prediction model with the center of mass movement and the posture as the objects is established; the effective normal pressure tightness of the supporting foot is defined as the sum of the net normal supporting force and the auxiliary downward pressure; according to the tangential force demand of each supporting foot, the net normal supporting force and the friction coefficient, the target auxiliary downward pressure meeting the anti-skid margin is calculated; the model optimization problem is solved, the optimal tangential force, the normal force and the target auxiliary pressure are output, and the corresponding foot end sealing, negative pressure generation or release reset are controlled. The application can apply the auxiliary downward pressure according to the slip risk, actively expand the friction margin, and give consideration to the conventional motion performance and the wet and slippery road anti-skid stability.

Description

Technical Field

[0001] This invention belongs to the field of robot motion control technology, specifically relating to a method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces. Background Technology

[0002] With the development of mobile robot technology in complex environments, heavy-duty quadruped robots, due to their strong terrain adaptability, obstacle-crossing ability, and load-bearing capacity, have broad application prospects in scenarios such as industrial inspection, material handling, equipment mounting, emergency rescue, field operations, and autonomous movement in special environments. Especially for legged robots designed for heavy-duty tasks, higher requirements are placed on their foot contact reliability, overall posture stability, and anti-slip ability on low-adhesion surfaces when conditions require stable load-bearing, passage on complex terrain, maneuverability, and safe operation.

[0003] Current technology suffers from the following shortcomings that urgently need to be addressed:

[0004] First, existing heavy-duty quadruped robots mostly maintain stability through gait adjustment, contact force distribution, and body posture compensation. Their control capabilities are limited by the robot's own weight and the normal contact conditions formed by the leg support. When running on wet, slippery, and hard surfaces, the equivalent friction coefficient between the foot and the ground decreases significantly, and the foot can hardly actively improve its effective adhesion. Under heavy-duty conditions, foot slippage, posture disturbance, and trajectory deviation are likely to occur.

[0005] Secondly, existing heavy-duty quadruped robots mostly use passive anti-slip methods such as rubber foot pads, anti-slip textures, flexible buffer pads, or local toothed structures at the foot end. Their adhesion performance mainly depends on the material and geometry, and it is difficult to actively adjust according to load changes, motion state, and slippage risk. The effective normal clamping force at the foot end can be actively adjusted according to motion state and slippage risk.

[0006] Furthermore, existing model predictive control methods typically only consider the contact force of the supporting foot as the optimization object and limit the tangential force through friction cone constraints. When the road surface friction coefficient decreases, the available friction margin is significantly reduced, making it difficult to meet the anti-slip stability requirements of heavy-duty robots during start-up, braking, steering, and anti-disturbance processes. Therefore, MPC (ModelPredict Control) cannot actively expand the feasible domain of foot friction constraints under low adhesion conditions.

[0007] Finally, under heavy load conditions, the tangential contact force required by the robot during start-up, braking, turning or disturbance resistance is large. Once the foot slips, it is easy to cause attitude instability, trajectory deviation or even overturning risk. Existing solutions lack a mechanism to coordinate the design of active attached foot structure with robot stability control algorithm. They cannot actively distribute auxiliary downforce according to the slip risk of each supporting foot, and it is difficult to simultaneously take into account foot anti-slip, attitude stability and motion performance under wet and slippery heavy load conditions. Summary of the Invention

[0008] To address the aforementioned problems, this invention provides a method for anti-slip stability control of a heavy-duty quadruped robot on slippery surfaces. By incorporating a controllable negative pressure amplification structure at the foot of the heavy-duty quadruped robot, the foot maintains normal support contact on conventional surfaces, while generating controllable auxiliary downward pressure on slippery surfaces or in situations with slippage risk. Within a model predictive control framework, based on the robot's body state, foot state, desired contact force, road friction state, and slippage risk of each foot, the required target auxiliary downward pressure for each foot is calculated, and the effective normal clamping force of the foot is adjusted accordingly. The original net normal support force is expanded into a combination of net normal support force and auxiliary downforce, thereby actively increasing the available friction margin at the foot end and suppressing foot slippage, trajectory deviation and posture instability on wet and slippery surfaces. At the same time, by limiting the amplitude, rate of change and support phase of the target auxiliary downforce, the auxiliary downforce is applied only to the support foot that needs to be added, avoiding unnecessary impact on normal gait movement, and improving the anti-slip capability, motion stability and operation safety of the heavy-duty quadruped robot in wet and slippery hard surfaces, low-adhesion operation scenarios and heavy-duty high-disturbance conditions.

[0009] The objective of this invention is achieved through the following technical solution:

[0010] A method for controlling the anti-slip stability of a heavy-duty quadruped robot on wet and slippery surfaces includes a controllable negative pressure attachment foot assembly at the end of each leg unit of the heavy-duty quadruped robot. The controllable negative pressure attachment foot assembly includes a sealing trigger mechanism and a negative pressure generating mechanism. The sealing trigger mechanism is used to form a sealed boundary between the foot and the ground when the robot enters the wet and slippery surface attachment condition. The negative pressure generating mechanism is used to generate an auxiliary downward pressure between the foot and the ground. The control method includes the following steps:

[0011] S1. Obtain the robot's current operating status, the contact status information of each leg unit's foot end, and the road surface status information;

[0012] S2. Generate a reference state sequence in the prediction time domain based on the robot task instructions, path planning results, speed instructions, and current state;

[0013] S3. Taking the robot's center of mass motion and posture motion as the prediction objects, and using the tangential contact force and net normal support force at the ends of each supporting foot as the basic control variables, a discretized robot AP-MPC control prediction model is established.

[0014] S4. Introduce auxiliary downward pressure, define the effective normal clamping force of the support foot as the sum of the net normal support force and the auxiliary downward pressure, and modify the anti-slip constraint at the foot end of the support foot accordingly;

[0015] S5. Calculate the target auxiliary downforce that meets the anti-skid margin requirements based on the tangential force requirements of each support foot, the net normal support force, the road surface friction coefficient, and the preset safety factor;

[0016] S6. Solve the AP-MPC optimization problem in each control cycle and output the optimal tangential contact force, net normal support force and target auxiliary downforce at the foot end of each support.

[0017] S7. The target auxiliary downward pressure is sent to the controllable negative pressure attachment foot assembly of the corresponding support foot, the control sealing trigger mechanism establishes a seal and starts the negative pressure generating mechanism to generate auxiliary downward pressure; when the foot enters the swing phase or the slip risk is eliminated, the pressure is released and the seal is released, so that the foot returns to the normal state.

[0018] Furthermore, the sealing triggering mechanism adopts a cam-type triggering structure, including a cam trigger, a sealing and pressing switching component, and an annular sealing ring; the annular sealing ring is located at the grounding edge of the foot end of the leg unit, used to form a sealing boundary with the ground in the sealed state; the cam trigger and the sealing and pressing switching component are located inside the lower leg mechanism, and the cam trigger, under the driving action, pushes the sealing and pressing switching component to move, causing the sealing and pressing switching component to drive the annular sealing ring into the pressing state; the negative pressure generating mechanism includes a miniature electric vacuum pump, a foot-bearing contact block, and a negative pressure adsorption hole; foot The bottom bearing contact block is located in the central area of ​​the bottom of the foot of the leg unit. It is used to contact the ground during the robot's normal walking and support, and bears the main normal load and tangential contact force. The negative pressure adsorption hole is set in the circumferential or outer circumferential area of ​​the foot bearing contact block. The negative pressure adsorption hole is connected to a micro electric vacuum pump. It is used to evacuate the contact area of ​​the foot after the seal is established, thereby generating a negative pressure adsorption effect. The micro electric vacuum pump is connected to the negative pressure adsorption hole through a negative pressure pipeline. It is used to evacuate the negative pressure area of ​​the foot after the seal is established, so that an auxiliary downward pressure is formed between the foot and the ground.

[0019] Furthermore, the controllable negative pressure attachment foot assembly has a normal support state, a seal establishment state, a negative pressure attachment state, and a release and reset state; in the normal support state, the sealing trigger mechanism and the micro electric vacuum pump are not activated; in the seal establishment state, the sealing trigger mechanism is activated, pressing the foot tightly against the ground for a seal; in the negative pressure attachment state, the negative pressure generating mechanism is activated, generating auxiliary downward pressure between the foot and the ground; in the release and reset state, the negative pressure generating mechanism stops or releases the negative pressure, and the sealing trigger mechanism releases the pressure.

[0020] Further, in S1, the robot's current operating status information includes the robot's center of mass position, robot speed, robot posture, and robot angular velocity; the leg unit foot contact status information includes whether each leg unit foot is in the support phase, the position of each leg unit foot relative to the robot's center of mass, the estimated contact force of each leg unit foot, and the current auxiliary downward pressure state of each leg unit foot; the road surface status information includes the wet and slippery road surface identification result and the estimated road surface friction coefficient; in S2, the reference state includes the robot's center of mass reference position, speed, posture, and angular velocity.

[0021] Furthermore, in S3, the discretized robot AP-MPC control prediction model expression is:

[0022] ;

[0023] in, For the first Robot state vector for each control cycle; The vector of the tangential contact force at the foot end of each supporting foot; The net normal support force vector at the foot end of each support; For the first Discrete state transition matrix corresponding to each control cycle; For the first The tangential contact force input matrix corresponding to each control cycle; For the first Net normal support force input matrix corresponding to each control cycle; These are the gravity term, the linearized bias term, and the known perturbation term.

[0024] Furthermore, in S4, the effective normal clamping force for:

[0025] ;

[0026] in, Let be the net normal support force at the foot end of the i-th support; The auxiliary downward pressure at the i-th supporting foot end;

[0027] The anti-slip constraint is:

[0028] ;

[0029] in, To preset the anti-slip safety factor, ; For the first The coefficient of friction of the road surface corresponding to the foot of each support.

[0030] Furthermore, in S5, the target assisted downforce for:

[0031] ;

[0032] Specifically, when the robot is on a slippery surface, starting under heavy load, braking, turning, or resisting disturbances, if the tangential force requirement at the supporting foot increases or the friction coefficient decreases, the target auxiliary downward pressure... The margin is increased accordingly to compensate for insufficient friction at the foot.

[0033] Furthermore, in S6, the objective function for solving the AP-MPC optimization problem is... for:

[0034] ;

[0035] in, To predict the first in the time domain The change in target-assisted downpressure corresponding to each prediction step is expressed as: , , and The weight matrix is ​​pre-defined based on the control objective;

[0036] The optimization problem satisfies the following constraints:

[0037] ;

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] in, For the first The contact phase variable at the foot end of each leg unit, for the supporting foot, For the swing foot, ; This represents the maximum net normal support force. To provide maximum auxiliary downforce; To assist in the allowable rate of change of downward pressure.

[0043] Furthermore, the control method is implemented through a heavy-duty quadruped robot anti-slip and stability control system for wet and slippery surfaces, the control system comprising:

[0044] The state perception module is used to acquire information about the robot's current operating state, foot contact state, and road surface state.

[0045] The contact state determination module is used to determine whether each foot is in the support phase or the swing phase and to generate contact phase variables;

[0046] The reference state generation module is used to generate a reference state sequence in the prediction time domain;

[0047] The AP-MPC control prediction module is used to establish the AP-MPC control prediction model and solve the tangential contact force, net normal support force and target auxiliary downforce of each support foot.

[0048] The auxiliary downforce calculation module is used to calculate the target auxiliary downforce of each support foot based on the anti-slip constraint;

[0049] The negative pressure execution control module is used to generate seal establishment command, negative pressure establishment command, negative pressure maintenance command and release reset command based on the target auxiliary pressure and contact phase variable;

[0050] A controllable negative pressure amplification foot-end execution module is installed at the end of each leg unit to respond to execution commands and generate target auxiliary downward pressure at the corresponding supporting foot;

[0051] The auxiliary pressure feedback module is used to obtain the pressure in the negative pressure chamber and the estimated actual auxiliary pressure, and feed it back to the AP-MPC control prediction module and the negative pressure execution control module.

[0052] Furthermore, the negative pressure execution control module assists in the downward pressure based on the target. and the area of ​​negative pressure on the foot The target negative pressure differential is determined and expressed as:

[0053] .

[0054] The present invention has the following beneficial effects:

[0055] This invention provides a controllable negative pressure attachment foot assembly at the end of the leg unit of a heavy-duty quadruped robot. This allows the foot to maintain normal support on conventional surfaces and generate auxiliary downward pressure as needed on wet or slippery surfaces or when there is a risk of slippage. This improves the effective normal clamping force between the foot and the ground and addresses the problem of insufficient foot adhesion on low-adhesion surfaces.

[0056] This invention designs the sealing triggering mechanism and the negative pressure sound generating mechanism in a coordinated manner, so that the foot can operate in the sequence of conventional support, seal establishment, negative pressure attachment and release reset. When attachment is needed, the seal is established first and then the negative pressure is formed. When the foot enters the swing phase or the risk of slippage is eliminated, the negative pressure is released and reset in time, thereby avoiding unnecessary dragging or constraint on normal gait movement caused by auxiliary attachment.

[0057] This invention constructs an auxiliary downforce model predictive control method (AP-MPC), which introduces the target auxiliary downforce into the model predictive control framework of the legged robot body layer, and expands the effective normal clamping force of the supporting foot from the net normal support force to a combination of the net normal support force and the auxiliary downforce, so that the controller can actively adjust the available friction margin at the foot end according to the tangential force requirement of the supporting foot, the net normal support force and the road surface friction coefficient.

[0058] This invention establishes an anti-slip constraint that includes auxiliary downward pressure and a solution relationship for the target auxiliary downward pressure, so that the auxiliary downward pressure of each support foot can be allocated as needed according to the degree of slippage, support phase and slippage risk, instead of using a fixed opening or uniform attachment method for all feet. This improves the anti-slip capability while reducing the energy consumption of negative pressure execution and minimizing the impact on the robot's normal motion performance.

[0059] This invention can provide adjustable auxiliary downforce by adding controllable negative pressure to the foot without changing the basic gait control framework of the legged robot. It takes into account both the motion performance on conventional roads and the anti-slip stability on wet and slippery roads, and has good engineering applicability. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of the overall structure of the heavy-duty quadruped robot described in an embodiment of the present invention.

[0061] Figure 2 This is a schematic diagram of the sealing triggering mechanism described in an embodiment of the present invention.

[0062] Figure 3 This is a bottom view of the controllable negative pressure attachment foot assembly described in an embodiment of the present invention.

[0063] Figure 4 This is a logic diagram showing the switching of the working state of the controllable negative pressure attachment foot assembly described in this embodiment of the invention.

[0064] Figure 5 This is a flowchart of a method for controlling the anti-slip stability of a heavy-duty quadruped robot on wet and slippery surfaces, as described in an embodiment of the present invention. Detailed Implementation

[0065] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments:

[0066] Example 1:

[0067] This embodiment describes a method for anti-slip stability control of a heavy-duty quadruped robot on wet and slippery surfaces, which includes two parts:

[0068] The first part improves the structure of the heavy-duty quadruped robot by installing a controllable negative pressure augmentation foot assembly 9 at the foot end of each leg unit. This assembly provides normal foot support on normal surfaces and generates controllable auxiliary downforce on slippery surfaces or in situations where slippage is a risk. Specifically:

[0069] As attached Figure 1 As shown, the heavy-duty quadruped robot in this embodiment includes a body 1 and multiple leg units mounted on the body 1. Each leg unit, from top to bottom, includes a hip connector 2, a hip drive motor assembly 3, a thigh mechanism 4, a lower leg drive motor assembly 5, a lower leg mechanism 8, and a controllable negative pressure attaching foot end assembly 9 disposed at the end of the lower leg mechanism 8. The hip connector 2 is used to connect the leg unit to the body 1. The hip drive motor assembly 3 is used to drive the leg unit to move relative to the body 1. The thigh mechanism 4 and the lower leg mechanism 8 constitute the main support structure of the leg unit. The lower leg drive motor assembly 5 is used to drive the relative movement between the thigh mechanism 4 and the lower leg mechanism 8 to achieve robot walking, support, and posture adjustment. The controllable negative pressure attaching foot end assembly 9 is disposed at the end of the lower leg mechanism 8 to form ordinary foot support on normal road surfaces and generate controllable auxiliary downward pressure on wet and slippery roads or in working conditions with slippage risk, so as to improve the effective normal clamping force and anti-slip ability between the foot end and the ground.

[0070] As attached Figure 3 As shown, the controllable negative pressure attachment foot assembly 9 includes a sealing trigger mechanism 6 and a negative pressure generating mechanism. The sealing trigger mechanism 6 is used to form a sealed boundary between the foot and the ground when the robot enters the wet and slippery road surface attachment condition. After the foot and the ground are sealed, the negative pressure generating mechanism evacuates the negative pressure area of ​​the foot, so that an auxiliary downward pressure is formed between the foot and the ground.

[0071] Preferably, as shown in the appendix Figure 2As shown, the sealing triggering mechanism 6 in this embodiment adopts a cam-type triggering structure, including a cam trigger 10, a sealing and pressing switching component 11, and an annular sealing ring 13. The annular sealing ring 13 is disposed at the grounding edge of the negative pressure adsorption hole 14, and is used to form a sealing boundary with the ground in the sealed state. The cam trigger 10 and the sealing and pressing switching component 11 are disposed inside the lower leg mechanism. Under the driving action, the cam trigger 10 pushes the sealing and pressing switching component 11 to move, so that the sealing and pressing switching component 11 drives the annular sealing ring 13 into the pressing state. Preferably, the sealing triggering mechanism 6 may also include a pre-compression elastic component, which is used to apply a pre-compression force to the foot sealing structure after the sealing and pressing switching component 11 is triggered. It should be noted that the specific transmission form of the sealing triggering mechanism 6 is not limited to a cam-type structure, as long as it can achieve the pressing and resetting of the foot sealing structure.

[0072] Preferably, such as Figure 3 As shown, the negative pressure generating mechanism includes a miniature electric vacuum pump 7, a foot-bearing contact block 12, and a negative pressure adsorption hole 14. The foot-bearing contact block 12 is located in the central area of ​​the bottom of the foot and is used to contact the ground during the robot's normal walking and support processes, bearing the main normal load and tangential contact force. The negative pressure adsorption hole 14 is located in the circumferential or outer circumferential area of ​​the foot-bearing contact block 12 and is connected to the miniature electric vacuum pump 7. It is used to evacuate the foot-contact area after the seal is established, thereby generating a negative pressure adsorption effect. The miniature electric vacuum pump 7 is located on one side of the lower leg mechanism 8 and is connected to the negative pressure adsorption hole 14 of the controllable negative pressure adsorption foot assembly 9 through a negative pressure pipeline. It is used to evacuate the negative pressure area of ​​the foot after the seal is established, so that an auxiliary downward pressure is formed between the foot and the ground.

[0073] As attached Figure 4 As shown, during robot operation, the controllable negative pressure attaching foot assembly 9 has a normal support state, a seal establishment state, a negative pressure attaching state, and a release and reset state.

[0074] In the normal support state, the sealing trigger mechanism 6 and the micro electric vacuum pump 7 are not activated. The robot mainly relies on the foot bearing contact block 12 to contact the ground and transmit the support force and tangential force. At this time, the controllable negative pressure attached foot end assembly 9 is used as a normal foot end and does not produce additional adsorption constraints on the robot's normal gait.

[0075] When the controller detects a slippery surface or a risk of slippage in the support foot, it controls the corresponding controllable negative pressure-enhancing foot assembly 9 to enter the seal-establishing state. At this time, the cam trigger 10 pushes the seal-pressing switch 11 to press the annular sealing ring 13 against the ground, providing initial sealing conditions for subsequent negative pressure establishment.

[0076] After the seal is established, the corresponding controllable negative pressure adsorption foot assembly 9 enters the negative pressure adsorption state. The micro electric vacuum pump 7 starts and evacuates the foot contact area through the negative pressure pipeline and negative pressure adsorption hole 14, creating a negative pressure state between the foot and the ground that is lower than the external atmospheric pressure, thereby generating auxiliary downward pressure. The auxiliary downward pressure and the net normal support force of the foot together increase the effective normal clamping force of the foot, thereby increasing the usable friction margin of the foot on wet and slippery surfaces and inhibiting foot slippage.

[0077] When the corresponding robot foot is about to enter the swing phase or the slippage risk is eliminated, the corresponding controllable negative pressure attached foot assembly 9 enters the release and reset state. At this time, the micro electric vacuum pump 7 stops pumping air or releases negative pressure, and then the sealing trigger mechanism 6 releases the clamping effect on the annular sealing ring 13, so that the controllable negative pressure attached foot assembly 9 returns to the normal support state.

[0078] The second part focuses on the anti-slip stability control of a heavy-duty quadruped robot on slippery surfaces. Within the predictive control framework of the robot's body layer model, based on the robot's current state, reference state, contact state information of the controllable negative pressure-adhesive foot assembly, road surface friction coefficient, and the tangential force requirements of the supporting feet, the required target auxiliary downward pressure for each supporting foot is calculated. The controllable negative pressure-adhesive foot assembly is then controlled to generate negative pressure at the corresponding supporting foot to improve the effective normal clamping force and anti-slip stability of the feet on slippery surfaces. Specifically, the following steps are included:

[0079] S1. Obtain the robot's current operating status, the contact status information of each leg unit's foot end, and the road surface status information.

[0080] In this embodiment, the robot's current operating status information includes at least the robot's center of mass position, robot speed, robot posture, and robot angular velocity;

[0081] Let the robot's current state be:

[0082]

[0083] in, For the position of the robot's center of mass, For robot speed, For the robot's attitude angle, This represents the robot's angular velocity.

[0084] The contact status information of the leg unit foot end includes at least whether each leg unit foot end is in the support phase, the position of each leg unit foot end relative to the fuselage center of gravity, the estimated contact force of each leg unit foot end, and the current auxiliary downforce state of each leg unit foot end.

[0085] The road surface condition information includes at least the wet and slippery road surface identification results and the estimated value of the road surface friction coefficient.

[0086] S2. Based on the robot task instructions, robot path planning results, robot speed instructions, and robot current state, generate a series of reference state sequences in the prediction time domain, including the robot's centroid reference position, velocity, attitude, and angular velocity, as subsequent tracking targets.

[0087] Suppose the desired robot motion command given by the upper-level controller is:

[0088]

[0089] in, For the robot's desired longitudinal velocity, For the robot's desired lateral velocity, For the desired yaw rate, Let x, y, and z be the desired reference values, and let them be the three axes of the robot coordinate system.

[0090] In the Within each control cycle, the prediction time domain Internally generated reference state sequence:

[0091]

[0092] in, Indicates the first Within the control cycle, in the prediction time domain, the first... Robot reference state vectors corresponding to each prediction step;

[0093]

[0094] in, Indicates the current control cycle number; Indicates the prediction step number within the prediction time domain. , To predict the length of the time domain; Indicates the robot's center of mass at the th... The reference position vector at time n can be written as: ; Indicates the robot's center of mass at the th... The reference velocity vector at time n can be written as: ; Indicates the robot in the The reference attitude angle vector at time n can be written as: ,in , , These represent the roll angle, pitch angle, and yaw angle, respectively. Indicates the robot in the The reference angular velocity vector at time n can be written as: .

[0095] When the robot performs a speed tracking task, the reference yaw angle can be recursively obtained from the desired yaw rate:

[0096]

[0097] Indicates the first Within the control cycle, the prediction time domain is... The reference yaw angle corresponding to each prediction step; Indicates the prediction time domain number The reference yaw angle corresponding to each prediction step; Indicates the current control cycle number; Indicates the prediction step number within the prediction time domain; Indicates the vertical direction around the robot coordinate system or world coordinate system. The desired yaw rate of the shaft; This indicates the control period or discrete sampling time.

[0098] The reference position can be obtained by integrating the desired velocity:

[0099]

[0100] in, This is the rotation matrix corresponding to the yaw angle. To control the cycle.

[0101] The reference attitude angle can be expressed as:

[0102]

[0103] in, For reference roll angle, For reference pitch angle, For the reference yaw angle, j+k represents the k+th yaw angle in the prediction time domain. One prediction step. When traveling on a level, wet, slippery surface, the preferred reference roll angle and reference pitch angle are:

[0104]

[0105] Therefore, the reference attitude angle under a horizontal, wet road surface can be written as:

[0106]

[0107] When the robot performs a preset path tracking task, the reference state sequence can also be directly obtained by sampling the desired trajectory output by the path planning module. Therefore, the reference state sequence is used to provide the model predictive controller with tracking targets for the robot's position, velocity, attitude, and angular velocity.

[0108] S3. Taking the robot's center of mass motion and posture motion as the prediction objects, and using the tangential contact force and net normal support force at the ends of each supporting foot of the robot as the basic control quantities, a discretized robot AP-MPC (Auxiliary Pressure Model Predictive Control) control prediction model is established to predict the robot's state changes at future moments.

[0109] Let the first The tangential contact force at the foot of each supporting foot is The net normal support force at the foot end is The normal unit vector of the contact point at the foot end is Then the first The net force exerted on the robot by each supporting foot is:

[0110]

[0111] The robot's dynamic equations can be expressed as:

[0112]

[0113]

[0114] in, For the overall quality of the robot; Let this be the acceleration vector along the robot's center of mass. Let this be the velocity vector of the robot's center of mass; For the first The tangential contact force vector of each supporting foot acts on the entire robot. For the first The net normal support force scalar force acting on the entire robot at the foot end of each support leg; To support the unit vector of the ground normal at the foot contact point; Indicates the first The normal contact force vector corresponding to the foot end of each support; This is the vector of gravitational acceleration; This is the vector of gravity acting on the robot; The rotational inertia matrix of the robot; This is the robot's angular velocity vector; This is the robot's angular acceleration vector; This is a gyroscopic coupling term generated by the robot's angular velocity and moment of inertia; For the first The position vector of each supporting foot contact point relative to the robot's center of mass; This represents the vector cross product operation; Indicates the first The torque generated by the contact force at the foot end of the support relative to the robot's center of mass.

[0115] Linearizing and discretizing the above continuous model near the current operating point, we obtain:

[0116]

[0117] in, This is a vector composed of the tangential contact forces at the ends of each supporting foot. The vector composed of the net normal support forces at the ends of each support foot; , , The discretized prediction model matrix: For the first The discrete state transition matrix corresponding to each control cycle is used to describe the relationship between the robot's body state from the current prediction step to the next prediction step, without considering changes in the current control input; that is, Reflects the current state of the robot State at the next moment The impact. For the first The tangential contact force input matrix corresponding to each control cycle is used to describe the tangential contact force vector at the foot end of each support foot. The impact on the robot's state at the next moment; among them, the tangential contact force mainly affects the robot's center of mass acceleration, robot speed, and the robot's posture change caused by the contact torque. For the first The net normal support force input matrix corresponding to each control cycle is used to describe the net normal support force vector of each support foot. The influence on the robot's state at the next moment; among them, the net normal support force is mainly used to balance the robot's gravity, adjust the robot's height, and generate attitude adjustment torque through the position of the foot end relative to the robot's center of mass. These are the gravity term, the linearized bias term, and the known perturbation term.

[0118] It should be noted that the auxiliary downward pressure supporting the foot end... Instead of being directly incorporated into the above dynamic equations as the robot's net support force, it mainly affects the anti-slip constraint by changing the effective normal clamping force between the foot and the ground.

[0119] S4. Construct an effective normal clamping force and introduce auxiliary downward pressure. The effective normal compressive force at the foot end of the support foot is defined as the net normal support force. With auxiliary downforce The sum of these values ​​is used to adjust the anti-slip constraints at the foot end of the support foot.

[0120] For the first Each support foot introduces target auxiliary downward pressure and constructs an effective normal clamping force. :

[0121]

[0122] in, The net normal support force at the foot of the support foot for achieving fuselage dynamic equilibrium. The auxiliary downward pressure generated by the controllable negative pressure attached to the foot end assembly 9 is used to support the foot end.

[0123] In the control of conventional legged robots, the tangential contact force supporting the foot end is usually limited by:

[0124]

[0125] In this embodiment, since the controllable negative pressure-adhesive foot assembly 9 can generate auxiliary downward pressure, the anti-slip constraint is modified as follows:

[0126]

[0127] Furthermore, to prevent the foot end of the support from operating in a critical slip state, a preset anti-slip safety factor is introduced. ,in Then the anti-slip constraint is:

[0128]

[0129] in, For the first The coefficient of friction of the road surface corresponding to the foot of each support.

[0130] S5. Based on the tangential force requirements at each support foot, the current net normal support force, the road surface friction coefficient, and the preset safety factor, calculate the target auxiliary downforce to meet the anti-skid margin requirements. This value tends to zero under dry or low tangential force conditions, and increases accordingly under wet or large disturbance conditions.

[0131] Based on the anti-slip constraint in step S4, solve for the first... The target auxiliary pressure at the foot end of the support meets the anti-slip margin requirements. :

[0132]

[0133] When the road surface friction coefficient is high or the tangential force requirement at the foot of the support is low, the target auxiliary downforce... The value is zero or small; when the robot is on a slippery surface, starting under heavy load, braking, turning, or resisting disturbances, if the tangential force requirement at the foot end increases or the friction coefficient decreases, the target auxiliary downward pressure will be zero. The margin is increased accordingly to compensate for insufficient friction at the foot.

[0134] S6. Solve the optimization problem of the robot AP-MPC control prediction model: In each control cycle, solve the optimization problem including state tracking error, contact force penalty, auxiliary downforce usage and rate of change constraints, while satisfying the support phase / swing phase logic, force limit, pressure change rate and other constraints, and output the optimal tangential contact force, net normal support force and target auxiliary downforce at each support foot end.

[0135] The robot AP-MPC control prediction model solves the following optimization problem in the prediction time domain during each control cycle:

[0136]

[0137] Wherein, objective function for:

[0138]

[0139] in, To predict the first in the time domain The change in target-assisted downpressure corresponding to each prediction step can be expressed as: , , and The weight matrix, which is pre-defined according to the control objective, can be either a positive definite matrix or a semi-positive definite matrix. This weight matrix is ​​not directly derived from the robot's dynamic equations, but rather serves as a design parameter for the controller in the robot's AP-MPC control predictive model, used to adjust the relative importance of different optimization objectives in the objective function.

[0140] Specifically, The weights are used to adjust the reference state for robot state tracking. When it is necessary to improve the tracking accuracy of the robot's position, velocity, attitude, or angular velocity, the weights can be increased. The weighting coefficients of the corresponding state variables. This is used to adjust the penalty weight of the tangential contact force at the foot end of the support foot. When it is necessary to suppress excessive tangential contact force at the foot end of the support foot and reduce the risk of foot slippage, the penalty weight can be increased. The weight coefficient of the corresponding item in the middle. The penalty weight is used to adjust the net normal support force at the foot of the support foot. When it is necessary to avoid excessive or overly concentrated normal support force distribution at the foot of the support foot, the penalty weight can be increased. The weight coefficient of the corresponding item in the middle. The penalty weight is used to adjust the amount of auxiliary downforce used. When it is necessary to reduce the workload of the controllable negative pressure attachment foot assembly or reduce auxiliary attachment energy consumption, the penalty weight can be increased. The weighting coefficient of the corresponding item; when the anti-skid requirement is high on wet and slippery road surfaces, it can be appropriately reduced. This makes the controller more inclined to apply auxiliary downforce. The penalty weight is used to adjust the amount of pressure change under auxiliary pressure. When it is necessary to limit frequent and rapid changes in negative pressure actuators and improve execution smoothness, the penalty weight can be increased. The weight coefficient of the corresponding item in the middle.

[0141] The first term is used to constrain the robot's state tracking reference state; the second and third terms are used to limit excessive contact force at the foot end of the support; the fourth term is used to limit the amount of auxiliary downforce used; and the fifth term is used to limit excessively rapid changes in auxiliary downforce.

[0142] The optimization problem must satisfy at least the following constraints:

[0143]

[0144]

[0145]

[0146]

[0147]

[0148] in, For the first The contact phase variable at the foot end of each leg unit; for the supporting foot, i.e., when the leg unit is in the supporting phase, For the swinging foot, that is, when the leg unit is in the swinging phase, . For the maximum net normal support force, To maximize auxiliary downforce, To assist in the allowable rate of change of downward pressure.

[0149] S7. Output and execute target auxiliary downforce: The optimized target auxiliary downforce is sent to the controllable negative pressure attachment foot assembly of the corresponding support foot. For the support foot, the control sealing trigger mechanism establishes a seal and starts the negative pressure generating mechanism to generate the required auxiliary downforce; for the swing foot or foot end where the risk of slippage has been eliminated, the pressure is released and the seal is released, so that the foot end returns to the normal support or swing state, realizing a smooth switch between anti-slip attachment and normal gait.

[0150] After the robot's AP-MPC control prediction model is optimized and solved, the optimal tangential contact force, net normal support force, and target auxiliary downward pressure are output for each supporting foot. For the swinging foot, the target auxiliary downward pressure is set to zero; for the supporting foot, the target auxiliary downward pressure is sent to the controllable negative pressure-attached foot assembly corresponding to the leg unit.

[0151] The controllable negative pressure augmentation foot assembly controls the sealing trigger mechanism and the negative pressure generating mechanism according to the target auxiliary pressure, so that the foot end of the support foot forms a corresponding negative pressure augmentation effect in the support phase; when the corresponding leg unit is about to enter the swing phase or the slippage risk is eliminated, the negative pressure generating mechanism is controlled to release pressure and release the sealing and pressing state, so that the foot end returns to the normal support or swing state.

[0152] Through the above method, this invention explicitly establishes a reference state sequence, discrete prediction equations, and auxiliary downforce anti-slip constraints in model predictive control. This enables the predictive control model not only to track the desired body motion state but also to solve the target auxiliary downforce at the foot end of each support foot as needed, based on insufficient friction margin on slippery surfaces. Therefore, compared to legged robots that rely solely on ordinary contact force distribution (MPC), this method can actively expand the effective friction boundary of the foot-ground interface, improving foot anti-slip capability, body posture stability, and safety during heavy-load operations on slippery surfaces.

[0153] Example 2:

[0154] This embodiment is a heavy-duty quadruped robot anti-slip and stability control system for wet and slippery surfaces, used to implement the control method described in Embodiment 1. The control system includes a state perception module, a contact state judgment module, a working state switching module, a reference state generation module, an AP-MPC control prediction module, an auxiliary downward pressure solution module, a negative pressure execution control module, an auxiliary downward pressure feedback module, and a controllable negative pressure attached foot end execution module.

[0155] The state perception module is used to acquire the robot's current operating state, leg unit foot contact state, and road surface state information. The robot's current operating state includes at least the robot's center of mass position, robot speed, robot posture, and robot angular velocity. The leg unit foot contact state includes at least the contact state of each leg unit foot, the position of each leg unit foot relative to the robot's center of mass, the estimated contact force of each leg unit foot, and the current auxiliary downward pressure state of each leg unit foot. The road surface state information includes at least the slippery road surface identification result and the estimated road surface friction coefficient. Here, the leg unit foot refers to the entire foot end that contacts the ground at the end of the leg unit; in this embodiment, it specifically corresponds to the controllable negative pressure-enhanced foot end assembly located at the end of the leg unit.

[0156] The contact state determination module is used to determine whether the foot of each leg unit of the robot is in the support phase or the swing phase based on gait timing, foot height, foot speed, or foot contact force information, to determine whether each leg unit is currently a support foot or a swing foot, and to generate the contact phase variable of the foot of each leg unit. When the... When the foot of each leg unit is in the support phase, the contact phase variable... When the first When the foot of each leg unit is in the swing phase, the contact phase variable This ensures that the net normal support force and auxiliary downward pressure are generated only on the support foot, avoiding the swing foot being constrained by negative pressure adsorption.

[0157] The working state switching module is used to control each controllable negative pressure attaching foot assembly to switch between normal support state, seal establishment state, negative pressure attaching state, and release reset state based on the wet and slippery road surface identification result, slip risk assessment result, contact phase variable, and target auxiliary downward pressure. (See attached diagram) Figure 4 As shown, when no slippery surface or slippage risk is detected, the corresponding leg unit foot maintains a normal support state; when a slippery surface or slippage risk is detected for the corresponding support foot, and the leg unit foot is in the support phase, the working state switching module controls the foot to enter the seal establishment state; when the seal is established and the target auxiliary downward pressure output by the auxiliary downward pressure calculation module is greater than the preset threshold, the working state switching module controls the foot to enter the negative pressure enhancement state; when the corresponding foot is about to enter the swing phase, the slippage risk is eliminated, or the target auxiliary downward pressure is reduced to below the preset release threshold, the working state switching module controls the foot to enter the release reset state.

[0158] The reference state generation module generates a reference state sequence in the prediction time domain based on upper-level task instructions, path planning results, desired velocity instructions, and the current robot state. The reference state sequence includes at least the robot's reference position, reference velocity, reference attitude, and reference angular velocity, providing a state tracking target for the AP-MPC control prediction module.

[0159] The AP-MPC control prediction module is used to establish the robot's AP-MPC control prediction model. Based on the current robot state, reference state sequence, foot contact phase variable, road surface friction coefficient, and foot contact force requirements, it solves for the tangential contact force, net normal support force, and target auxiliary downforce of each supporting foot in the prediction time domain. During the solution process, the AP-MPC control prediction module introduces anti-slip constraints including auxiliary downforce, increasing the upper limit of available friction force at the foot of each supporting foot from that under normal foot conditions. Expand to ,in, For the first The coefficient of friction of the road surface corresponding to each support foot end. For the first The net normal support force of a support foot, For the first A controllable negative pressure is applied to the foot end assembly to generate target auxiliary downward pressure.

[0160] The auxiliary downforce calculation module is used to calculate the target auxiliary downforce at the foot of each support foot to meet the anti-slip margin requirements based on the tangential contact force requirement, net normal support force, road surface friction coefficient, and preset anti-slip safety factor. For the foot of the leg unit in the swing phase, the auxiliary downforce calculation module sets the corresponding target auxiliary downforce to zero; for the foot of the leg unit in the support phase and at risk of slippage, the auxiliary downforce calculation module calculates the required target auxiliary downforce based on the anti-slip constraints and sends it to the negative pressure execution control module.

[0161] The negative pressure execution control module generates execution commands for the corresponding controllable negative pressure attachment foot assembly based on the target auxiliary downward pressure, contact phase variables, and working state switching results. These execution commands include at least a seal establishment command, a negative pressure establishment command, a negative pressure maintenance command, and a release / reset command. When the corresponding foot enters the seal establishment state, the negative pressure execution control module controls the seal trigger mechanism to press the sealing part, forming an initial seal between the foot and the ground. When the corresponding foot enters the negative pressure attachment state, the negative pressure execution control module controls the negative pressure generating mechanism to start and adjusts the negative pressure chamber pressure according to the target auxiliary downward pressure, causing the controllable negative pressure attachment foot assembly to generate the corresponding auxiliary downward pressure. When the corresponding foot enters the release / reset state, the negative pressure execution control module first controls the negative pressure generating mechanism to stop pumping or depressurizing, and then controls the seal trigger mechanism to release the seal pressing, allowing the foot to return to its normal support state or enter a swinging state.

[0162] Furthermore, the negative pressure execution control module can assist the downward pressure based on the target. and the area of ​​negative pressure on the foot The target negative pressure differential is determined, which can be expressed as:

[0163]

[0164] The operating state of the negative pressure generating mechanism is controlled based on the target negative pressure differential. Therefore, the target auxiliary downward pressure obtained by the AP-MPC predictive control module can be converted into a negative pressure control command that can be executed by the controllable negative pressure augmentation foot assembly.

[0165] The controllable negative pressure amplification foot end execution module is set at the end of each leg unit. It is used to respond to the execution command output by the negative pressure execution control module, and form a target auxiliary downward pressure at the corresponding support foot end through the foot bearing contact block 12, sealing trigger mechanism 6, annular sealing ring 13 and negative pressure generating mechanism.

[0166] The auxiliary downpressure feedback module is used to acquire the pressure of the negative pressure chamber, the sealing status, the working status of the negative pressure generating mechanism, and the estimated value of the actual auxiliary downpressure, and feeds it back to the AP-MPC predictive control module and the negative pressure execution control module. The AP-MPC predictive control module corrects the target auxiliary downpressure solution result for the next control cycle based on the feedback information; the negative pressure execution control module adjusts the working status of the negative pressure generating mechanism based on the feedback information, so that the actual auxiliary downpressure tracks the target auxiliary downpressure.

[0167] Through the aforementioned system, this invention establishes a closed-loop control process: "state perception—contact judgment—reference state generation—AP-MPC model control—assisted downward pressure solution—foot end state switching—negative pressure execution control—assisted downward pressure feedback." Therefore, the target assisted downward pressure not only remains at the control algorithm solution level but can be further transformed into the sealing establishment, negative pressure establishment, negative pressure maintenance, and release reset actions of each controllable negative pressure-attached foot end assembly, enabling the attachment... Figure 4 The foot end working state switching logic shown is related to the appendix. Figure 5 The AP-MPC anti-skid stability control system shown forms a corresponding relationship, thereby realizing the on-demand application and cyclic feedback control of the auxiliary downforce of each support foot under wet and slippery road surface.

Claims

1. A method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces, characterized in that, A controllable negative pressure attachment foot assembly is provided at the end of each leg unit of the heavy-duty quadruped robot. The controllable negative pressure attachment foot assembly includes a sealing trigger mechanism and a negative pressure generating mechanism; the control method includes the following steps: S1. Obtain the robot's current operating status, the contact status information of each leg unit's foot end, and the road surface status information; S2. Generate a reference state sequence in the prediction time domain based on the robot task instructions, path planning results, speed instructions, and current state; S3. Taking the robot's center of mass motion and posture motion as the prediction objects, and using the tangential contact force and net normal support force at the ends of each supporting foot as the basic control variables, a discretized robot AP-MPC control prediction model is established. S4. Introduce auxiliary downward pressure, define the effective normal clamping force of the support foot as the sum of the net normal support force and the auxiliary downward pressure, and modify the anti-slip constraint at the foot end of the support foot accordingly; S5. Calculate the target auxiliary downforce that meets the anti-skid margin requirements based on the tangential force requirements of each support foot, the net normal support force, the road surface friction coefficient, and the preset safety factor; S6. Solve the AP-MPC optimization problem in each control cycle and output the optimal tangential contact force, net normal support force and target auxiliary downforce at the foot end of each support. S7. The target auxiliary downward pressure is sent to the controllable negative pressure attachment foot assembly of the corresponding support foot, the control sealing trigger mechanism establishes a seal and starts the negative pressure generating mechanism to generate auxiliary downward pressure; when the foot enters the swing phase or the slip risk is eliminated, the pressure is released and the seal is released, so that the foot returns to the normal state.

2. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 1, characterized in that, The sealing triggering mechanism adopts a cam-type triggering structure, including a cam trigger, a sealing and clamping switching component, and an annular sealing ring. The annular sealing ring is located at the grounding edge of the foot end of the leg unit, used to form a sealing boundary with the ground when the seal is established. The cam trigger and the sealing and clamping switching component are located inside the lower leg mechanism. Under the driving action, the cam trigger pushes the sealing and clamping switching component to move, causing the sealing and clamping switching component to drive the annular sealing ring into the clamping state. The negative pressure generating mechanism includes a miniature electric vacuum pump, a foot-bearing contact block, and a negative pressure adsorption hole. The contact block is located in the central area of ​​the bottom of the foot of the leg unit. It is used to contact the ground during the robot's normal walking and support, and bears the main normal load and tangential contact force. The negative pressure adsorption hole is set in the circumferential or outer circumferential area of ​​the foot bearing contact block. The negative pressure adsorption hole is connected to a micro electric vacuum pump. It is used to evacuate the contact area of ​​the foot after the seal is established, thereby generating a negative pressure adsorption effect. The micro electric vacuum pump is connected to the negative pressure adsorption hole through a negative pressure pipeline. It is used to evacuate the negative pressure area of ​​the foot after the seal is established, so that an auxiliary downward pressure is formed between the foot and the ground.

3. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 1, characterized in that, The controllable negative pressure attachment foot assembly has a normal support state, a seal establishment state, a negative pressure attachment state, and a release and reset state. In the normal support state, the sealing trigger mechanism and the micro electric vacuum pump are not activated. In the seal establishment state, the sealing trigger mechanism is activated, pressing the foot tightly against the ground for a seal. In the negative pressure attachment state, the negative pressure generating mechanism is activated, generating auxiliary downward pressure between the foot and the ground. In the release and reset state, the negative pressure generating mechanism stops or releases the negative pressure, and the sealing trigger mechanism releases the pressure.

4. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 1, characterized in that, In S1, the robot's current operating status information includes the robot's center of mass position, robot speed, robot posture, and robot angular velocity; the leg unit foot contact status information includes whether each leg unit foot is in the support phase, the position of each leg unit foot relative to the robot's center of mass, the estimated contact force of each leg unit foot, and the current auxiliary downward pressure state of each leg unit foot. The road surface condition information includes the wet and slippery road surface identification results and the estimated value of the road surface friction coefficient; in S2, the reference state includes the robot's center of mass reference position, velocity, attitude and angular velocity.

5. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 1, characterized in that, In S3, the discretized robot AP-MPC control prediction model expression is: ； in, For the first Robot state vector for each control cycle; The vector of the tangential contact force at the foot end of each supporting foot; The net normal support force vector at the foot end of each support; For the first Discrete state transition matrix corresponding to each control cycle; For the first The tangential contact force input matrix corresponding to each control cycle; For the first Net normal support force input matrix corresponding to each control cycle; These are the gravity term, the linearized bias term, and the known perturbation term.

6. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 1, characterized in that, In S4, the effective normal clamping force for: ； in, Let be the net normal support force at the foot end of the i-th support; The auxiliary downward pressure at the i-th supporting foot end; The anti-slip constraint is: ； in, To preset the anti-slip safety factor, ; For the first The coefficient of friction of the road surface corresponding to the foot of each support.

7. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 6, characterized in that, In S5, the target assisted downforce for: ； Specifically, when the robot is on a slippery surface, starting under heavy load, braking, turning, or resisting disturbances, if the tangential force requirement at the supporting foot increases or the friction coefficient decreases, the target auxiliary downward pressure... The margin is increased accordingly to compensate for insufficient friction at the foot.

8. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 1, characterized in that, In S6, the objective function for solving the AP-MPC optimization problem is... for: ； in, To predict the first in the time domain The change in target-assisted downpressure corresponding to each prediction step is expressed as: , , and The weight matrix is ​​pre-defined based on the control objective; The optimization problem satisfies the following constraints: ； ； ； ； ； in, For the first The contact phase variable at the foot end of each leg unit, for the supporting foot, For the swing foot, ; This represents the maximum net normal support force. To provide maximum auxiliary downforce; To assist in the allowable rate of change of downward pressure.

9. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 1, characterized in that, It is achieved through a heavy-duty quadruped robot anti-slip and stability control system on wet and slippery surfaces, the control system including: The state perception module is used to acquire information about the robot's current operating state, foot contact state, and road surface state. The contact state determination module is used to determine whether each foot is in the support phase or the swing phase and to generate contact phase variables; The reference state generation module is used to generate a reference state sequence in the prediction time domain; The AP-MPC control prediction module is used to establish the AP-MPC control prediction model and solve the tangential contact force, net normal support force and target auxiliary downforce of each support foot. The auxiliary downforce calculation module is used to calculate the target auxiliary downforce of each support foot based on the anti-slip constraint; The negative pressure execution control module is used to generate seal establishment command, negative pressure establishment command, negative pressure maintenance command and release reset command based on the target auxiliary pressure and contact phase variable; A controllable negative pressure amplification foot-end execution module is installed at the end of each leg unit to respond to execution commands and generate target auxiliary downward pressure at the corresponding supporting foot; The auxiliary pressure feedback module is used to obtain the pressure in the negative pressure chamber and the estimated actual auxiliary pressure, and feed it back to the AP-MPC control prediction module and the negative pressure execution control module.

10. The method for anti-slip and stability control of a heavy-duty quadruped robot on wet and slippery surfaces as described in claim 9, characterized in that, The negative pressure execution control module assists the pressure based on the target. and the area of ​​negative pressure on the foot The target negative pressure differential is determined and expressed as follows: 。

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