Flight operation robot cooperative carrying method and system

Abstract

The invention discloses a flying operation robot collaborative carrying method and system, and relates to the field of flying operation robot collaboration, and the method comprises the steps: obtaining the state information and end effector information of each flying operation robot; further constructing a multi-degree-of-freedom coupling dynamic model and an adhesion interface contact dynamic model of each flight operation robot; further determining an integrated closed-chain dynamic model of the flying operation robot and the carrying target; according to the state information and the integrated closed-chain dynamical model, physical characteristic parameters of the carrying target are determined; according to the physical characteristic parameters, a real-time control strategy of each flying operation robot is determined based on an integrated closed-chain dynamic model and an adhesion interface contact dynamic model; carrying the carrying target according to the real-time control strategy; according to the invention, cooperative carrying of non-specific targets can be realized, and the application effect and range of the flight operation robot in a real scene are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of flying operation robot cooperation, and particularly relates to a flying operation robot cooperation carrying method and system. BACKGROUND

[0002] The flying operation robot is a new type of intelligent equipment composed of a flying platform and an operation mechanism, and has three-dimensional space maneuvering capability and physical environment interaction capability. The flying operation robot has unique advantages in dangerous goods carrying and other unmanned emergency rescue tasks. However, due to the limited payload capacity of the flying platform, the carrying capacity of a single flying operation robot is obviously insufficient when facing large-volume and heavy targets, which seriously restricts the application range. It has important practical significance and application value to complete the carrying task by using the multi-robot cooperative operation mode.

[0003] At present, the planning and control method for the flying operation robot cooperative carrying task has obvious limitations. These methods are usually only applicable to specific types and fixed shapes of carrying targets, and are difficult to cope with various non-specific random targets encountered in real scenes such as emergency rescue. Specifically, on the one hand, the connection and fixation between the robot end effector and the carrying target need to be pre-connected by manual operation (such as rope hoisting or mechanical structure fixation), or a special matching mechanism needs to be designed to realize the connection (such as installing a mechanical claw at the end of the robot, and setting a hook of the corresponding size on the target object); on the other hand, the existing method requires to pre-master the physical characteristic parameters (all or part) of the carrying target such as the center of mass, mass and inertia, and needs to pre-plan the contact position of each robot end effector and the target, and ensure the balance of the carrying process through manual operation or special matching mechanism.

[0004] The emergence of biomimetic silicone rubber-based adhesion array material provides a new idea to solve this problem. This material can realize reversible adhesion and detachment to surfaces of different shapes and different materials. Based on this, the end effector designed based on this material can complete the cooperative carrying of non-specific random targets without pre-artificial connection or special matching mechanism. However, this new operation mode also brings new technical challenges: first, the contact dynamics characteristics of the adhesion interface are complex, which are significantly different from the traditional mechanical fixation, rigid grasping or rope connection, and the control difficulty is greatly increased, so the existing cooperative carrying planning and control method is difficult to be directly applied; second, when grasping or carrying non-specific random targets, it is impossible to pre-plan the contact position of each robot end effector and the target, and it is also impossible to pre-know the physical characteristic parameters of the target, which makes the existing cooperative carrying planning and control method completely invalid.

[0005] Therefore, based on the above problems, there is an urgent need to provide a new flight operation robot cooperative carrying method, which can realize cooperative carrying of non-specific targets and improve the application effect and range of flight operation robots in real scenes. SUMMARY

[0006] The purpose of the present application is to provide a flight operation robot cooperative carrying method and system, which can realize cooperative carrying of non-specific targets without pre-matching design or fixed connection of robot end effectors and carrying targets, and without pre-designing the contact position of each robot end effector and carrying target, thereby improving the application effect and range of flight operation robots in real scenes.

[0007] To achieve the above purpose, the present application provides the following solutions:

[0008] In a first aspect, the present application provides a flight operation robot cooperative carrying method, which comprises:

[0009] Obtaining state information and end effector information of each flight operation robot; the state information includes flight platform state variables, flight platform independent state variables, flight platform under-actuated non-independent state variables, flight operation robot state variables and flight robot independent state variables; the end effector information includes normal pressure of micro single adhesion strut pair on the carrying target, adhesion array area and adhesion strut density;

[0010] According to the state information, a multi-degree-of-freedom coupled dynamics model of each flight operation robot is constructed; the multi-degree-of-freedom coupled dynamics model includes a kinematics model and a dynamics model;

[0011] According to the end effector information, an adhesion interface contact dynamics model of each flight operation robot is constructed;

[0012] According to the multi-degree-of-freedom coupled dynamics model and the adhesion interface contact dynamics model, an integrated closed-chain dynamics model of the flight operation robot and the carrying target is determined;

[0013] According to the state information and the integrated closed-chain dynamics model, the physical characteristic parameters of the carrying target are determined; the physical characteristic parameters include the inertia of the carrying target, the center of mass position of the carrying target and the mass of the carrying target;

[0014] According to the physical characteristic parameters, the real-time control strategy of each flight operation robot is determined based on the integrated closed-chain dynamics model and the adhesion interface contact dynamics model, and the carrying target is carried according to the real-time control strategy.

[0015] Optionally, the constructing, according to the state information, of a multi-degree-of-freedom coupled dynamics model of each flight operation robot specifically comprises:

[0016] determining a kinematics model of each flight operation robot by using the formula

[0017] determining a dynamics model of each flight operation robot by using the formula

[0018] wherein, is an end effector velocity of the flight operation robot, t is time, J tx,e (Φ a (t),q(t)) is a Jacobian matrix J t,e (Φ a ,q) of the end effector, is a derivative of the flight operation robot independent state variable, is a derivative of the flight operation robot state variable, is a second derivative of the flight operation robot state variable, M(ξ) is an inertia matrix, is a Coriolis and centrifugal force matrix, g(ξ) is a gravity matrix, μ u is a generalized input force, μ ext is a generalized external force.

[0019] Optionally, the constructing, according to the end effector information, of an adhesion interface contact dynamics model of each flight operation robot specifically comprises:

[0020] determining an adhesion array mechanics model based on a single adhesion strut mechanics model according to the end effector information;

[0021] constructing an adhesion performance space based on the adhesion array mechanics model; the adhesion performance space comprises: a normal component constraint range of an action force received by an end adhesion effector, a tangential component constraint range of the action force, and an action torque constraint range of the action force received by the end adhesion effector;

[0022] constructing an adhesion interface contact dynamics model in the adhesion performance space by using the formula

[0023] wherein, f ext is an action force received by an end adhesion effector, k cont is an equivalent stiffness coefficient, Δp e is a position change amount of an end effector of the flight operation robot, c cont is an equivalent damping coefficient, is an end effector velocity of the flight operation robot, Ω is an adhesion performance space.​​​

[0024] Optionally, determining the integrated closed-loop dynamic model of the flying robot and the transported target based on the multi-degree-of-freedom coupled dynamic model and the adhesion interface contact dynamic model specifically includes:

[0025] Using formula Determine the integrated closed-loop dynamic model of the flying operation robot and the transported target;

[0026] Where i is the number of the flying operation robot, n is the total number of flying operation robots, and m o Let g be the mass of the target object being transported, and f be the acceleration due to gravity. ext,i v is the force acting on the i-th end-effector. o m is the speed at which the target is moved. ext,i Let the torque be the torque applied to the i-th end-effector. To transport the target angular velocity, For the angular acceleration of the transported target, R o The rotation matrix used to move the target coordinate system to the world coordinate system. Let I be the position of the contact point between the i-th end effector of the flying robot and the target, relative to the target's center of mass. o The inertia matrix of the transport target.

[0027] Optionally, determining the physical characteristic parameters of the transport target based on the state information and the integrated closed-loop dynamics model specifically includes:

[0028] Using formula Determine the inertia of the transport target;

[0029] Using formula Determine the location of the center of gravity of the transport target;

[0030] Using formula Determine the target quality for handling;

[0031] in, K is an estimate of the inertia of the transported target. fc For force gain, Let i be the estimated angular acceleration of the target being transported in the inertial coordinate system, where i is the number of the flying robot and n is the total number of flying robots. Let be the position of the contact point between the i-th end effector of the flying operation robot and the transport target relative to the geometric center of each contact point between the end effector of the flying operation robot and the transport target. This is an estimated position of the contact point between the end effector of each flying robot and the target being transported, relative to the target's center of mass. an estimated value of a position of a geometric center of a contact point between the end effector of each flying operation robot and the carrying target relative to a mass center of the carrying target; an estimated value of a mass of the carrying target, n is a total number of the flying operation robots, f ft an estimated value of a non-zero force, an estimated value of an acceleration of the mass center of the carrying target, g is a gravitational acceleration.

[0032] Optionally, the determining of the real-time control strategy of each flying operation robot based on the physical characteristic parameters, the integrated closed-chain dynamics model and the adhesion interface contact dynamics model comprises:

[0033] determining a target expected dynamic trajectory of the carrying process according to the physical characteristic parameters;

[0034] determining a real-time distribution of an end adhesion interaction force of each flying operation robot based on an integrated closed-chain dynamics model according to the target expected dynamic trajectory;

[0035] tracking the real-time distribution of the end adhesion interaction force based on an adhesion interface contact dynamics model and determining a real-time control strategy of each flying operation robot.

[0036] Optionally, the determining of the target expected dynamic trajectory of the carrying process according to the physical characteristic parameters comprises:

[0037] using a formula to determine the target expected dynamic trajectory of the carrying process;

[0038] wherein, an expected acceleration of the carrying target, ζ o an expected dynamic trajectory damping of the carrying target, ω n,o an expected dynamic trajectory bandwidth of the carrying target, an expected velocity of the carrying target, p o,ref an expected position of the carrying target, p o,des a target position of the carrying target, an expected angular acceleration of the carrying target, K ω,o a first expected attitude trajectory gain of the carrying target, an expected angular velocity of the carrying target, K R,o a second expected attitude trajectory gain of the carrying target, Log represents a rotation matrix logarithm mapping, R o,des a target attitude of the carrying target, R o,ref an expected attitude of the carrying target.

[0039] Optionally, the determining the real-time distribution of the end adhesion interaction force of each flying operation robot based on the target expected dynamic trajectory and the integrated closed-chain dynamics model specifically comprises:

[0040] The real-time distribution of the end adhesion interaction force of each flying operation robot is determined by using the formula

[0041] Wherein, F ext,des is the expected adhesion interaction force of the end effector of each flying operation robot, W int is the first weighting matrix, ΔF ext,des is the change amount of F ext,des , W Δ is the second weighting matrix, n is the total number of flying operation robots, i is the flying operation robot number, f ext,des,i is the expected adhesion interaction force of the end effector of the i-th flying operation robot, f o,des is the expected force required to drive the carried object to move along the expected dynamic trajectory, is the position estimation value of the contact point between the end effector of the i-th flying operation robot and the carried target relative to the mass center of the carried target, m o,des is the expected moment required to drive the carried object to move along the expected dynamic trajectory, and Ω is the adhesion performance space.

[0042] Optionally, the real-time distribution of the end adhesion interaction force is tracked based on the adhesion interface contact dynamics model, and the real-time control strategy of each flying operation robot is determined, specifically comprising:

[0043] The real-time distribution of the end adhesion interaction force is tracked by using the formula

[0044] Wherein, k cont is the equivalent stiffness coefficient, p e,des is the expected position of the end effector, p e is the position of the end effector of the flying operation robot, c cont is the equivalent damping coefficient, is the expected velocity of the end effector, f ext,des is the expected end adhesion interaction force, f ext is the force received by the end adhesion effector.

[0045] In a second aspect, the application provides a flying operation robot cooperative carrying system, which comprises:

[0046] ​​a state information and end effector information acquisition module, configured to acquire state information and end effector information of each flight operation robot; the state information comprises: flight platform state variables, flight platform independent state variables, flight platform under-actuated non-independent state variables, flight operation robot state variables and flight robot independent state variables; and the end effector information comprises: normal pressure of a micro single adhesion support rod pair on a carrying target, adhesion array area and adhesion support rod density;

[0047] a multi-degree-of-freedom coupled dynamics model construction module, configured to construct a multi-degree-of-freedom coupled dynamics model of each flight operation robot according to the state information; the multi-degree-of-freedom coupled dynamics model comprises: a kinematics model and a dynamics model;

[0048] an adhesion interface contact dynamics model construction module, configured to construct an adhesion interface contact dynamics model of each flight operation robot according to the end effector information;

[0049] an integrated closed-chain dynamics model determination module, configured to determine an integrated closed-chain dynamics model of the flight operation robot and the carrying target according to the multi-degree-of-freedom coupled dynamics model and the adhesion interface contact dynamics model;

[0050] a physical property parameter determination module, configured to determine physical property parameters of the carrying target according to the state information and the integrated closed-chain dynamics model; the physical property parameters comprise: carrying target inertia, carrying target center of mass position and carrying target mass;

[0051] a carrying module, configured to determine a real-time control strategy of each flight operation robot based on the integrated closed-chain dynamics model and the adhesion interface contact dynamics model according to the physical property parameters, and carry the carrying target according to the real-time control strategy.

[0052] According to the specific embodiments provided in the application, the application has the following technical effects:

[0053] The application provides a flight operation robot cooperative carrying method and system, which realizes the grasping of a carrying target with different shapes or material surfaces by arranging an adhesion array on an end effector, improves the application effect and range in a real scene, realizes the dynamic trajectory generation of the target in the carrying process by establishing an integrated closed-chain dynamics model, improves the carrying stability, determines the real-time control strategy of each flight operation robot through the multi-degree-of-freedom coupled dynamics model and the adhesion interface contact dynamics model, realizes the tracking control of each flight operation robot, and improves the flexibility and carrying precision in the carrying process. BRIEF DESCRIPTION OF DRAWINGS

[0054] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on these drawings.

[0055] Figure 1 A flowchart of a flying work robot cooperative carrying method in an embodiment of the present application;

[0056] Figure 2 A flying work robot three-machine cooperative carrying diagram in an embodiment of the present application;

[0057] Figure 3 A flying work robot four-machine cooperative carrying diagram in an embodiment of the present application;

[0058] Figure 4 A flying work robot five-machine cooperative carrying diagram in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments only constitute some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0060] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the drawings and specific embodiments.

[0061] In an exemplary embodiment, as shown in Figure 1 a flying work robot cooperative carrying method is provided, comprising the following S1-S6. Wherein:

[0062] S1: obtaining state information and end effector information of each flying work robot.

[0063] The flying work robot in the present application is composed of a body, a flight platform, a work mechanism and a controller, wherein the flight platform contains four ducted propellers, the work mechanism includes a four-degree-of-freedom serial manipulator and an end effector, and the controller is used to realize real-time control of the flying work robot cooperative carrying process.

[0064] S1 specifically includes:

[0065] S11: obtaining state information.

[0066] The number of flight operation robots in the application is n, when the number of flight operation robots is 3, the cooperative carrying mode is as shown in Figure 2 ; when the number of flight operation robots is 4, the cooperative carrying mode is as shown in Figure 3 ; when the number of flight operation robots is 5, the cooperative carrying mode is as shown in Figure 4 ; for any flight operation robot i (the subscript i is omitted in the following formula), the state information of the flight operation robot is obtained, and the flight platform state variable is defined as The flight platform independent state variable is η a =[x a y a z a ψ a ] T , the flight platform under-actuated non-independent state variable is The flight operation robot state variable ξ=[ζ T q T ] T , and the flight operation robot independent state variable (generalized joint variable) is

[0067] The flight platform state variable includes the flight platform position p a =[x a y a z a ] T and the flight platform angle information is the roll angle, θ a is the pitch angle, and ψ a is the yaw angle; the flight platform independent state variable η a =[x a y a z a ψ a ] T includes the flight platform position p a =[x a y a z a ] T and the yaw angle ψ a in the flight platform angle information; the flight platform under-actuated non-independent state variable includes the roll angle and the pitch angle θ a in the flight platform angle information; the flight operation robot state variable ξ=[ζ T q T ] T includes the flight platform state variable and the joint angles of the manipulator q = [q1 q2 q3 q4] T ; flight operation robot independent state variable including flight platform independent state variable η a = [x a y a z a ψ a ] T and the joint angles of the manipulator q = [q1 q2 q3 q4] T .

[0068] Specifically, the flight platform position, flight platform angle information, flight platform speed flight platform angular velocity and the joint angles of the manipulator can be directly obtained, and the state information of the flight operation robot is derived from the above directly obtainable parameters.

[0069] S12: Obtain end effector information.

[0070] For any flight operation robot i, the normal pressure of the micro single adhesion strut pair of the flight operation robot end effector on the target is defined as F P , the adhesion array area is S a , and the adhesion strut density is η a . Among them, the normal pressure F P of the micro single adhesion strut pair of the flight operation robot end effector on the target can be directly obtained, the adhesion array area S a and the adhesion strut density η a are parameters determined when the flight operation robot is designed.

[0071] S2: According to the state information, construct a multi-degree-of-freedom coupled dynamics model of each flight operation robot.

[0072] Based on the multi-rigid-body dynamics theory, the kinematic model and the dynamics model of each flight operation robot are constructed, and the multi-degree-of-freedom coupled dynamics model includes the kinematic model and the dynamics model.

[0073] S2 specifically includes:

[0074] S21: Construct a kinematic model of each flight operation robot.

[0075] The expression of the flight operation robot end effector position p e is:

[0076]

[0077] Where R a is the rotation matrix from the flight platform coordinate system to the world coordinate system, The position of the end effector relative to the flight platform.

[0078] The linear velocity of the working mechanism mechanical arm link k in the link k coordinate system and the angular velocity The calculation formula is:

[0079]

[0080] wherein, is the rotation matrix of the mechanical arm link k coordinate system and the k-1 coordinate system, and is the linear velocity and angular velocity of the mechanical arm link k-1 in the link k-1 coordinate system, is the position of the mechanical arm link k relative to the k-1 coordinate system, is the velocity of the mechanical arm joint angle k, e zk is the unit vector of the link k coordinate system Z axis.

[0081] The end effector velocity of the flight working robot is further obtained by recursive solving as follows:

[0082]

[0083] wherein, J t,e (Φ a , q) is the Jacobian matrix of the end effector.

[0084] According to the small angle assumption of the body attitude angle, the influence of the flight platform under-actuated non-independent state variable on the end effector velocity is ignored, and the kinematics model of the flight working robot is obtained, and the calculation formula is:

[0085]

[0086] wherein, t is time, J tx,e (Φ a (t), q(t)) is the term related to the independent state variable of the flight working robot in the Jacobian matrix J t,e (Φ a , q) of the end effector, is the derivative of the independent state variable of the flight working robot.

[0087] S22: Construct the dynamics model of each flight working robot.

[0088] The Newton-Euler equation of the flight platform of the flight working robot is:

[0089]

[0090] wherein, and These are the net external force and net external torque acting on the flight platform, respectively, m a For the quality of the flight platform, To accelerate the flight platform, For the speed of the flight platform, For the angular velocity of the flight platform, For the angular acceleration of the flight platform, I a This represents the inertia matrix of the flight platform.

[0091] The Newton-Euler equations for link k of the robotic arm of the working mechanism are:

[0092]

[0093] in, and These are the net external force and net external torque acting on the robotic arm link k, respectively, m lk with I lk Let K be the mass and inertia matrix of the robotic arm link k. and These are the linear acceleration and angular acceleration of the center of mass of the robotic arm link k, respectively. Let be the angular velocity of the center of mass of the robotic arm link k.

[0094] The force balance equations and torque balance equations for the link k of the robotic arm of the working mechanism are as follows:

[0095]

[0096] Among them, R k Let be the rotation matrix from the k-coordinate system to the world coordinate system of the robotic arm link. Let k-1 be the force acting on link k of the robotic arm. Let τ be the torque τ exerted by link k-1 on link k in the robotic arm. k The driving torque on joint k of the robotic arm. Let K be the position of the center of mass of link k in the robotic arm relative to the link k coordinate system. Let be the rotation matrix between the k-coordinate system and the k+1 coordinate system of the robotic arm link. Let K be the force exerted by link k on link k+1 of the robotic arm. Let g be the position of link k+1 of the robotic arm relative to coordinate system k, g be the acceleration due to gravity, T be the transpose, and e be the position of link k+1 of the robotic arm. zk Let be the unit vector of the Z-axis in the k-coordinate system of the link.

[0097] The dynamic model of the flying operation robot is further obtained through recursive solution, and the calculation formula is as follows:

[0098]

[0099] where M(ξ) is the inertia matrix, is the Coriolis and centrifugal force matrix, g(ξ) is the gravity matrix, μ u is the generalized input force, including the ducted propeller lift and counter torque, and the mechanical arm joint driving torque in the generalized space, μ ext is the generalized external force, including the force f ext and the moment m ext exerted on the end effector, is the derivative of the flight operation robot state variable, is the second derivative of the flight operation robot state variable.

[0100] S3: According to the end effector information, construct the adhesion interface contact dynamics model of each flight operation robot.

[0101] S3 specifically includes:

[0102] S31: According to the end effector information, determine the adhesion array mechanics model based on the single adhesion strut mechanics model.

[0103] The calculation formula of the single adhesion strut mechanics model is as follows:

[0104]

[0105] where R adh is the radius of the micro adhesion strut end ball of the biomimetic silicone rubber-based adhesion array material, E' adh is the equivalent elastic modulus, γ adh is the surface energy, F P is the normal pressure of the micro single adhesion strut of the end effector on the carrying target, r a is the contact radius of the micro single adhesion strut of the end effector and the carrying target, and π is the circular constant.

[0106] Integrate the single adhesion strut mechanics model to obtain the adhesion array mechanics model, and the calculation formula is as follows:

[0107]

[0108] where F adh is the total adhesion force of the adhesion array, η a is the adhesion strut density, S a is the adhesion array area, d is the separation distance, σ o is the standard deviation of the rough peak of the contact surface of the carrying target, μ o is the mean of the rough peak, and z is the rough peak height.

[0109] The adhesion array mechanical model is used to solve the adhesion performance space, while the adhesion interface contact dynamics model is constrained by the adhesion performance space.

[0110] S32: Constructing the adhesion performance space based on the adhesion array mechanical model.

[0111] The adhesion force saturation boundary F can be calculated using the adhesion array mechanical model. sat (i.e., the total adhesive force F of the adhesive array) adh (maximum value) and minimum preload boundary F pre (i.e., the minimum normal pressure F that satisfies the requirement of total adhesion force of the minimum adhesion array) P The desorption force boundary F can be obtained by performing performance testing on the end-adhesion actuator using a multi-functional friction and wear testing machine. detach Desorption moment boundary M detach and microstructure failure boundary τ max .

[0112] Based on the above parameters, the adhesion performance space is constructed as follows:

[0113]

[0114] The adhesion performance space includes: the force f acting on the end effector. ext The constraint ranges of the normal component, tangential component, and torque on the end effector are defined. In the adhesion performance space expression, τ represents the root shear stress of the adhesive microstructure at the contact interface, and f... ext,n f is the normal component of the force acting on the end effector. ext,t m is the tangential component of the force acting on the end effector. ext This refers to the torque applied to the end-effector.

[0115] S33: Construct a contact dynamics model of the adhesive interface within the adhesive performance space.

[0116] Specifically, the calculation formula for the adhesion interface contact dynamics model is as follows:

[0117]

[0118] Among them, f ext k represents the force acting on the end effector. cont Δp is the equivalent stiffness coefficient. e c represents the position change of the end effector of the flying robot. cont This is the equivalent damping coefficient. Ω represents the end effector speed of the flying robot, and Ω represents the adhesion performance space.

[0119] S4: Determine the integrated closed-chain dynamics model of the flying operation robot and the carrying target according to the multi-degree-of-freedom coupling dynamics model and the adhesion interface contact dynamics model.

[0120] Specifically, the mass center position of the carrying target is defined as p o , the speed of the carrying target is v o , and the angular velocity of the carrying target relative to the carrying target coordinate system, i.e., the angular velocity of the carrying target, is For any flying operation robot i, the expression of the contact point position p c,i of the end effector and the carrying target is as follows:

[0121]

[0122] wherein R o is the rotation matrix of the carrying target coordinate system to the world coordinate system, is the position of the contact point of the end effector of the i-th flying operation robot relative to the mass center of the carrying target. During cooperative carrying, p c,i = p e,i .

[0123] The calculation formula of the integrated closed-chain dynamics model of the flying operation robot and the carrying target is as follows:

[0124]

[0125] wherein i is the flying operation robot number, n is the total number of flying operation robots, m o is the mass of the carrying target, g is the acceleration of gravity, f ext,i is the force received by the i-th end adhesion effector, v o is the speed of the carrying target, m ext,i is the torque received by the i-th end adhesion effector, is the angular velocity of the carrying target, is the angular acceleration of the carrying target, R o is the rotation matrix of the carrying target coordinate system to the world coordinate system, I o is the inertia matrix of the carrying target.

[0126] S5: Determine the physical characteristic parameters of the carrying target according to the state information and the integrated closed-chain dynamics model. The physical characteristic parameters include the inertia of the carrying target, the mass center position of the carrying target, and the mass of the carrying target.

[0127] S5 specifically includes:

[0128] S51: Determine the inertia of the carrying target.

[0129] Specifically, p c,i and pc,j respectively the position of the contact point of the i-th and j-th flying working robot end effector with the handling target, and respectively the velocity of the contact point of the i-th and j-th flying working robot end effector with the handling target, p c,ij = p c,i -p c,j the relative position of the contact point of the i-th and j-th flying working robot end effector with the handling target, the relative velocity of the contact point of the i-th and j-th flying working robot end effector with the handling target, the normalized orthogonal relative velocity of the contact point of the i-th and j-th flying working robot end effector with the handling target, the superscript represents the orthogonal complement operator.

[0130] Further, the angular velocity estimate of the handling target in the inertial coordinate system the direction estimate of the angular velocity of the handling target in the inertial coordinate system The calculation formula is as follows:

[0131]

[0132] wherein, LP is the low-pass filtered value of the variable.

[0133] The angular velocity estimate of the handling target in the inertial coordinate system The calculation formula is as follows:

[0134]

[0135] The geometric center p of the contact point of each flying working robot end effector with the handling target o,g The calculation formula is as follows:

[0136]

[0137] Further, the position of the contact point of the i-th flying working robot end effector with the handling target relative to the geometric center of the contact point of each flying working robot end effector with the handling target is:

[0138]

[0139] The position of the geometric center of the contact point of each flying working robot end effector with the handling target relative to the center of mass of the handling target is defined as The force f exerted by each flying working robot end effector on the handling target c,i According to the integrated closed-chain dynamics model of the flying working robot and the handling target, the following can be obtained:

[0140]

[0141] where I o is the inertia matrix of the transported object, is the angular acceleration of the transported object in the inertial coordinate system.

[0142] Let be the estimated value of the angular acceleration of the transported object in the inertial coordinate system, K fc is the force gain, the estimated value of the inertia matrix of the transported object is calculated as is:

[0143]

[0144] S52: Determine the mass center position of the transported object.

[0145] Let f c,i = f fc , f fc be a non-zero force, the estimated value of the position of the geometric center of the contact point between each aerial work robot end effector and the transported object relative to the mass center of the transported object is calculated as is:

[0146]

[0147] Further, the estimated value of the position of the contact point between each aerial work robot end effector and the transported object relative to the mass center of the transported object is is:

[0148]

[0149] S53: Determine the mass of the transported object.

[0150] The estimated value of the velocity of the mass center of the transported object is:

[0151]

[0152] According to the integrated closed-chain dynamics model of the aerial work robot and the transported object, we have:

[0153]

[0154] where m o is the mass of the transported object, is the acceleration of the mass center of the transported object.

[0155] The estimated value of the mass of the transported object is calculated as:

[0156]

[0157] wherein, is an acceleration estimation value of the center of mass of the carrying target.

[0158] S6: determining a real-time control strategy of each flying operation robot based on the integrated closed-chain dynamics model and the adhesion interface contact dynamics model according to the physical property parameters; and carrying the carrying target according to the real-time control strategy.

[0159] S6 specifically includes:

[0160] S61: determining a target expected dynamic trajectory of the carrying process according to the physical property parameters.

[0161] Given the target position p of the carrying target o,des and the target attitude R of the carrying target o,des , considering the flexibility and smoothness of the carrying process trajectory, the expected position p of the carrying target o,ref , the expected speed the expected attitude R of the carrying target o,ref and the expected angular velocity of the carrying target in the carrying process are generated. The target expected dynamic trajectory expression of the carrying process is:

[0162]

[0163] wherein, is the expected acceleration of the carrying target, ζ o is the expected dynamic trajectory damping of the carrying target, ω n,o is the expected dynamic trajectory bandwidth of the carrying target, is the expected angular acceleration of the carrying target, K ω,o is the first expected attitude trajectory gain of the carrying target, K R,o is the second expected attitude trajectory gain of the carrying target, and Log represents the logarithmic mapping of the rotation matrix.

[0164] The flexibility and smoothness of the carrying process trajectory are realized by adjusting parameters ζ o , ω n,o , K ω,o , K R,o .

[0165] S62: determining the real-time distribution of the end adhesion interaction force of each flying operation robot based on the integrated closed-chain dynamics model according to the target expected dynamic trajectory.

[0166] According to the end effector position p of each flying operation robot e,i , the speed , the attitude R e,i , and the angular velocity and a rotation matrix from the contact point coordinate system of the aerial work robot end-effector to the carrying target coordinate system The real-time position estimate of the carrying target in three-dimensional space is calculated The velocity estimate The attitude estimate The angular velocity estimate Respectively,

[0167]

[0168] Wherein, SVD represents the attitude average method based on singular value decomposition.

[0169] Further calculate the expected force f required to drive the carrying object to move along the expected dynamic trajectory o,des And the moment m o,des The calculation formula is:

[0170]

[0171] Wherein, The mass of the carrying target, The expected acceleration of the carrying target, The expected velocity of the carrying target, The mass center position estimate of the carrying target, K fd,o , K fp,o The expected force gain of the carrying target, K md,o , K mp,o The expected moment gain of the carrying target, The expected angular acceleration of the carrying target, The expected angular velocity of the carrying target, R o,ref The expected attitude of the carrying target.

[0172] Define the expected adhesion interaction force F of each aerial work robot end-effector ext,des As follows:

[0173] F ext,des = [f ext,des,1 f ext,des,2 … f ext,des,n ] T ;

[0174] Wherein, f ext,des,i The expected adhesion interaction force of the i-th aerial work robot end-effector, i=1,2,…,n.

[0175] The following receding horizon optimization problem is constructed to solve the real-time distribution of the expected adhesion interaction force of each aerial work robot, that is, the optimal distribution at the current time, and the calculation formula is as follows:

[0176]

[0177] where ΔF ext,des is the change of F ext,des , W int is the first weighting matrix, and W Δ is the second weighting matrix.

[0178] S63: Based on the adhesion interface contact dynamics model, the real-time distribution of the end adhesion interaction force is tracked, and the real-time control strategy of each flight work robot is determined.

[0179] The application uses a controller to realize the tracking of the end effector to the expected adhesion interaction force f ext,des .

[0180] According to the adhesion interface contact dynamics model, the tracking of the end effector of the flight work robot to the expected adhesion interaction force f ext,des can be realized by tracking the expected position p e,des and the expected speed of the end effector:

[0181]

[0182] The trajectory tracking task behavior function h task is defined as:

[0183]

[0184] where K task is the trajectory tracking control gain.

[0185] The work mechanism joint performance null space behavior function h perf is:

[0186]

[0187] where q k is the kth joint angle of the work mechanism, q k,mid is the median value of the joint angle, q k,min and q k,max are the minimum and maximum values of the joint angle respectively, and K perf is the work mechanism joint performance control gain.

[0188] The work mechanism safety collision avoidance null space behavior function is:

[0189]

[0190] where d k is the distance from the work mechanism link k to the environmental obstacle, and dmin Kminis the minimum safety distance of the working mechanism link to the environmental obstacles, safe Ksafis the safety collision avoidance control gain of the working mechanism.

[0191] The control law designed based on the null space behavior decomposition is:

[0192]

[0193] wherein, is the reference of the generalized joint variable velocity of the flying working robot, is the pseudo-inverse matrix of J tx,e , is the gradient of h perf and h safe . Each generalized joint variable realizes the tracking of by a PID controller.

[0194] Based on the same inventive concept, the embodiments of the present application also provide a flying working robot cooperative carrying system. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme described in the above method, so the specific limitations in the following flying working robot cooperative carrying system embodiments can be referred to the limitations of the flying working robot cooperative carrying method in the above text, which will not be repeated here.

[0195] In an exemplary embodiment, a flying working robot cooperative carrying system is provided, comprising:

[0196] a state information and end effector information acquisition module configured to acquire state information and end effector information of each flying working robot; the state information comprises: flying platform state variables, flying platform independent state variables, flying platform under-actuated non-independent state variables, flying working robot state variables and flying robot independent state variables; and the end effector information comprises: normal pressure of micro single adhesion strut pair on a carrying target, adhesion array area and adhesion strut density;

[0197] a multi-degree-of-freedom coupled dynamics model construction module configured to construct a multi-degree-of-freedom coupled dynamics model of each flying working robot according to the state information; the multi-degree-of-freedom coupled dynamics model comprises: a kinematics model and a dynamics model;

[0198] an adhesion interface contact dynamics model construction module configured to construct an adhesion interface contact dynamics model of each flying working robot according to the end effector information;

[0199] ​An integrated closed-chain dynamics model determination module is configured to determine an integrated closed-chain dynamics model of the flying operation robot and the carrying target according to the multi-degree-of-freedom coupled dynamics model and the adhesion interface contact dynamics model;

[0200] A physical characteristic parameter determination module is configured to determine a physical characteristic parameter of the carrying target according to the state information and the integrated closed-chain dynamics model; the physical characteristic parameter includes an inertia of the carrying target, a center of mass position of the carrying target, and a mass of the carrying target;

[0201] A carrying module is configured to determine a real-time control strategy of each flying operation robot based on the integrated closed-chain dynamics model and the adhesion interface contact dynamics model according to the physical characteristic parameter, and carry the carrying target according to the real-time control strategy.

[0202] The technical features of the above embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but it should be considered that any combination of the technical features is within the scope of the present disclosure as long as there is no contradiction.

[0203] The principles and implementation modes of the present application are described by using specific examples. The above description of the embodiments is only used to help understand the method and its core idea; meanwhile, for those skilled in the art, the specific implementation modes and application scope can be changed according to the idea of the present application. In conclusion, the content of the present description should not be understood as a limitation of the present application.

Claims

1. A flying work robot cooperative carrying method characterized by, The flying operation robot cooperative carrying method comprises: acquiring state information and end effector information of each flying operation robot; the state information comprises: flying platform state variables, flying platform independent state variables, flying platform under-actuated non-independent state variables, flying operation robot state variables and flying robot independent state variables; the end effector information comprises: normal pressure of micro single adhesion strut pair on a carrying target, adhesion array area and adhesion strut density; constructing a multi-degree-of-freedom coupled dynamics model of each flying operation robot according to the state information; the multi-degree-of-freedom coupled dynamics model comprises: a kinematics model and a dynamics model; constructing an adhesion interface contact dynamics model of each flying operation robot according to the end effector information; determining an integrated closed-chain dynamics model of the flying operation robot and the carrying target according to the multi-degree-of-freedom coupled dynamics model and the adhesion interface contact dynamics model; determining physical characteristic parameters of the carrying target according to the state information and the integrated closed-chain dynamics model; the physical characteristic parameters comprise: carrying target inertia, carrying target center of mass position and carrying target mass; determining a real-time control strategy of each flying operation robot based on the integrated closed-chain dynamics model and the adhesion interface contact dynamics model according to the physical characteristic parameters; and carrying the carrying target according to the real-time control strategy.

2. The aerial work robot collaborative handling method according to claim 1, characterized in that, The method specifically comprises: Using the formula determining a kinematic model of each flying work robot; Using the formula determining a dynamics model of each flying operation robot; wherein is the end effector velocity of the aerial work robot, t is time, J tx,e (Φ a (t), q(t)) is the Jacobian matrix J t,e (Φ a , q) of the end effector, is the derivative of the aerial work robot independent state variable, is the derivative of the aerial work robot state variable, is the second derivative of the aerial work robot state variable, M(ξ) is the inertia matrix, is the Coriolis and centrifugal force matrix, g(ξ) is the gravity matrix, μ u is the generalized input force, μ ext is the generalized external force.

3. The aerial work robot collaborative handling method according to claim 1, characterized in that, The method specifically comprises: determining an adhesion array mechanics model based on a single adhesion strut mechanics model according to the end effector information; constructing an adhesion performance space based on the adhesion array mechanics model; the adhesion performance space comprises: normal component constraint range, tangential component constraint range of an action force received by an end adhesion effector and action torque constraint range of the end adhesion effector; Using the formula An adhesion interface contact dynamics model is constructed within the adhesion property space; wherein f ext is the force experienced by the end-effector, k cont is the equivalent stiffness coefficient, Δp e is the position change of the end-effector of the flying work robot, c cont is the equivalent damping coefficient, is the velocity of the end-effector of the flying work robot, Ω is the adhesion performance space.

4. The aerial work robot collaborative handling method according to claim 1, characterized in that, The method specifically comprises: Using the formula A closed-chain dynamics model of the flying operating robot and the carrying target is determined; where i is the flight operation robot number, n is the total number of flight operation robots, m o is the target mass, g is the acceleration of gravity, f ext,i is the force received by the i-th end adhesion actuator, v o is the speed of the target, m ext,i is the torque received by the i-th end adhesion actuator, is the angular velocity of the target, is the angular acceleration of the target, R o is the rotation matrix of the target coordinate system to the world coordinate system, is the position of the contact point of the i-th flight operation robot end actuator with the target relative to the center of mass of the target, I o is the inertia matrix of the target.

5. The aerial work robot collaborative handling method according to claim 1, characterized in that, The method specifically comprises: Using the formula determine the transport target inertia; Using the formula determine the transport target center of mass position; Using the formula determining a target mass for transport; wherein, is an estimate of the target inertia, fc is an action force gain, is an estimate of the angular acceleration of the target in the inertial frame, i is the flying work robot number, n is the total number of flying work robots, is the position of the ith flying work robot end effector contact point with the target relative to the geometric center of each flying work robot end effector contact point with the target, is an estimate of the position of each flying work robot end effector contact point with the target relative to the target center of mass, is an estimate of the position of the geometric center of each flying work robot end effector contact point with the target relative to the target center of mass; is an estimate of the target mass, n is the total number of flying work robots, f ft is a non-zero action force, is an estimate of the target center of mass acceleration, g is the gravitational acceleration.

6. The aerial work robot collaborative handling method according to claim 1, characterized in that, The method specifically comprises: determining a target expected dynamic trajectory of a carrying process according to the physical characteristic parameters; determining real-time distribution of end adhesion interaction force of each flying operation robot based on the integrated closed-chain dynamics model according to the target expected dynamic trajectory; tracking the real-time distribution of the end adhesion interaction force based on the adhesion interface contact dynamics model, and determining the real-time control strategy of each flying operation robot.

7. The aerial work robot collaborative handling method according to claim 6, characterized in that, The method specifically comprises: Using the formula determining a target desired dynamic trajectory for the transport process; wherein, is a desired acceleration of the transport target, ζ o is a desired dynamic trajectory damping of the transport target, ω n,o is a desired dynamic trajectory bandwidth of the transport target, is a desired velocity of the transport target, p o,ref is a desired position of the transport target, p o,des is a target position of the transport target, is a desired angular acceleration of the transport target, K ω,o is a first desired attitude trajectory gain of the transport target, is a desired angular velocity of the transport target, K R,o is a second desired attitude trajectory gain of the transport target, Log denotes a rotation matrix logarithm mapping, R o,des is a target attitude of the transport target, R o,ref is a desired attitude of the transport target.

8. The flying work robot cooperative carrying method according to claim 6, characterized by, The method comprises the following steps: Using the formula determining a real-time distribution of the end adhesion interaction force of each flying operation robot; wherein F ext,des is the desired adhesion interaction force of the end-effector of each flying service robot, W int is a first weighting matrix, ΔF ext,des is the change amount of F ext,des , W Δ is a second weighting matrix, n is the total number of flying service robots, i is the flying service robot number, f ext,des,i is the desired adhesion interaction force of the end-effector of the i-th flying service robot, f o,des is the desired action force required to drive the carried object to move along the desired dynamic trajectory, is the position estimation value of the contact point between the end-effector of the i-th flying service robot and the carried target relative to the centroid of the carried target, m o,des is the desired action torque required to drive the carried object to move along the desired dynamic trajectory, Ω is the adhesion performance space.

9. The flying work robot cooperative carrying method according to claim 6, characterized by, The method comprises the following steps: Using the formula Tracking real-time distribution of end-stick interactions; where k cont is the equivalent stiffness coefficient, p e,des is the end effector desired position, p e is the aerial work robot end effector position, c cont is the equivalent damping coefficient, is the end effector desired velocity, f ext,des is the desired end effector adhesion interaction force, f ext is the force experienced by the end effector in adhesion.

10. A flying job robot cooperative handling system characterized by, The flying operation robot cooperative carrying system comprises: A state information and end effector information acquisition module is configured to acquire state information and end effector information of each flying operation robot; the state information comprises flying platform state variables, flying platform independent state variables, flying platform under-actuated non-independent state variables, flying operation robot state variables and flying robot independent state variables; and the end effector information comprises normal pressure of a micro single adhesion strut pair on a carrying target, adhesion array area and adhesion strut density; A multi-degree-of-freedom coupled dynamics model construction module is configured to construct a multi-degree-of-freedom coupled dynamics model of each flying operation robot according to the state information; the multi-degree-of-freedom coupled dynamics model comprises a kinematics model and a dynamics model; An adhesion interface contact dynamics model construction module is configured to construct an adhesion interface contact dynamics model of each flying operation robot according to the end effector information; An integrated closed-chain dynamics model determination module is configured to determine an integrated closed-chain dynamics model of the flying operation robot and the carrying target according to the multi-degree-of-freedom coupled dynamics model and the adhesion interface contact dynamics model; A physical property parameter determination module is configured to determine physical property parameters of the carrying target according to the state information and the integrated closed-chain dynamics model; the physical property parameters comprise carrying target inertia, carrying target center of mass position and carrying target mass; A carrying module is configured to determine a real-time control strategy of each flying operation robot based on the integrated closed-chain dynamics model and the adhesion interface contact dynamics model according to the physical property parameters; and the carrying module is configured to carry the carrying target according to the real-time control strategy.

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