A multi-modal motion control method and system for a locust-like air-land cross-domain robot

Abstract

The application discloses a multi-mode motion control method and system of a locust-imitating land-air cross-domain robot, and relates to the field of robot control. The method comprises the following steps: modeling the robot to obtain a first motion state displacement, a first motion state motor rotation angle, a second motion state displacement and a second motion state motor rotation angle; the first motion state is linear motion, and the second motion state is self-rotating motion; establishing a passive elastic power model to obtain the height and angle of the robot in the jumping process; controlling the robot to reach the height; constructing a longitudinal channel transfer function and a controller to control the gliding posture of the robot; and the controller comprises an inner loop posture controller and an outer loop position controller. The application can guarantee the stability of the aerial posture of the robot and smoothly connect the gliding mode.

Description

Technical Field

[0001] This invention relates to the field of robot control, and in particular to a multimodal motion control method and system for a locust-inspired land-air cross-domain robot. Background Technology

[0002] Bionic multimodal robots refer to robots developed using bionic principles that possess three or more motion modes (e.g., crawling, running, jumping, gliding, flying, etc.). They have broad application prospects in both civilian and military fields. At the same time, using bionic robots to study animal behavior and its interaction with the environment also provides new methods and approaches for humans to explore the laws of life.

[0003] In unstructured natural environments, micro-robots struggle to overcome obstacles several times their own size, requiring them to jump or even fly to reach their destinations. Existing robots often lack the ability to simultaneously crawl, jump, and glide, and struggle to achieve stable, natural, and rapid switching between these modes.

[0004] First, the robot needs to make fine adjustments to its position and attitude before takeoff. It needs to move to the optimal takeoff point by crawling and adjust the initial takeoff angle to achieve the best flight effect.

[0005] Secondly, micro-robots have limited mobility and struggle to take off within small areas on the ground. They need to use jumping as a takeoff method to provide sufficient instantaneous takeoff speed.

[0006] Finally, there is a problem of rollover stall when transitioning from the jump to the gliding mode. Therefore, a control strategy needs to be proposed to ensure the stability of the robot's attitude in the air and smoothly transition to the gliding mode.

[0007] Therefore, it is necessary to study the switching of motion modes and solve the above problems by establishing mathematical models of different motion modes and analyzing the leaping mechanism. Summary of the Invention

[0008] The purpose of this invention is to provide a multimodal motion control method and system for a locust-inspired land-air cross-domain robot, which can ensure the stability of the robot's aerial posture and smoothly connect to the gliding mode.

[0009] To achieve the above objectives, the present invention provides the following solution:

[0010] In a first aspect, the present invention provides a multimodal motion control method for a locust-inspired land-air cross-domain robot, comprising:

[0011] A crawling model is performed on the robot to obtain the displacement of the first motion state, the rotation angle of the motor in the first motion state, the displacement of the second motion state, and the rotation angle of the motor in the second motion state; the first motion state is linear motion, and the second motion state is self-rotational motion.

[0012] A passive elastic dynamic model was established to obtain the robot's height and angle during the jumping process;

[0013] Control the robot to reach the specified height;

[0014] A longitudinal channel transfer function and a controller are constructed to control the gliding attitude of the robot; the controller includes an inner loop attitude controller and an outer loop position controller.

[0015] Optionally, the expressions for the displacement of the first motion state and the rotation angle of the motor in the first motion state are as follows:

[0016] When X-(xp1+xp2)·N≥xp1

[0017]

[0018] When X-(xp1+xp2)·N≤xp1

[0019]

[0020] Where N represents the period integer, X represents the linear motion distance in the first motion state, xp1 represents the distance the robot has traveled in stage one, xp2 represents the distance the robot has traveled in stage two, and Θ1 represents the rotation angle of the motor in the first motion state.

[0021] Optionally, the expressions for the displacement in the second motion state and the rotation angle of the motor in the second motion state are as follows:

[0022] When d·α-(xp1+xp2)·N≥xp1

[0023]

[0024] When d·α-(xp1+xp2)·N≤xp1

[0025]

[0026] Where N represents the period integer, α represents the robot's planar rotation angle, xp1 represents the distance the robot travels in phase one, xp2 represents the distance the robot travels in phase two, and Θ2 represents the motor rotation angle in the second motion state.

[0027] Optionally, the expression for the robot's jump height is as follows:

[0028]

[0029] Where Θ0 represents the robot's jump height, g represents the acceleration due to gravity, and S represents the straight-line distance between the robot's jump position and the obstacle. This represents the robot's velocity in the x-direction when it jumps. This represents the robot's velocity in the y-direction when it takes off.

[0030] Optionally, the expression for the longitudinal channel transfer function is as follows:

[0031]

[0032] Where θ(s) represents the transfer function of the pitch angle, and s represents the complex variable of the Laplace transform. Indicates intermediate variables. Indicates intermediate variables. δ represents an intermediate variable. e (s) represents the rudder angle of the robot in the complex field. Indicates an intermediate variable.

[0033] Optionally, the expression for the inner loop attitude controller is as follows:

[0034]

[0035] Where, δ e (t) represents the time domain of the robot's rudder angle, θ c Let θ(t) represent the desired angle of the robot in the time domain, and θ(t) represent the robot's angle in the time domain. The PID represents the differential adjustment in the robot's angle control, where q(t) represents the robot's angular velocity. This represents the proportional component in the PID (Proportional Indicator) for adjusting the robot's angle.

[0036] Optionally, the expression for the outer loop position controller is as follows:

[0037]

[0038] Where, θ c (t) represents the angle that the robot is expected to reach in the time domain. This represents the proportional element in the PID for height adjustment, h c (t) represents the desired height of the robot in the time domain, h(t) represents the robot's height in the time domain, and τ represents the integration factor. This indicates the integral regulation in the PID for height adjustment, h c(τ) represents the height the robot is expected to reach at an instant, and h(τ) represents the robot's height at an instant.

[0039] Secondly, the present invention provides a multimodal motion control system for a locust-inspired land-air cross-domain robot, comprising:

[0040] The crawling modeling module is used to model the crawling motion of the robot and obtain the displacement of the first motion state, the rotation angle of the motor in the first motion state, the displacement of the second motion state, and the rotation angle of the motor in the second motion state; the first motion state is linear motion, and the second motion state is self-rotational motion.

[0041] The passive elastic dynamic model building module is used to build a passive elastic dynamic model and obtain the robot's height and angle during the jumping process;

[0042] The control module is used to control the robot to reach the specified height;

[0043] The controller construction module is used to construct the longitudinal channel transfer function and the controller to control the gliding attitude of the robot; the controller includes: an inner loop attitude controller and an outer loop position controller.

[0044] Thirdly, the present invention provides an electronic device, including a memory and a processor, wherein the memory is used to store a computer program, and the processor runs the computer program to enable the electronic device to perform the above-described multimodal motion control method for a locust-inspired land-air cross-domain robot.

[0045] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described multimodal motion control method for a locust-inspired land-air cross-domain robot.

[0046] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0047] The multimodal motion control method and system for the locust-inspired land-air cross-domain robot provided by this invention allows the robot to autonomously plan its wheel-leg gait to accurately reach the takeoff point based on the takeoff position and gliding direction. It also adjusts its direction through self-rotation. After the position and direction are adjusted, a jump signal is input. Upon receiving the jump signal, the robot can autonomously plan the jump starting angle based on the obstacle height and distance from the obstacle, instantly release energy, and quickly reach directly above the obstacle without flipping over, entering the gliding mode. Based on the maximum gliding height hc, the robot autonomously adjusts the rudder angle according to its posture when entering the gliding mode, ultimately achieving the required maximum gliding height. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 The flowchart shows the multimodal motion control method for the locust-inspired land-air cross-domain robot provided by this invention.

[0050] Figure 2 This is a schematic diagram of the robot's shape and mechanism according to the present invention;

[0051] Figure 3 This is a schematic diagram of the wheel leg of the present invention, which is composed of a modified four-bar linkage;

[0052] Figure 4 This is a schematic diagram of the wheel leg design parameters of the present invention, which is composed of a modified four-bar linkage.

[0053] Figure 5 A schematic diagram of the movement state of the wheel leg of the present invention on a flat road surface;

[0054] Figure 6 A schematic diagram showing the second motion state of the wheel leg of the present invention on a smooth road surface;

[0055] Figure 7 This is a schematic diagram of the robot of the present invention moving along a straight line;

[0056] Figure 8 This is a schematic diagram of the robot's own rotation according to the present invention;

[0057] Figure 9 This is a schematic diagram of the jump dynamics model of the present invention;

[0058] Figure 10 This is a schematic diagram showing the robot of the present invention reaching its maximum height;

[0059] Figure 11 This is a schematic diagram of the coordinate system of the present invention;

[0060] Figure 12 This is a block diagram of the pitch channel transfer function of the present invention;

[0061] Figure 13 This is a schematic diagram of the inner loop attitude controller of the present invention;

[0062] Figure 14 This is a schematic diagram of the height channel transfer function of the present invention;

[0063] Figure 15 This is a schematic diagram of the outer ring position controller of the present invention. Detailed Implementation

[0064] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] The purpose of this invention is to provide a multimodal motion control method and system for a locust-inspired land-air cross-domain robot, which can ensure the stability of the robot's aerial posture and smoothly connect to the gliding mode.

[0066] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0067] The robot to be controlled by this invention consists of bionic crawling legs (front wheeled legs), bionic jumping legs (hind legs), bionic forewings, bionic hindwings, rudders, a fuselage, and a front-mounted motor. See the schematic diagram of the robot's shape and structure. Figure 2 .

[0068] Figure 1 The flowchart of the multimodal motion control method for the locust-inspired land-air cross-domain robot provided by this invention is as follows: Figure 1 As shown, the method of the present invention includes:

[0069] Step 1: Crawling Modeling

[0070] The model established in this invention rigidifies the robot body except for the two front wheels, and only considers the motion of the front wheels.

[0071] Figure 3 For the structure of the robot's front wheel legs, a kinematic analysis is first performed:

[0072] Assuming the mobile robot moves along the positive x-axis in a legged configuration with no slippage along the y-axis, the parameters of the entire movement process can be represented on the xz plane. We will now focus on one wheel for analysis; design parameters are detailed below. Figure 4 .

[0073] like Figure 4 As shown, the design parameters are R = 50.00 mm, r = 15.00 mm, l = 22.00 mm, and b = 28.00 mm.

[0074] Easy to obtain:

[0075]

[0076] Eccentricity:

[0077]

[0078] The unfolding radius of the wheel is obtained by the cosine theorem as follows:

[0079]

[0080] When the wheel rotates one full revolution, the wheel-leg performs three sets of repeated motions, each set of motion (hereinafter referred to as one cycle) rotates by an angle of 2π / 3, and one cycle can be divided into two phases. The first phase is along the edge of the wheel rolling, that is, from State 1 (see Figure 5 ) to State 2 (see Figure 6 ), and the second phase is rotation around endpoint A, that is, from State 2 back to State 1.

[0081] The parameters of each phase of the wheel-leg in one cycle are examined as follows:

[0082]

[0083]

[0084]

[0085]

[0086]

[0087] The displacements of the overall centroid of the mobile robot in the x and z directions are represented by the displacements of the wheel center P in the x and z directions, with the horizontal ground taken as the z=0 plane, and the displacement equations of the wheel center P in the x and z directions are respectively as follows:

[0088] kT≤t<kT+t1:

[0089]

[0090]

[0091] kT+t1≤t<(k+1)T:

[0092]

[0093]

[0094] The velocity equations of the wheel center P in the x and z directions can be derived by differentiating the displacement equations of the wheel center P in the x and z directions with respect to time t respectively as follows:

[0095] When kT≤t<kT+t1:

[0096]

[0097]

[0098] When kT+t1≤t<(k+1)T:

[0099]

[0100]

[0101] T is a period, t1 is the duration of phase one within a period, s is the displacement of wheel center P in the x direction within a period, s1 is the displacement of wheel center P in the x direction in phase one within a period, and k is the number of periods experienced before this period.

[0102] See Figure 7 This is a schematic diagram of the robot moving in a straight line. The robot moves a distance x from its initial position to the target position along a straight line.

[0103] From the above modeling results, we can conclude that:

[0104] xp1 represents the straight-line distance traveled by the robot in Phase 1;

[0105] xp2 is the straight-line distance traveled by the robot in phase two;

[0106] N is the number of cycles, and Θ is the motor rotation angle.

[0107]

[0108] When X-(xp1+xp2)·N≥xp1

[0109]

[0110] When X-(xp1+xp2)·N≤xp1

[0111]

[0112] Figure 8 This is a schematic diagram of the robot's rotation. Because the robot's body width is relatively small, the circular motion of the center of mass caused by the movement of a single wheel is ignored.

[0113] When bending, one wheel leg moves while the other wheel leg remains stationary. Based on geometric relationships:

[0114] The distance traveled by the moving wheel is X = d·α, where α is also the robot's planar rotation angle.

[0115] When the distance traveled by the moving wheel is X = d·α, the angle of rotation of the robot in the plane is α.

[0116] Motor rotation angle The solution is to replace X in equations (1) and (2) with X = d·α.

[0117] The expressions for T, t1, s, and s1 are as follows:

[0118]

[0119]

[0120]

[0121] s1=Rβ

[0122] Step 2: Jump Modeling

[0123] The key structure for jumping motion is the bionic jumping foot; therefore, the dynamic model mainly examines the influence of the extension of this mechanism on the robot's jumping motion. First, the dynamics of this structure are analyzed, a passive elastic dynamic model is established, and the Lagrangian method is used for motion analysis.

[0124] Multibody dynamics analysis:

[0125] In actual jumping operations, the robot's mass attributes and their distribution directly affect its jumping stability. Therefore, it is necessary to establish, for example... Figure 9 The passive elastic dynamics model shown is used to analyze the motion state of the robot. The model also satisfies the following assumptions: at takeoff, point G on the robot's foot does not slide relative to the ground, the foot is simplified to a planar hinge, and the tibia rotates about a fixed axis G.

[0126] Jump dynamics is defined as follows: the relative motion angle between the links is q. i The relative angular velocity is The relative motion angle is The center of mass of the link (or triangular truss) is CoM. i The distance from the center of mass to the starting end of the connecting rod is l. i The mass is m i The moment of inertia is I i Specifically, the body parts are characterized by rectangles with mass concentrated in CoM5.

[0127] First, this invention performs energy analysis on each part. When analyzing the elastic potential energy of the spring, this invention uses the transformation matrix T between the two mounting points E and I. E and T I The spring extension length was calculated, and its spring constant was selected as 2000 N / m based on the motion requirements. The energy analysis results for each part are as follows:

[0128]

[0129] in:

[0130]

[0131]

[0132]

[0133] Next, using the Lagrange method, we differentiate and rearrange the generalized coordinates to obtain the equations of motion for the mechanical system, as follows:

[0134]

[0135] Where M is the robot's inertial force term, C is the centrifugal force term, and N is the potential energy term.

[0136]

[0137]

[0138]

[0139] in:

[0140]

[0141] Control strategy:

[0142] After reaching the designated location, the robot faces the obstacle and jumps at a certain angle, reaching its maximum height (d / 2 + H) just as it clears the obstacle. Figure 10 As shown.

[0143] have

[0144]

[0145]

[0146]

[0147] The takeoff angle can be obtained from the above formula:

[0148]

[0149] Step 3: Gliding Modeling

[0150] To obtain the dynamic equations for the robot in gliding mode, Newton's second law is applied to the translational and rotational degrees of freedom. Since Newton's laws hold true in an inertial frame of reference, the micro-insect-like robot involved in this study uses a flat ground as the frame of reference for dynamic analysis of rigid body translation and rotation.

[0151] Kinetic analysis:

[0152] (1) Translational motion

[0153] With the ground as the frame of reference, the robot's translational motion in gliding mode obeys Newton's second law, and the inertial frame is... The velocity derivative term in the system By substituting the velocity derivative and angular velocity in the equation, we obtain the following expression for the translational Newton's second law in the machine system:

[0154]

[0155]

[0156] in, Speeds u, v, and w are in i b j b k b The instantaneous projection on the axis, after integration, satisfies the following dynamic relationship in translation:

[0157]

[0158] (2) Rotational motion

[0159] Similarly, Newton's second law of rotation in a mechanical system is expressed as follows:

[0160]

[0161] In gliding mode, the robot is a rigid body, and its angular momentum is defined as the product of the inertia matrix and the angular velocity. Where J is called the inertia matrix, defined in the machine system, its diagonal terms are called moments of inertia, a measure of acceleration tendency relative to a specific axis of rotation. The robot of this invention, relative to i... b -k b The plane is perfectly symmetric, therefore J xy =J yz =0.

[0162]

[0163]

[0164] Angular velocities p, q, and r are in i b j b k b The instantaneous projection on the axis, after integration, rotates in accordance with the following dynamic relationship:

[0165]

[0166] in:

[0167]

[0168]

[0169] After analyzing the robot's translational and rotational motions, we need to establish a longitudinal channel transfer function and a controller to control the gliding attitude.

[0170] Vertical channel transfer function:

[0171] Typically, a flight control loop consists of an inner loop and an outer loop: altitude h is the controlled object of the outer loop, and pitch angle θ is the controlled object of the inner loop. Next, the transfer functions of the pitch and altitude channels are obtained.

[0172] The robot's longitudinal attitude in the air can be adjusted by the up-and-down movement of the pitch control blades on its belly, i.e., by the deflection angle δ. e Control the pitch angle θ. There are:

[0173]

[0174] middle When the roll angle φ is very small Approaching zero.

[0175] Taking the differential of the above equation, we have:

[0176]

[0177] Substitution

[0178]

[0179] And θ=α+γ, we have:

[0180]

[0181] in:

[0182]

[0183]

[0184]

[0185]

[0186] Applying a Laplace transform to the above equation yields the transfer function for the pitch channel:

[0187]

[0188] Specifically, when the robot is flying in a straight line, r = p = φ = γ = 0, and under normal circumstances... Very small, therefore It can be ignored. Based on this, the following was established: Figure 12 The diagram shows the transfer function block diagram for the pitch channel.

[0189] Next, we need to design the inner-loop attitude controller. The pitch angle θ is the most fundamental parameter for longitudinal motion control. This invention designs an inner-loop attitude controller (such as...). Figure 13 As shown, the robot's pitch angle θ is adjusted. Specifically, the attitude controller selects pitch displacement θ and pitch rate q as feedback, uses a cascaded PD method for control, and uses the rudder blades on the belly as actuators to adjust the pitch attitude. The rudder deflection command δ e The governing equations are as follows:

[0190]

[0191] The robot's longitudinal position can be adjusted by changing its pitch attitude, i.e., at airspeed V. a While keeping the elevation constant, the altitude h is controlled by the pitch angle θ. We have

[0192]

[0193] in,

[0194] When the robot is flying in a straight line, we have v = w = φ = 0 and u = V. a And the pitch angle θ is very small, therefore d h It is almost zero and negligible. Taking a Laplace transform on both sides of the above equation yields the transfer function of the height channel, as shown in the block diagram below. Figure 14 As shown.

[0195]

[0196] Next, the outer loop position controller is designed. Height h is another key parameter for longitudinal motion control. This invention designs an outer loop position controller (such as...). Figure 15 As shown, the robot's height h is adjusted. Specifically, the position controller selects height h as feedback and uses a cascaded PI control method. The height is adjusted by changing the pitch angle, and the pitch angle command θ is used. c The governing equations are as follows:

[0197]

[0198] When the robot jumps to its highest point, it enters gliding mode. If you want the robot to reach a maximum height of H+hc (i.e., the height of the obstacle plus the maximum gliding height hc), you need to control the robot's gliding position and attitude.

[0199] After inputting the desired maximum gliding height hc for the robot, the corresponding robot angle θc is obtained based on the outer ring position controller. The rudder angle δe is used to control the robot angle to reach θc, and finally the robot reaches the maximum gliding height hc.

[0200] Step 4: Motion Mode Transition Process

[0201] Based on the locomotion mechanism of insects, this paper proposes the following to address the robot's "climbing, leaping, and flying" integrated locomotion capability: Figure 1 The diagram shown is a block diagram of longitudinal motion control.

[0202] First, for the crawling mode: the crawling trajectory is planned according to the task objective, and then the rotation angle of the two wheel-leg motors is solved based on the inverse kinematics model of the wheel-legs. The robot autonomously plans its gait based on the path and uses a PD motor position controller to perform closed-loop control of the rotation angle of the wheel legs. After accurately reaching the take-off position and adjusting its own direction, it sends a jump signal δj.

[0203] The robot will switch to jumping mode: the take-off trajectory is planned according to the height of the obstacle, the angle θ0 at the moment of take-off is solved by inverse dynamics based on the elastic leg model, and the extension of the jumping leg is controlled by an open-loop nonlinear torque controller.

[0204] Next, it is necessary to transition from the jumping mode to the gliding mode. Since the robot's jump is a short, explosive movement, using an IMU to detect the initial attitude is prone to time lag, leading to angular momentum accumulation and causing the pitch attitude to exceed the controllable range. Therefore, by using the predicted robot height H and robot angle θ before the end of the jumping mode as variable inputs for the gliding mode, the problem of insufficient sensor refresh rate can be solved.

[0205] Finally, in gliding mode, a PID closed-loop method is used to control the robot's position and attitude based on the desired maximum gliding height hc. An internal attitude loop and an external position loop are established. Based on the aerodynamic model, the robot's rudder angle δe is adjusted to achieve the adjustment of the robot's aerial posture.

[0206] In order to implement the method corresponding to Embodiment 1 above and achieve the corresponding functions and technical effects, a multimodal motion control system for a locust-inspired land-air cross-domain robot is provided below.

[0207] Specifically, it includes:

[0208] The crawling modeling module is used to model the crawling motion of the robot and obtain the displacement of the first motion state, the rotation angle of the motor in the first motion state, the displacement of the second motion state, and the rotation angle of the motor in the second motion state; the first motion state is linear motion, and the second motion state is self-rotational motion.

[0209] The passive elastic dynamic model building module is used to build a passive elastic dynamic model and obtain the robot's height and angle during the jumping process;

[0210] The control module is used to control the robot to reach the specified height;

[0211] The controller construction module is used to construct the longitudinal channel transfer function and the controller to control the gliding attitude of the robot; the controller includes: an inner loop attitude controller and an outer loop position controller.

[0212] In addition, this embodiment of the invention also provides a computer scale storage medium that stores a computer program, which, when executed by a processor, implements a multimodal motion control method for a locust-inspired land-air cross-domain robot as described in the above embodiment.

[0213] Based on the above description, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned computer storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0214] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0215] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A multimodal motion control method for a locust-inspired land-air cross-domain robot, characterized in that, include: A crawling model is performed on the robot to obtain the displacement of the first motion state, the rotation angle of the motor in the first motion state, the displacement of the second motion state, and the rotation angle of the motor in the second motion state; the first motion state is linear motion, and the second motion state is self-rotational motion. The expressions for the displacement in the first motion state and the rotation angle of the motor in the first motion state are as follows: when hour when hour Where N represents the period integer, and X represents the linear motion distance in the first motion state. This indicates the distance the robot has traveled in phase one. This indicates the distance the robot has traveled in phase two. This indicates the motor's rotation angle in the first motion state; The expressions for the displacement and the motor rotation angle in the second motion state are as follows: when hour when hour Where N represents a periodic integer, This represents the robot's planar rotation angle. This indicates the distance the robot has traveled in phase one. This indicates the distance the robot has traveled in phase two. 2 indicates the motor rotation angle in the second motion state; A passive elastic dynamic model was established to obtain the robot's height and angle during the jumping process; The expression for the robot's take-off height is as follows: in, 0 represents the robot's jump height, g represents the acceleration due to gravity, and S represents the straight-line distance between the robot's jump position and the obstacle. This represents the robot's velocity in the x-direction when it jumps. This represents the robot's velocity in the y-direction when it takes off. Control the robot to reach the specified height; A longitudinal channel transfer function and a controller are constructed to control the gliding attitude of the robot; the controller includes an inner loop attitude controller and an outer loop position controller.

2. The multimodal motion control method for the locust-inspired land-air cross-domain robot according to claim 1, characterized in that, The expression for the longitudinal channel transfer function is as follows: in, The transfer function representing the pitch angle. Describe the complex variable of the Laplace transform. Indicates intermediate variables. Indicates intermediate variables. Indicates intermediate variables. This represents the rudder angle of a robot in the complex field. Indicates an intermediate variable.

3. The multimodal motion control method for the locust-inspired land-air cross-domain robot according to claim 1, characterized in that, The expression for the inner loop attitude controller is as follows: in, The time domain representing the robot's rudder angle, This represents the angle that the robot is expected to reach in the time domain. Represents the robot's angle in the time domain. This represents the differential adjustment in the PID for robot angle adjustment. This represents the robot's angular velocity. This represents the proportional component in the PID (Proportional Indicator) for adjusting the robot's angle.

4. The multimodal motion control method for the locust-inspired land-air cross-domain robot according to claim 1, characterized in that, The expression for the outer ring position controller is as follows: in, This represents the angle that the robot is expected to reach in the time domain. This represents the proportional component in the PID for height adjustment. This represents the desired height the robot will reach in the time domain. This represents the robot's height in the time domain. Indicates the integrating factor. This indicates the integral adjustment in the PID for height adjustment. This indicates the height you want the robot to reach at any given moment. This indicates the robot's height at any given moment.

5. A multimodal motion control system for a locust-inspired land-air cross-domain robot, used to implement the multimodal motion control method for the locust-inspired land-air cross-domain robot as described in any one of claims 1-4, characterized in that, include: The crawling modeling module is used to model the crawling motion of the robot and obtain the displacement of the first motion state, the rotation angle of the motor in the first motion state, the displacement of the second motion state, and the rotation angle of the motor in the second motion state; the first motion state is linear motion, and the second motion state is self-rotational motion. The passive elastic dynamic model building module is used to build a passive elastic dynamic model and obtain the robot's height and angle during the jumping process; The control module is used to control the robot to reach the specified height; The controller construction module is used to construct the longitudinal channel transfer function and the controller to control the gliding attitude of the robot; the controller includes: an inner loop attitude controller and an outer loop position controller.

6. An electronic device, characterized in that, The device includes a memory and a processor, the memory being used to store a computer program, and the processor running the computer program to enable the electronic device to perform the multimodal motion control method for the locust-inspired land-air cross-domain robot according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the multimodal motion control method for the locust-inspired land-air cross-domain robot as described in any one of claims 1 to 4.

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