A driving stability control method and system for a Mecanum wheeled robot

Abstract

The present invention discloses a driving stability control method and system for a Mecanum wheeled robot, including: obtaining geometric structure data and motion state data of the Mecanum wheeled robot; obtaining the nonholonomic constraints of the Mecanum wheeled robot according to the geometric structure data and motion state data of the Mecanum wheeled robot, and obtaining the dynamic equation of the Mecanum wheeled robot in combination with the Lagrangian principle; determining the mechanism information of the slip of the Mecanum wheeled robot according to the dynamic equation; setting and executing an adaptive control strategy for real-time tracking of the target trajectory according to the mechanism information of the slip of the Mecanum wheeled robot and the preset target trajectory. The coupling kinematics and dynamics analysis method reveals the slip generation mechanism of the Mecanum wheeled robot, comprehensively considers the influence of the slip on the longitudinal control and lateral control of the system, realizes high-precision control of the Mecanum wheeled robot, and improves the driving stability of the Mecanum wheeled robot.

Description

Technical Field

[0001] The present invention relates to the field of robot control technology, and in particular to a driving stability control method and system for a Mecanum wheeled robot. Background Art

[0002] In recent years, with the rapid development of computer and microelectronics manufacturing technology, robots have become an interdisciplinary and multi-integrated technical field. Due to the advantages of Mecanum wheel mobile robots such as no turning radius, flexible movement in limited space, and easy model construction, Mecanum wheel mobile robots have been widely used in many scenarios, such as road cleaning, shopping guides, ammunition loading, and the circulation of aircraft parts.

[0003] With the increase in the application fields of wheeled robots, Mecanum wheeled mobile robots will face challenges from unknown and complex environments at work. The trajectory tracking and control of wheeled robots in the human-machine-environment integration scenario has become a frontier issue in current research. The Mecanum wheeled mobile robot system has strong coupling and nonlinear characteristics. The traditional modeling idea is generally to simplify the motion process of the system, such as assuming that the robot's motion is always in an ideal motion state of pure rolling. However, in an unstructured environment, there may be relative slip (longitudinal and lateral slip) or even detachment between the driving wheels of the Mecanum wheeled mobile robot and the ground, which makes the precise tracking and control of the Mecanum wheeled robot extremely complex and difficult. Therefore, it is an urgent problem to establish a perfect dynamic model of the Mecanum wheeled mobile robot and predict its dynamic behavior. How to accurately reflect the dynamic contact behavior between the Mecanum wheel and the ground when the wheel slips and detaches from the ground is a key scientific issue. In addition, current research on the control of Mecanum-wheeled mobile robots mainly tends to focus on kinematic control, ignoring the force environment of the system, making it impossible to accurately track the robot's target trajectory in an unstructured environment. Therefore, comprehensively considering non-smooth factors such as slippage, and realizing high-precision tracking control of Mecanum-wheeled mobile robots in unstructured environments has positive theoretical significance and broad application prospects. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the above-mentioned technologies to a certain extent. To this end, the first purpose of the present invention is to propose a driving stability control method for a Mecanum wheeled robot, coupling kinematics and dynamics analysis methods to reveal the slippage generation mechanism of the Mecanum wheeled robot, comprehensively considering the impact of slippage on the longitudinal control and lateral control of the system, and setting and executing an adaptive control strategy for real-time tracking of the target trajectory according to the slippage mechanism information of the Mecanum wheeled robot and the preset target trajectory, so as to achieve high-precision control of the Mecanum wheeled robot and improve the driving stability of the Mecanum wheeled robot.

[0005] The second object of the present invention is to provide a driving stability control system for a Mecanum wheeled robot.

[0006] To achieve the above object, a first embodiment of the present invention provides a driving stability control method for a Mecanum wheeled robot, comprising:

[0007] Obtain the geometric structure data and motion state data of the Mecanum wheeled robot;

[0008] The nonholonomic constraints of the Mecanum wheeled robot are obtained according to the geometric structure data and motion state data of the Mecanum wheeled robot, and the dynamic equation of the Mecanum wheeled robot is obtained by combining the Lagrangian principle.

[0009] Determine the mechanism information of the Mecanum wheel robot's slip based on the dynamic equation;

[0010] According to the sliding mechanism information of the Mecanum wheel robot and the preset target trajectory, an adaptive control strategy for real-time tracking of the target trajectory is set and executed.

[0011] According to some embodiments of the present invention, the geometric structure data includes a hub, a roller mounted on the hub, a diameter and a width of the Mecanum wheel, and a size of the roller; and the motion state data includes speed, acceleration, angular velocity, and motion direction.

[0012] According to some embodiments of the present invention, obtaining the nonholonomic constraints of the Mecanum wheeled robot according to the geometric structure data and the motion state data of the Mecanum wheeled robot includes:

[0013] The Mecanum wheeled robot has four wheels, and the rotation speed and direction of each wheel are w i and θ i (i=1,2,3,4), the linear velocity and angular velocity of the Mecanum wheeled robot are v and w respectively, determine the kinematic equation of the Mecanum wheeled robot;

[0014]

[0015] Among them, J(θ) is the Jacobian matrix of the Mecanum wheeled robot, which describes the mapping relationship between the wheel speed and the overall motion state of the Mecanum wheeled robot;

[0016] Analyze the first value range of J(θ) and w i The second value range of the Mecanum wheeled robot is retrieved by querying the corresponding data table to determine the control information of the wheel speed of the Mecanum wheeled robot and the restriction information of the rolling direction of the roller when the wheel contacts the ground, which are used as the non-holonomic constraints of the Mecanum wheeled robot.

[0017] According to some embodiments of the present invention, the dynamic equations of the Mecanum wheeled robot are obtained by combining the Lagrangian principle, including:

[0018] The Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, L;

[0019] L=TU

[0020] Where, T is the kinetic energy of the Mecanum wheeled robot; U is the potential energy of the Mecanum wheeled robot;

[0021] The kinetic energy T can be expressed as the sum of the rotational kinetic energy of each wheel and the translational kinetic energy of the robot, that is:

[0022]

[0023] Where n is the number of wheels included in the Mecanum wheeled robot; i is the moment of inertia of the i-th wheel; m is the mass of the Mecanum wheeled robot;

[0024] Apply Lagrange's equations;

[0025]

[0026] in, To represent the derivative operation with respect to time t, describe the rate at which a variable changes over time; q' j is the generalized speed of the Mecanum wheeled robot; q j is the generalized coordinate of the Mecanum wheeled robot, which is the rotation angle of the wheel or the position coordinate of the robot; G is the nonholonomic constraint of the Mecanum wheeled robot; Q j is the generalized coordinate q j The corresponding generalized force includes driving force and friction force;

[0027] By substituting the Lagrangian function and the generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed of each wheel, the steering, the linear velocity and angular velocity variables of the robot, and the interaction relationship between them.

[0028] According to some embodiments of the present invention, the mechanism information includes whether the friction of the wheel is greater than a preset friction threshold, whether there is a movement greater than a preset speed, whether there is a movement greater than a preset acceleration, and whether the wheel layout and driving method are reasonable.

[0029] According to some embodiments of the present invention, an adaptive control strategy for real-time tracking of a target trajectory is set according to the mechanism information of the Mecanum wheel robot slipping and a preset target trajectory, including:

[0030] Collect the sliding trajectory of the Mecanum wheel robot after sliding;

[0031] Calculate the distance information between the sliding trajectory and the target trajectory;

[0032]

[0033] Where D is the distance information between the sliding trajectory and the target trajectory; m is the number of trajectory points included in the sliding trajectory, which is also the number of trajectory points included in the target trajectory, and the two are equal; (x 1i ,y 1i , z 1i ) is the coordinate of the i-th track point included in the sliding track; (x 2i ,y 2i , z 2i ) is the coordinate of the i-th trajectory point included in the target trajectory;

[0034] Compare the distance information with the preset distance information, and when it is determined that the distance information is less than or equal to the preset distance information, execute the current control strategy; when it is determined that the distance is less than or greater than the preset distance information, segment the sliding trajectory to obtain s segments of sliding trajectories; segment the target trajectory to obtain s segments of target trajectories;

[0035] Calculate the matching degree P between the sliding trajectory and the target trajectory:

[0036]

[0037] Among them, p i is the matching degree between the ith sub-slip trajectory and the ith sub-target trajectory;

[0038] According to the matching degree, the preset slip level data table is queried to determine the corresponding slip level;

[0039] When the slip level is determined to be high, an adaptive control strategy for adjusting wheel layout and driving mode is generated;

[0040] When the slip level is determined to be a medium level, an adaptive control strategy for deceleration is generated;

[0041] When the slip level is determined to be a low level, an adaptive control strategy for increasing the friction of the wheels is generated.

[0042] To achieve the above object, a second embodiment of the present invention provides a Mecanum wheeled robot driving stability control system, comprising:

[0043] The acquisition module is used to obtain the geometric structure data and motion state data of the Mecanum wheeled robot;

[0044] A calculation module is used to obtain the nonholonomic constraints of the Mecanum wheeled robot according to the geometric structure data and motion state data of the Mecanum wheeled robot, and obtain the dynamic equation of the Mecanum wheeled robot in combination with the Lagrangian principle;

[0045] A determination module is used to determine the mechanism information of the Mecanum wheel robot slipping according to the dynamic equation;

[0046] The setting module is used to set and execute the adaptive control strategy for real-time tracking of the target trajectory according to the mechanism information of the Mecanum wheel robot slip and the preset target trajectory.

[0047] According to some embodiments of the present invention, the computing module includes:

[0048] Determine the submodule for the Mecanum wheeled robot with 4 wheels, each with a rotation speed and a steering speed of w i and θ i (i=1,2,3,4), the linear velocity and angular velocity of the Mecanum wheeled robot are v and w respectively, determine the kinematic equation of the Mecanum wheeled robot;

[0049]

[0050] Among them, J(θ) is the Jacobian matrix of the Mecanum wheeled robot, which describes the mapping relationship between the wheel speed and the overall motion state of the Mecanum wheeled robot;

[0051] Analysis submodule, used to analyze the first value range of J(θ) and w iThe second value range of the Mecanum wheeled robot is retrieved by querying the corresponding data table to determine the control information of the wheel speed of the Mecanum wheeled robot and the restriction information of the rolling direction of the roller when the wheel contacts the ground, which are used as the non-holonomic constraints of the Mecanum wheeled robot.

[0052] According to some embodiments of the present invention, the computing module further includes:

[0053] Define submodules for:

[0054] The Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, L;

[0055] L=TU

[0056] Where, T is the kinetic energy of the Mecanum wheeled robot; U is the potential energy of the Mecanum wheeled robot;

[0057] The kinetic energy T can be expressed as the sum of the rotational kinetic energy of each wheel and the translational kinetic energy of the robot, that is:

[0058]

[0059] Where n is the number of wheels included in the Mecanum wheeled robot; i is the moment of inertia of the i-th wheel; m is the mass of the Mecanum wheeled robot;

[0060] Application submodules for:

[0061] Apply Lagrange's equations;

[0062]

[0063] in, To represent the derivative operation with respect to time t, describe the rate at which a variable changes over time; q' j is the generalized speed of the Mecanum wheeled robot; q j is the generalized coordinate of the Mecanum wheeled robot, which is the rotation angle of the wheel or the position coordinate of the robot; G is the nonholonomic constraint of the Mecanum wheeled robot; Q j is the generalized coordinate q j The corresponding generalized force includes driving force and friction force;

[0064] By substituting the Lagrangian function and the generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed of each wheel, the steering, the linear velocity and angular velocity variables of the robot, and the interaction relationship between them.

[0065] According to some embodiments of the present invention, the setting module includes:

[0066] The acquisition submodule is used to: acquire the sliding trajectory of the Mecanum wheel robot after sliding;

[0067] Generate submodules for:

[0068] Calculate the distance information between the sliding trajectory and the target trajectory;

[0069]

[0070] Where D is the distance information between the sliding trajectory and the target trajectory; m is the number of trajectory points included in the sliding trajectory, which is also the number of trajectory points included in the target trajectory, and the two are equal; (x 1i ,y 1i , z 1i ) is the coordinate of the i-th track point included in the sliding track; (x 2i ,y 2i , z 2i ) is the coordinate of the i-th trajectory point included in the target trajectory;

[0071] Compare the distance information with the preset distance information, and when it is determined that the distance information is less than or equal to the preset distance information, execute the current control strategy; when it is determined that the distance is less than or greater than the preset distance information, segment the sliding trajectory to obtain s segments of sliding trajectories; segment the target trajectory to obtain s segments of target trajectories;

[0072] Calculate the matching degree P between the sliding trajectory and the target trajectory:

[0073]

[0074] Among them, p i is the matching degree between the ith sub-slip trajectory and the ith sub-target trajectory;

[0075] According to the matching degree, the preset slip level data table is queried to determine the corresponding slip level;

[0076] When the slip level is determined to be high, an adaptive control strategy for adjusting wheel layout and driving mode is generated;

[0077] When the slip level is determined to be a medium level, an adaptive control strategy for deceleration is generated;

[0078] When the slip level is determined to be a low level, an adaptive control strategy for increasing the friction of the wheels is generated.

[0079] The present invention proposes a driving stability control method and system for a Mecanum wheeled robot, coupling kinematics and dynamics analysis methods to reveal the slippage generation mechanism of the Mecanum wheeled robot, comprehensively considering the impact of the slippage on the longitudinal control and lateral control of the system, and setting and executing an adaptive control strategy for real-time tracking of the target trajectory according to the slippage mechanism information of the Mecanum wheeled robot and a preset target trajectory, so as to achieve high-precision control of the Mecanum wheeled robot and improve the driving stability of the Mecanum wheeled robot.

[0080] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0081] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0082] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0083] Figure 1 is a flow chart of a driving stability control method for a Mecanum wheeled robot according to an embodiment of the present invention;

[0084] Figure 2 is a block diagram of a Mecanum wheeled robot driving stability control system according to an embodiment of the present invention;

[0085] Figure 3 is a schematic diagram of a Mecanum wheeled robot according to an embodiment of the present invention;

[0086] Figure 4 Schematic diagram of a Mecanum wheeled robot according to an embodiment of the present invention. DETAILED DESCRIPTION

[0087] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0088] like Figure 1 As shown, the first embodiment of the present invention proposes a driving stability control method for a Mecanum wheeled robot, comprising steps S1-S4:

[0089] S1, obtaining the geometric structure data and motion state data of the Mecanum wheeled robot;

[0090] S2. Obtain the nonholonomic constraints of the Mecanum wheeled robot based on the geometric structure data and motion state data of the Mecanum wheeled robot, and obtain the dynamic equation of the Mecanum wheeled robot in combination with the Lagrangian principle;

[0091] S3, determining the mechanism information of the Mecanum wheel robot slipping according to the dynamic equation;

[0092] S4. According to the sliding mechanism information of the Mecanum wheel robot and the preset target trajectory, an adaptive control strategy for real-time tracking of the target trajectory is set and executed.

[0093] The working principle of the above technical solution is as follows: Figure 3-4As shown in the figure, two types of Mecanum wheeled robots are shown. The geometric structure data include the wheel hub, the roller mounted on the wheel hub, the diameter and width of the Mecanum wheel and the size of the roller; the motion state data include speed, acceleration, angular velocity and motion direction. Mecanum Wheel, referred to as Mecanum Wheel, is the core component of the Mecanum wheeled robot. Its geometric structure mainly includes the following parts: Wheel hub: the part fixed to the center of the wheel disc, serving as the support and driving center of the entire wheel. Roller: a drum-shaped roller mounted on the wheel hub that can rotate freely around its own axis. The outer contours of these rollers coincide with the theoretical circumference of the wheel, ensuring the continuity of the wheel's contact with the ground. The central axis of the roller is usually at a 45° angle to the central axis of the wheel hub. Overall size: the diameter and width of the Mecanum wheel and the size of the roller (such as length, diameter), etc., which are determined according to specific design and application requirements. For example, the diameter of the wheel may vary depending on factors such as load capacity and movement speed. Each Mecanum wheel has three degrees of freedom: the wheel rotates around its own axis, the roller rotates around its own axis, and the wheel rotates around its contact point with the ground. The motion state data of the Mecanum wheeled robot includes its speed, acceleration, angular velocity, and direction of motion. Speed: The movement speed of the robot can be achieved by controlling the rotation speed of the Mecanum wheel. Since the Mecanum wheel has three degrees of freedom (rotation around its own axis, roller rotation around its own axis, and wheel rotation around the contact point with the ground), the movement speed in any direction can be synthesized by adjusting the rotation speed and direction of different wheels. Acceleration: The acceleration of the robot depends on the driving torque and load of the Mecanum wheel. By controlling the output torque of the motor, the acceleration of the robot can be precisely controlled. Angular velocity: The angular velocity of the robot can also be achieved by adjusting the rotation speed and direction of the Mecanum wheel. For example, when all wheels rotate at the same speed but in different directions, the robot will rotate around its geometric center. Movement direction: The Mecanum wheeled robot can achieve full range of motion in a plane, including forward, backward, sideways, and rotation in place. These motion directions can be achieved by adjusting the speed and direction of the Mecanum wheels. The motion state data of the Mecanum wheeled robot is usually collected through sensors (such as encoders, gyroscopes, etc.) and processed and analyzed by the control system.

[0094] Working principle of Mecanum wheel: The rollers on the Mecanum wheel are installed on the wheel surface at a certain angle (usually 45 degrees), so that when the wheel rotates, the rollers not only move along the circumference of the wheel, but also move along its axial direction (i.e. perpendicular to the rotation axis of the wheel). This design enables the robot to achieve complex movement patterns by adjusting the speed and direction of each Mecanum wheel.

[0095] In this embodiment, the non-holonomic constraints of the Mecanum wheeled robot are mainly derived from its contact mode with the ground. Since the roller is in high-pair contact with the ground, and the axis of the roller is at a certain angle to the wheel axis, the movement of the robot is subject to the complex influence of ground friction and roller rotation. This constraint relationship makes it impossible for the robot to achieve movement in any direction only through position control, but needs to be achieved by adjusting the rotation speed and steering of each wheel. For the Mecanum wheeled robot, its non-holonomic constraints are mainly reflected in the fact that its movement is not only controlled by the wheel rotation speed, but also restricted by the rolling direction of the roller when the wheel contacts the ground. The non-holonomic constraints of the Mecanum wheeled robot include: rolling constraint: When the roller on the Mecanum wheel contacts the ground, its rolling direction is jointly affected by the wheel rotation speed and steering. Since the roller is at a certain angle to the wheel axis, the rotation of the wheel will cause the roller to roll obliquely on the ground. This rolling direction is fixed and cannot be changed by simple position adjustment. Omnidirectional movement constraint: The Mecanum wheeled robot can achieve omnidirectional movement, but this does not mean that it can change its movement direction or speed instantly. The direction and speed of the robot's movement are determined by the rotation speed and direction of each wheel, and there are certain constraints between these parameters. For example, to achieve straight-line movement, the rotation speed and direction of all wheels need to be the same; to achieve rotation in place, the rotation speed and direction of the wheels need to be adjusted so that the total torque on the robot as a whole is zero, but the linear speed is zero. Ground contact constraint: During the movement of the Mecanum wheeled robot, the contact point between its wheels and the ground must maintain continuous and stable contact. This contact constraint limits the robot's ability to move under certain extreme conditions, such as on uneven ground or when encountering obstacles.

[0096] Due to the complexity of nonholonomic constraints, it is usually difficult to fully express them with simple mathematical equations. We start with the robot's kinematic equations and indirectly describe nonholonomic constraints by analyzing the relationship between the wheel speed, steering and the overall motion state of the robot. The kinematic equations of a wheeled robot mainly describe the relationship between the position, velocity and acceleration of the robot's end effector (such as grippers, tools, etc.) and the position, velocity and acceleration of each joint of the robot (for a wheeled robot, it can be understood as each wheel). The kinematic equations do not involve the action of forces, but only focus on how the robot realizes the movement of the end effector based on the movement of the joints.

[0097] The Lagrange principle is one of the basic principles in analytical mechanics, which establishes the relationship between the difference between the kinetic energy and potential energy of a system (i.e., the Lagrange function) and the motion of the system.

[0098] The dynamic equation of a wheeled robot involves the action of forces, which describes the relationship between the driving force or torque of each joint (wheel) of the robot and the robot's motion state (position, velocity, acceleration). The dynamic equation is a complex dynamic system, and the dynamic response to the object being handled depends on the robot's dynamic model and control algorithm.

[0099] The target trajectory is a moving trajectory determined based on the starting point, end point and driving requirements. In the process of executing the target trajectory, in the actual working environment, the Mecanum wheeled mobile robot often slips due to reasons such as slippery ground, ice and aging of the outer rubber of the wheels, which seriously affects the position and motion state of the robot; in addition, slippage is difficult to measure directly and accurately, which increases the control difficulty of the trajectory tracking of the Mecanum wheeled mobile robot. Based on the fact that slippage can also cause the Mecanum wheeled robot to be unable to execute the target trajectory, the mechanism information of slippage is determined, and an adaptive control strategy for real-time tracking of the target trajectory is set to achieve high-precision and stable control of the Mecanum wheeled robot and improve the driving stability of the Mecanum wheeled robot.

[0100] The beneficial effects of the above technical solution are as follows: the coupling kinematic and dynamic analysis methods reveal the slippage mechanism of the Mecanum wheeled robot, and the impact of slippage on the longitudinal control and lateral control of the system is comprehensively considered. According to the slippage mechanism information of the Mecanum wheeled robot and the preset target trajectory, an adaptive control strategy for real-time tracking of the target trajectory is set and executed to achieve high-precision control of the Mecanum wheeled robot and improve the driving stability of the Mecanum wheeled robot.

[0101] According to some embodiments of the present invention, obtaining the nonholonomic constraints of the Mecanum wheeled robot according to the geometric structure data and the motion state data of the Mecanum wheeled robot includes:

[0102] The Mecanum wheeled robot has four wheels, and the rotation speed and direction of each wheel are w i and θ i (i=1,2,3,4), the linear velocity and angular velocity of the Mecanum wheeled robot are v and w respectively, determine the kinematic equation of the Mecanum wheeled robot;

[0103]

[0104] Among them, J(θ) is the Jacobian matrix of the Mecanum wheeled robot, which describes the mapping relationship between the wheel speed and the overall motion state of the Mecanum wheeled robot;

[0105] Analyze the first value range of J(θ) and w i The second value range of the Mecanum wheeled robot is retrieved by querying the corresponding data table to determine the control information of the wheel speed of the Mecanum wheeled robot and the restriction information of the rolling direction of the roller when the wheel contacts the ground, which are used as the non-holonomic constraints of the Mecanum wheeled robot.

[0106] Working principle and beneficial effects of the above technical solution: Jacobian matrix is ​​a mathematical tool that describes the relationship between the speed of the robot end effector and the joint speed. For the Mecanum wheeled robot, the Jacobian matrix describes the mapping relationship between the wheel speed and the overall motion state of the robot (such as linear velocity and angular velocity). Through the Jacobian matrix, the motion state of the robot in space is calculated according to the wheel speed, thereby achieving precise control of the robot motion. Construction of Jacobian matrix of Mecanum wheeled robot: Determine the robot's degrees of freedom: The degrees of freedom of the Mecanum wheeled robot depend on the number and layout of its wheels. For example, a robot consisting of four Mecanum wheels usually has three translational degrees of freedom and one rotational degree of freedom (i.e., X-axis translation, Y-axis translation, Z-axis rotation, and yaw-axis rotation). Establish the robot's kinematic model: This includes determining the geometric parameters of the wheels, kinematic constraints, and their relationship with the overall motion of the robot. Differential kinematic equation: Differentiate the robot's kinematic equation to find the relationship between the wheel speed and the robot's overall motion state. This usually involves modeling small changes in the position or attitude of the robot's end effector and correlating them with changes in the wheel speed. Solving the Jacobian matrix: By solving the differential kinematic equations, the specific expression of the Jacobian matrix can be obtained. This matrix maps the wheel speed to the overall motion state of the robot. The Jacobian matrix has important applications in motion control, path planning and stability analysis. The specific form of the Jacobian matrix will vary depending on the layout of the Mecanum wheels and the structure of the robot. Analyzing and calculating it will help to better understand and control the motion of the Mecanum wheeled robot. Determine the first value range and w of the kinematic equation analysis J(θ) of the Mecanum wheeled robot i The second value range is used to query the corresponding data table of the first value range - the second value range - the control information of the wheel speed and the restriction information of the rolling direction of the roller when the wheel contacts the ground, and the corresponding information is determined to facilitate the accurate determination of the non-complete constraints of the Mecanum wheeled robot.

[0107] According to some embodiments of the present invention, the dynamic equation of the Mecanum wheeled robot is obtained by combining the Lagrangian principle, including:

[0108] The Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, L;

[0109] L=TU

[0110] Where, T is the kinetic energy of the Mecanum wheeled robot; U is the potential energy of the Mecanum wheeled robot;

[0111] The kinetic energy T can be expressed as the sum of the rotational kinetic energy of each wheel and the translational kinetic energy of the robot, that is:

[0112]

[0113] Where n is the number of wheels included in the Mecanum wheeled robot; i is the moment of inertia of the i-th wheel; m is the mass of the Mecanum wheeled robot;

[0114] Apply Lagrange's equations;

[0115]

[0116] in, To represent the derivative operation with respect to time t, describe the rate at which a variable changes over time; q' j is the generalized speed of the Mecanum wheeled robot; q j is the generalized coordinate of the Mecanum wheeled robot, which is the rotation angle of the wheel or the position coordinate of the robot; G is the nonholonomic constraint of the Mecanum wheeled robot; Q j is the generalized coordinate q j The corresponding generalized force includes driving force and friction force;

[0117] By substituting the Lagrangian function and the generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed of each wheel, the steering, the linear velocity and angular velocity variables of the robot, and the interaction relationship between them.

[0118] The working principle and beneficial effects of the above technical solution are as follows: First, the Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, and U is the potential energy of the Mecanum wheeled robot, which can generally be ignored. Applying the Lagrangian equation, by substituting the Lagrangian function and generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed, steering, linear velocity and angular velocity variables of each wheel, and the interaction relationship between them. It is convenient to accurately obtain the dynamic equation of the Mecanum wheeled robot.

[0119] According to some embodiments of the present invention, the mechanism information includes whether the friction of the wheel is greater than a preset friction threshold, whether there is a movement greater than a preset speed, whether there is a movement greater than a preset acceleration, and whether the wheel layout and driving method are reasonable.

[0120] Working principle and beneficial effects of the above technical solution: Dynamic equation analysis, friction between roller and ground: The slip of Mecanum wheel is mainly affected by the friction between roller and ground. If the friction is insufficient (such as the ground is slippery or the roller is worn), the robot may slip. Wheel speed and acceleration: The rotation speed and acceleration of Mecanum wheel directly affect the movement speed and acceleration of the robot. Too high wheel speed or acceleration may reduce the contact time between roller and ground, thereby reducing friction and increasing the possibility of slip. Wheel layout and drive mode: The layout of Mecanum wheel on the robot (such as number, position) and drive mode (such as independent drive or cooperative drive) will also affect slip. Reasonable layout and drive mode can optimize the mobility of the robot and reduce slip. Therefore, the slip mechanism information is insufficient friction: When the friction between roller and ground is not enough to provide sufficient traction, the robot will slip. High-speed or high-acceleration movement: When moving at high speed or high acceleration, the contact time between roller and ground is reduced, friction is reduced, and the risk of slip is increased. Improper wheel layout and drive mode: Improper wheel layout and drive mode may cause the robot to slip more easily in certain moving directions.

[0121] According to some embodiments of the present invention, an adaptive control strategy for real-time tracking of a target trajectory is set according to the mechanism information of the Mecanum wheel robot slipping and a preset target trajectory, including:

[0122] Collect the sliding trajectory of the Mecanum wheel robot after sliding;

[0123] Calculate the distance information between the sliding trajectory and the target trajectory;

[0124]

[0125] Where D is the distance information between the sliding trajectory and the target trajectory; m is the number of trajectory points included in the sliding trajectory, which is also the number of trajectory points included in the target trajectory, and the two are equal; (x 1i ,y 1i , z 1i ) is the coordinate of the i-th track point included in the sliding track; (x 2i ,y 2i , z 2i ) is the coordinate of the i-th trajectory point included in the target trajectory;

[0126] Compare the distance information with the preset distance information, and when it is determined that the distance information is less than or equal to the preset distance information, execute the current control strategy; when it is determined that the distance is less than or greater than the preset distance information, segment the sliding trajectory to obtain s segments of sliding trajectories; segment the target trajectory to obtain s segments of target trajectories;

[0127] Calculate the matching degree P between the sliding trajectory and the target trajectory:

[0128]

[0129] Among them, p i is the matching degree between the ith sub-slip trajectory and the ith sub-target trajectory;

[0130] According to the matching degree, the preset slip level data table is queried to determine the corresponding slip level;

[0131] When the slip level is determined to be high, an adaptive control strategy for adjusting wheel layout and driving mode is generated;

[0132] When the slip level is determined to be a medium level, an adaptive control strategy for deceleration is generated;

[0133] When the slip level is determined to be a low level, an adaptive control strategy for increasing the friction of the wheels is generated.

[0134] The working principle of the above technical solution is: collect the slip trajectory of the Mecanum wheel robot after slipping, calculate the distance information between the slip trajectory and the target trajectory, compare the distance information with the preset distance information, and when it is determined that the distance information is less than or equal to the preset distance information, execute the current control strategy, that is, do not change the strategy. When it is determined that the distance is less than or greater than the preset distance information, the slip trajectory and the target trajectory are divided respectively, the corresponding parts are matched respectively, the matching degree of the final slip trajectory and the target trajectory is calculated, and the preset slip level data table is queried according to the matching degree to determine the corresponding slip level; that is, determine the range to which the matching degree belongs, and determine the slip level corresponding to the range. The lower the matching degree, the higher the slip level. When the slip level is determined to be a high level, an adaptive control strategy for adjusting the wheel layout and driving mode is generated; when the slip level is determined to be a medium level, an adaptive control strategy for deceleration is generated; when the slip level is determined to be a low level, an adaptive control strategy for increasing the friction of the wheel is generated.

[0135] The beneficial effects of the above technical solution are: generating corresponding adaptive control strategies based on different slip levels, improving the stability and mobility of the robot, avoiding too fast or too hasty movement, ensuring sufficient friction between the roller and the ground, and improving the stability of the Mecanum wheel robot movement.

[0136] like Figure 2 As shown, the second embodiment of the present invention proposes a Mecanum wheeled robot driving stability control system, including:

[0137] The acquisition module is used to obtain the geometric structure data and motion state data of the Mecanum wheeled robot;

[0138] A calculation module is used to obtain the nonholonomic constraints of the Mecanum wheeled robot according to the geometric structure data and motion state data of the Mecanum wheeled robot, and obtain the dynamic equation of the Mecanum wheeled robot in combination with the Lagrangian principle;

[0139] A determination module is used to determine the mechanism information of the Mecanum wheel robot slipping according to the dynamic equation;

[0140] The setting module is used to set and execute the adaptive control strategy for real-time tracking of the target trajectory according to the mechanism information of the Mecanum wheel robot slip and the preset target trajectory.

[0141] The beneficial effects of the above technical solution are as follows: the coupling kinematic and dynamic analysis methods reveal the slippage mechanism of the Mecanum wheeled robot, and the impact of slippage on the longitudinal control and lateral control of the system is comprehensively considered. According to the slippage mechanism information of the Mecanum wheeled robot and the preset target trajectory, an adaptive control strategy for real-time tracking of the target trajectory is set and executed to achieve high-precision control of the Mecanum wheeled robot and improve the driving stability of the Mecanum wheeled robot.

[0142] According to some embodiments of the present invention, the computing module includes:

[0143] Determine the submodule for the Mecanum wheeled robot with 4 wheels, each with a rotation speed and a steering speed of w i and θ i (i=1,2,3,4), the linear velocity and angular velocity of the Mecanum wheeled robot are v and w respectively, determine the kinematic equation of the Mecanum wheeled robot;

[0144]

[0145] Among them, J(θ) is the Jacobian matrix of the Mecanum wheeled robot, which describes the mapping relationship between the wheel speed and the overall motion state of the Mecanum wheeled robot;

[0146] Analysis submodule, used to analyze the first value range of J(θ) and w i The second value range of the Mecanum wheeled robot is retrieved by querying the corresponding data table to determine the control information of the wheel speed of the Mecanum wheeled robot and the restriction information of the rolling direction of the roller when the wheel contacts the ground, which are used as the non-holonomic constraints of the Mecanum wheeled robot.

[0147] Working principle and beneficial effects of the above technical solution: Determine the first value range of J(θ) and w of the kinematic equation analysis of the Mecanum wheeled robot iThe second value range is used to query the corresponding data table of the first value range - the second value range - the control information of the wheel speed and the restriction information of the rolling direction of the roller when the wheel contacts the ground, and the corresponding information is determined to facilitate the accurate determination of the non-complete constraints of the Mecanum wheeled robot.

[0148] According to some embodiments of the present invention, the computing module further includes:

[0149] Define submodules for:

[0150] The Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, L;

[0151] L=TU

[0152] Where, T is the kinetic energy of the Mecanum wheeled robot; U is the potential energy of the Mecanum wheeled robot;

[0153] The kinetic energy T can be expressed as the sum of the rotational kinetic energy of each wheel and the translational kinetic energy of the robot, that is:

[0154]

[0155] Where n is the number of wheels included in the Mecanum wheeled robot; i is the moment of inertia of the i-th wheel; m is the mass of the Mecanum wheeled robot;

[0156] Application submodules for:

[0157] Apply Lagrange's equations;

[0158]

[0159] in, To represent the derivative operation with respect to time t, describe the rate at which a variable changes over time; q' j is the generalized speed of the Mecanum wheeled robot; q j is the generalized coordinate of the Mecanum wheeled robot, which is the rotation angle of the wheel or the position coordinate of the robot; G is the nonholonomic constraint of the Mecanum wheeled robot; Q j is the generalized coordinate q j The corresponding generalized force includes driving force and friction force;

[0160] By substituting the Lagrangian function and the generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed of each wheel, the steering, the linear velocity and angular velocity variables of the robot, and the interaction relationship between them.

[0161] The working principle and beneficial effects of the above technical solution are as follows: First, the Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, and U is the potential energy of the Mecanum wheeled robot, which can generally be ignored. Applying the Lagrangian equation, by substituting the Lagrangian function and generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed, steering, linear velocity and angular velocity variables of each wheel, and the interaction relationship between them. It is convenient to accurately obtain the dynamic equation of the Mecanum wheeled robot.

[0162] According to some embodiments of the present invention, the setting module includes:

[0163] The acquisition submodule is used to: acquire the sliding trajectory of the Mecanum wheel robot after sliding;

[0164] Generate submodules for:

[0165] Calculate the distance information between the sliding trajectory and the target trajectory;

[0166]

[0167] Where D is the distance information between the sliding trajectory and the target trajectory; m is the number of trajectory points included in the sliding trajectory, which is also the number of trajectory points included in the target trajectory, and the two are equal; (x 1i ,y 1i , z 1i ) is the coordinate of the i-th track point included in the sliding track; (x 2i ,y 2i , z 2i ) is the coordinate of the i-th trajectory point included in the target trajectory;

[0168] Compare the distance information with the preset distance information, and when it is determined that the distance information is less than or equal to the preset distance information, execute the current control strategy; when it is determined that the distance is less than or greater than the preset distance information, segment the sliding trajectory to obtain s segments of sliding trajectories; segment the target trajectory to obtain s segments of target trajectories;

[0169] Calculate the matching degree P between the sliding trajectory and the target trajectory:

[0170]

[0171] Among them, p i is the matching degree between the ith sub-slip trajectory and the ith sub-target trajectory;

[0172] According to the matching degree, the preset slip level data table is queried to determine the corresponding slip level;

[0173] When the slip level is determined to be high, an adaptive control strategy for adjusting wheel layout and driving mode is generated;

[0174] When the slip level is determined to be a medium level, an adaptive control strategy for deceleration is generated;

[0175] When the slip level is determined to be a low level, an adaptive control strategy for increasing the friction of the wheels is generated.

[0176] The beneficial effects of the above technical solution are: generating corresponding adaptive control strategies based on different slip levels, improving the stability and mobility of the robot, avoiding too fast or too hasty movement, ensuring sufficient friction between the roller and the ground, and improving the stability of the Mecanum wheel robot movement.

[0177] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A driving stability control method for a Mecanum wheeled robot, characterized in that: include: Obtain the geometric structure data and motion state data of the Mecanum wheeled robot; The nonholonomic constraints of the Mecanum wheeled robot are obtained according to the geometric structure data and motion state data of the Mecanum wheeled robot, and the dynamic equation of the Mecanum wheeled robot is obtained by combining the Lagrangian principle. Determine the mechanism information of the Mecanum wheel robot's slip based on the dynamic equation; According to the sliding mechanism information of the Mecanum wheel robot and the preset target trajectory, an adaptive control strategy for real-time tracking of the target trajectory is set and executed; According to the sliding mechanism information of the Mecanum wheel robot and the preset target trajectory, an adaptive control strategy for real-time tracking of the target trajectory is set, including: Collect the sliding trajectory of the Mecanum wheel robot after sliding; Calculate the distance information between the sliding trajectory and the target trajectory; Where D is the distance information between the sliding trajectory and the target trajectory; m is the number of trajectory points included in the sliding trajectory, which is also the number of trajectory points included in the target trajectory, and the two are equal; (x 1i ,y 1i , z 1i ) is the coordinate of the i-th track point included in the sliding track; (x 2i ,y 2i , z 2i ) is the coordinate of the i-th trajectory point included in the target trajectory; Compare the distance information with the preset distance information, and when it is determined that the distance information is less than or equal to the preset distance information, execute the current control strategy; when it is determined that the distance is less than or greater than the preset distance information, segment the sliding trajectory to obtain s segments of sliding trajectories; segment the target trajectory to obtain s segments of target trajectories; Calculate the matching degree P between the sliding trajectory and the target trajectory: Among them, p i is the matching degree between the ith sub-slip trajectory and the ith sub-target trajectory; According to the matching degree, the preset slip level data table is queried to determine the corresponding slip level; When the slip level is determined to be high, an adaptive control strategy for adjusting wheel layout and driving mode is generated; When the slip level is determined to be a medium level, an adaptive control strategy for deceleration is generated; When the slip level is determined to be a low level, an adaptive control strategy for increasing the friction of the wheels is generated.

2. The driving stability control method of the Mecanum wheeled robot according to claim 1, characterized in that: The geometric structure data includes the hub, the rollers mounted on the hub, the diameter and width of the Mecanum wheel and the size of the rollers; the motion state data includes the speed, acceleration, angular velocity and motion direction.

3. The driving stability control method of the Mecanum wheeled robot according to claim 1, characterized in that: According to the geometric structure data and motion state data of the Mecanum wheeled robot, the non-holonomic constraints of the Mecanum wheeled robot are obtained, including: The Mecanum wheeled robot has four wheels, and the rotation speed and direction of each wheel are w i and θ i (i=1,2,3,4), the linear velocity and angular velocity of the Mecanum wheeled robot are v and w respectively, determine the kinematic equation of the Mecanum wheeled robot; Among them, J(θ) is the Jacobian matrix of the Mecanum wheeled robot, which describes the mapping relationship between the wheel speed and the overall motion state of the Mecanum wheeled robot; Analyze the first value range of J(θ) and w i The second value range of the Mecanum wheeled robot is retrieved by querying the corresponding data table to determine the control information of the wheel speed of the Mecanum wheeled robot and the restriction information of the rolling direction of the roller when the wheel contacts the ground, which are used as the non-holonomic constraints of the Mecanum wheeled robot.

4. The driving stability control method of the Mecanum wheeled robot according to claim 3, characterized in that: Combining the Lagrangian principle, the dynamic equations of the Mecanum wheeled robot are obtained, including: The Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, L; L=TU Where, T is the kinetic energy of the Mecanum wheeled robot; U is the potential energy of the Mecanum wheeled robot; The kinetic energy T can be expressed as the sum of the rotational kinetic energy of each wheel and the translational kinetic energy of the robot, that is: Where n is the number of wheels included in the Mecanum wheeled robot; i is the moment of inertia of the i-th wheel; m is the mass of the Mecanum wheeled robot; Apply Lagrange's equations; in, To represent the derivative operation with respect to time t, describe the rate at which a variable changes over time; q' j is the generalized speed of the Mecanum wheeled robot; q j is the generalized coordinate of the Mecanum wheeled robot, which is the rotation angle of the wheel or the position coordinate of the robot; G is the nonholonomic constraint of the Mecanum wheeled robot; Q j is the generalized coordinate q j The corresponding generalized force includes driving force and friction force; By substituting the Lagrangian function and the generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed of each wheel, the steering, the linear velocity and angular velocity variables of the robot, and the interaction relationship between them.

5. The driving stability control method of the Mecanum wheeled robot according to claim 1, characterized in that: The mechanism information includes whether the friction of the wheel is greater than a preset friction threshold, whether there is movement greater than a preset speed, whether there is movement greater than a preset acceleration, and whether the wheel layout and driving method are reasonable.

6. A Mecanum wheeled robot driving stability control system, characterized in that: include: The acquisition module is used to obtain the geometric structure data and motion state data of the Mecanum wheeled robot; A calculation module is used to obtain the nonholonomic constraints of the Mecanum wheeled robot according to the geometric structure data and motion state data of the Mecanum wheeled robot, and obtain the dynamic equation of the Mecanum wheeled robot in combination with the Lagrangian principle; A determination module is used to determine the mechanism information of the Mecanum wheel robot slipping according to the dynamic equation; A setting module is used to set and execute an adaptive control strategy for real-time tracking of a target trajectory according to the sliding mechanism information of the Mecanum wheel robot and a preset target trajectory; The setting module includes: The acquisition submodule is used to: acquire the sliding trajectory of the Mecanum wheel robot after sliding; Generate submodules for: Calculate the distance information between the sliding trajectory and the target trajectory; Where D is the distance information between the sliding trajectory and the target trajectory; m is the number of trajectory points included in the sliding trajectory, which is also the number of trajectory points included in the target trajectory, and the two are equal; (x 1i ,y 1i , z 1i ) is the coordinate of the i-th track point included in the sliding track; (x 2i ,y 2i , z 2i ) is the coordinate of the i-th trajectory point included in the target trajectory; Compare the distance information with the preset distance information, and when it is determined that the distance information is less than or equal to the preset distance information, execute the current control strategy; when it is determined that the distance is less than or greater than the preset distance information, segment the sliding trajectory to obtain s segments of sliding trajectories; segment the target trajectory to obtain s segments of target trajectories; Calculate the matching degree P between the sliding trajectory and the target trajectory: Among them, p i is the matching degree between the ith sub-slip trajectory and the ith sub-target trajectory; According to the matching degree, the preset slip level data table is queried to determine the corresponding slip level; When the slip level is determined to be high, an adaptive control strategy for adjusting wheel layout and driving mode is generated; When the slip level is determined to be a medium level, an adaptive control strategy for deceleration is generated; When the slip level is determined to be a low level, an adaptive control strategy for increasing the friction of the wheels is generated.

7. The Mecanum wheeled robot driving stability control system as claimed in claim 6, characterized in that: Computing module, including: Determine the submodule for the Mecanum wheeled robot with 4 wheels, each with a rotation speed and a steering speed of w i and θ i (i=1,2,3,4), the linear velocity and angular velocity of the Mecanum wheeled robot are v and w respectively, determine the kinematic equation of the Mecanum wheeled robot; Among them, J(θ) is the Jacobian matrix of the Mecanum wheeled robot, which describes the mapping relationship between the wheel speed and the overall motion state of the Mecanum wheeled robot; Analysis submodule, used to analyze the first value range of J(θ) and w i The second value range of the Mecanum wheeled robot is retrieved by querying the corresponding data table to determine the control information of the wheel speed of the Mecanum wheeled robot and the restriction information of the rolling direction of the roller when the wheel contacts the ground, which are used as the non-holonomic constraints of the Mecanum wheeled robot.

8. The Mecanum wheeled robot driving stability control system as claimed in claim 7, characterized in that: The computing module also includes: Define submodules for: The Lagrangian function of the Mecanum wheeled robot is defined as the difference between kinetic energy and potential energy, L; L=TU Where, T is the kinetic energy of the Mecanum wheeled robot; U is the potential energy of the Mecanum wheeled robot; The kinetic energy T can be expressed as the sum of the rotational kinetic energy of each wheel and the translational kinetic energy of the robot, that is: Where n is the number of wheels included in the Mecanum wheeled robot; i is the moment of inertia of the i-th wheel; m is the mass of the Mecanum wheeled robot; Application submodules for: Apply Lagrange's equations; in, To represent the derivative operation with respect to time t, describe the rate at which a variable changes over time; q' j is the generalized speed of the Mecanum wheeled robot; q j is the generalized coordinate of the Mecanum wheeled robot, which is the rotation angle of the wheel or the position coordinate of the robot; G is the nonholonomic constraint of the Mecanum wheeled robot; Q j is the generalized coordinate q j The corresponding generalized force includes driving force and friction force; By substituting the Lagrangian function and the generalized coordinates, the dynamic equation of the Mecanum wheeled robot is obtained; the dynamic equation includes the rotation speed of each wheel, the steering, the linear velocity and angular velocity variables of the robot, and the interaction relationship between them.

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