An obstacle avoidance control method for underwater robots based on fuzzy artificial potential field technology

Abstract

The present invention provides an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology, wherein the method comprises: determining a current position, a current speed, an obstacle position and an obstacle speed; determining a desired target position based on the current position, the current speed, the obstacle position and the obstacle speed; based on the fuzzy artificial potential field, applying the current position, the current speed, the obstacle position, the obstacle speed and the desired target position to determine a planned obstacle avoidance path to reach the desired target position; based on the planned obstacle avoidance path, applying sliding mode control to perform real-time control to reach the desired target position. The method determines the planned obstacle avoidance path from the current position to the desired target position through the fuzzy artificial potential field, completes the obstacle avoidance task through sliding mode control, overcomes the influence of the obstacle movement on the movement of the underwater robot, realizes the obstacle avoidance task of static obstacles and dynamic obstacles at the same time, and thus improves the effect of the obstacle avoidance task in the underwater variable environment.

Description

Technical Field

[0001] The invention relates to the field of automatic control technology, and in particular to an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology. Background Art

[0002] With the advancement of science and technology, human exploration of the ocean has gradually increased. Due to uncertain factors such as boulders, fish schools and sunken ships in the ocean environment, the operation of underwater robots will be affected, causing collision damage to underwater robots. Therefore, improving the autonomous obstacle avoidance planning and rapid response capabilities of underwater robots has become an important vision of current underwater robot research.

[0003] At present, the obstacle avoidance task for underwater robots is mainly studied in one of the two scenarios: static obstacles or dynamic obstacles, and most of the research is on static obstacles. However, the underwater environment is changeable, and the existing single-scenario obstacle avoidance task cannot cope with the changeable underwater environment, and thus the effect of the underwater robot's obstacle avoidance task in the real underwater environment is not ideal. Summary of the invention

[0004] The present invention provides an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology, which is used to solve the defect in the prior art that the underwater robot has unsatisfactory obstacle avoidance task effect when dealing with a changeable underwater environment.

[0005] The present invention provides an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology, comprising:

[0006] Determine the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed;

[0007] Determining a desired target position based on the current underwater robot position, the current underwater robot speed, the obstacle position, and the obstacle speed;

[0008] Based on a fuzzy artificial potential field, applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position, determining a planned obstacle avoidance path to reach the desired target position; the fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field;

[0009] Based on the planned obstacle avoidance path, sliding mode control is applied to control the underwater robot in real time to reach the desired target position.

[0010] According to an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the present invention, based on the fuzzy artificial potential field, the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the expected target position are applied to determine a planned obstacle avoidance path to reach the expected target position, including:

[0011] Based on the repulsive potential field, applying a preset safety distance, a preset repulsive coefficient, the current underwater robot position, the obstacle position and the desired target position, determining a repulsive component force for preventing collision and a repulsive component force for preventing falling into a local minimum;

[0012] Based on the fuzzy attraction potential field, a preset attraction coefficient, the current underwater robot position and the expected target position are applied to determine the expected attraction force, and based on the fuzzy attraction compensation potential field in the fuzzy attraction potential field, the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed are applied to determine the attraction compensation force;

[0013] Determine a repulsive resultant force based on the anti-collision repulsive force and the anti-falling into local minimum repulsive force, and determine an attractive resultant force based on the expected attractive force and the attractive compensation force;

[0014] The planned obstacle avoidance path is determined based on the repulsive resultant force and the attractive resultant force.

[0015] According to an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the present invention, the calculation formula of the repulsive force is as follows:

[0016]

[0017]

[0018]

[0019] In the formula, F r is the repulsive force, F r1 is the anti-collision repulsion force, F r2 To prevent falling into the local minimum repulsive force, U r is the repulsive potential field function, k r is the preset repulsion coefficient, ρ is the minimum distance between the underwater robot and the obstacle, and ρ c is the current position of the underwater robot, ρ0 is the preset safety distance, ρ d is the expected target position, and n is a positive integer greater than 0.

[0020] According to an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the present invention, the calculation formula of the attraction resultant force is as follows:

[0021]

[0022]

[0023] Where U a is the fuzzy attractive potential field function, is the attractive potential field of the desired target position, U a_cir is the fuzzy attraction compensation potential field function, k a is the preset attraction coefficient, ρ c is the current position of the underwater robot, ρ d is the desired target position, F a is the attractive force, F a_cir is the attraction compensation force, V cir is the obstacle speed, y′ is the speed component of the current underwater robot speed in the direction of the obstacle speed, and Δx is the distance between the underwater robot and the obstacle position in the direction perpendicular to the obstacle speed.

[0024] According to an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the present invention, based on the planned obstacle avoidance path, the underwater robot is controlled in real time by applying sliding mode control to reach the desired target position, including:

[0025] Based on a non-singular terminal sliding mode controller, the control input force and torque are determined by applying the system state, the expected state and the preset underwater robot dynamic expression; the non-singular terminal sliding mode controller is determined based on the inverse tangent sliding mode surface and the sliding mode reaching law; the inverse tangent sliding mode surface is determined based on the inverse tangent trigonometric function and the auxiliary variable;

[0026] Based on the control input force and torque, a nonlinear mapping relationship between the preset control input force and torque and the control parameters of the flippers is applied to determine the control parameters of the flippers; the control parameters include an initial offset angle, a flapping frequency and a flapping amplitude;

[0027] Based on the planned obstacle avoidance path, the control parameters of the flippers are applied to perform real-time control to reach the desired target position.

[0028] According to an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the present invention, the non-singular terminal sliding mode controller is determined based on the following steps:

[0029] Based on the inverse tangent trigonometric function, the inverse tangent sliding surface is designed, and the inverse tangent sliding surface is expressed as:

[0030]

[0031] Where s is the inverse tangent sliding surface, x1 is the system state, x2 is the derivative of the system state x1, β, p and q are the auxiliary variables, where β>0, p and q are odd numbers and arctan is the introduced inverse tangent trigonometric function;

[0032] Based on the inverse tangent sliding surface and the sliding mode reaching law, the non-singular terminal sliding mode controller is designed. The sliding mode reaching law is expressed as:

[0033]

[0034] The non-singular terminal sliding mode controller is expressed as:

[0035]

[0036]

[0037] In the formula, is the sliding mode reaching law, k and eta are positive numbers, sgn is the sign function, η is the system state, is the first-order derivative of the system state, is the second-order derivative of the system state, η d is the desired state, is the second-order derivative of the desired state, is the mass matrix, is the preset underwater robot dynamics expression, are the control input forces and moments, is the external disturbance, e=η d -η is the state error vector.

[0038] The present invention also provides an underwater robot obstacle avoidance control device based on fuzzy artificial potential field technology, comprising:

[0039] A determination module is used to determine the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed;

[0040] A desired target determination module, used to determine the desired target position based on the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed;

[0041] A route planning module, for determining a planned obstacle avoidance path to reach the desired target position based on a fuzzy artificial potential field, applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position; the fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field;

[0042] The control module is used to control the underwater robot in real time based on the planned obstacle avoidance path by applying sliding mode control to reach the desired target position.

[0043] The present invention also provides an underwater robot obstacle avoidance control system based on fuzzy artificial potential field technology, comprising: a global vision system and an underwater robot; the underwater robot comprises: flippers and the underwater robot obstacle avoidance control device based on fuzzy artificial potential field technology;

[0044] in,

[0045] The global vision system is used to identify the underwater robot and the obstacle, determine the current position of the underwater robot and the obstacle, and calculate the current speed of the underwater robot and the speed of the obstacle by using a differential tracking method;

[0046] The fins are used to execute the control force and torque output by the underwater robot obstacle avoidance control device based on fuzzy artificial potential field technology to drive the underwater robot to move.

[0047] The present invention also provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned underwater robot obstacle avoidance control methods based on fuzzy artificial potential field technology.

[0048] The underwater robot obstacle avoidance control method, device and underwater robot based on fuzzy artificial potential field technology provided by the present invention obtain the desired target position through the current position and speed of the underwater robot and the position and speed of the obstacle, and determine the planned obstacle avoidance path from the current position of the underwater robot to the desired target position based on the fuzzy artificial potential field, and complete the obstacle avoidance task through sliding mode control, overcoming the influence of obstacle movement on the obstacle avoidance ability of the underwater robot, and realizing the obstacle avoidance task of static obstacles and dynamic obstacles at the same time, thereby improving the effect of obstacle avoidance tasks in underwater changeable environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 It is a flow chart of an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the present invention;

[0051] Figure 2 It is a flow chart of the method for obtaining a planned obstacle avoidance path provided by the present invention;

[0052] Figure 3 It is a schematic diagram of the force information on the underwater robot generated by the repulsive field and the fuzzy attractive potential field provided by the present invention;

[0053] Figure 4 It is a flow chart of the sliding mode real-time control method provided by the present invention;

[0054] Figure 5 It is a comparison curve diagram of the position change simulation of the underwater robot provided by the present invention under the control of the inverse tangent sliding mode controller and the traditional sliding mode controller;

[0055] Figure 6 It is a structural schematic diagram of an underwater robot obstacle avoidance control device based on fuzzy artificial potential field technology provided by the present invention;

[0056] Figure 7 It is a structural schematic diagram of an underwater robot obstacle avoidance control system based on fuzzy artificial potential field technology provided by the present invention;

[0057] Figure 8 It is a curve diagram of the change of the position and heading angle of the underwater robot when avoiding a stationary obstacle provided by the present invention;

[0058] Fig. 9 It is a curve diagram of the change of the control output force and torque of the inverse tangent sliding mode controller provided by the present invention when avoiding a stationary obstacle;

[0059] Fig.10 It is a curve diagram of the change of the position and heading angle of the underwater robot when avoiding a unidirectional moving obstacle provided by the present invention;

[0060] Fig.11 It is a curve diagram of the change of the position and heading angle of the underwater robot when avoiding a reciprocating obstacle provided by the present invention. DETAILED DESCRIPTION

[0061] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0062] At present, the obstacle avoidance task for underwater robots is mainly studied in one of the two scenarios: static obstacles or dynamic obstacles, and most of the research is on static obstacles. However, the underwater environment is changeable, and the existing single-scenario obstacle avoidance task cannot cope with the changeable underwater environment, and thus the effect of the underwater robot's obstacle avoidance task in the real underwater environment is not ideal.

[0063] Therefore, how to cope with the changing underwater environment and simultaneously deal with static and dynamic obstacles is a technical problem that needs to be solved urgently by those skilled in the art.

[0064] In view of the above technical problems, an embodiment of the present invention provides an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology. Figure 1 FIG. 1 is a flow chart of an underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the present invention. Figure 1 As shown, the method includes:

[0065] Step 110, determining the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed;

[0066] It should be noted that the current position of the underwater robot can be obtained in real time based on positioning systems such as GPS, Beidou or global cameras, the position of obstacles can be obtained in real time based on global cameras, sonar or multi-beam sensors, etc., and the current speed of the underwater robot and the speed of obstacles can be calculated in real time based on differential tracking algorithms, and the embodiments of the present invention do not limit this. In addition, the obstacle can be an annular obstacle and the underwater robot can pass through the annular area. The current position of the underwater robot, the current speed of the underwater robot, the position of obstacles and the speed of obstacles can all be completed based on a preset coordinate system, which can be preset by the positioning system or preset by the host computer, and the embodiments of the present invention do not limit this.

[0067] Step 120, determining a desired target position based on the current underwater robot position, the current underwater robot speed, the obstacle position, and the obstacle speed;

[0068] Specifically, when the obstacle speed is 0, that is, the state of the obstacle is stationary, the expected target position can be directly determined according to the position of the obstacle. When the obstacle speed is greater than 0, that is, the state of the obstacle is moving, the target position at the current moment is determined according to the obstacle position, and the expected target position is calculated according to the current underwater robot position, the current underwater robot speed, the target position at the current moment and the obstacle speed.

[0069] It should be noted that if the obstacle is stationary, the expected target position can be the geometric center point of the annular obstacle. If the obstacle is moving, the moving straight line of the obstacle can be determined according to the obstacle position and the obstacle speed, and the moving straight line of the underwater robot can be determined according to the current underwater robot position and the current underwater robot speed. The geometric center point of the annular obstacle is used to determine the expected target position, and the embodiments of the present invention are not limited to this.

[0070] Step 130, based on the fuzzy artificial potential field, applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the expected target position, determine the planned obstacle avoidance path to reach the expected target position; the fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field;

[0071] Taking into account the complex underwater environment, the relationship between the underwater robot's speed and the obstacle position will become very complicated, resulting in poor results in the obstacle avoidance task. Therefore, in order to overcome the influence of obstacle movement on the underwater robot's obstacle avoidance ability, the embodiment of the present invention introduces a fuzzy artificial potential field of a fuzzy attractive potential field function, so that when the underwater robot approaches an obstacle, the underwater robot can quickly change direction and move to the desired target position.

[0072] Specifically, the repulsive potential field and the fuzzy attractive potential field in the fuzzy artificial potential field are respectively the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the expected target position, and the repulsive force and the attractive force are obtained, and the obstacle avoidance path is planned according to the repulsive force and the attractive force. Among them, the attractive force is obtained by the attractive potential field of the expected position and the fuzzy attractive compensation potential field.

[0073] It should be noted that the fuzzy attraction compensation potential field can determine the attraction compensation force in the direction of the desired target position based on the speed difference between the velocity component in the velocity direction of the underwater robot and the obstacle, and the relative distance between the distance component in the direction perpendicular to the velocity direction of the underwater robot and the obstacle, so that the underwater robot can quickly change direction and move to the desired target position.

[0074] Step 140 , based on the planned obstacle avoidance path, sliding mode control is applied to control the underwater robot in real time to reach the desired target position.

[0075] Specifically, real-time control is performed through sliding mode control to move to the desired target position along the planned obstacle avoidance path.

[0076] It should be noted that the sliding mode control can be a sliding mode controller designed based on a conventional sliding surface, or a sliding mode controller designed based on a sliding surface determined by an inverse tangent trigonometric function. The control parameters of the drive device are determined by the control input force and torque output by the sliding mode controller to complete the propulsion of the underwater robot.

[0077] The underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the embodiment of the present invention obtains the desired target position through the current position and speed of the underwater robot, as well as the position and speed of the obstacle, and determines the planned obstacle avoidance path from the current position of the underwater robot to the desired target position based on the fuzzy artificial potential field, and completes the obstacle avoidance task through sliding mode control, overcoming the influence of obstacle movement on the obstacle avoidance ability of the underwater robot, and realizing the obstacle avoidance task of both static obstacles and dynamic obstacles at the same time, thereby improving the effect of obstacle avoidance tasks in underwater changeable environments.

[0078] Based on the above embodiments, Figure 2 FIG. 1 is a flow chart of the method for obtaining a planned obstacle avoidance path provided by the present invention. Figure 2 As shown, step 130 includes:

[0079] Step 131, based on the repulsive potential field, applying the preset safety distance, the preset repulsive coefficient, the current underwater robot position, the obstacle position and the expected target position, determine the repulsive component force to prevent collision and the repulsive component force to prevent falling into the local minimum;

[0080] Step 132, based on the fuzzy attraction potential field, applying the preset attraction coefficient, the current underwater robot position and the expected target position, determining the expected attraction force, and based on the fuzzy attraction compensation potential field in the fuzzy attraction potential field, applying the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed, determining the attraction compensation force;

[0081] Step 133, determining a repulsive resultant force based on the anti-collision repulsive force and the anti-falling into local minimum repulsive force, and determining an attractive resultant force based on the expected attractive force and the attractive compensation force;

[0082] Step 134, based on the repulsive force and the attractive force, determine the planned obstacle avoidance path.

[0083] Considering that the artificial potential field is prone to produce local minimum points, resulting in the failure of the obstacle avoidance task, the present invention solves the problem of possibly falling into the local minimum by adding the distance between the expected target position and the current position of the underwater robot in the repulsive potential field.

[0084] Specifically, according to the current position of the underwater robot and the position of the obstacle, the distance from the current position of the underwater robot to the obstacle is determined, and according to the current position of the underwater robot and the expected target position, the distance from the current position of the underwater robot to the expected target position is determined. The repulsive potential field calculates the repulsive force to prevent collision and the repulsive force to prevent falling into the local minimum according to the preset safety distance, the preset repulsive coefficient, the distance from the current position of the underwater robot to the obstacle, and the distance from the current position of the underwater robot to the expected target position, and the repulsive force to prevent falling into the local minimum is calculated respectively, and the repulsive resultant force is calculated by the repulsive force to prevent collision and the repulsive force to prevent falling into the local minimum.

[0085] According to the direction of the obstacle speed, the speed difference between the speed component of the current underwater robot position speed in this direction and the speed of the obstacle is determined. According to the direction perpendicular to the obstacle speed direction, the relative distance between the current underwater robot position and the obstacle position in the direction is determined. The fuzzy attraction potential field calculates the expected attraction based on the preset attraction coefficient and the distance from the current underwater robot position to the expected target position. The fuzzy attraction compensation potential field in the fuzzy attraction potential field determines the attraction compensation force based on the above speed difference and relative distance, and determines the attraction resultant force based on the expected attraction and the attraction compensation force. Finally, the obstacle avoidance path is planned based on the repulsion resultant force and the attraction resultant force.

[0086] It should be noted that the fuzzy attraction compensation potential field, according to the above speed difference and relative distance, determines the attraction compensation force through the reasoning rules in the fuzzy reasoning table, where the fuzzy reasoning table is shown in the following table:

[0087]

[0088] In the table, NB, NS, Z, PZ, PS, PM, PMB, and PB represent negative large, negative small, zero, positive zero, positive small, positive medium, positive medium large, and positive large, respectively. The fuzzy attraction compensation potential field uses the standard triangle as the membership degree and the centroid method for fuzzy reasoning.

[0089] on the other hand, Figure 3 Schematic diagram of the force information on the underwater robot generated by the repulsive field and the fuzzy attractive potential field provided by the present invention. Figure 3 As shown in the figure, the obstacle is a circular obstacle, that is, the expected target position is the center of the obstacle, and the obstacle is the annular edge of the circular obstacle. The repulsive field and the fuzzy attractive potential field interact with the underwater robot, and the direction of the final path planning is given based on the final resultant force information, where F a To attract the combined force, F r1 To prevent the collision repulsion force, F r2 To prevent the repulsive force from falling into the local minimum, V cir is the obstacle speed, Fa_cir To attract compensation force.

[0090] Based on the above embodiment, the calculation formula of the repulsive force is as follows:

[0091]

[0092]

[0093]

[0094] In the formula, F r is the repulsive force, F r1 To prevent the collision repulsion force, F r2 In order to avoid falling into the local minimum repulsive force, U r is the repulsive potential field function, k r is the preset repulsion coefficient, ρ is the minimum distance between the underwater robot and the obstacle, and ρ c is the current position of the underwater robot, ρ0 is the preset safety distance, ρ d is the expected target position, and n is a positive integer greater than 0.

[0095] Based on the above embodiment, the calculation formula of the attraction resultant force is as follows:

[0096]

[0097]

[0098] Where U a is the fuzzy attractive potential field function, is the attractive potential field of the desired target position, U a_cir is the fuzzy attraction compensation potential field function, k a is the preset attraction coefficient, ρ c is the current position of the underwater robot, ρ d is the desired target position, F a To attract the combined force, F a_cir To attract the compensation force, V cir is the obstacle speed, y′ is the velocity component of the current underwater robot speed in the direction of the obstacle speed, and Δx is the distance between the underwater robot and the obstacle position in the direction perpendicular to the obstacle speed.

[0099] Based on the above embodiments, Figure 4 Schematic diagram of the flow of the sliding mode real-time control method provided by the present invention. Figure 4 As shown, step 140 includes:

[0100] Step 141, based on a non-singular terminal sliding mode controller, applying the system state, the desired state and the preset underwater robot dynamic expression, the control input force and torque are determined; the non-singular terminal sliding mode controller is determined based on the inverse tangent sliding mode surface and the sliding mode reaching law; the inverse tangent sliding mode surface is determined based on the inverse tangent trigonometric function and the auxiliary variable;

[0101] Step 142, based on the control input force and torque, applying the nonlinear mapping relationship between the preset control force and torque and the control parameters of the flippers, determining the control parameters of the flippers; the control parameters include an initial offset angle, a flapping frequency, and a flapping amplitude;

[0102] Step 143, based on the planned obstacle avoidance path, the control parameters of the flippers are applied to perform real-time control to reach the desired target position.

[0103] Considering that when the underwater robot performs an obstacle avoidance task, if the sliding mode control can reach a stable state faster, the corresponding obstacle avoidance operation can be performed faster based on the current speed and position of the obstacle, thereby improving the effect of the obstacle avoidance task. Therefore, the embodiment of the present invention performs sliding mode control by introducing an inverse tangent sliding surface determined by an inverse tangent trigonometric function and a non-singular terminal sliding mode controller designed by the inverse tangent sliding surface.

[0104] Specifically, an inverse tangent sliding surface is first constructed according to the inverse tangent trigonometric function and auxiliary variables, and a non-singular terminal sliding mode controller is constructed according to the inverse tangent sliding surface and the sliding mode reaching law. Then, the non-singular terminal sliding mode controller obtains and outputs the control input force and torque according to the system state, the expected state and the preset underwater robot dynamic expression, and obtains the control parameters of the flippers corresponding to the control input force and torque output by the non-singular terminal sliding mode controller according to the nonlinear mapping relationship between the control force and torque and the control parameters of the flippers established according to the preset fuzzy inference rule table, and the control parameters of the flippers are applied for real-time control, so that the underwater robot moves along the planned obstacle avoidance path and reaches the expected target position. Among them, the control parameters include the initial offset angle, the flapping frequency and the flapping amplitude. In addition, the auxiliary variables used when constructing the inverse tangent sliding surface are preset, and the auxiliary variables can be one or more, which is not limited in the embodiment of the present invention. The sliding mode reaching law can be a constant speed reaching law, an exponential reaching law, a power reaching law, etc., or a reaching law designed based on the inverse tangent sliding surface, which is not limited in the embodiment of the present invention. The system state includes: the current underwater robot position and the current underwater robot yaw angle; the expected state includes: the expected target position and the expected yaw angle.

[0105] The underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by an embodiment of the present invention reduces the movement time of the system state on the sliding surface by introducing the inverse tangent sliding surface determined by the inverse tangent trigonometric function, converges to the desired state more quickly, and realizes faster corresponding obstacle avoidance operations based on the current speed and position of the obstacle, thereby improving the effect of the obstacle avoidance task.

[0106] Based on the above embodiment, the non-singular terminal sliding mode controller is determined based on the following steps:

[0107] Based on the inverse tangent trigonometric function, the inverse tangent sliding surface is designed. The inverse tangent sliding surface is expressed as:

[0108]

[0109] Where s is the inverse tangent sliding surface, x1 is the system state, x2 is the derivative of the system state x1, β, p and q are auxiliary variables, where β>0, p and q are odd numbers and arctan(x1) is the introduced inverse tangent trigonometric function;

[0110] Based on the inverse tangent sliding surface and sliding reaching law, a non-singular terminal sliding mode controller is designed. The non-singular terminal sliding mode controller is expressed as:

[0111]

[0112]

[0113] In the formula, is the sliding mode reaching law, k and eta are positive numbers, sgn is the sign function, η is the system state, is the first-order derivative of the system state, is the second-order derivative of the system state, η d For the expected state, is the second-order derivative of the desired state, is the mass matrix, To preset the underwater robot dynamic expression, To control the input force and torque, is the external disturbance, e=η d -η is the state error vector.

[0114] It should be noted that the availability of inverse tangent sliding surface design can be verified through the following steps.

[0115] The first step is to establish the relationship between the control input and the system state of the underwater robot by taking the derivative of the inverse tangent sliding surface. The derivative results are as follows:

[0116]

[0117] Since the inverse trigonometric functions are non-singular singular functions, It is an auxiliary function introduced and is always greater than zero, so the singular phenomenon is avoided in the design of the sliding mode controller.

[0118] In the second step, when the reaching law of the designed sliding surface is:

[0119]

[0120]

[0121] Where k, eta and ε are positive numbers, and sgn is the sign function.

[0122] The system state of the underwater robot can converge to the inverse tangent sliding surface. At this time, s = 0, and the convergence time of the system state moving along the sliding surface is calculated:

[0123]

[0124]

[0125]

[0126] Get the convergence time:

[0127]

[0128] because The convergence time of the underwater robot system state along the sliding surface has an upper limit:

[0129]

[0130] In addition, in order to verify the stability of the non-singular terminal sliding mode controller, the Lyapunov function is designed as follows:

[0131]

[0132]

[0133]

[0134] When the parameters are chosen to satisfy When the conditions are met, the underwater robot system satisfies Lyapunov stability, and the underwater robot can move to the desired position within a limited time.

[0135] on the other hand, Figure 5 It is a simulation comparison curve diagram of the position change of the underwater robot provided by the present invention under the control of the inverse tangent sliding mode controller and the traditional sliding mode controller. Figure 5As shown, the solid line is the position change curve of the underwater robot under the control of the designed non-singular terminal sliding mode controller, and the dotted line is the position change curve of the underwater robot under the control of the traditional sliding mode controller. The designed non-singular terminal sliding mode controller can enable the underwater robot to reach the target position faster.

[0136] The underwater robot obstacle avoidance control device provided by the present invention is described below. The underwater robot obstacle avoidance control device described below and the underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology described above can be referenced to each other.

[0137] Figure 6 Schematic diagram of the structure of the underwater robot obstacle avoidance control device provided by the present invention. Figure 6 As shown, the device includes: a determination module 610, a desired target determination module 620, a path planning module 630 and a control module 640.

[0138] in,

[0139] The determination module 610 is used to determine the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed;

[0140] The desired target determination module 620 is used to determine the desired target position based on the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed;

[0141] The path planning module 630 is used to determine the planned obstacle avoidance path to the desired target position based on the fuzzy artificial potential field, the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position; the fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field;

[0142] The control module 640 is used to control the underwater robot in real time based on the planned obstacle avoidance path and apply sliding mode control to reach the desired target position.

[0143] In an embodiment of the present invention, a determination module is used to determine the current underwater robot position, the current underwater robot position speed, the obstacle position and the obstacle speed; a desired target determination module is used to determine the desired target position based on the current underwater robot position, the current underwater robot position speed, the obstacle position and the obstacle speed; a path planning module is used to determine the planned obstacle avoidance path to reach the desired target position based on a fuzzy artificial potential field, applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position; the fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field; a control module is used to control the underwater robot in real time based on the planned obstacle avoidance path using sliding mode control to reach the desired target position, overcome the influence of obstacle movement on the obstacle avoidance capability of the underwater robot, and realize the obstacle avoidance task that can simultaneously avoid static obstacles and dynamic obstacles, thereby improving the effect of obstacle avoidance tasks in underwater variable environments.

[0144] Based on any of the above embodiments, the path planning module 630 includes:

[0145] A repulsive potential field submodule is used to determine a repulsive force to prevent collision and a repulsive force to prevent falling into a local minimum based on the repulsive potential field, applying a preset safety distance, a preset repulsive coefficient, the current underwater robot position, the obstacle position and the expected target position;

[0146] The attraction potential field submodule is used to determine the expected attraction force based on the fuzzy attraction potential field, by applying the preset attraction coefficient, the current underwater robot position and the expected target position, and to determine the attraction compensation force based on the fuzzy attraction compensation potential field in the fuzzy attraction potential field, by applying the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed;

[0147] A resultant force calculation submodule, for determining a repulsive resultant force based on a repulsive force for preventing collision and a repulsive force for preventing falling into a local minimum, and determining an attractive resultant force based on an expected attractive force and an attractive compensation force;

[0148] The obstacle avoidance path planning submodule is used to determine the obstacle avoidance path based on the repulsive force and the attractive force.

[0149] Based on any of the above embodiments, the control module 640 includes:

[0150] The control input force and torque determination submodule is used to determine the control input force and torque based on a non-singular terminal sliding mode controller, applying the system state, the expected state and the preset underwater robot dynamic expression; the non-singular terminal sliding mode controller is determined based on the inverse tangent sliding mode surface and the sliding mode reaching law; the inverse tangent sliding mode surface is determined based on the inverse tangent trigonometric function and the auxiliary variable, and the system state includes: the current underwater robot position and the current underwater robot yaw angle;

[0151] A control parameter determination submodule is used to determine the control parameters of the flippers based on the control input force and torque by applying a nonlinear mapping relationship between the preset control force and torque and the control parameters of the flippers; the control parameters of the flippers include an initial offset angle, a flapping frequency and a flapping amplitude;

[0152] The control submodule is used to perform real-time control based on the planned obstacle avoidance path and apply the control parameters of the flippers to reach the desired target position.

[0153] Figure 7 Schematic diagram of the structure of the underwater robot obstacle avoidance control system based on fuzzy artificial potential field technology provided by the present invention. Figure 7 As shown, the system includes: a global vision system 710 and an underwater robot 720, wherein the underwater robot 720 includes any of the above-mentioned underwater robot obstacle avoidance control devices 721 based on fuzzy artificial potential field technology and flippers 722.

[0154] in,

[0155] The global vision system 710 is used to identify the underwater robot 720 and obstacles, determine the current position of the underwater robot and the obstacle, and calculate the current speed of the underwater robot and the speed of the obstacle using a differential tracking method;

[0156] The flippers 722 are used to receive the control force and torque output by the underwater robot obstacle avoidance control device 721 based on the fuzzy artificial potential field technology, and push the underwater robot 720 to move.

[0157] In order to verify the effectiveness of the obstacle avoidance of the underwater robot, the present invention provides an underwater robot autonomous obstacle avoidance experiment conducted on a platform built in an indoor pool.

[0158] A circular obstacle is placed in the pool. The circular obstacle can be pulled into different motion states by a rope. The underwater robot needs to pass through the center without touching the edge of the circular obstacle to complete the underwater obstacle avoidance task. The underwater robot initially moves along the x-axis, and the circular obstacle can move unidirectionally along the y-axis, or move back and forth.

[0159] The first experiment was based on the underwater robot's obstacle avoidance task against a stationary circular obstacle. It took 23 seconds to complete the underwater robot's autonomous obstacle avoidance task. Figure 8 is a curve diagram of the change of the position and heading angle of the underwater robot when avoiding a stationary obstacle provided by the present invention, Fig. 9 : is a curve diagram of the change of the control output force and torque of the inverse tangent sliding mode controller provided by the present invention when avoiding a stationary obstacle. Fig. 9 As shown, the non-singular terminal sliding mode controller can be based on Figure 8Given the desired target position and heading, the output control input force and torque are adjusted in time to produce corresponding changes, so that the underwater robot can track the planned obstacle avoidance path. Finally, the underwater robot completes the underwater obstacle avoidance task within the allowable range of position error and heading angle error.

[0160] The second experiment was an underwater robot's obstacle avoidance task against a unidirectional moving circular obstacle. It took 14 seconds to complete the underwater autonomous obstacle avoidance task. Fig.10 : is a curve diagram of the position and heading angle of the underwater robot when avoiding a unidirectional moving obstacle provided by the present invention. Fig.10 As shown in the figure, when the underwater robot passes through the unidirectional moving ring, its error along the y-axis direction of the geographic coordinate system and the error of the heading angle are both within the allowable error range, and the underwater autonomous obstacle avoidance task is successfully completed.

[0161] The third experiment was a task for an underwater robot to avoid a circular obstacle that moved back and forth. It took 16 seconds to complete the underwater autonomous obstacle avoidance task. Fig.11 It is a curve diagram of the change of the position and heading angle of the underwater robot when avoiding a reciprocating obstacle provided by the present invention. Finally, the underwater robot completed the underwater autonomous obstacle avoidance experiment within the allowable error range.

[0162] The embodiment of the present invention realizes the autonomous obstacle avoidance task of the underwater robot for obstacles in different motion states by adopting the above technical solution.

[0163] The present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology provided by the above methods. The method includes: determining the current underwater robot position, the current underwater robot position speed, the obstacle position and the obstacle speed; determining the desired target position based on the current underwater robot position, the current underwater robot position speed, the obstacle position and the obstacle speed; based on the fuzzy artificial potential field, applying the current underwater robot position, the current underwater robot position speed, the obstacle position, the obstacle speed and the desired target position to determine the planned obstacle avoidance path to reach the desired target position; the fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field; based on the planned obstacle avoidance path, applying sliding mode control for real-time control to reach the desired target position.

[0164] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology, characterized in that: include: Determine the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed; Determining a desired target position based on the current underwater robot position, the current underwater robot speed, the obstacle position, and the obstacle speed; Based on the fuzzy artificial potential field, applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position, determining a planned obstacle avoidance path to reach the desired target position; The fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field; Based on the planned obstacle avoidance path, the underwater robot is controlled in real time by applying sliding mode control to reach the desired target position; The method of determining a planned obstacle avoidance path to reach the desired target position by applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position based on the fuzzy artificial potential field comprises: Based on the repulsive potential field, a preset safety distance, a preset repulsive coefficient, the current underwater robot position, the obstacle position and the expected target position are applied to determine a repulsive component force for preventing collision and a repulsive component force for preventing falling into a local minimum; based on the fuzzy attractive potential field, a preset attraction coefficient, the current underwater robot position and the expected target position are applied to determine an expected attractive force, and based on the fuzzy attractive compensation potential field in the fuzzy attractive potential field, an attractive compensation force is determined by applying the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed; Determine a repulsive resultant force based on the anti-collision repulsive force and the anti-falling into local minimum repulsive force, and determine an attractive resultant force based on the expected attractive force and the attractive compensation force; determine the planned obstacle avoidance path based on the repulsive resultant force and the attractive resultant force; The calculation formula of the attractive force is as follows: ； In the formula, is the fuzzy attractive potential field function, is the attractive potential field of the desired target position, is the fuzzy attraction compensation potential field function, is the preset attraction coefficient, is the current position of the underwater robot, is the desired target position, is the attractive force, is the attractive compensation force, is the obstacle speed, is the velocity component of the current underwater robot velocity in the direction of the obstacle velocity, is the distance between the underwater robot and the obstacle position in the direction perpendicular to the obstacle speed.

2. The underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology according to claim 1 is characterized in that: The calculation formula of the repulsive force is as follows: ； In the formula, is the repulsive force, To prevent the collision repulsion component, To prevent the repulsive force from falling into the local minimum, is the repulsive potential field function, is the preset rejection coefficient, is the minimum distance between the underwater robot and the obstacle, is the current position of the underwater robot, is the preset safety distance, is the desired target position, n is a positive integer greater than 0.

3. The underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology according to any one of claims 1 to 2, characterized in that: The method of applying sliding mode control to control the underwater robot in real time based on the planned obstacle avoidance path to reach the desired target position includes: Based on a non-singular terminal sliding mode controller, the control input force and torque are determined by applying the system state, the expected state and the preset underwater robot dynamic expression; the non-singular terminal sliding mode controller is determined based on the inverse tangent sliding mode surface and the sliding mode reaching law; the inverse tangent sliding mode surface is determined based on the inverse tangent trigonometric function and the auxiliary variable; Based on the control input force and torque, a nonlinear mapping relationship between the preset control input force and torque and the control parameters of the flippers is applied to determine the control parameters of the flippers; the control parameters include an initial offset angle, a flapping frequency and a flapping amplitude; Based on the planned obstacle avoidance path, the control parameters of the flippers are applied to perform real-time control to reach the desired target position.

4. The underwater robot obstacle avoidance control method based on fuzzy artificial potential field technology according to claim 3 is characterized in that: The non-singular terminal sliding mode controller is determined based on the following steps: Based on the inverse tangent trigonometric function, the inverse tangent sliding surface is designed, and the inverse tangent sliding surface is expressed as: ； In the formula, s is the inverse tangent sliding surface, is the system state, The system status The derivative of , and is the auxiliary variable, where ，p and q is an odd number and , is the inverse tangent trigonometric function introduced; Based on the inverse tangent sliding surface and the sliding mode reaching law, the non-singular terminal sliding mode controller is designed. The sliding mode reaching law is expressed as: ； The non-singular terminal sliding mode controller is expressed as: ； In the formula, is the sliding mode reaching law, k and eta is a positive number, sgn is the sign function, is the system state, is the first-order derivative of the system state, is the second-order derivative of the system state, is the desired state, is the second-order derivative of the desired state, is the mass matrix, is the preset underwater robot dynamics expression, are the control input forces and moments, For external disturbances, is the state error vector.

5. An underwater robot obstacle avoidance control device based on fuzzy artificial potential field technology, characterized in that: include: A determination module is used to determine the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed; A desired target determination module, used to determine the desired target position based on the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed; A route planning module, for determining a planned obstacle avoidance path to reach the desired target position by applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position based on a fuzzy artificial potential field; The fuzzy artificial potential field includes a repulsive potential field and a fuzzy attractive potential field; A control module, used to control the underwater robot in real time by applying sliding mode control based on the planned obstacle avoidance path to reach the desired target position; The method of determining a planned obstacle avoidance path to reach the desired target position by applying the current underwater robot position, the current underwater robot speed, the obstacle position, the obstacle speed and the desired target position based on the fuzzy artificial potential field comprises: Based on the repulsive potential field, a preset safety distance, a preset repulsive coefficient, the current underwater robot position, the obstacle position and the expected target position are applied to determine a repulsive component force for preventing collision and a repulsive component force for preventing falling into a local minimum; based on the fuzzy attractive potential field, a preset attraction coefficient, the current underwater robot position and the expected target position are applied to determine an expected attractive force, and based on the fuzzy attractive compensation potential field in the fuzzy attractive potential field, an attractive compensation force is determined by applying the current underwater robot position, the current underwater robot speed, the obstacle position and the obstacle speed; Determine a repulsive resultant force based on the anti-collision repulsive force and the anti-falling into local minimum repulsive force, and determine an attractive resultant force based on the expected attractive force and the attractive compensation force; determine the planned obstacle avoidance path based on the repulsive resultant force and the attractive resultant force; The calculation formula of the attractive force is as follows: ； In the formula, is the fuzzy attractive potential field function, is the attractive potential field of the desired target position, is the fuzzy attraction compensation potential field function, is the preset attraction coefficient, is the current position of the underwater robot, is the desired target position, is the attractive force, is the attractive compensation force, is the obstacle speed, is the velocity component of the current underwater robot velocity in the direction of the obstacle velocity, is the distance between the underwater robot and the obstacle position in the direction perpendicular to the obstacle speed.

6. An underwater robot obstacle avoidance control system based on fuzzy artificial potential field technology, characterized in that: include: Global vision systems and underwater robots; The underwater robot comprises: flippers and the underwater robot obstacle avoidance control device based on fuzzy artificial potential field technology as described in claim 5; in, The global vision system is used to identify the underwater robot and the obstacle, determine the current position of the underwater robot and the obstacle, and calculate the current speed of the underwater robot and the speed of the obstacle by using a differential tracking method; The fins are used to execute the control force and torque output by the underwater robot obstacle avoidance control device based on fuzzy artificial potential field technology to drive the underwater robot to move.

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