Amphibious unmanned boat autonomous landing system and control method thereof

Abstract

The present invention discloses an amphibious unmanned boat autonomous landing system and a control method thereof, the system comprises an unmanned measurement and control platform, a water driving subsystem and a land driving subsystem; the unmanned measurement and control platform collects multi-source information of the external environment of the amphibious unmanned boat, runs an autonomous landing control algorithm based on the collected data, and constructs a nearshore path planning environment model with a double-layer grid map overlay structure; generates a global path that meets the kinematic characteristics of the unmanned boat and connects the initial posture and the target posture based on the Hybrid A* algorithm, and locally optimizes the global path based on the TEB algorithm; identifies the parameters of the three-degree-of-freedom motion model of the unmanned boat; performs curve path tracking on the planned path based on the NMPC algorithm, calculates control instructions and issues control instructions to the water driving subsystem and the land driving subsystem. The present invention can realize the unmanned operation of the wheeled amphibious boat and the efficient and reliable autonomous landing function of the amphibious unmanned boat.

Description

Technical Field

[0001] The present invention relates to the technical field of autonomous driving of amphibious unmanned boats, and in particular to an autonomous landing system of an amphibious unmanned boat and a control method thereof. Background Art

[0002] Unmanned boats play a huge role in military defense, security patrol, emergency rescue and hydrological monitoring due to their flexibility, high intelligence and ability to perform tasks in harsh environments. Wheeled amphibious boats have the characteristics of efficient driving and flexible switching in both water and land environments. They can travel at high speed in some water-land switching scenarios without the need for lifting and landing like ordinary boats, thereby improving work efficiency and broadening application scenarios.

[0003] However, there has been little research on the autonomous landing technology of amphibious boats at home and abroad. At the same time, the autonomous landing of amphibious unmanned boats has brought great challenges due to the large number of obstacles near the shore and the harsh landing conditions of wheeled amphibious boats. Therefore, how to achieve efficient and reliable autonomous landing of wheeled amphibious boats is an urgent problem to be solved. Summary of the invention

[0004] In order to overcome the defects and shortcomings of the prior art, the present invention provides an amphibious unmanned boat autonomous landing system and a control method thereof, which can realize the unmanned operation of the wheeled amphibious boat and can realize the efficient and reliable autonomous landing function of the amphibious unmanned boat.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention provides an amphibious unmanned boat autonomous landing system, comprising: an unmanned measurement and control platform, a water driving subsystem and a land driving subsystem;

[0007] The unmanned measurement and control platform is used to collect multi-source information about the external environment of the amphibious unmanned boat, run the autonomous landing control algorithm in real time based on the collected data, calculate the control instructions, and send the control instructions to the water driving subsystem and the land driving subsystem to achieve unmanned control;

[0008] The implementation of the autonomous landing control algorithm includes:

[0009] Construct a nearshore path planning environment model with a double-layer grid map overlay structure;

[0010] Based on the Hybrid A* algorithm, a global path that meets the kinematic characteristics of the unmanned boat and connects the initial posture and the target posture is generated, and the global path is locally optimized based on the TEB algorithm;

[0011] Identify the parameters of the three-degree-of-freedom motion model of the unmanned boat;

[0012] Perform curve path tracking on the planned path based on the NMPC algorithm;

[0013] When it is determined that the target landing point has been reached, the water driving subsystem is switched to the land driving subsystem;

[0014] The water driving subsystem is used to receive control instructions sent by the unmanned measurement and control platform to drive the amphibious unmanned boat to autonomously navigate on water;

[0015] The land driving subsystem is used to receive control instructions sent by the unmanned measurement and control platform to drive the amphibious unmanned boat to drive autonomously on land.

[0016] As a preferred technical solution, the unmanned measurement and control platform includes a main control module, a positioning module, a sensing module, a communication module and a power module;

[0017] The main control module includes an industrial computer, an industrial switch and a data acquisition controller. The industrial computer is used to run the autonomous landing control algorithm, the industrial switch is used to transmit multi-source sensor information and control instructions, and the data acquisition controller is used to send control instructions to the water driving subsystem and the land driving subsystem and collect feedback status;

[0018] The positioning module includes an inertial measurement unit and a GPS, wherein the inertial measurement unit is used to collect the attitude and speed information of the unmanned boat, and the GPS is used to collect the position information of the unmanned boat;

[0019] The perception module includes a laser radar, a multi-beam sonar, an RGB camera, and a thermal imaging camera, which are used to collect multi-source sensor information of the external environment;

[0020] The communication module adopts a radio station for remote communication with the shore-based host computer;

[0021] The power module is used to supply power to the main control module, the positioning module, the sensing module and the communication module.

[0022] As a preferred technical solution, the water driving subsystem is provided with a water driving module, which includes a propeller, a speed controller, an electric pump and a rudder angle sensor. The propeller is used to provide power for the amphibious unmanned boat to navigate on water. The speed controller is used to convert the mechanical control of the propeller speed of the propeller into electric control. The electric pump is used to convert the oil circuit control of the steering operation into circuit control by opening and closing the solenoid valve. The rudder angle sensor is used to feed back the rudder angle signal, thereby realizing closed-loop control of the rudder angle.

[0023] As a preferred technical solution, the land driving subsystem is provided with a land driving module, which includes a driving mechanism for providing power for the amphibious unmanned boat to travel on land, and communicates with the unmanned measurement and control platform through the CAN protocol, thereby realizing the control of the lifting and lowering of the driving mechanism, the rotation speed and the front wheel angle.

[0024] The present invention also provides a control method for an amphibious unmanned boat autonomous landing system, provided with the above-mentioned amphibious unmanned boat autonomous landing system, the method comprising the following steps:

[0025] Construct a nearshore path planning environment model with a double-layer grid map overlay structure;

[0026] Based on the Hybrid A* algorithm, a global path that meets the kinematic characteristics of the unmanned boat and connects the initial posture and the target posture is generated, and the global path is locally optimized based on the TEB algorithm;

[0027] Identify the parameters of the three-degree-of-freedom motion model of the unmanned boat;

[0028] Perform curve path tracking on the planned path based on the NMPC algorithm;

[0029] When it is determined that the target landing point has been reached, the water driving subsystem is switched to the land driving subsystem.

[0030] As a preferred technical solution, the nearshore path planning environment model with a double-layer grid map overlay structure is constructed, specifically including:

[0031] Extract water surface areas based on satellite maps and build static map layers;

[0032] Extract the traversable area based on point cloud information and build a dynamic obstacle map layer;

[0033] The static map layer and the dynamic obstacle map layer are superimposed according to the set rules, and finally a path planning grid map for the landing scenario is formed;

[0034] The set rules are expressed as:

[0035]

[0036] Among them, s, o, and f represent the static map layer, obstacle map layer, and final map layer respectively. Represents the index within the obstacle layer grid map.

[0037] As a preferred technical solution, extracting the water surface area based on the satellite map and constructing a static map layer specifically includes:

[0038] Select the water surface area pixels in the satellite map image as seed points;

[0039] Convert satellite map RGB images to LAB color space;

[0040] The region growing algorithm is used to extract the water surface area, and a raster map is constructed with pixel size as the resolution.

[0041] As a preferred technical solution, the extraction of traversable areas based on point cloud information and the construction of a dynamic obstacle map layer specifically include:

[0042] Correct point cloud information based on inertial navigation data;

[0043] Filter the point cloud information;

[0044] Map point cloud information to a raster map of a set resolution.

[0045] As a preferred technical solution, the identification of the three-degree-of-freedom motion model parameters of the unmanned boat specifically includes:

[0046] 10° and 20° Z-type real ship experiments were carried out. During the process, the longitudinal speed u, lateral speed v, bow speed r, heading angle ψ, thruster thrust angle δ and rotation speed n of the unmanned boat were collected at a frequency of 20 Hz. The least squares method was used to identify and verify the parameters of the unmanned boat motion model.

[0047] As a preferred technical solution, the curve path tracking of the planned path based on the NMPC algorithm specifically includes:

[0048] Construct the state space model of unmanned boat motion:

[0049]

[0050] y=Px

[0051] Among them, a * are the parameters related to the unmanned motion model, x = [u, v, r, x, y, ψ] T is the state vector, u=[τ u ,τ r ] T is the control variable, y=[x,y,ψ] T is the output vector,

[0052] The Runge-Kutta method is used to discretize the motion state space model formula of the unmanned boat:

[0053]

[0054] The optimization objective function is set as:

[0055]

[0056] Among them, N is the prediction step length, y d =[x d ,y d ,ψ d ] T is the desired tracking pose, Q = (q1 … q N ) represents the output error weight matrix, R = (r1 … r N ) represents the input weight matrix;

[0057] The unmanned boat propulsion system has propulsion angle saturation constraints and propulsion angular velocity saturation constraints, which are expressed as follows:

[0058] δ min ≤δ≤δ max

[0059] Δδ min ≤Δδ≤Δδ max

[0060] Among them, δ min and δ max Indicates the lower and upper limits of the thruster thrust angle, Δδ min and Δδ max Indicates the lower and upper limits of the propulsion angular velocity of the thruster;

[0061] The optimization problem is transformed into a standard quadratic programming form. The optimal control variable increment sequence is obtained by finding the optimal solution. The first element of the sequence is added to the previous control variable to obtain the control input at the current moment. The above steps are repeated to achieve curve path tracking based on the NMPC algorithm.

[0062] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0063] The present invention can realize the unmanned operation of the wheeled amphibious boat and can realize the efficient and reliable autonomous landing function of the amphibious unmanned boat. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a schematic diagram of the architecture of the autonomous landing system of an amphibious unmanned boat of the present invention;

[0065] Figure 2 The schematic diagram of the implementation architecture of the autonomous landing control algorithm of the autonomous landing system of the amphibious unmanned boat of the present invention;

[0066] Figure 3 It is a structural schematic diagram of the water travel subsystem of the present invention;

[0067] Figure 4 It is a schematic structural diagram of the land driving subsystem of the present invention;

[0068] Figure 5It is a flow chart of a control method of an amphibious unmanned boat autonomous landing system of the present invention;

[0069] Figure 6 A schematic diagram of a grid map construction method based on point cloud information in the present invention;

[0070] Figure 7 A schematic diagram of the construction of a nearshore path planning environment model of a double-layer grid map overlay structure of the present invention;

[0071] Figure 8 This is a flow chart of the unmanned boat motion model parameter identification of the present invention. DETAILED DESCRIPTION

[0072] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0073] Example 1

[0074] like Figure 1 , Figure 2 As shown, this embodiment provides an amphibious unmanned boat autonomous landing system, including: an unmanned measurement and control platform, a water driving subsystem and a land driving subsystem;

[0075] Among them, the unmanned measurement and control platform is used to collect multi-source information about the external environment of the amphibious unmanned boat, run the autonomous landing control algorithm in real time based on the collected data, calculate the control instructions, and send the control instructions to the water driving subsystem and the land driving subsystem to realize unmanned control;

[0076] The water driving subsystem receives control instructions from the unmanned measurement and control platform to drive the amphibious unmanned boat to sail autonomously on the water;

[0077] The land driving subsystem receives control instructions sent by the unmanned measurement and control platform to drive the amphibious unmanned boat to drive autonomously on land.

[0078] like Figure 2 As shown, the implementation of the autonomous landing control algorithm includes:

[0079] Construct a nearshore path planning environment model with a double-layer grid map overlay structure;

[0080] Based on the Hybrid A* algorithm, a global path that meets the kinematic characteristics of the unmanned boat and connects the initial posture and the target posture is generated, and the global path is locally optimized based on the TEB algorithm;

[0081] Identify the parameters of the three-degree-of-freedom motion model of the unmanned boat;

[0082] Perform curve path tracking on the planned path based on the NMPC algorithm;

[0083] When it is determined that the target landing point has been reached, the water driving subsystem is switched to the land driving subsystem.

[0084] Combination Figure 1 As shown, the unmanned measurement and control platform includes a main control module, a positioning module, a perception module, a communication module and a power module;

[0085] In this embodiment, the main control module includes: an industrial computer, an industrial switch and a data acquisition controller, wherein the industrial computer is used to run the autonomous landing control algorithm, the industrial switch is used to transmit multi-source sensor information and control instructions, and the data acquisition controller is used to send control instructions to the water driving subsystem and the land driving subsystem and collect feedback status;

[0086] In this embodiment, the positioning module includes an inertial measurement unit and a GPS, wherein the inertial measurement unit is used to collect the attitude and speed information of the unmanned boat, and the GPS is used to collect the position information of the unmanned boat;

[0087] In this embodiment, the perception module includes a laser radar, a multi-beam sonar, an RGB camera, and a thermal imaging camera, which are used to collect multi-source sensor information of the external environment;

[0088] In this embodiment, the communication module is provided with a radio station for remote communication with the shore-based host computer;

[0089] In this embodiment, the power module includes a UPS, a voltage stabilizing module and a relay, wherein the UPS supplies power to each component, and the voltage stabilizing module and the relay ensure the safety of power supply to each component;

[0090] like Figure 3 As shown, the water driving subsystem is provided with a water driving module, which includes a propeller, a speed controller, an electric pump and a rudder angle sensor, wherein the propeller is used to provide power for the amphibious unmanned boat to sail on water, the speed controller is used to convert the mechanical control of the propeller speed of the propeller into electric control, the electric pump converts the oil circuit control of the steering operation into circuit control by opening and closing the solenoid valve, and the rudder angle sensor is used to feed back the rudder angle signal, thereby realizing the closed-loop control of the rudder angle;

[0091] like Figure 4 As shown, the land driving subsystem is provided with a land driving module, which includes a driving mechanism for providing power for the amphibious unmanned boat to travel on land, and communicates with the main control module through the CAN protocol, thereby realizing the control of the lifting and lowering of the driving mechanism, the rotation speed and the front wheel angle.

[0092] Example 2

[0093] like Figure 5As shown, this embodiment provides a control method for an amphibious unmanned boat autonomous landing system, provided with the amphibious unmanned boat autonomous landing system of the above-mentioned embodiment 1, and the method comprises the following steps:

[0094] Step S1: Constructing a nearshore path planning environment model with a double-layer grid map overlay structure, specifically including:

[0095] S11: Extract water surface areas based on satellite maps and construct static map layers;

[0096] Specifically, firstly, the pixels of the water surface area in the satellite map image are selected as seed points; secondly, the satellite map RGB image is converted to the LAB color space; finally, the region growing algorithm is used to extract the water surface area, and a raster map is constructed with the pixel size as the resolution;

[0097] S12: Extract the traversable area based on the point cloud information and build a dynamic obstacle map layer;

[0098] Specifically, the point cloud information is first corrected based on the inertial navigation data; secondly, the point cloud information is filtered; finally, Figure 6 As shown in the figure, the point cloud information is mapped to a grid map of set resolution, where L represents the laser radar and p * represents a point cloud point, ρ max Represents the maximum detection distance of the laser radar, and the grid map resolution Δx is calculated by the following formula:

[0099]

[0100] In the formula, scale represents the satellite map scale, and PPI represents the resolution of the host computer display device;

[0101] S13: Figure 7 As shown, the map layers constructed above are superimposed according to the set rules to finally form a path planning grid map for the landing scene. The superposition rules are shown in the following formula:

[0102]

[0103] In the formula, the superscript S indicates the map layer, s, o, and f indicate the static map layer, obstacle map layer, and final map layer respectively, and the subscript indicates the grid index. Represents the index within the obstacle layer grid map;

[0104] Step S2: Based on the Hybrid A* and TEB fusion algorithm, a near-shore smooth path connecting the initial posture and the target posture is planned to meet the kinematic constraints and collision avoidance constraints of the unmanned boat;

[0105] In this embodiment, a global path that meets the kinematic characteristics of the unmanned boat and connects the initial posture and the target posture is generated based on the Hybrid A* algorithm, and then the global path is locally optimized in terms of obstacle avoidance safety, path smoothness, etc. based on the TEB algorithm.

[0106] Step S3: Identify the motion model parameters of the unmanned boat through operational experiments;

[0107] like Figure 8 As shown in the figure, the three-degree-of-freedom motion model parameters of the unmanned boat are identified through operational experiments, including:

[0108] Conduct 10° and 20° Z-shaped real ship experiments, during which the unmanned boat longitudinal speed u, lateral speed v, bow speed r, heading angle ψ, propeller thrust angle δ and speed n are collected at a frequency of 20Hz. Based on the above data, the least squares method is used to identify and verify the parameters of the unmanned boat motion model;

[0109] Step S4: performing curve path tracking on the planned path based on the NMPC algorithm;

[0110] In this embodiment, the motion state space model of the unmanned boat is constructed:

[0111]

[0112] y=Px

[0113] In the formula, a * are the parameters related to the unmanned motion model, x = [u, v, r, x, y, ψ] T is the state vector, u=[τ u ,τ r ] T is the control variable, y=[x,y,ψ] T is the output vector,

[0114] The above formula is discretized using the Runge-Kutta method:

[0115]

[0116] In order to ensure the final convergence of the path tracking error and the heading angle error, and to minimize the change in the thrust angle to reduce energy loss, the objective function for optimization is set as follows:

[0117]

[0118] Where N is the prediction step length, y d =[x d ,y d ,ψ d ] Tis the desired tracking pose, Q = (q1 … q N ) represents the output error weight matrix, R=(r1 ... r N ) represents the input weight matrix.

[0119] The propulsion system of the unmanned boat has the constraints of propulsion angle saturation and propulsion angular velocity. These constraints must be considered when conducting research. The above two constraints can be expressed as follows:

[0120] δ min ≤δ≤δ max

[0121] Δδ min ≤Δδ≤Δδ max

[0122] Among them, δ min and δ max Indicates the lower and upper limits of the thruster thrust angle, Δδ min and Δδ max Indicates the lower and upper limits of the thruster's angular velocity.

[0123] The above optimization problem is transformed into a standard quadratic programming form. The optimal control variable increment sequence is obtained by finding the optimal solution. The first element of the sequence is added to the previous control variable to obtain the control input at the current moment. The above steps are repeated to achieve curve path tracking based on the NMPC algorithm.

[0124] Step S5: Arrive at the target landing point, switch the water driving subsystem to the land driving subsystem to achieve autonomous landing.

[0125] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. An amphibious unmanned boat autonomous landing system, characterized in that: include: Unmanned measurement and control platform, water driving subsystem and land driving subsystem; The unmanned measurement and control platform is used to collect multi-source information about the external environment of the amphibious unmanned boat, run the autonomous landing control algorithm in real time based on the collected data, calculate the control instructions, and send the control instructions to the water driving subsystem and the land driving subsystem to achieve unmanned control; The implementation of the autonomous landing control algorithm includes: Construct a nearshore path planning environment model with a double-layer grid map overlay structure; Based on the Hybrid A* algorithm, a global path that meets the kinematic characteristics of the unmanned boat and connects the initial posture and the target posture is generated, and the global path is locally optimized based on the TEB algorithm; Identify the parameters of the three-degree-of-freedom motion model of the unmanned boat; Perform curve path tracking on the planned path based on the NMPC algorithm; The curve path tracking of the planned path based on the NMPC algorithm specifically includes: Construct the motion state space model of the unmanned boat: Y=PX Among them, a * are the parameters related to the unmanned motion model, X = [u, v, r, x, y, ψ] T is the state vector, u represents the longitudinal velocity of the unmanned boat, v represents the lateral velocity of the unmanned boat, r represents the bowing velocity, ψ represents the heading angle, U=[τ u ,τ r ] T is the control variable, Y=[x,y,ψ] T is the output vector, The Runge-Kutta method is used to discretize the motion state space model formula of the unmanned boat: The optimization objective function is set as: Among them, N is the prediction step length, Y d =[x d ,y d ,ψ d ] is the desired tracking pose, Q=(q1...q N ) represents the output error weight matrix, R = (r1...r N ) represents the input weight matrix; The unmanned boat propulsion system has thrust angle saturation constraints and pushing angular velocity constraints, which are expressed as follows: d min ≤δ≤δ max Dd min ≤Δδ≤Δδ max Among them, δ min and δ max Indicates the lower and upper limits of the thruster thrust angle, Δδ min and Δδ max Indicates the lower and upper limits of the propulsion angular velocity of the thruster; The optimization problem is transformed into a standard quadratic programming form. The optimal control variable increment sequence is obtained by finding the optimal solution. The control input at the current moment can be obtained by adding the first element of the sequence to the previous control variable. The above steps are repeated to achieve curve path tracking based on the NMPC algorithm. When it is determined that the target landing point has been reached, the water driving subsystem is switched to the land driving subsystem; The water driving subsystem is used to receive control instructions sent by the unmanned measurement and control platform to drive the amphibious unmanned boat to autonomously navigate on water; The land driving subsystem is used to receive control instructions sent by the unmanned measurement and control platform to drive the amphibious unmanned boat to drive autonomously on land.

2. The amphibious unmanned boat autonomous landing system according to claim 1 is characterized in that: The unmanned measurement and control platform includes a main control module, a positioning module, a sensing module, a communication module and a power module; The main control module includes an industrial computer, an industrial switch and a data acquisition controller. The industrial computer is used to run the autonomous landing control algorithm, the industrial switch is used to transmit multi-source sensor information and control instructions, and the data acquisition controller is used to send control instructions to the water driving subsystem and the land driving subsystem and collect feedback status; The positioning module includes an inertial measurement unit and a GPS, wherein the inertial measurement unit is used to collect the attitude and speed information of the unmanned boat, and the GPS is used to collect the position information of the unmanned boat; The perception module includes a laser radar, a multi-beam sonar, an RGB camera, and a thermal imaging camera, which are used to collect multi-source sensor information of the external environment; The communication module adopts a radio station for remote communication with the shore-based host computer; The power module is used to supply power to the main control module, the positioning module, the sensing module and the communication module.

3. The amphibious unmanned boat autonomous landing system according to claim 1 is characterized in that: The water driving subsystem is provided with a water driving module, which includes a propeller, a speed controller, an electric pump and a rudder angle sensor. The propeller is used to provide power for the amphibious unmanned boat to navigate on water. The speed controller is used to convert the mechanical control of the propeller speed of the propeller into electric control. The electric pump is used to convert the oil circuit control of the steering operation into circuit control by opening and closing the solenoid valve. The rudder angle sensor is used to feed back the rudder angle signal, thereby realizing closed-loop control of the rudder angle.

4. The amphibious unmanned boat autonomous landing system according to claim 1, characterized in that: The land driving subsystem is provided with a land driving module, which includes a driving mechanism for providing power for the amphibious unmanned boat to travel on land, and communicates with the unmanned measurement and control platform through the CAN protocol, thereby realizing the control of the lifting and lowering of the driving mechanism, the rotation speed and the front wheel angle.

5. A control method for an amphibious unmanned boat autonomous landing system, characterized in that: An amphibious unmanned boat autonomous landing system according to any one of claims 1 to 4 is provided, and the method comprises the following steps: Construct a nearshore path planning environment model with a double-layer grid map overlay structure; Based on the Hybrid A* algorithm, a global path that meets the kinematic characteristics of the unmanned boat and connects the initial posture and the target posture is generated, and the global path is locally optimized based on the TEB algorithm; Identify the parameters of the three-degree-of-freedom motion model of the unmanned boat; Perform curve path tracking on the planned path based on the NMPC algorithm; The curve path tracking of the planned path based on the NMPC algorithm specifically includes: Construct the motion state space model of the unmanned boat: Y=PX Among them, a * are the parameters related to the unmanned motion model, X = [u, v, r, x, y, ψ] T is the state vector, u represents the longitudinal velocity of the unmanned boat, v represents the lateral velocity of the unmanned boat, r represents the bowing velocity, ψ represents the heading angle, U=[τ u ,τ r ] T is the control variable, Y=[x,y,ψ] T is the output vector, The Runge-Kutta method is used to discretize the motion state space model formula of the unmanned boat: The optimization objective function is set as: Among them, N is the prediction step length, Y d =[x d ,y d ,ψ d ] is the desired tracking pose, Q = (q1…q N ) represents the output error weight matrix, R = (r1…r N ) represents the input weight matrix; The unmanned boat propulsion system has thrust angle saturation constraints and pushing angular velocity constraints, which are expressed as follows: d min ≤δ≤δ max Dd min ≤Δδ≤Δδ max Among them, δ min and δ max Indicates the lower and upper limits of the thruster thrust angle, Δδ min and Δδ max Indicates the lower and upper limits of the propulsion angular velocity of the thruster; The optimization problem is transformed into a standard quadratic programming form. The optimal control variable increment sequence is obtained by finding the optimal solution. The control input at the current moment can be obtained by adding the first element of the sequence to the previous control variable. The above steps are repeated to achieve curve path tracking based on the NMPC algorithm. When it is determined that the target landing point has been reached, the water driving subsystem is switched to the land driving subsystem.

6. The control method of the amphibious unmanned boat autonomous landing system according to claim 5, characterized in that: The nearshore path planning environment model of the double-layer grid map overlay structure is constructed, specifically including: Extract water surface areas based on satellite maps and build static map layers; Extract the traversable area based on point cloud information and build a dynamic obstacle map layer; The static map layer and the dynamic obstacle map layer are superimposed according to the set rules, and finally a path planning grid map for the landing scenario is formed; The set rules are expressed as: Among them, s, o, and f represent the static map layer, obstacle map layer, and final map layer respectively. Represents the index within the obstacle layer grid map.

7. The control method of the amphibious unmanned boat autonomous landing system according to claim 6, characterized in that: The method of extracting the water surface area based on the satellite map and constructing the static map layer specifically includes: Select the water surface area pixels in the satellite map image as seed points; Convert satellite map RGB images to LAB color space; The region growing algorithm is used to extract the water surface area, and a raster map is constructed with pixel size as the resolution.

8. The control method of the amphibious unmanned boat autonomous landing system according to claim 6, characterized in that: The extracting of the traversable area based on the point cloud information and constructing the dynamic obstacle map layer specifically includes: Correct point cloud information based on inertial navigation data; Filter the point cloud information; Map point cloud information to a raster map of a set resolution.

9. The control method of the amphibious unmanned boat autonomous landing system according to claim 5, characterized in that: The identification of the three-degree-of-freedom motion model parameters of the unmanned boat specifically includes: 10° and 20° Z-type real ship experiments were carried out. During the process, the longitudinal speed u, lateral speed v, bow speed r, heading angle ψ, thruster thrust angle δ and rotation speed n of the unmanned boat were collected at a frequency of 20 Hz. The least squares method was used to identify and verify the parameters of the unmanned boat motion model.

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