Propulsion layout optimization design method for agile underwater robot

Abstract

The invention belongs to the technical field of underwater robots, and particularly relates to a propulsion layout optimization design method of an agile underwater robot, which comprises the following steps of: S1, establishing models of various performance indexes of the ROV about the pose of a propeller, and obtaining three main parameters omega, M and E which influence the performance of the underwater robot, m is the maximum thrust of the underwater robot, and E is the overall efficiency of the robot; and S2, obtaining a unified parameter y for measuring the performance of the underwater robot, and carrying out design optimization by utilizing an optimization algorithm based on the relationship between the evaluation indexes and the design parameters so as to achieve the purpose of finally optimizing the performance index y. According to the underwater robot design method based on the rejection evolutionary algorithm, systematized and personalized optimization design can be carried out for complex underwater robot operation tasks.

Description

Technical Field

[0001] The invention belongs to the technical field of underwater robots, and in particular relates to a propulsion layout optimization design method for an agile underwater robot. Background Art

[0002] In recent years, with the rapid growth of marine resource development, environmental monitoring, scientific research and national defense needs, underwater remotely operated vehicle (ROV) technology has received widespread attention and rapid development. As an underwater operation tool controlled by a mother ship, ROV has gradually occupied an important position in deep-sea exploration, seabed construction, pipeline inspection, salvage operations and other fields due to its high efficiency, flexibility and safety. Especially in the development of deep-sea resources, ROV is widely used to complete high-risk underwater tasks that are difficult for humans to carry out directly.

[0003] As one of the key technologies of ROV, thruster layout design has a significant impact on its control performance, energy efficiency and mission adaptability. The current ROV thruster layout design mostly adopts empirical layout or limited optimization, which often fails to take into account the multi-task requirements in complex marine environments. How to achieve higher control stability, lower energy consumption and better environmental adaptability through optimized design has become an important research direction for the development of ROV technology.

[0004] At present, the ROV thruster layout design optimization methods mainly include experience-based layout design and numerical simulation-assisted design.

[0005] The experience-based thruster layout design method usually relies on the designer's practical accumulation and existing ROV cases, and determines the number, type and layout of the thrusters according to the mission requirements. This type of design often adopts a symmetrical layout or a fixed array layout, such as evenly distributing the thrusters around the ROV frame to provide balanced thrust or achieve basic control functions. Early ROVs, such as the "Jason" series, adopted a cross-shaped symmetrical layout and successfully achieved 6-DOF motion control. This method is suitable for shallow water or low-cost mission environments, with simple design and low implementation cost. However, its optimization space is limited and it is difficult to cope with complex mission requirements. At the same time, due to the lack of precise calculations, the interference effect between thrusters may lead to a reduction in thrust efficiency.

[0006] The numerical simulation method can accurately evaluate the thrust distribution, hydrodynamic interference and overall control performance under different layouts by constructing a three-dimensional model of the thruster layout and using computational fluid dynamics (CFD) to perform flow field analysis. The simulation results can be used to optimize the thruster position and angle to improve the control stability of the ROV under different working conditions. For example, CFD simulation can reveal the vortex effect between thrusters and provide data support for reducing energy consumption and thrust loss. In addition, multi-body dynamics simulation can analyze the posture changes of the ROV during movement and provide guidance for layout adjustment. Although the numerical simulation method is accurate and reliable, its calculation time is long and the design cycle is limited by simulation resources, especially under high-precision simulation requirements. Summary of the invention

[0007] In order to solve the problems in the related art, the present application provides a propulsion layout optimization design method for an agile underwater robot, which solves the defects mentioned in the background technology.

[0008] The technical solution is as follows:

[0009] A method for optimizing the propulsion layout of an agile underwater robot comprises the following steps:

[0010] S1. Establish a model of the thruster posture of each ROV performance index to obtain the three main parameters ω, M and E that affect the performance of the underwater robot, where ω is the maneuverability of the underwater robot, M is the maximum thrust of the underwater robot, and E is the overall efficiency of the robot;

[0011] S2. Obtain a unified parameter y for measuring the performance of underwater robots:

[0012] y=α1ω+α2M+α3E

[0013] Based on the relationship between the above evaluation indicators and the design parameters, the optimization algorithm is used to optimize the design to achieve the optimal final performance indicator y.

[0014] In a further technical solution, step S1 includes:

[0015] The manipulability of underwater robots is as follows:

[0016]

[0017] Where K is the underwater robot power distribution matrix, which defines the relationship between the thrust of each propeller and the resultant external force (torque) on the underwater robot, as follows:

[0018] τ=Kf

[0019] Where f is the thrust of all thrusters, and τ is the total external force (torque) acting on the underwater robot.

[0020] In a further technical solution, step S1 further includes:

[0021] The maximum thrust M of the underwater robot can be calculated by the following steps:

[0022] M=M fx ×M fy ×M fz

[0023] Among them, M fx ,M fy ,M fz is the maximum thrust (torque) of the robot in all directions. Any of these indicators can be obtained by calculating the following linear optimization problem:

[0024]

[0025] subject to Ax≤b and Aeq·x=beq;

[0026] Among them, x is the output vector and a is the vector that defines the calculation direction.

[0027] In a further technical solution, step S1 further includes:

[0028] In any direction j, the force efficiency of the underwater robot is defined as

[0029]

[0030] Where m is the number of robot thrusters, f ji The thrust of each thruster required to produce a unit thrust in the corresponding direction, and the efficiency of the force is ultimately the product of the three directions.

[0031]

[0032] Similarly, the torque efficiency can be calculated as

[0033]

[0034] The overall efficiency E of the robot is:

[0035] E=E f ×E τ

[0036] Use the formula to calculate the overall efficiency E of the robot.

[0037] By adopting the above technical solution, compared with the prior art, the beneficial effects of the technology of this patent are:

[0038] 1. The underwater robot design method based on the exclusion evolution algorithm of the present invention can perform systematic and personalized optimization design for complex underwater robot operation tasks. The present invention can comprehensively consider the robot's maneuverability, maximum thrust, and propulsion efficiency to perform multi-objective optimization design.

[0039] 2. The underwater robot thruster design optimization algorithm proposed in the present invention can systematically design the underwater robot thruster posture for specific mission scenarios, thereby improving the design efficiency of the underwater robot. At the same time, the adopted design method can also improve the comprehensive motion performance of the designed robot, thereby greatly improving underwater detection and operation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0041] Figure 1 It is an optimization graph of the negative number (-y) of the robot's performance as the optimization iterations in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The preferred embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0043] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0044] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0045] An optimization design method for the propulsion layout of an agile underwater robot is proposed. The position and posture of each thruster are used as design parameters. Aiming at complex underwater operation tasks, the performance indicators of the underwater robot, such as maximum thrust (torque), maneuverability and propulsion efficiency, are comprehensively optimized.

[0046] First, the model of ROV performance indicators related to thruster posture is established, as follows:

[0047] Underwater robot maneuverability

[0048]

[0049] Where K is the underwater robot power distribution matrix, which defines the relationship between the thrust of each propeller and the resultant external force (torque) on the underwater robot, as follows:

[0050] τ=Kf

[0051] Where f is the thrust of the eight thrusters, and τ is the resultant external force (torque) acting on the underwater robot.

[0052] The maximum thrust M of the underwater robot is calculated by the following steps:

[0053] M=M fx ×M fy ×M fz

[0054] Among them, M fx ,M fy ,M fz is the maximum thrust (torque) of the robot in all directions. Any of these indicators can be obtained by calculating the following linear optimization problem:

[0055]

[0056] subject to Ax≤b and Aeq·x=beq

[0057] Where x is the output vector and a is the vector that defines the calculation direction.

[0058] In any direction j, the force efficiency of the underwater robot is defined as

[0059]

[0060] Where m is the number of robots pushing machines, f ji The thrust of each thruster required to produce a unit thrust in the corresponding direction, and the efficiency of the force is ultimately the product of the three directions.

[0061] Similarly, the torque efficiency can be calculated as

[0062] The overall efficiency of the robot is:

[0063] E=E f ×E τ

[0064] Through the above calculation formula, the three main parameters ω, M and E that affect the performance of the underwater robot are obtained.

[0065] By taking their weighted sum, we can obtain a unified parameter y to measure the performance of the underwater robot:

[0066] y=α1ω+α2M+α3E

[0067] Based on the relationship between the above evaluation indicators and the design parameters, the optimization algorithm is used to optimize the design to achieve the optimal final performance indicator y.

[0068] Since the underwater robot contains 6 or more thrusters, the position of each thruster will introduce 2 design parameters. This design problem with multiple design parameters often causes the optimal solution finally obtained to fall into the dilemma of local optimality. Therefore, the present invention adopts the exclusion evolution algorithm to solve this problem. The exclusion evolution algorithm is an optimization algorithm based on biological evolution theory and introduces the exclusion mechanism, which aims to enhance the diversity and exploration ability of the population through the exclusion effect between individuals.

[0069] The optimization mechanism of this algorithm adds repulsive behavior between individuals on the basis of traditional evolutionary operations (such as selection, crossover, and mutation): when two individuals are close to each other in the search space, repulsive effects will occur, thus pushing them to move to different areas.

[0070] This mechanism effectively prevents the population from gathering near the local optimal solution and improves the global search capability.

[0071] In addition, the repulsion strength is usually related to the distance, and a balance can be achieved between population diversity and convergence speed by dynamically adjusting the repulsion parameters, making it suitable for multimodal optimization problems and high-dimensional complex problems.

[0072] like Figure 1 As shown, this embodiment adopts the optimization algorithm, and we can significantly improve the performance of the underwater robot. Taking the common eight-thruster as an example, facing the same optimization index, the conventional symmetrical distribution y=0.74 relying on common sense, and the y=2.20 obtained by the optimization algorithm can significantly improve the performance of the underwater robot.

[0073] This method establishes a calculation model for the maneuverability, maximum thrust and efficiency of the underwater robot and proposes a unified performance index parameter to evaluate the design optimization effect of the underwater robot.

[0074] Based on the obtained unified performance index parameters and their calculation model, a multi-objective design optimization method for underwater robots is established in combination with the exclusion evolutionary algorithm.

[0075] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not covered by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0076] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A propulsion layout optimization design method for an agile underwater robot, characterized in that: The following steps are involved: S1. Establish a model of the thruster posture of each ROV performance index to obtain the three main parameters ω, M and E that affect the performance of the underwater robot, where ω is the maneuverability of the underwater robot, M is the maximum thrust of the underwater robot, and E is the overall efficiency of the robot; S2. Obtain a unified parameter y for measuring the performance of underwater robots: y=α1ω+α2M+α3E Based on the relationship between the above evaluation indicators and the design parameters, the optimization algorithm is used to optimize the design to achieve the optimal final performance indicator y.

2. The method for optimizing the propulsion layout of an agile underwater robot according to claim 1, characterized in that: Step S1 includes: The manipulability of underwater robots is as follows: Where K is the underwater robot power distribution matrix, which defines the relationship between the thrust of each propeller and the resultant external force (torque) on the underwater robot, as follows: τ=Kf Where f is the thrust of all thrusters, and τ is the total external force (torque) acting on the underwater robot.

3. The method for optimizing the propulsion layout of an agile underwater robot according to claim 1, characterized in that: Step S1 also includes: The maximum thrust M of the underwater robot can be calculated by the following steps: M=M fx ×M fy ×M fz Among them, M fx ,M fy ,M fz is the maximum thrust (torque) of the robot in all directions. Any of these indicators can be obtained by calculating the following linear optimization problem: subject to Ax≤b and Aeq·x=beq; Among them, x is the output vector and a is the vector that defines the calculation direction.

4. The method for optimizing the propulsion layout of an agile underwater robot according to claim 1, characterized in that: Step S1 also includes: In any direction j, the force efficiency of the underwater robot is defined as Where m is the number of robot thrusters, f ji The thrust of each thruster required to produce a unit thrust in the corresponding direction, and the efficiency of the force is ultimately the product of the three directions. Similarly, the torque efficiency can be calculated as The overall efficiency E of the robot is: E=E f ×And τ Use the formula to calculate the overall efficiency E of the robot.

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