A method and device for controlling a somersaulting action of a biped robot

Abstract

This invention relates to the field of machine control, and in particular to a method and apparatus for controlling the jumping and somersaulting motion of a biwheeled legged robot. The method includes: simplifying the biwheeled legged robot into a structure comprising a base, legs, and wheels, as the target structure; constructing dynamic models of the target structure during the standing phase and the flight phase; determining the states of the target structure at the instant of takeoff and landing based on the target jump height and target jump distance; determining a reference trajectory during the jumping and somersaulting process based on dynamic constraints, torque constraints, joint limitations, and the dynamic model; designing corresponding controllers during the takeoff preparation phase and the landing recovery phase to track the motion trajectory and maintain balance; and designing an attitude adjustment controller based on wheel speed adjustment during the flight phase to ensure the smooth completion of the jumping and somersaulting motion. This invention ensures that the robot can complete the somersaulting motion.

Description

Technical Field

[0001] This invention relates to the field of machine control, and in particular to a method and apparatus for controlling the jumping and somersaulting motion of a bipedal robot. Background Technology

[0002] Wheeled robots (WBRs) are robots with strong locomotion potential. They combine the efficient movement capabilities of wheeled robots on flat terrain with the excellent obstacle-crossing capabilities of legged robots on rugged terrain, thus showing broad application prospects in modern commerce and logistics, community services, reconnaissance and rescue, and other fields. Currently, jumping is common in various robot applications, helping robots overcome obstacles and improve movement efficiency. At the same time, complex jumping movements also bring new challenges to the planning and control of robot movements. Summary of the Invention

[0003] To address the aforementioned technical problems, the technical solution adopted by this invention is as follows:

[0004] According to a first aspect of the present invention, a method for controlling the jumping and somersaulting motion of a biwheeled legged robot is provided, the method comprising the following steps:

[0005] S100, the biwheeled legged robot is simplified into a structure including a base, legs and wheels, which is taken as the target structure. The dynamic models of the target structure in the standing phase and the flight phase are constructed respectively to describe the basic physical characteristics of the biwheeled legged robot.

[0006] S200, based on the target jump height and target jump distance, determine the critical state variables corresponding to the target structure at the moment of takeoff and the moment of landing, and use them as the first set state variable and the second set state variable, respectively.

[0007] S300, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the standing phase, and the first set state variables, determine the optimization problem of the target structure in the take-off phase as the first optimization problem. Based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the flight phase, and the second set state variables, determine the optimization problem of the target structure in the flight phase as the second optimization problem.

[0008] S400, solve the first optimization problem and the second optimization problem respectively to obtain the corresponding first expected trajectory and second expected trajectory.

[0009] S500, during the take-off phase, the first controller tracks the trajectory of the two-wheeled legged robot based on the first desired trajectory, and during the jump phase, the second controller tracks the trajectory of the two-wheeled legged robot based on the second desired trajectory, so that the two-wheeled legged robot can complete the jump somersault action.

[0010] According to a second aspect of the present invention, a control device for a jumping and somersaulting motion of a bipedal robot is provided, the device comprising:

[0011] The dynamic model construction module is used to simplify the biwheeled legged robot into a structure including a base, legs and wheels as the target structure, and to construct dynamic models of the target structure in the standing phase and the flight phase, respectively, to describe the basic physical characteristics of the biwheeled legged robot.

[0012] The critical state determination module is used to determine the critical state variables corresponding to the target structure at the moment of takeoff and the moment of landing based on the target jump height and the target jump distance, and use them as the first set state variable and the second set state variable, respectively.

[0013] The desired trajectory acquisition module is used to determine the optimization problem of the target structure in the take-off phase, as the first optimization problem, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the standing phase, and the first set state variables; and to determine the optimization problem of the target structure in the flight phase, as the second optimization problem, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the flight phase, and the second set state variables; and to solve the first optimization problem and the second optimization problem respectively to obtain the corresponding first desired trajectory and second desired trajectory.

[0014] The control module is used to track the trajectory of the bi-wheeled legged robot using a first controller based on a first desired trajectory during the take-off phase, and to track the trajectory of the bi-wheeled legged robot using a second controller based on a second desired trajectory during the jump phase, so that the bi-wheeled legged robot can complete the jump somersault action.

[0015] The present invention has at least the following beneficial effects:

[0016] The jumping and somersaulting motion control method and apparatus for a bipedal robot provided in this invention comprehensively considers system dynamics, joint constraints, and torque constraints in trajectory planning to ensure the rationality and feasibility of the planned trajectory. It also designs an efficient controller capable of ensuring robust balance control and accurate trajectory tracking during the take-off phase, smooth attitude adjustment during flight, and stable landing during the recovery phase. Furthermore, this scheme is based on a generalized WBR model, exhibiting good applicability and scalability.

[0017] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0019] Figure 1 A flowchart of a method for controlling the jumping and somersaulting motion of a biwheeled robot provided in an embodiment of the present invention;

[0020] Figure 2 A simplified structural diagram of a bipedal robot provided in an embodiment of the present invention;

[0021] Figure 3 This is a schematic diagram of a bipedal robot performing a somersault, as provided in an embodiment of the present invention. Detailed Implementation

[0022] 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.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of this invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0024] It should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the steps as sequential processes, many of these steps can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the steps can be rearranged. A process can be terminated when its operation is complete, but it may also have additional steps not included in the figures. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0025] This invention provides a method for controlling the jumping and somersaulting motion of a bipedal robot, such as... Figure 1 As shown, the method includes the following steps:

[0026] S100, the biwheeled legged robot is simplified into a structure including a base, legs and wheels, which is taken as the target structure. The dynamic models of the target structure in the standing phase and the flight phase are constructed respectively to describe the basic physical characteristics of the biwheeled legged robot.

[0027] In this embodiment of the invention, the structure of the biwheeled legged robot (hereinafter referred to as WBR) can be an existing structure, for example, including a base, two hip joints, left and right legs, and mounted hardware devices. Each hip joint is equipped with three joint motors: one motor controls the forward and backward swinging of the leg, one motor controls the left and right swinging of the leg, and one motor controls the angle of the knee joint. Each leg has a hub motor and a wheel mounted at its foot end; the hub motor controls the movement of the wheel. The mounted hardware devices may include an IMU and an onboard computing unit.

[0028] In embodiments of the present invention, such as Figure 2 As shown, the bipedal robot can be simplified to a structure including a base 1, legs 2 and wheels 3, where legs 2 are virtual legs and can be formed by the line connecting the center of the base 1 and the center of the wheels 3.

[0029] In this embodiment of the invention, the dynamic model of WBR is established using the Lagrange method at different stages of the entire movement. Specifically, the dynamic model in the standing phase satisfies the following conditions:

[0030] M s q 2 +C s q 1 +G s =u

[0031] Where q is the state variable of the target structure, q 1 q is the first derivative of q. 2 The second derivative of q, q = (θ) w ,L,θ p θ h ), θ w Let θ be the rotation angle of the wheel of the target structure, L be the leg length of the target structure, and θ be the rotation angle of the wheel of the target structure. h The angle θ is the angle between the hip joint and the line containing the leg. p M is the angle between the line containing the leg and the vertical direction. s The inertia matrix during the standing phase, J w Let m be the moment of inertia of the wheels of the bipedal robot.w R is the mass of the wheel of the target structure. w Let m be the radius of the wheel of the target structure. b J is the mass of the base of the target structure. b C is the moment of inertia of the base of the target structure; s The Coriolis force matrix for the standing phase. θ 1 p For θ p The first derivative, L 1 G is the first derivative of L. s Let be the gravity vector during the standing phase. Where g is the acceleration due to gravity, and u is the control input variable of the target structure. , τ w τ is the torque of the wheel of the target structure. h F is the torque of the hip joint of the target structure. L The generalized force on the leg of the target structure can be calculated using the principle of virtual work, based on the angle of the knee joint, the leg length, and the torque of the motor controlling the knee joint.

[0032] Furthermore, the dynamic model during the flight phase satisfies the following conditions:

[0033] M f q 2 +C f q 1 +G f =u

[0034] Among them, M f C is the inertial matrix during the flight phase. f For the Coriolis matrix during the flight phase, G f This is the gravity vector during the flight phase. m0 is an intermediate variable, m0 = (1 - m b / (m w +m b )) 2 ×m b +(m b / (m w +m b )) 2 ×m w ; , .

[0035] S200, based on the target jump height and target jump distance, determine the critical state variables corresponding to the target structure at the moment of takeoff and the moment of landing, and use them as the first set state variable and the second set state variable, respectively.

[0036] In this embodiment of the invention, referencing the human jumping and somersaulting motion, the robot's jumping process is divided into three stages: a jump preparation stage, a flight stage, and a landing recovery stage. The critical state between the jump preparation stage and the flight stage is the moment of takeoff, and the critical state between the flight stage and the landing recovery stage is the moment of landing. The user first selects a set of desired jump height and jump distance, and then calculates the desired critical state variables during the action based on the corresponding height and distance.

[0037] In this embodiment of the invention, the critical state variable may include (L, L) 1 L 2 θ w θ w 1 θ w 2 θ p θ p 1 θ p 2 θ h θ h 1 θ h 2 ), where L is the leg length of the target structure, L 1 Let L be the first derivative of L. 2 Let θ be the second derivative of L. w Let θ be the rotation angle of the wheel of the target structure. w 1 For θ w The first derivative, θ w 2 For θ w The second derivative, θ p Let θ be the angle between the line containing the legs of the target structure and the vertical direction. p 1 For θ p The first derivative, θ p 2 For θ p The second derivative, θ h Let θ be the angle of the hip joint of the bipedal robot. h 1 For θ h The first derivative, θ h 2 For θ h The second derivative.

[0038] In this embodiment of the invention, the first derivative of L represents the velocity of the change in leg length, the second derivative of L represents the acceleration of the change in leg length, and θ w The first derivative represents the angular velocity of the wheel, θ. wThe second derivative of θ represents the angular acceleration of the wheel. h The first derivative represents the angular velocity of the hip joint, θ. h The second derivative of θ represents the angular acceleration of the hip joint. p The first derivative represents the angular velocity of the bipedal robot relative to the world coordinate system, θ. p The second derivative of represents the angular acceleration of the bipedal robot relative to the world coordinate system.

[0039] The critical state variables at the instant of liftoff can be obtained through the following steps:

[0040] S1. Based on the target jump height, the flight time of the center of mass of the bipedal robot in the air is calculated using the laws of projectile motion.

[0041] In this embodiment of the invention, the flight time t = 2 × (2 × H / g) 1 / 2 H represents the target jump height.

[0042] S2, based on the flight time and target jump distance, calculate the horizontal take-off speed required for the bipedal robot at the moment of take-off, and based on the target jump height, determine the vertical take-off speed required at the moment of take-off.

[0043] As those skilled in the art will know, any method for calculating the horizontal take-off speed required for a bipedal robot at the moment of take-off based on flight time and target jump distance, and for determining the vertical take-off speed required at the moment of take-off based on target jump height, falls within the protection scope of this invention.

[0044] S3, determine the first derivative of L and the first derivative of θw at the instant of takeoff based on the horizontal and vertical takeoff velocities.

[0045] As those skilled in the art will know, any method for determining the first derivative of L and the first derivative of θw at the moment of takeoff based on the horizontal takeoff velocity and the vertical takeoff velocity is within the scope of protection of this invention.

[0046] The values ​​θw, L, θp, and θh at the instant of takeoff can be set based on actual needs and can be empirical values. Among the state variables at the instant of takeoff, except for the second derivative of the leg length, the second derivatives of θw, θp, and θh are all set to 0 for better stability. The second derivative of L can be obtained from the mechanical analysis at the instant of takeoff.

[0047] In this embodiment of the invention, θw in the state corresponding to the moment of landing can be determined based on the conservation of angular momentum in the air. L at the moment of landing can be set to a value close to the maximum leg length, such as 90% of the maximum leg length, θh at the moment of landing can be set to 0, and θw at the moment of landing can be set to 0.

[0048] In this embodiment of the invention, the somersault motion of the bipedal robot can be described as the system's θp increasing by one revolution in the air. The θp corresponding to the moment of landing can be set to be equal to 2π, or set to satisfy (2π-θp). p ) ≤ △θ, where △θ is a preset angle difference. △θ can be set to a number infinitely close to 0.

[0049] The first derivative of L at the moment of impact can be set to a negative number close to 0. The first derivatives of θw, θp, and θh at the moment of impact can be set to 0. The second derivatives of L, θw, θp, and θh at the moment of impact can be set to 0.

[0050] S300, based on dynamic constraints, torque constraints, joint limitations, the dynamic model in the standing phase and the state corresponding to the moment of takeoff, determine the optimization problem of the target structure in the takeoff phase as the first optimization problem, and based on dynamic constraints, torque constraints, joint limitations, the dynamic model in the flight phase and the state corresponding to the moment of landing, determine the optimization problem of the target structure in the flight phase as the second optimization problem.

[0051] In this embodiment of the invention, the trajectory planning problem for robot jumping can be regarded as a nonlinear optimization problem, taking into account the system's torque constraints, joint limitations, dynamic model, and critical state variables.

[0052] Specifically, in this embodiment of the invention, the first optimization problem satisfies the following conditions:

[0053]

[0054] The constraints include:

[0055] (1) M s q 2 +C s q 1 +G s =u;

[0056] (2) q belongs to Q, u belongs to N;

[0057] (3) [q 1 [q(0), q(0)]=[q 1 0, q0], that is, q 1 (0) = q 1 0, q(0) = q.

[0058] Where q(T1) is the state variable at the moment of takeoff planned in the first optimization problem, q 1 (T1) is the first derivative of q(T1), q 2 (T1) is the second derivative of q(T1).

[0059] φ1 F ( ) represents the expected deviation in the first optimization problem, φ1 F (q) 2 (T1), q 1 (T1), q(T1)) = ||q 2 (T1)-q 2 T1 || K1 +||q 1 (T1)-q 1 T1 || K2 +||q(T1)-q T1 || K3 q T1 Set the state variable q for the first one. 1 T1 For q T1 First derivative, q 2 T1 For q T1 The second derivative of φ1, ||| represents the norm, K1, K2, and K3 are the first, second, and third weights, respectively, and T1 is the time corresponding to the standing phase. That is, φ1 F ( ) are the weighted sums of the deviations between state variables, the deviations between the first derivatives of state variables, and the deviations between the second derivatives of state variables, respectively.

[0060] Γ1(u) represents the energy consumption during the standing phase, Γ1(u) = ||τ w || K4 +||τ k || K5 +||τ h || K6 , τ k K represents the knee joint torque, with K4, K5, and K6 being the fourth, fifth, and sixth weights, respectively.

[0061] Q represents the constraint range of the state variable, and N represents the constraint range of the control input variable, which can be set according to actual needs.

[0062] q(0) is the initial state variable in the first optimization problem. 1 (0) is the first derivative of q(0), q0 is the initial state in the expected trajectory during the standing phase, and q 10 is the first derivative of q0. t1 is any moment in the standing phase, and the value of t1 ranges from 0 to T1. dt1 represents the integration over t1.

[0063] In this embodiment of the invention, the values ​​of the first to sixth weights can be set according to actual needs. Generally, the weights corresponding to the first and second derivatives are greater than the weights of the corresponding state variables themselves. For example, L 1 and L 2 The corresponding weight is greater than the weight corresponding to L. Furthermore, the second optimization problem satisfies the following condition:

[0064] minφ2 F (q) 2 (T2), q 1 (T2), q(T2))+∫ T2 T1 Γ2(u)dt2

[0065] The constraints include:

[0066] (1) M f q 2 +C f q 1 +G f =u;

[0067] (2) q belongs to Q, u belongs to N;

[0068] (3) [q 1 [(T1), q(T1)]=[q 1 T1 q T1 ], i.e., q 1 (T1) = q 1 T1 q(T1) = q T1 .

[0069] Where q(T2) is the state variable at the moment of takeoff in the second optimization problem, q 1 (T2) is the first derivative of q(T2), q 2 (T2) is the second derivative of q(T2).

[0070] φ2 F ( ) represents the expected deviation in the second optimization problem, φ2 F (q) 2 (T2), q 1 (T2), q(T2)) = ||q 2 (T2)-q 2 T2 || K1 +||q 1 (T2)-q 1T2 || K2 +||q(T2)-q T2 || K3 q T2 Set the state variable q for the second. 1 T2 For q T2 First derivative, q 2 T2 For q T2 The second derivative of T2 is the time corresponding to the flight phase.

[0071] Γ2(u) represents the energy consumption during the flight phase, Γ2(u) = ||τ w || K4 +||τ k || K5 +||τ h || K6 , τ k Let q be the knee joint torque. q(T1) is the final state variable planned in the first optimization problem. 1 (T1) is the first derivative of q(T1), t2 is any moment in the flight phase, and the value of t2 ranges from T1 to T2. dt2 represents the integration over t2.

[0072] In this embodiment of the invention, the constraints (1) in the first optimization problem and the second optimization problem are dynamic model constraints, constraints (2) are joint restrictions and torque constraints, and constraints (3) are initial state constraints. The optimization problem includes the deviation between the final state of the system and the desired state, as well as the energy consumption during the process. The first optimization problem is to minimize the deviation between the planned state variables at the moment of takeoff and the set state variables at the moment of takeoff. The second optimization problem is to minimize the deviation between the planned state variables at the moment of landing and the set state variables at the moment of takeoff.

[0073] S400, solve the first optimization problem and the second optimization problem respectively to obtain the corresponding first expected trajectory and second expected trajectory.

[0074] In this embodiment of the invention, the desired trajectory is obtained using the CasADi solver. The first desired trajectory is the desired trajectory corresponding to the standing phase, including the values ​​of the state variables at each moment of the standing phase; the second desired trajectory is the desired trajectory corresponding to the flight phase, including the values ​​of the state variables at each moment of the flight phase.

[0075] S500, during the take-off phase, the first controller tracks the trajectory of the two-wheeled legged robot based on the first desired trajectory, and during the jump phase, the second controller tracks the trajectory of the two-wheeled legged robot based on the second desired trajectory, so that the two-wheeled legged robot can complete the jump somersault action.

[0076] In this embodiment of the invention, the desired trajectory is the center-of-mass trajectory of the bipedal robot when performing its work.

[0077] During the takeoff phase, the controller tracks the reference trajectory and maintains system balance. By controlling the position and speed of the leg joints and wheels, the WBR (Wide-Body-Body) is ensured to take off smoothly. In this embodiment of the invention, the control algorithm can be a linear quadratic regulator, i.e., the first controller is a linear quadratic regulator. The state-space equation of the robot system is as follows:

[0078] x 1 s =Ax s +Bu s y s =x s ;

[0079] x s =[θ w ,L,θ h θ p θ 1 w L 1 θ 1 h θ 1 p ]

[0080] Where, x s u represents the state variable of the system. s y represents the system input. s Indicates the system output, A and B are based on x. s The matrix obtained from the relationship between x s 1 For x s The first derivative of represents the velocity corresponding to the state variable.

[0081] In this embodiment of the invention, the target structure can be considered as a system. The control law of the corresponding linear quadratic regulator can be obtained by solving the Riccati algebraic equation.

[0082] During flight, this invention utilizes an attitude adjustment controller based on wheel speed regulation, i.e., the second controller is the attitude adjustment controller. The attitude of the WBR is adjusted by regulating the wheel speed, ensuring smoothness during the aerial rotation process. The specific control algorithm is as follows:

[0083] θ w 2 =K w (θ) w 1 -θ w 1c )+K p1 (θ) p -θ p c )+K p2 (θ) p 1 -θ p 1c );

[0084] θ h 2 =K h1 (θ) h -θ h c )+K h2 (θ) h 1 -θ h 1c );

[0085] L 2 =K L1 (LL) c )+K L2 (L) 1 -L 1c (where K) w For θ w The corresponding adjustable parameter, K p1 For θ p The corresponding adjustable parameter, K p2 For θ p 1 The corresponding adjustable parameter, K h1 For θ h The corresponding adjustable parameter, K h2 For θ h 1 The corresponding adjustable parameter, K L1 K is the adjustable parameter corresponding to L. L2 For L 1 The corresponding adjustable parameter. θ w 1 θ w 2 θ p θ p 1 θ h θ h 1 L and L 1θ is the value input into the attitude adjustment controller based on the second desired trajectory. w 1c θ w 2c θ p c θ p 1c θ h c θ h 1c L c and L 1c These are values ​​measured by sensors on a bipedal robot.

[0086] In this embodiment of the invention, the operation of the bipedal robot during the landing and recovery phase can be controlled according to the state variables corresponding to the instant of landing, or it can be set to reasonable fixed values ​​for control based on actual conditions; this invention does not impose any particular limitations. During the landing and recovery phase, a first controller is also used for trajectory tracking to maintain balance.

[0087] The jumping and somersaulting motion control method for a two-wheeled legged robot provided in this embodiment of the invention, in a practical application scenario, the process of controlling the two-wheeled legged robot to perform a somersaulting motion can be as follows: Figure 3 As shown. By Figure 3 It can be seen that the robot can perform a somersault and land smoothly.

[0088] The jumping and somersaulting motion control method for a bipedal robot provided in this invention comprehensively considers system dynamics, joint constraints, and torque constraints in trajectory planning to ensure the rationality and feasibility of the planned trajectory. By designing state variables at the moment of takeoff and landing, dynamic balance during the jump is guaranteed. Furthermore, a linear quadratic regulator is used for trajectory tracking during the takeoff phase, and an attitude adjustment controller is used for trajectory tracking during the flight phase, maintaining the system's robustness in the face of external disturbances and internal uncertainties. Whether in the takeoff, flight, or recovery phases, the controller effectively tracks the trajectory and adjusts the attitude to ensure the smooth completion of the action. This invention not only improves the motion performance of the WBR (Wheel Bike Backbone) but also expands its application scenarios, enabling it to perform tasks in more complex environments.

[0089] Based on the same inventive concept, embodiments of the present invention also provide a control device for the jumping and somersaulting motion of a bipedal robot. The device includes:

[0090] The dynamic model construction module is used to simplify the biwheeled legged robot into a structure including a base, legs and wheels as the target structure, and to construct dynamic models of the target structure in the standing phase and the flight phase, respectively, to describe the basic physical characteristics of the biwheeled legged robot.

[0091] The critical state determination module is used to determine the critical state variables corresponding to the target structure at the moment of takeoff and the moment of landing based on the target jump height and the target jump distance, and use them as the first set state variable and the second set state variable, respectively.

[0092] The desired trajectory acquisition module is used to determine the optimization problem of the target structure in the take-off phase, as the first optimization problem, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the standing phase, and the first set state variables; and to determine the optimization problem of the target structure in the flight phase, as the second optimization problem, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the flight phase, and the second set state variables; and to solve the first optimization problem and the second optimization problem respectively to obtain the corresponding first desired trajectory and second desired trajectory.

[0093] The control module is used to track the trajectory of the bi-wheeled legged robot using a first controller based on a first desired trajectory during the take-off phase, and to track the trajectory of the bi-wheeled legged robot using a second controller based on a second desired trajectory during the jump phase, so that the bi-wheeled legged robot can complete the jump somersault action.

[0094] This device can be used to perform Figure 1 The method shown in the illustrated embodiment is relevant here; therefore, the functions that each functional module of the device can achieve can be referred to. Figure 1 The embodiments shown are described in detail below.

[0095] It should be understood that the various forms of processes shown above can be used to reorder, add, or delete steps. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this invention can be achieved, and this is not limited herein.

[0096] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for controlling the jumping and somersaulting motion of a bipedal robot, characterized in that, The method includes the following steps: S100, the biwheeled legged robot is simplified into a structure including a base, legs and wheels as the target structure, and the dynamic models of the target structure in the standing phase and the flight phase are constructed respectively to describe the basic physical characteristics of the biwheeled legged robot. S200, based on the target jump height and the target jump distance, determine the critical state variables corresponding to the target structure at the moment of takeoff and the moment of landing, and use them as the first set state variable and the second set state variable, respectively; S300, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the standing phase and the first set state variables, determine the optimization problem of the target structure in the take-off phase as the first optimization problem; based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the flight phase and the second set state variables, determine the optimization problem of the target structure in the flight phase as the second optimization problem; S400, solve the first optimization problem and the second optimization problem respectively to obtain the corresponding first expected trajectory and second expected trajectory; S500, during the take-off phase, the first controller tracks the trajectory of the two-wheeled legged robot based on the first desired trajectory, and during the jump phase, the second controller tracks the trajectory of the two-wheeled legged robot based on the second desired trajectory, so that the two-wheeled legged robot can complete the jump somersault action.

2. The method according to claim 1, characterized in that, The dynamic model during the standing phase satisfies the following conditions: M s q 2 +C s q 1 +G s =u Where, q 1 Let q be the first derivative of the state variable q of the target structure. 2 The second derivative of q, q = (θ) w ,L,θ p θ h ), θ w Let θ be the rotation angle of the wheel of the target structure, L be the leg length of the target structure, and θ be the rotation angle of the wheel of the target structure. h The angle of the hip joint, θ, of a bipedal robot. p M is the angle between the straight line containing the legs of the target structure and the vertical direction. s The inertia matrix during the standing phase, J w Let m be the moment of inertia of the wheels of the biwheeled robot. w R is the mass of the wheel of the target structure. w Let m be the radius of the wheel of the target structure. b J is the mass of the base of the target structure. b C is the moment of inertia of the base of the target structure; s The Coriolis force matrix for the standing phase. θ 1 p For θ p The first derivative, L 1 G is the first derivative of L. s Let be the gravity vector during the standing phase. Where g is the acceleration due to gravity, and u is the control input variable of the target structure. , τ w τ is the torque of the wheel of the target structure. h F is the torque of the hip joint of the target structure. L The generalized force on the legs of the target structure; The dynamic model during the flight phase satisfies the following conditions: M f q 2 +C f q 1 +G f =u Among them, M f C is the inertial matrix during the flight phase. f For the Coriolis matrix during the flight phase, G f This is the gravity vector during the flight phase. m0 is an intermediate variable, m0 = (1 - m b / (m w +m b )) 2 ×m b +(m b / (m w +m b )) 2 ×m w ; , .

3. The method according to claim 2, characterized in that, The first optimization problem satisfies the following conditions: ； The constraints include: (1)M s q 2 +C s q 1 +G s =u; (2) q belongs to Q, u belongs to N; (3)[q 1 (0), q(0)]=[q 1 0, q0]; Where q(T1) is the state variable at the moment of takeoff planned in the first optimization problem, q 1 (T1) is the first derivative of q(T1), q 2 (T1) is the second derivative of q(T1), φ1 F ( ) represents the expected deviation in the first optimization problem, φ1 F (q) 2 (T1), q 1 (T1), q(T1)) = ||q 2 (T1)-q 2 T1 || K1 +||q 1 (T1)-q 1 T1 || K2 +||q(T1)-q T1 || K3 q T1 Set the state variable q for the first one. 1 T1 For q T1 First derivative, q 2 T1 For q T1 The second derivative of Γ1(u) is given by K1, K2, and K3, which represent the first, second, and third weights, respectively. T1 is the time corresponding to the standing phase, and Γ1(u) is the energy consumption corresponding to the standing phase, where Γ1(u) = ||τ. w || K4 +||τ k || K5 +||τ h || K6 , τ k K4, K5, and K6 represent the knee joint torque, respectively; || represents the norm, Q represents the constraint range of the state variables, N represents the constraint range of the control input variables, q(0) represents the initial state variables planned in the first optimization problem, and q 1 (0) is the first derivative of q(0), q0 is the initial state in the expected trajectory during the standing phase, and q 1 0 is the first derivative of q0, t1 is any moment in the standing phase, and the value of t1 ranges from 0 to T1. dt1 represents the integration over t1.

4. The method according to claim 3, characterized in that, The second optimization problem satisfies the following conditions: minφ2 F (q 2 (T2),q 1 (T2),q(T2))+∫ T2 T1 Γ2(u)dt2 The constraints include: (1)M f q 2 +C f q 1 +G f =u; (2) q belongs to Q, u belongs to N; (3)[q 1 (T1), q(T1)]=[q 1 T1 ,q T1 ]; Where q(T2) is the state variable at the moment of takeoff in the second optimization problem, q 1 (T2) is the first derivative of q(T2), q 2 (T2) is the second derivative of q(T2), φ2 F ( ) represents the expected deviation in the second optimization problem, φ2 F (q) 2 (T2), q 1 (T2), q(T2)) = ||q 2 (T2)-q 2 T2 || K1 +||q 1 (T2)-q 1 T2 || K2 +||q(T2)-q T2 || K3 q T2 Set the state variable q for the second. 1 T2 For q T2 First derivative, q 2 T2 For q T2 The second derivative T2 represents the time corresponding to the flight phase, and Γ2(u) represents the energy consumption corresponding to the flight phase, Γ2(u) = ||τ w || K4 +||τ k || K5 +||τ h || K6 , τ k Let || be the knee joint torque; || denotes the norm; Q is the constraint range of the state variable; N is the constraint range of the control input variable; q(T1) is the final state variable planned in the first optimization problem; q 1 (T1) is the first derivative of q(T1), t2 is any moment in the flight phase, and the value of t2 ranges from T1 to T2. dt2 represents the integration over t2.

5. The method according to claim 1, characterized in that, The first controller is a linear quadratic regulator, and the second controller is an attitude adjustment controller.

6. The method according to claim 1, characterized in that, The critical state variables include (L, L) 1 L 2 θ w θ w 1 θ w 2 θ p θ p 1 θ p 2 θ h θ h 1 θ h 2 ), where L is the leg length of the target structure, L 1 Let L be the first derivative of L. 2 Let θ be the second derivative of L. w Let θ be the rotation angle of the wheel of the target structure. w 1 For θ w The first derivative, θ w 2 For θ w The second derivative, θ p Let θ be the angle between the line containing the legs of the target structure and the vertical direction. p 1 For θ p The first derivative, θ p 2 For θ p The second derivative, θ h Let θ be the angle of the hip joint of the bipedal robot. h 1 For θ h The first derivative, θ h 2 For θ h The second derivative; Among them, θ is the state variable at the moment of landing. p It is set to equal to 2π, or it is set to satisfy (2π-θ) p )≤△θ, where △θ is the preset angle difference.

7. A control device for the jumping and somersaulting motion of a bipedal robot, characterized in that, The device includes: The dynamic model construction module is used to simplify the biwheeled legged robot into a structure including a base, legs and wheels as the target structure, and to construct the dynamic model of the target structure in the standing phase and the dynamic model in the flight phase, respectively, to describe the basic physical characteristics of the biwheeled legged robot. The critical state determination module is used to determine the critical state variables of the target structure at the moment of takeoff and the moment of landing based on the target jump height and the target jump distance, and use them as the first set state variable and the second set state variable, respectively. The desired trajectory acquisition module is used to determine the optimization problem of the target structure in the take-off phase, as the first optimization problem, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the standing phase, and the first set state variables; and to determine the optimization problem of the target structure in the flight phase, as the second optimization problem, based on dynamic constraints, moment constraints, joint limitations, the dynamic model in the flight phase, and the second set state variables; and to solve the first optimization problem and the second optimization problem respectively to obtain the corresponding first desired trajectory and second desired trajectory. The control module is used to track the trajectory of the bi-wheeled legged robot using a first controller based on a first desired trajectory during the take-off phase, and to track the trajectory of the bi-wheeled legged robot using a second controller based on a second desired trajectory during the jump phase, so that the bi-wheeled legged robot can complete the jump somersault action.

8. The apparatus according to claim 7, characterized in that, The dynamic model during the standing phase satisfies the following conditions: M s q 2 +C s q 1 +G s =u Where q is the state variable of the target structure, q 1 q is the first derivative of q. 2 The second derivative of q, q = (θ) w ,L,θ p θ h ), θ w Let θ be the rotation angle of the wheel of the target structure, L be the leg length of the target structure, and θ be the rotation angle of the wheel of the target structure. h The angle of the hip joint, θ, of a bipedal robot. p M is the angle between the straight line containing the legs of the target structure and the vertical direction. s The inertia matrix during the standing phase, J w Let m be the moment of inertia of the wheels of the biwheeled robot. w R is the mass of the wheel of the target structure. w Let m be the radius of the wheel of the target structure. b J is the mass of the base of the target structure. b C is the moment of inertia of the base of the target structure; s The Coriolis force matrix for the standing phase. θ 1 p For θ p The first derivative, L 1 G is the first derivative of L. s Let be the gravity vector during the standing phase. u is the control input variable of the target structure. , τ w τ is the torque of the wheel of the target structure. h F is the torque of the hip joint of the target structure. L The generalized force on the legs of the target structure; The dynamic model during the flight phase satisfies the following conditions: M f q 2 +C f q 1 +G f =u Among them, M f C is the inertial matrix during the flight phase. f For the Coriolis matrix during the flight phase, G f This is the gravity vector during the flight phase. m0 is an intermediate variable, m0 = (1 - m b / (m w +m b )) 2 ×m b +(m b / (m w +m b )) 2 ×m w ; , .

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