Multi-uav cooperative hoisting system constraint space crossing trajectory planning method and system

Abstract

The present application relates to the technical field of trajectory planning of nonlinear underactuated electromechanical systems, and particularly relates to a multi-unmanned aerial vehicle cooperative hoisting system constraint space crossing trajectory planning method and system. The method comprises the following steps: based on a polyhedral volume constituted by the hoisting system and a hoisting rope tension, a hoisting system crossing formation optimization model under a constraint space is constructed to obtain an optimal formation of the hoisting system crossing the constraint space; a circumscribed sphere center and a radius under the optimal formation of the hoisting system crossing the constraint space are calculated; based on the circumscribed sphere center and the radius, a trajectory planning model of the hoisting system crossing the constraint space based on time optimization is constructed by considering dynamic constraints, driver constraints and flight path point constraints; based on the relative position relationship among the circumscribed sphere center, the unmanned aerial vehicle and the load, the trajectory planning model of the hoisting system crossing the constraint space is adopted to obtain a trajectory of the hoisting system crossing the constraint space; and under the guidance of the trajectory of the hoisting system crossing the constraint space, a load transportation task is completed.

Description

Technical Field

[0001] This invention relates to the technical field of trajectory planning for nonlinear underactuated electromechanical systems, and in particular to a method and system for planning constrained space traversal trajectories for a multi-UAV cooperative hoisting system. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] The use of drone-based hoisting systems for aerial transport has attracted widespread attention from researchers. Especially in search and rescue missions, drone hoisting systems need to rapidly deliver supplies or emergency equipment in confined spaces. The aerial transport discussed in this invention refers to three drones connected by slings to a spherical load to complete a transport mission across a confined space. Using multiple drones for coordinated transport can solve the problem of insufficient carrying capacity of a single drone.

[0004] Preliminary research has been conducted on unmanned aerial vehicle (UAV) hoisting systems for transporting loads in constrained spaces. However, most of this research focuses on single-UAV hoisting systems. Utilizing multiple UAVs for joint load transport can effectively improve the system's carrying capacity. However, the introduction of multiple UAVs greatly complicates the system's formation adjustment. Furthermore, the method of transporting loads by connecting multiple UAVs with lanyards creates coupling not only between the UAVs and the load but also between the UAVs themselves, posing a significant challenge to load transport in constrained spaces. Summary of the Invention

[0005] To address the technical problems mentioned above, this invention provides a method and system for planning trajectory crossings in constrained spaces in a multi-UAV collaborative hoisting system. This method enables safe and rapid load transport within constrained spaces, thereby improving the actual performance of the multi-UAV hoisting system.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] The first aspect of the present invention provides a method for planning the trajectory of a constrained space crossing in a multi-UAV collaborative hoisting system.

[0008] A method for planning the trajectory of a multi-UAV collaborative hoisting system across constrained space, including:

[0009] Based on the polyhedral volume of the hoisting system and the tension of the hoisting rope, an optimization model for the hoisting system's crossing formation under constrained space is constructed to obtain the optimal formation for the hoisting system to cross the constrained space.

[0010] Calculate the center and radius of the circumsphere of the hoisting system under the optimal formation for traversing the constrained space;

[0011] Based on the center and radius of the circumscribed sphere, and considering dynamic constraints, actuator constraints, and waypoint constraints, a time-optimal trajectory planning model for the hoisting system traversing constrained space is constructed. Based on the relative positional relationship between the center of the circumscribed sphere, the UAV, and the load, the trajectory of the hoisting system traversing constrained space is obtained using the trajectory planning model for the hoisting system traversing constrained space.

[0012] Guided by the trajectory of the hoisting system traversing the constrained space, the load transportation task is completed.

[0013] Furthermore, the optimization model for the hoisting system traversing the formation under the constrained space is as follows:

[0014] J1=min(ρ v J v +ρ w J w )

[0015] st:||p i -p o ||=l i i = 1, 2, 3

[0016] ||p i -p o ||≥d s i≠j, i,j=1,2,3

[0017] T imin ≤T i ≤T imax

[0018]

[0019] Where ||·|| represents the Euclidean norm, p represents the volume of the tetrahedron formed by the hoisting system. i and p o Let i represent the positions of the i-th drone and the payload, respectively. The weight ρ represents the total tension in the suspension rope. v and ρ w Used to weigh the two indicators J v and J w The importance of l i Let d represent the length of the i-th suspension rope. s T represents the safe distance between drones. imin and T imax Indicates the tension T in the suspension rope i range, m o Let g represent the mass of the load, and g represent the gravitational constant.

[0020] Furthermore, the optimal formation for the hoisting system to traverse the constrained space includes the position of each UAV and the position of the load.

[0021] Furthermore, the dynamic constraints are:

[0022] The dynamics of the circumscribed sphere of the hoisting system are expressed as:

[0023]

[0024] Among them, v r and a r These represent the velocity and acceleration of the center of the sphere connected to the hoisting system, respectively; acceleration is selected as the input u. r Therefore, u r =a r The state changes of the circumscribed sphere's center are described by the relationship between the states of adjacent nodes:

[0025] x dynr,k+1 =x dynr,k +f RK (x dynr,k ,u r,k )·dt

[0026] in, p r,k+1 and v r,k+1 These represent the positions of the circumscribed ball's center at time t. k+1 Position and velocity at time t; dt = t N / N represents the discrete time step, t N The total time to complete the constraint space traversal is represented by N, where N represents the number of nodes; u r,k This indicates that the center of the circumscribed ball is at t. k Acceleration at any moment.

[0027] Furthermore, the driver constraint is:

[0028] v min ≤v r,k ≤v max ,a min ≤a r,k ≤a max

[0029] Among them, v min and v max Let a represent the minimum and maximum allowable ball center velocities, respectively. min and a max These represent the minimum and maximum allowable acceleration at the center of the sphere, respectively.

[0030] Furthermore, the waypoint constraints are as follows:

[0031] The center of the circumscribed sphere should pass through the track point, i.e., the center p of the constrained space, within a certain allowable error. wi Define the following waypoint constraints:

[0032]

[0033] in, Indicates at t k The allowable error for passing the i-th waypoint at any given time is p. r,k This indicates that the center of the circumscribed ball is at t. k The position at any given moment.

[0034] Furthermore, the time-optimal hoisting system trajectory planning model for traversing constrained space is as follows:

[0035]

[0036] stx dynr,k+1 -x dynr,k -u r,k =0

[0037] a min ≤u r,k ≤a max

[0038] v min ≤v r,k ≤v max

[0039] κ k+1 -κ k +γ k =0

[0040] κ0=1,κ N =0

[0041]

[0042]

[0043]

[0044] Among them, t N The x represents the total time to complete the constraint space traversal, and N represents the number of nodes; dynr,k+1 and x dynr,k These represent the positions of the circumscribed ball's center at time t. k+1 and t k The state at time, u r,k This indicates that the center of the circumscribed ball is at t. k acceleration at time, v min and v max Let a represent the minimum and maximum allowable ball center velocities, respectively. minand a max These represent the minimum and maximum allowable acceleration at the center of the sphere, respectively; κ k Indicates the waypoint at t k The process variable at time κ k+1 Indicates the waypoint at t k+1 The process variable at time γ k The process variable representing the waypoint in t k The changing of time, The process variable representing the i-th waypoint in time t k The changing of time, This indicates that the i-th waypoint is at t. k The process state at any given moment. This indicates that the (i+1)th waypoint is at t k The process state at any given time, where M represents the number of tracked waypoints, and p wi p represents the center of the constrained space. r,k This indicates that the center of the circumscribed ball is at t. k Location at any given moment Indicates at t k The allowable error for passing the i-th waypoint at any given time is δ. 2 This indicates the maximum permissible error after passing through the track points.

[0045] A second aspect of the present invention provides a constrained space traversal trajectory planning system for a multi-UAV collaborative hoisting system.

[0046] A constrained space traversal trajectory planning system for multi-UAV collaborative hoisting systems, including:

[0047] The first optimization module is configured to: construct an optimization model of the hoisting system's crossing formation under constrained space based on the polyhedral volume of the hoisting system and the tension of the hoisting rope, and obtain the optimal formation of the hoisting system crossing the constrained space;

[0048] The calculation module is configured to calculate the center and radius of the circumsphere of the hoisting system under the optimal formation for traversing the constrained space.

[0049] The second optimization module is configured to: construct a time-optimal trajectory planning model for the hoisting system traversing the constrained space based on the center and radius of the circumscribed sphere, considering dynamic constraints, actuator constraints, and waypoint constraints; and obtain the trajectory of the hoisting system traversing the constrained space by adopting the trajectory planning model for the hoisting system traversing the constrained space based on the relative positional relationship between the center of the circumscribed sphere, the UAV, and the load.

[0050] The task execution module is configured to complete the load delivery task under the guidance of the hoisting system's trajectory through the constrained space.

[0051] A third aspect of the present invention provides a computer-readable storage medium.

[0052] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system as described in the first aspect above.

[0053] A fourth aspect of the present invention provides a computer device.

[0054] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system as described in the first aspect above.

[0055] Compared with the prior art, the beneficial effects of the present invention are:

[0056] 1. Considering that most existing methods focus on single UAV load transportation tasks under constrained space, the load transportation trajectory planning method for multi-UAV hoisting systems under constrained space proposed in this invention can enhance the role of hoisting systems in practical applications and further expand the application scope of hoisting systems.

[0057] 2. In the process of generating the trajectory of the hoisting system traversing the constrained space, the present invention fully considers the system dynamics, actuators and track point constraints, and can quickly transport the load to the desired location while ensuring that the system does not collide with the constrained space.

[0058] 3. This invention is expected to be further applied to large unmanned helicopters, which has significant economic value and practical application significance for logistics transportation, disaster relief and other fields. Attached Figure Description

[0059] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0060] Figure 1 This is a flowchart of the constrained space crossing trajectory planning method for the multi-UAV collaborative hoisting system of the present invention;

[0061] Figure 2 The experimental results of the method proposed in this invention include the position x1, y1, z1 and velocity v of UAV 1. x1 ,v y1 ,v z1 ;

[0062] Figure 3 The experimental results of the method proposed in this invention include the position x2, y2, z2 and velocity v of the UAV 2. x2 ,vy2 ,v z2 ;

[0063] Figure 4 The experimental results of the method proposed in this invention include the UAV's position x3, y3, z3 and velocity v. x3 ,v y3 ,v z3 ;

[0064] Figure 5 The load position x in the experimental results of the method proposed in this invention o ,y o ,z o ;

[0065] Figure 6 A side view of the trajectory of the hoisting system traversing the constrained space in the experimental results of the method proposed in this invention;

[0066] Figure 7 A top view of the trajectory of the hoisting system traversing the constrained space in the experimental results of the method proposed in this invention. Detailed Implementation

[0067] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0068] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, 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.

[0069] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0070] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and systems according to various embodiments of this disclosure. It should be noted that each block in a flowchart or block diagram may represent a module, segment, or portion of code, which may include one or more executable instructions for implementing the logical functions specified in the various embodiments. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutively represented blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, may be implemented using a dedicated hardware-based system that performs the specified functions or operations, or using a combination of dedicated hardware and computer instructions.

[0071] Example 1

[0072] like Figure 1 As shown, this embodiment provides a method for planning the trajectory of a multi-UAV collaborative hoisting system traversing constrained space. This embodiment uses the application of this method to a server as an example for illustration. It can be understood that this method can also be applied to a terminal, or to a system including a terminal, a server, and a system, and can be implemented through the interaction between the terminal and the server. The server can be an independent physical server, a server cluster composed of multiple physical servers, or a distributed system. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network servers, cloud communication, middleware services, domain name services, CDN security services, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and the server can be directly or indirectly connected through wired or wireless communication, which is not limited in this application. In this embodiment, the method includes:

[0073] First, optimization indices are constructed based on the energy and formation optimization of the multi-UAV hoisting system. Specifically, by balancing the total tension of the hoisting ropes with the volume of the polyhedron formed by the hoisting system, the optimal formation of the hoisting system for traversing the constrained space is obtained.

[0074] Secondly, based on the previous step of formation optimization, the center and radius of the circumscribed sphere of the multi-UAV collaborative hoisting system are obtained. At the same time, it is assumed that the formation of the hoisting system remains unchanged during the entire constrained space crossing process, that is, the relative positions between the UAVs are fixed. Based on this, the trajectory planning problem of the hoisting system crossing the constrained space can be transformed into the trajectory planning problem of the center of the circumscribed sphere of the hoisting system passing through the center of the constrained space.

[0075] Furthermore, taking into account dynamics, actuators, and waypoint constraints, with the goal of minimizing transport time, trajectory planning is performed on the center of the circumscribed sphere of the hoisting system, and the trajectory of each UAV is obtained based on the relative positional relationship between the center of the circumscribed sphere and the UAV.

[0076] Finally, driven by the generated planned trajectory, the hoisting system completes the task of traversing the constrained space, transporting the load from the initial position to the target position.

[0077] The technical solution of this embodiment will be described in detail below:

[0078] Step 1: Construct the constraint space crossing formation optimization index and solve for the optimal formation of the hoisting system crossing the constraint space;

[0079] To ensure no collisions occur between UAVs within the hoisting system, the smaller the volume of the polyhedron forming the hoisting system, the higher the success rate of the system in traversing constrained spaces. Furthermore, when considering the hoisting system's constrained space traversal formation, the tension of the hoisting ropes should be fully considered to avoid system instability due to excessive rope tension. Therefore, considering both optimization objectives, the hoisting system traversal formation optimization model under constrained space can be constructed as follows:

[0080]

[0081] Where ||·|| represents the Euclidean norm, Let p represent the volume of the tetrahedron formed by the hoisting system. i and p o Let i represent the positions of the i-th drone and the payload, respectively. The weight ρ represents the total tension in the suspension rope. v and ρ w Used to weigh the two indicators J v and J w The importance of l i Let d represent the length of the i-th suspension rope. s T represents the safe distance between drones. imin and T imax Indicates the tension T in the suspension rope i range, m o Let g represent the mass of the load, and g represent the gravitational constant. The constraints of the optimization problem in Equation (1) from top to bottom are: rope length constraint, collision avoidance constraint between UAVs, rope tension constraint, and load dynamics constraint.

[0082] Step 2: Solve for the center and radius of the circumscribed sphere of the hoisting system under the optimal crossing formation;

[0083] The optimal formation of the hoisting system traversing the constraint space can be obtained by solving the optimization problem in equation (1), which includes the position of the UAV. and the location of the load Next, the center p of the ball on the outside of the hoisting system r and radius r c The following relationship must be satisfied:

[0084]

[0085] Subsequently, by expanding and rearranging equation (2), we can obtain the center of the circumscribed sphere.

[0086]

[0087] Among them, b i The definition is as follows:

[0088]

[0089] Step 3: Considering dynamics, actuators, and waypoint constraints, obtain the time-optimal system-constrained space traversal trajectory;

[0090] In this invention, it is assumed that the hoisting system maintains a fixed formation during the traversal of the constrained space, meaning that the relative positions of the UAVs remain unchanged throughout the entire traversal. Based on this assumption, the trajectory planning problem for the hoisting system traversing the constrained space can be transformed into a planning problem for the center of the circumscribed sphere of the hoisting system. After obtaining the trajectory of the center sphere, the trajectory of the UAVs during the entire traversal can be calculated based on the relative positional relationship between the UAVs and the center sphere. To complete the constrained space traversal task, the trajectory planning problem for the center sphere needs to satisfy the following two objectives: (1) The center sphere of the hoisting system should pass through the waypoint (center of the constrained space) within a certain allowable error; (2) The hoisting system should complete the load transport task under the constrained space in the shortest possible time while ensuring no collision with the constrained space, thereby improving the load transport efficiency. To achieve the above objectives, the following constraints are defined:

[0091] 1) Dynamic constraints

[0092] The dynamics of the circumscribed sphere of the hoisting system can be expressed as:

[0093]

[0094] Among them, v r and a r These represent the velocity and acceleration of the center of the external sphere in the hoisting system, respectively. Acceleration is selected as the input u. r Therefore, u r =a r Dynamic constraints are used to describe the state changes of the circumscribed sphere's center. This invention selects the fourth-order Runge-Kutta method to characterize the relationship between the states of adjacent nodes:

[0095] x dynr,k+1 =x dynr,k +f RK (x dynr,k ,u r,k )·dt (6)

[0096] in, p r,k+1 and v r,k+1 These represent the positions of the circumscribed ball's center at time t. k+1 Position and velocity at any given moment. dt = t N / N represents the discrete time step, t N This represents the total time required to complete the constraint space traversal, and N represents the number of nodes.

[0097] 2) Driver constraints

[0098] Assume that during the constrained space traversal, the velocities and accelerations of the drone and payload are consistent with those of the center of the circumscribed sphere. Therefore, by limiting the velocity and acceleration of the center of the circumscribed sphere, the velocities and accelerations of the drone and payload can be constrained. To this end, the following constraints are established:

[0099] v min ≤v r,k ≤v max ,a min ≤a r,k ≤a max (7)

[0100] Among them, v min and v max Let a represent the minimum and maximum allowable ball center velocities, respectively. min and a max These represent the minimum and maximum allowable acceleration at the center of the sphere, respectively.

[0101] 3) Waypoint constraints

[0102] The center of the circumscribed sphere should pass through the track point, i.e., the center p of the constrained space, within a certain allowable error. wi Therefore, the following waypoint constraints are defined:

[0103]

[0104] in, Indicates at t k The allowable error when the time passes through the i-th track point.

[0105] Define process variables The process of traversing the constrained space is measured, where M represents the number of tracking waypoints, and κ... k Contains the i-th waypoint at t k Process state at any given moment This indicates that the center of the ball has passed the i-th waypoint. This indicates that the center of the ball has not yet passed the i-th waypoint. κ k The evolution process is as follows:

[0106] κ k+1 =κ k -γ k (9)

[0107] in, The process variable representing the i-th waypoint in time t k The change in time. To ensure that the hoisting system passes through the track points in the prescribed order (i.e., first passing through track point 1, then track point 2, and so on), the process variable should possess the following properties:

[0108]

[0109] Subsequently, the following complementary constraints are defined:

[0110]

[0111] The constraint in equation (11) is a strict hard constraint, meaning that the center of the circumscribed sphere of the hoisting system must pass through the track point. However, this constraint may lead to the failure of solving the optimization problem. Therefore, the constraint is appropriately modified to accommodate a certain degree of track point tolerance error. The modified constraint can be expressed as:

[0112]

[0113] Where δ represents the maximum allowable distance to pass through the i-th waypoint.

[0114] To efficiently complete the constrained space traversal task and transport the payload to the target location, the transport time needs to be included in the optimization variable. Therefore, the optimization variable can be expressed as x = [t]. N ,x0,...,x N ], where each node x i Including dynamic state x dynr,k Control input u r,k Process variable κ k and process change γk It should be noted that only the first N-1 nodes include the process variable κ. k and control input u r,k The Nth node only includes the dynamic state x. dynr,N and process variable κ N ,Right now

[0115]

[0116] Therefore, according to equations (5)-(13), the time-optimal hoisting system trajectory planning model for traversing constrained space can be established as follows:

[0117]

[0118] The trajectory of the center of the circumscribed sphere of the hoisting system can be obtained by solving the optimization problem (5). Next, based on the relative positional relationship between the center of the circumscribed sphere, the UAV, and the load, the trajectory of the hoisting system traversing the constrained space can be calculated.

[0119] Step 4: Guided by the constrained space traversal trajectory, quickly complete the load transportation task.

[0120] Experimental results

[0121] To verify the effectiveness of the trajectory planning method for the hoisting system under constrained space proposed in this invention, tests were conducted on a self-built flying hoisting system platform following the above procedure. Three quadcopter drones with a wheelbase of 330mm were selected, and a Pixhawk 4 flight controller was chosen. Each drone was equipped with an onboard Raspberry Pi computer. The position information of each drone and its payload was sent to the Pixhawk flight controller via a ROS topic through the Raspberry Pi. The Pixhawk processed the position information and the attitude information measured by the IMU to obtain the control input for each motor of the drone. The desired position and desired velocity information of each drone were obtained by sending a specific ROS topic from the ground station. The main physical parameters of the three-drone hoisting system are as follows:

[0122] m q1 =m q2 =m q3 =1.22kg,m o =0.41kg, l1=l2=l3=1.2m, g=9.8kg·m / s 2 .

[0123] The parameter settings for optimization problem (1) are as follows:

[0124] T i,min =0.1N,T i,max =10N,ρ w =0.5,ρv =0.5,d s = 1.1m.

[0125] The initial and desired load positions are [-0.50, -1.29, 0.60]. T m and [-0.20, 1.50, 0.84] T m, the center of the constraint space is located in [0.20, -0.10, 1.87]. T m and [-0.20, 0.50, 1.91] T Given a constrained space radius of 1.25m, the velocity and acceleration constraints of the circumscribed sphere of the hoisting system are as follows:

[0126]

[0127]

[0128] The relative positions of the circumscribed sphere's center with respect to the drone and payload are defined as follows:

[0129] p ro =p r -p o ,p r1 =p r -p1,p r2 =p r -p2,p r3 =p r -p3.

[0130] Table 1 shows the relative positions of the circumscribed sphere of the hoisting system, the UAV, and the load under the optimal crossing formation. Figures 2 to 7 The corresponding experimental results are presented. The position and velocity of the k-th drone are respectively x k ,y k ,z k and v xk ,v yk ,v zk The location of the load corresponds to x. o ,y o ,z o The solid lines represent the results of the proposed method, and the dashed lines represent the desired position / velocity. To visually illustrate the process of the hoisting system traversing the constrained space, top and side views of the system's (UAV and payload's) three-dimensional trajectory during the entire constrained space traversal are provided. It can be seen that the planning method proposed in this invention can drive the UAV safely through the constrained space while ensuring the payload is delivered to the desired target location.

[0131] Table 1. Relative positional relationship between the drone, payload, and the center of the circumscribed sphere.

[0132]

[0133] In summary, the present invention can generate a hoisting system traversing trajectory in a constrained space. This trajectory can ensure that the hoisting system does not collide with the constrained space, and can quickly transport the load to the target location. It can be applied to practical systems.

[0134] Example 2

[0135] This embodiment provides a constrained space crossing trajectory planning system for a multi-UAV collaborative hoisting system.

[0136] A constrained space traversal trajectory planning system for multi-UAV collaborative hoisting systems, including:

[0137] The first optimization module is configured to: construct an optimization model of the hoisting system's crossing formation under constrained space based on the polyhedral volume of the hoisting system and the tension of the hoisting rope, and obtain the optimal formation of the hoisting system crossing the constrained space;

[0138] The calculation module is configured to calculate the center and radius of the circumsphere of the hoisting system under the optimal formation for traversing the constrained space.

[0139] The second optimization module is configured to: construct a time-optimal trajectory planning model for the hoisting system traversing the constrained space based on the center and radius of the circumscribed sphere, considering dynamic constraints, actuator constraints, and waypoint constraints; and obtain the trajectory of the hoisting system traversing the constrained space by adopting the trajectory planning model for the hoisting system traversing the constrained space based on the relative positional relationship between the center of the circumscribed sphere, the UAV, and the load.

[0140] The task execution module is configured to complete the load delivery task under the guidance of the hoisting system's trajectory through the constrained space.

[0141] It should be noted that the first optimization module, calculation module, second optimization module, and task execution module described above are the same examples and application scenarios implemented in the steps of Embodiment 1, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the above modules, as part of a system, can be executed in a computer system such as a set of computer-executable instructions.

[0142] Example 3

[0143] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system as described in Embodiment 1 above.

[0144] Example 4

[0145] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system as described in Embodiment 1 above.

[0146] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0147] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0148] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0149] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0150] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0151] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for planning the trajectory of a multi-UAV collaborative hoisting system traversing constrained space, characterized in that, include: Based on the polyhedral volume of the hoisting system and the tension of the hoisting rope, an optimization model for the hoisting system's crossing formation under constrained space is constructed to obtain the optimal formation for the hoisting system to cross the constrained space. Calculate the center and radius of the circumsphere of the hoisting system under the optimal formation for traversing the constrained space; Based on the center and radius of the circumscribed sphere, and considering dynamic constraints, actuator constraints, and waypoint constraints, a time-optimal trajectory planning model for the hoisting system traversing constrained space is constructed. Based on the relative positional relationship between the center of the circumscribed sphere, the UAV, and the load, the trajectory of the hoisting system traversing constrained space is obtained using the trajectory planning model for the hoisting system traversing constrained space. Guided by the trajectory of the hoisting system traversing the constrained space, the load transportation task is completed; The optimization model for the hoisting system traversing the formation under the constrained space is as follows: in, Denotes the Euclidean norm. This represents the volume of the tetrahedron formed by the hoisting system. and They represent the first The location of the drone and its payload; The weight represents the total tension in the suspension ropes. and Used to weigh the two indicators and The importance of Indicates the first The length of the suspension rope, Indicates the safe distance between drones. and Indicates the tension of the suspension rope Scope For the mass of the load, Represents the gravitational constant. ; The waypoint constraint is that the center of the circumscribed sphere should pass through the waypoint within a certain allowable error, i.e., the center of the constraint space. Define the following waypoint constraints: in, Indicates in Time passed the first The allowable error for each waypoint Indicates the center of the circumference ball is at... The position at that moment; The time-optimal hoisting system trajectory planning model for traversing constrained space is as follows: in, This represents the total time required to complete the constraint space traversal. Indicates the number of nodes; and These represent the positions of the circumscribed ball's center and the center of the circumscribed ball. and The state at any given moment, Indicates the center of the circumference ball is at... acceleration at any moment and These represent the minimum and maximum permissible ball center velocities, respectively. and These represent the minimum and maximum allowable acceleration at the center of the sphere, respectively. Indicates the waypoint is at Process variables at any given time, Indicates the waypoint is at Process variables at any given time, The process variable representing the waypoint is in The changing of time, Indicates the first The process variables of each waypoint are in The changing of time, Indicates the first Each waypoint The process state at any given moment. Indicates the first +1 waypoint The process state at any given moment. Indicates the number of track points. Represents the center of the constrained space. Indicates the center of the circumference ball is at... Location at any given moment Indicates in Time passed the first The allowable error for each waypoint This indicates the maximum permissible error when passing through a track point.

2. The constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system according to claim 1, characterized in that, The optimal formation for the hoisting system to traverse the constrained space includes the position of each UAV and the position of the payload.

3. The constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system according to claim 1, characterized in that, The dynamic constraints are: The dynamics of the circumscribed sphere of the hoisting system are expressed as: in, and These represent the velocity and acceleration of the center of the sphere connected to the hoisting system, respectively; acceleration is selected as the input. Therefore, there is The state changes of the circumscribed sphere's center are described by the relationship between the states of adjacent nodes: in, , and These represent the positions of the circumscribed ball's center and the center of the circumscribed ball. Position and velocity at any given moment; Indicates the discrete time step. This represents the total time required to complete the constraint space traversal. Indicates the number of nodes; Indicates the center of the circumference ball is at... Acceleration at any moment.

4. The constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system according to claim 1, characterized in that, The driver constraint is: in, and These represent the minimum and maximum permissible ball center velocities, respectively. and These represent the minimum and maximum allowable acceleration at the center of the sphere, respectively.

5. A constrained space traversal trajectory planning system for a multi-UAV collaborative hoisting system, characterized in that, include: The first optimization module is configured to: construct an optimization model of the hoisting system's crossing formation under constrained space based on the polyhedral volume of the hoisting system and the tension of the hoisting rope, and obtain the optimal formation of the hoisting system crossing the constrained space; The calculation module is configured to calculate the center and radius of the circumsphere of the hoisting system under the optimal formation for traversing the constrained space. The second optimization module is configured to: construct a time-optimal trajectory planning model for the hoisting system traversing the constrained space based on the center and radius of the circumscribed sphere, considering dynamic constraints, actuator constraints, and waypoint constraints; and obtain the trajectory of the hoisting system traversing the constrained space by adopting the trajectory planning model for the hoisting system traversing the constrained space based on the relative positional relationship between the center of the circumscribed sphere, the UAV, and the load. The task execution module is configured to complete the load delivery task under the guidance of the trajectory of the hoisting system traversing the constrained space; The optimization model for the hoisting system traversing the formation under the constrained space is as follows: in, Denotes the Euclidean norm. This represents the volume of the tetrahedron formed by the hoisting system. and They represent the first The location of the drone and its payload; The weight represents the total tension in the suspension ropes. and Used to weigh the two indicators and The importance of Indicates the first The length of the suspension rope, Indicates the safe distance between drones. and Indicates the tension of the suspension rope Scope For the mass of the load, Represents the gravitational constant. ; The waypoint constraint is that the center of the circumscribed sphere should pass through the waypoint within a certain allowable error, i.e., the center of the constraint space. Define the following waypoint constraints: in, Indicates in Time passed the first The allowable error for each waypoint Indicates the center of the circumference ball is at... The position at that moment; The time-optimal hoisting system trajectory planning model for traversing constrained space is as follows: in, This represents the total time required to complete the constraint space traversal. Indicates the number of nodes; and These represent the positions of the circumscribed ball's center and the center of the circumscribed ball. and The state at any given moment, Indicates the center of the circumference ball is at... acceleration at any moment and These represent the minimum and maximum permissible ball center velocities, respectively. and These represent the minimum and maximum allowable acceleration at the center of the sphere, respectively. Indicates the waypoint is at Process variables at any given time, Indicates the waypoint is at Process variables at any given time, The process variable representing the waypoint is in The changing of time, Indicates the first The process variables of each waypoint are in The changing of time, Indicates the first Each waypoint The process state at any given moment. Indicates the first +1 waypoint The process state at any given moment. Indicates the number of track points. Represents the center of the constrained space. Indicates the center of the circumference ball is at... Location at any given moment Indicates in Time passed the first The allowable error for each waypoint This indicates the maximum permissible error when passing through a track point.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system as described in any one of claims 1-4.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the constrained space traversal trajectory planning method for a multi-UAV cooperative hoisting system as described in any one of claims 1-4.

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