Ship motion model parameter estimation system, motion model parameter estimation method, and program

Abstract

To easily estimate parameters of a ship's specific motion model. [Solution] A parameter estimation system that estimates parameters of a ship's motion model includes an estimation unit that uses a navigation log when the ship navigates in a predetermined motion pattern and estimates parameters of a motion model specific to the ship that corresponds to the predetermined motion pattern indicated by the navigation log.

Description

[Technical field]

[0001] The present invention relates to a ship motion model parameter estimation system, a motion model parameter estimation method, and a program. [Background technology]

[0002] Conventionally, techniques for controlling ship navigation based on ship motion models have been developed.

[0003] For example, Patent Document 1 discloses a configuration for controlling automatic steering, in which control parameters are set by making non-dimensional motion parameters dimensional when the ship speed changes. Patent Document 2 discloses a configuration for correcting engine control parameters based on actual measured values ​​from sensors, etc., in relation to an autopilot for a ship. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2023-139851 A [Patent Document 2] Patent No. 6430985 Summary of the Invention [Problem to be solved by the invention]

[0005] The control model used for the automatic piloting of a ship needs to be set after identifying the parameters of the motion model based on the results of various tests and simulations, taking into account various factors such as the shape and specifications of the ship, and this identification requires a lot of cost and time. In particular, ships are often produced individually according to orders rather than mass-produced in the same way. Therefore, it is necessary to identify the parameters of the motion model individually according to the characteristics of each ship, and this increases the cost and time required for identifying the parameters of the motion model. For example, the test conditions and environments of ships are diverse, and it is difficult to use the measurement data of one ship as it is to control another ship. In addition, even for the same ship, the shape and characteristics change due to aging, etc., so the accuracy of the motion model once identified may change. Therefore, it is required to update the motion model for the ship as appropriate.

[0006] In view of the above problems, an object of the present invention is to easily estimate parameters of a ship-specific motion model. [Means for solving the problem]

[0007] In order to solve the above problems, one aspect of the present invention has the following configuration. That is, a parameter estimation system for estimating parameters of a ship motion model includes: an estimation unit that uses a navigation log when the ship navigates in a predetermined motion pattern to estimate parameters of a motion model specific to the ship that corresponds to the predetermined motion pattern indicated by the navigation log; has.

[0008] Another aspect of the present invention has the following configuration. That is, a parameter estimation method for estimating parameters of a ship motion model includes: an estimation step of estimating parameters of a motion model specific to the ship corresponding to the predetermined motion pattern indicated by a navigation log obtained when the ship navigates in a predetermined motion pattern; has.

[0009] Another aspect of the present invention has the following configuration: Computer, an estimation unit that uses a navigation log when the ship navigates in a predetermined navigation pattern to estimate parameters of a motion model specific to the ship that corresponds to the predetermined navigation pattern indicated by the navigation log; Function as. Effect of the Invention

[0010] According to the present invention, it is possible to easily estimate parameters of a ship-specific motion model. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a block diagram showing an example of the configuration of a parameter estimation system for an exercise model according to a first embodiment of the present invention; [Diagram 2] FIG. 1 is a block diagram showing an example of the configuration of a ship according to a first embodiment of the present invention. [Diagram 3] FIG. 1 is a sequence diagram showing a process flow according to a first embodiment of the present invention. [Figure 4] FIG. 2 is a schematic diagram showing an example of a motion pattern of a marine vessel according to the first embodiment of the present invention; [Diagram 5] FIG. 1 is a schematic diagram showing inputs and outputs related to parameter estimation according to a first embodiment of the present invention; [Figure 6] 1 is a flowchart of a process according to a first embodiment of the present invention; [Figure 7] FIG. 11 is a sequence diagram showing a process flow according to a modification of the first embodiment of the present invention. [Figure 8] 1 is a flowchart of a process according to a modified example of the first embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, the embodiment for carrying out the present invention will be described with reference to the drawings. Note that the embodiment described below is one embodiment for explaining the present invention, and is not intended to be interpreted as limiting the present invention, and all configurations described in each embodiment are not necessarily essential configurations for solving the problems of the present invention. Also, in each drawing, the same components are given the same reference numbers to indicate their correspondence. Note that in order to avoid unnecessary redundancy and to facilitate understanding by those skilled in the art, some of the explanations may be omitted or simplified. For example, detailed explanations of already well-known matters or duplicate explanations of substantially the same configurations may be omitted.

[0013] First Embodiment [System Configuration] FIG. 1 is a schematic diagram showing an example of the configuration of a motion model parameter estimation system (hereinafter simply referred to as "parameter estimation system") according to a first embodiment of the present invention. The motion model parameter estimation system is a system for estimating parameters of a motion model related to automatic navigation of a ship and constructing a control model corresponding to the ship. The motion model parameter estimation system may be used in a form mounted on the ship, or may be configured as a separate device and configured to be able to provide the ship with a control model based on the motion model whose parameters have been estimated. The parameter estimation system 100 may be configured, for example, by an information processing device such as a PC (Personal Computer), or may be configured by a control device such as an ECU (Electronic Control Unit) mounted on the ship.

[0014] The parameter estimation system 100 includes a control unit 101, a storage unit 102, an input unit 103, an output unit 104, and a communication unit 105. Each unit is configured to be able to communicate with each other via an internal bus or the like.

[0015] The control unit 101 is responsible for controlling the operation of the parameter estimation system 100. The control unit 101 is composed of, for example, a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit), and provides various functions by reading and executing various programs and data stored in the storage unit 102.

[0016] The storage unit 102 is a storage device for storing programs, data, and the like for executing various control processes and various functions by the control unit 101. The storage unit 102 is composed of volatile / non-volatile storage devices such as a RAM (Random Access Memory), a ROM (Read Only Memory), an HDD (Hard disk Drive), and a flash memory.

[0017] The input unit 103 is composed of a mouse, a keyboard, a microphone, etc., and accepts input of operations from a user, etc. The output unit 104 is composed of a display, a speaker, etc., and outputs various data. The output by the output unit 104 may be any of visual, auditory, and tactile outputs such as images, sounds, and vibrations. In addition, the input unit 103 and the output unit 104 may be integrated using a touch panel display, etc.

[0018] The communication unit 106 is a communication interface for communicating with an external device via a network (not shown). The communication unit 106 may be configured to be compatible with a plurality of communication standards depending on the configuration of the network. The network may be configured, for example, by the Internet, an intranet, a wireless LAN (Local Area Network), a WAN (Wide Area Network), or the like. Note that the communication standards and wired / wireless communication related to the network are not particularly limited, and the network may be configured by combining a plurality of communication standards.

[0019] 2 is a block diagram showing an example of the configuration of a ship according to this embodiment. The ship 200 is configured to be capable of automatic navigation using a control model constructed based on the estimation results of parameters of a motion model according to this embodiment. The ship 200 includes a control unit 201, a storage unit 202, an operation unit 203, a drive unit 204, an output unit 205, a sensor unit 206, an antenna unit 207, and a camera 208.

[0020] The control unit 201 is responsible for controlling the ship 200. For example, the control unit 201 is composed of a central processing unit (CPU), a graphics processing unit (GPU), a dedicated circuit, and the like, and provides various functions by reading and executing various programs and data stored in the storage unit 202.

[0021] The storage unit 202 is a storage device for storing programs, data, and the like for executing various control processes and functions provided by the control unit 201. The storage unit 202 is composed of volatile / non-volatile storage devices such as a RAM (Random Access Memory), a ROM (Read Only Memory), an HDD (Hard disk Drive), and a flash memory.

[0022] The operation unit 203 accepts various operations related to the navigation of the ship 200. The operation unit 203 may be configured to include an accelerator lever, a steering wheel, a joystick lever, a shift lever, various switches, and the like. The operations here may include operations related to navigation such as steering, acceleration and deceleration, as well as operations related to each part constituting the ship 200. The drive unit 204 performs operations related to the navigation of the ship 200 based on instructions from the control unit 201 and operations from the operation unit 203. The drive unit 204 may be configured to include, for example, an engine, a motor, a thruster, a propeller, a pump, and the like. The type of the drive unit 204 is not particularly limited, and may be configured to enable automatic navigation using parameter estimation of a motion model and a control model, which will be described later.

[0023] The output unit 205 is composed of a display, a speaker, etc., and outputs various data. The output by the output unit 205 may be any of visual, auditory, and tactile output, such as an image, sound, and vibration. For example, the output unit 205 may display various data acquired by the sensor unit 206, the antenna unit 207, and the camera 208 on a predetermined user interface screen. The output unit 205 may also output information for performing navigation using map information, etc.

[0024] The sensor unit 206 is composed of a plurality of sensors for acquiring peripheral information and internal information of the ship 200. The sensor unit 206 may include a plurality of types of sensors, such as a wind direction and speed gauge, an acceleration sensor, a temperature sensor, a humidity sensor, LiDAR, a radar, a gyro sensor, a position sensor, a rotation sensor, and a sonar. Also, a plurality of sensors of one type may be provided. The various sensors included in the sensor unit 206 may be configured to acquire information of the entire ship 200, as well as information of a predetermined part constituting the ship 200. The antenna unit 207 is a part for transmitting and receiving information to and from the outside. The antenna unit 207 may include a plurality of types of antennas, such as a Global Navigation Satellite System (GNSS) antenna and an Automatic Identification System (AIS) antenna. The camera 208 is an imaging device for acquiring peripheral images of the ship 200. The direction of the image that can be acquired by the camera 208 is not particularly limited, and the camera 208 may be configured to acquire images in all directions.

[0025] [Parameter estimation of the motion model] The following describes parameter estimation of a motion model for automatic maneuvering of the ship 200 in this embodiment. FIG. 3 is a sequence diagram showing the flow of control model construction including parameter estimation of the motion model according to this embodiment. Parameter estimation of the motion model according to this embodiment uses a navigation log 310 acquired when the ship 200 actually sails. In this embodiment, the navigation log 310 includes self-position information 311 and driving information 312. The self-position information 311 is information obtained by self-position estimation, and includes the current position (latitude, longitude, altitude), direction Including position angle and speed. The method of self-location estimation is not particularly limited, and a known method may be used. For example, the method of self-location estimation described in JP 2023-041501 A by the present applicant may be used.

[0026] The driving information 312 includes the propeller rotation speed (hereinafter simply "rotation speed") and the rudder angle. Note that the information included in the navigation log 310 here is an example and may include other information. For example, the driving information 312 may further include torque, acceleration, and the rotation direction of the propeller. Each piece of information included in the navigation log 310 is acquired by the sensor unit 206, the antenna unit 207, and the camera 208 mounted on the ship 200, and is recorded in association with time information at the time of acquisition, etc. The navigation log 310 may be recorded during manual navigation or during automatic navigation. In this example, it is described as being recorded during automatic navigation.

[0027] In step S301, the parameter estimation system 100 acquires the navigation log 310. Here, the navigation log 310 may only be acquired within a predetermined range for estimating parameters of the motion model, or the navigation log 310 may be acquired and then a range to be used may be specified by a user. The parameter estimation system 100 may also perform a predetermined pre-processing on the acquired navigation log 310. The pre-processing here may include a process of deriving values ​​to be used in each subsequent step from information included in the navigation log 310.

[0028] In step S302, the parameter estimation system 100 determines the motion pattern of the ship 200 using the acquired navigation log 310. FIG. 4 shows examples of motion patterns. Here, five examples are shown, but more motion patterns may be handled. FIG. 4(a) shows a motion pattern of straight travel at a constant speed. FIG. 4(b) shows a motion pattern of turning right at a constant speed. FIG. 4(c) shows a motion pattern of a U-turn by turning right at a constant speed. FIG. 4(d) shows a motion pattern of turning right after going straight and fully opening the throttle. FIG. 4(e) shows a meandering motion pattern from turning left to turning right at a constant speed. Note that multiple motion patterns may be determined from the acquired navigation log 310. Alternatively, multiple motion patterns may be combined and used as a new motion pattern.

[0029] In step S303, the parameter estimation system 100 sets a gain (weight) for each parameter included in the calculation formula used for parameter estimation based on the determined motion pattern. In other words, the behavior of the ship 200 changes depending on the motion pattern of the ship 200. Therefore, the weight of each parameter included in the motion model is adjusted depending on the motion pattern. The gain for each parameter set here may be defined in advance in association with the motion pattern, or may be set by the user. Examples of parameters for setting weights will be described later.

[0030] In step S304, the parameter estimation system 100 performs parameter estimation of the motion model using the navigation log 310 and a calculation formula with gain setting. In this embodiment, MHE (Moving Horizon Estimation), which is a known finite-time optimal estimation method, is used for parameter estimation. MHE is a known method, and is an estimation method of a nonlinear model that can estimate a state at a predetermined time using measured values ​​at a finite time. An example of a parameter estimation method of a motion model using MHE will be described later. Note that the estimation method is not limited to MHE, and estimation methods using other nonlinear models may also be applied.

[0031] In step S305, the parameter estimation system 100 uses the estimated parameters to construct a control model for controlling the ship 200. The control model is constructed by determining control values ​​based on each parameter of the estimated motion model so that the ship 200 proceeds along a desired navigation route. The constructed control model is stored in association with the ship 200 and the motion pattern. When the parameter estimation system 100 and the ship 200 are configured as separate devices, the control model is stored so that it can be provided from the parameter estimation system 100 to the ship 200.

[0032] In step S306, the ship 200 performs predictive control for automatic navigation using the control model constructed by the parameter estimation system 100.

[0033] In step S307, the ship 200 performs automatic navigation by driving the drive unit 204 according to the control value based on the predictive control. In addition, when the ship 200 performs automatic navigation, the ship 200 may timely acquire a navigation log 310 and store it so that it can be provided to the parameter estimation system 100.

[0034] FIG. 5 is a conceptual diagram for explaining parameter estimation of the above-mentioned motion model. In estimating the parameters, a gain (weight) setting for each parameter is performed for the MHE calculation formula in accordance with the motion pattern. Then, input parameters are input to the MHE calculation formula in which the gain setting for each parameter has been performed. In this example, the speed, turning speed, and rudder angular velocity of the ship 200 are used as input parameters. These input parameters may be directly used from information included in the navigation log 310, or may be used after deriving different values ​​based on the information included in the navigation log 310. Then, as estimated parameters, the mass, added mass, moment of inertia (yaw), added moment of inertia (yaw), resistance and drag proportional to speed and acceleration, rotation speed vs. thrust characteristics, rotation speed, and rudder angular velocity of the ship 200 at a certain time (future) are obtained. Note that the estimated parameters are merely examples, and are not limited thereto, and other parameters may be estimated.

[0035] The time to be estimated and the range (time interval) used as input are not particularly limited. For example, the MHE equation of motion may be configured to estimate parameters 0.5 seconds later using information shown in the past navigation log 310 for 20 seconds from the current time as input parameters.

[0036] Here, an example of the method for the processes of steps S302 to S304 will be described. In this example, the ENU coordinate system is used as the coordinate system for description. The ENU coordinate system is a three-dimensional coordinate system consisting of an E axis (East), an N axis (North), and an U axis (Up), and the current position of the ship 200 is set as the origin. The E axis corresponds to the X direction, the N axis corresponds to the Y direction, and the U axis corresponds to the Z direction, with the North direction, East direction, and Up direction being positive directions. Furthermore, thrust that moves the hull in the positive direction of each axis is considered to be positive. The negative direction of the X axis (towards the stern) is considered to be a rudder angle of 0.

[0037] In this embodiment, the following equations (1) to (9) are used to estimate parameters using continuous-time model predictive control (MPC). Note that, although an example using a relatively simple model is shown here as an example, the present invention is not limited to this, and a more complicated model may be used. Also, in this embodiment, a small vessel having a relatively small size will be described. Therefore, the following model may be adjusted as appropriate according to the characteristics of the vessel.

[0038]

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[0039]

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[0040]

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[0041]

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[0042]

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[0043] Among the parameters shown above, the following values ​​indicate the state obtained by self-location estimation (UKF (Unscented Kalman Filter) / EKF (Extended Kalman Filter)). In self-location estimation, a value obtained by fusing information obtained from sensors such as GNSS (Global Navigation Satellite System) and IMU (Inertial Measurement Unit) is used. This information is acquired and derived from the navigation log 310 including self-location information 311 and driving information 312 shown in FIG. 3.

[0044]

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[0045] Among the above parameters, the following values ​​are specific to each ship. These are the parameters to be estimated by the MHE in this embodiment.

[0046]

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[0047] The thrust model for the boat 200 varies depending on the number and arrangement of actuators (not shown) included in the drive unit 204 provided on the boat 200. Here, an example of a thrust model for a single outboard motor that does not take into account fluid forces will be described. Boat actuators can be configured as inboard-outboard motors, inboard motors, etc., and thrust models corresponding to these may also be used. The outboard motor is equipped with a propeller (not shown) that generates thrust in the X direction and a steering wheel that rotates the thrust direction of the propeller around the Z axis, and these are configured to be attached as a unit to the outside of the hull.

[0048] The thrust force generated by an actuator (not shown) provided on the ship 200 and applied to the hull is calculated by the following equation (10).

[0049]

number

[0050] Of the above values, L x , L y is determined based on the value obtained by measuring the installation position of the outboard motor. By combining and rearranging the above equation (10) with equations (1) to (9) that show the motion model of the hull, the following equation (11) is derived.

[0051]

number

[0052] Here, it is assumed that the thrust generated by the propeller (not shown) of the boat 200 is generally estimated by accumulating information such as propeller characteristics, engine characteristics, and a torque sensor installed on the propeller shaft. However, since this method is difficult to apply to small boats, in this embodiment, the thrust generated by the propeller is treated as a function of the rotation speed and converted from the rotation speed. For parameter estimation, a generalized logic function (GLF) is used and defined as follows. In the following equations (12) to (14), A, K, B, v, C, and M are coefficients that depend on the configuration of actuators such as outboard motors, and therefore parameter estimation is required.

[0053]

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[0054] In this example, normalization is performed to eliminate differences in bounds / scales and other ship-related factors when estimating parameters with MHE, making the settings easier. This conversion process is not performed within the MPC, but is instead performed on the outboard motor thrust F obtained by the MPC. P This is then converted back to the rotation speed r and output to the actuator.

[0055] The above motion model is defined as the state equation of a nonlinear system in the following equation (15).

[0056]

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[0057] In this example, the optimization problem handled by the MPC is expressed by the following formula (16). At this time, the MPC is used to perform tracking control by treating x(t) = v(t). Note that the calculation flow of the nonlinear MPC is publicly known, so details are omitted here.

[0058]

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[0059] And, MHE is used as a method for estimating the state. In this example, the optimization problem can be defined as the following equation (17).

[0060]

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[0061] By solving this optimization problem, the parameters of the motion model are estimated from N pieces of state data. For the state data, the speed and angular velocity shown in equations (5) and (6) are used, and information on the number of rotations and rudder angle is input as u. At this time, if the observation noise v is large, it is difficult to predict the model, so the accuracy of the state data is important. For this reason, it is desirable to have higher accuracy in estimating the ship's own position, i.e., the self-position information 311.

[0062] Moreover, which parameter is to be emphasized during estimation is set as a weight as shown in equation (18).

[0063]

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[0064] Similarly, the observation noise v and the process noise w are also weighted as shown in the following equations (19) and (20).

[0065]

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[0066] The weights as described above are set according to the characteristics of the state, so there is little change due to the ship's motion pattern. On the other hand, the weights P PIt is necessary to determine and adjust the motion pattern because the degree of the influence varies depending on the motion pattern of the ship 200. For this reason, the motion pattern is determined in step S302, and gain setting is performed in step S303 based on the result.

[0067]

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[0068]

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[0069] Next, an example of parameter estimation corresponding to each movement pattern will be described.

[0070] (In the case of linear motion) For example, in the case of linear motion that accelerates in stages, the ship motion is calculated by the following conditions for the above equation (11).

[0071]

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[0072] In addition, when a boat has one outboard motor, the actuator is generally located in the center of the left and right sides of the hull. y = 0. The ship motion at this time is expressed by the following equation (22) based on the above equation (11).

[0073]

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[0074] F p Since is converted by GLF as described above, taking this into consideration, further rearrangement of equation (22) gives the following equation (23).

[0075]

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[0076] In this way, the number of parameters that need to be estimated is limited, making the estimation easier. At this time, the following weight setting for the remaining U becomes important.

[0077]

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[0078] In addition, since rectilinear motion allows the ship to travel using the maximum engine power, it is also easy to estimate the following GLF parameters, which are the conversion coefficients between thrust and rotational speed.

[0079]

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[0080] On the other hand, the impact on parameters required for movement in the Y direction (left and right direction of the ship) and turning movement is small, and if estimation is performed on these, there is a high possibility that the parameters will converge to incorrect parameters, so the weights below are adjusted to suppress the impact.

[0081]

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[0082] Taking these factors into consideration, weights are set and parameters are estimated using MHE to estimate parameters related to straight-line motion and conversion coefficients between thrust and rotation speed.

[0083] (For low and high speed turns) The motion pattern of the turning motion will be described. The terms "high speed" and "low speed" are not particularly limited, and are arbitrarily set based on a predetermined standard depending on the vessel. For example, a speed faster than a predetermined speed may be treated as "high speed", and a speed slower than the predetermined speed may be treated as "low speed".

[0084] For more accurate estimation of the turning motion pattern, it is preferable to estimate each parameter either at high speed or at low speed. When the ship is turning at a high speed, the Coriolis force and drag shown in the following equations (24) and (25), which are among the elements included in the above equation (1), have a large effect.

[0085]

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[0086]

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[0087] Therefore, it becomes relatively difficult to grasp the change in added mass shown in the following equation (26), which is one of the elements included in the above equation (1).

[0088]

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[0089] Considering the above reasons, by estimating the parameters of the added mass described below using the motion pattern of turning at low speed, it becomes possible to make a more accurate estimation even at high speed.

[0090]

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[0091] The following parameters regarding Y-direction speed and turning are also important.

[0092]

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[0093] On the other hand, the following parameters related to the square of the velocity may be estimated during a high-speed turning motion pattern.

[0094]

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[0095] At this time, the following parameters proportional to the speed also have a large effect, so it is desirable to use these with importance.

[0096]

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[0097] (Estimated flow) By performing parameter estimation in the following order, it is possible to estimate the hull and thrust model parameters in a short time. (1) Repeated gradual acceleration and deceleration while driving in a straight line (2) Steady circular turns, figure eight movements, and meandering patterns at sufficiently low speeds (3) High speed steady circular, figure eight, and meandering patterns

[0098] In addition, more accurate parameter estimation is possible by combining the following techniques: Within each pattern, P is estimated iteratively while gradually changing the weights. After making an estimate in the above order, P P We change the weights and re-estimate the above patterns (1) to (3). To cancel the effects of wind and currents, data on forward motion is also used to estimate the wave's speed. In other words, in addition to estimating the wave's speed in a straight line, data on the reverse direction is also used to estimate the wave's speed in a straight line.

[0099] [Processing flow] Fig. 6 is a flowchart of processing including parameter estimation of a motion model according to this embodiment. This processing flow is realized, for example, by the control unit 101 of the parameter estimation system 100 reading and executing a program and various data stored in the storage unit 102. Here, the parameter estimation system 100 and the ship 200 are described as being configured as separate devices. Of the steps shown in Fig. 5, the steps processed by the parameter estimation system 100 are shown in focus.

[0100] Before this processing flow is started, the target ship 200 is assumed to have navigated and the navigation log 310 at that time is assumed to be available. The contents of the navigation log 310 are not particularly limited, but it is assumed that data corresponding to a motion pattern of interest, such as that shown in FIG. 4, has been acquired.

[0101] In step S601, the parameter estimation system 100 acquires the navigation log 310. At this time, the parameter estimation system 100 may perform pre-processing such as filtering on the acquired navigation log 310. The pre-processing may include a process of deriving values ​​used in each subsequent step from information included in the navigation log.

[0102] In step S602, the parameter estimation system 100 determines the motion pattern indicated by the navigation log 310 acquired in step S601. The type of the motion pattern to be determined may be specified in advance.

[0103] In step S603, the parameter estimation system 100 sets a gain (weight) for each parameter corresponding to the movement pattern determined in step S602. The gain set here may be predefined corresponding to the movement pattern. At this time, a gain for a parameter identified independently of the movement pattern may also be set.

[0104] In step S604, the parameter estimation system 100 estimates various parameters of the maneuver model at a desired time by inputting each input parameter shown in the navigation log 310 into the MHE calculation formula whose gain was set in step S603. The parameter estimation is based on each calculation formula as described above.

[0105] In step S605, the parameter estimation system 100 constructs a control model using the parameters of the motion model estimated in step S604. At this time, a low pass filter (LPF) or the like may be applied to suppress abrupt changes in the values ​​of the estimated parameters. This makes it possible to improve the stability of behavior in navigation control using the control model.

[0106] In step S606, the parameter estimation system 100 records the control model constructed in step S605 in association with the motion pattern, and then ends this processing flow.

[0107] In the above example, the movement pattern is determined from the navigation log 310, and the gain setting corresponding to the movement pattern is performed (steps S602 to S603). However, if the movement pattern indicated by the navigation log 310 is specified in advance, these steps may be omitted, and the process of step S604 may be performed using a calculation formula that has been used to set the gain corresponding to the movement pattern in advance.

[0108] [Variations] In the above embodiment, an example has been described in which a navigation log obtained during automatic navigation of the ship 200 is used. As a modified example, a mode in which a navigation log is recorded during manual navigation will be described.

[0109] Fig. 7 is a sequence diagram showing the flow of constructing a control model including estimating parameters of a motion model in this modified example. The configuration of a navigation log 720 and the processes of steps S704 to S709 are similar to the navigation log 310 and steps S301 to S307 shown in Fig. 3. Here, the method of generating the navigation log is different.

[0110] In step S701, the vessel 200 issues a manual operation instruction to the operator of the vessel 200 via the output unit 205 etc. The instruction here is presented based on a predetermined motion pattern.

[0111] In step S702, the ship 200 receives, via the operation unit 203, a control command for manual steering.

[0112] In step S703, the ship 200 navigates by operating the drive unit 204 based on the control command received in step S702. At this time, the ship 200 sequentially records information acquired by the sensor unit 206 and the like as a navigation log 720. It may be determined whether or not a predetermined motion pattern corresponding to the instruction presented in step S701 matches a motion pattern indicated by the navigation log 720 obtained as a result of the drive control in step S703. At this time, if the motion patterns do not match, the ship 200 may again be instructed to manually steer the ship.

[0113] Then, using the navigation log obtained from manual steering in this way, we estimate the parameters of the motion model in the same manner as in Figure 3, and construct a control model.

[0114] Fig. 8 is a flowchart of processing including parameter estimation of a motion model based on the processing sequence shown in Fig. 7. Here, the description will be given assuming that the parameter estimation system 100 and the ship 200 are configured as an integrated unit. Therefore, this processing flow is realized, for example, by the control unit 201 of the ship 200 reading and executing programs and various data stored in the storage unit 202.

[0115] Before this processing flow is started, information regarding the motion pattern is registered in advance, and instructions for manual steering of the ship can be presented to the user.

[0116] In step S801, the ship 200 determines a ship maneuvering pattern for manual maneuvering. In this determination, a ship maneuvering pattern corresponding to a motion pattern with less accumulated data in the navigation log 720 may be preferentially determined, or a ship maneuvering pattern may be determined by focusing on a specific motion pattern.

[0117] In step S802, the vessel 200 prompts the operator to steer based on the maneuvering pattern determined in step S801. The prompting here may include rudder angle, acceleration / deceleration, steering timing, etc. The method of presentation is not particularly limited, and may be presented by displaying on a screen (not shown), or may be given by voice or the like.

[0118] In step S803, the vessel 200 receives a maneuvering instruction from the operator. Then, the vessel 200 operates the drive unit 204 based on the received maneuvering instruction to navigate the vessel 200. After manual navigation based on the maneuvering pattern is completed, the process proceeds to step S805.

[0119] In step S804, the ship 200 acquires a navigation log 720 based on the navigation in step S803. At this time, the parameter estimation system 100 may perform preprocessing such as filtering on the acquired navigation log 720. The preprocessing may include a process of deriving values ​​used in each subsequent step from information included in the navigation log 720.

[0120] In step S805, the vessel 200 determines the motion pattern based on the navigation log 720 acquired in step S804. The result of the determination may be recorded in association with the navigation log 720.

[0121] In step S806, the vessel 200 determines whether the maneuvering pattern determined in step S801 matches the motion pattern determined in step S805. This determination may be made, for example, based on the similarity of the navigation routes. If it is determined that the patterns match (step S806: YES), the processing of the vessel 200 proceeds to step S807. On the other hand, if the patterns do not match, that is, if the vessel is not sailing according to the maneuvering instructions (step S806: NO), the processing of the vessel 200 returns to step S802 and the processing is repeated. At this time, the processing may return to step S801, and a different maneuvering pattern may be executed.

[0122] In step S807, the vessel 200 sets a gain for each parameter corresponding to the motion pattern determined in step S805. The gain set here may be defined in advance in accordance with the motion pattern.

[0123] In step S808, the ship 200 estimates parameters of the motion model at a desired time by inputting each input parameter shown in the navigation log 720 to the MHE calculation model for which the gain was set in step S807. The parameter estimation is based on each calculation formula as described above.

[0124] In step S809, the ship 200 constructs a control model using the parameters of the motion model estimated in step S808. At this time, a low pass filter (LPF) or the like may be applied to suppress abrupt changes in the values ​​of the estimated parameters. This makes it possible to improve the stability of behavior in navigation control using the constructed control model.

[0125] In step S810, the vessel 200 records the control model constructed in step S809 in association with the motion pattern, and then ends this processing flow.

[0126] The ship 200 can navigate automatically using the control model constructed in step S810 based on instructions from the operator. The above-described processing flow may be configured to be repeated for feedback, thereby enabling improvement in the accuracy of the control model.

[0127] In addition, during manual navigation, a control value obtained by the manual control may be compared with a control value obtained by a control model based on a motion model in which parameters are estimated, and the control value obtained by the manual control may be adjusted based on the difference between the control values. Alternatively, the difference may be notified to the operator.

[0128] As described above, this embodiment makes it possible to easily estimate parameters of a ship-specific motion model. In addition, by using MHE, complex processing including many parameters becomes possible. In addition, it becomes possible to improve the robustness of parameter estimation.

[0129] <Other embodiments> There are no particular limitations on the specifications, characteristics, size, shape, etc. of the ship to which the above-mentioned motion model parameter estimation process can be applied. For example, the method according to the present invention can be applied even to a ship with a small amount of accumulated navigation logs.

[0130] In addition, in the present invention, a program or application for realizing the functions of one or more of the above-mentioned embodiments can be supplied to a system or device via a network or a storage medium, etc., and one or more processors in a computer of the system or device can read and execute the program, thereby realizing the present invention.

[0131] Moreover, it may be realized by a circuit that realizes one or more functions (for example, an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA)).

[0132] Although various embodiments have been described above with reference to the drawings, it goes without saying that the present disclosure is not limited to the examples. It is clear to a person skilled in the art that various modifications, corrections, substitutions, additions, deletions, and equivalents may be made within the scope of the claims, and it is understood that these also naturally belong to the technical scope of the present disclosure. In addition, the components in the various embodiments described above may be arbitrarily combined within the scope of the invention.

[0133] As such, the present invention is not limited to the above-described embodiments, and the present invention also contemplates mutual combinations of the various components of the embodiments, as well as modifications and applications by those skilled in the art based on the descriptions in the specification and well-known technologies, and these are included in the scope of protection sought.

[0134] As described above, the present specification discloses the following:

[0135] (Technology 1) A parameter estimation system (e.g., 100) for estimating parameters of a motion model of a vessel (e.g., 200), comprising: An estimation unit (e.g., 101) that uses a navigation log when the ship navigates in a predetermined motion pattern to estimate parameters of a motion model specific to the ship that corresponds to the predetermined motion pattern indicated by the navigation log; A parameter estimation system having This configuration makes it possible, for example, to easily estimate parameters of a ship-specific motion model.

[0136] (Technology 2) The parameter estimation system described in Technology 1, wherein the estimation unit determines the predetermined movement pattern indicated by the navigation log, and sets gains for parameters included in the movement model in accordance with the determined predetermined movement pattern. With this configuration, for example, a gain can be set in accordance with the motion pattern, enabling more accurate parameter estimation of the motion model in accordance with the motion pattern of each ship.

[0137] (Technology 3) The parameter estimation system according to Technology 1 or Technology 2, wherein the predetermined motion pattern includes a pattern of repeating stepwise acceleration and deceleration while moving straight, a steady turning pattern, a figure-of-eight motion, and a meandering pattern. This configuration makes it possible to estimate parameters of a ship-specific motion model by assuming various motion patterns of the ship.

[0138] (Technology 4) The estimation unit is (1) A pattern of repeated gradual acceleration and deceleration while traveling in a straight line. (2) A steady-state turning / figure-eight / snaking pattern at a first speed that is faster than the specified speed; (3) a steady circular / figure-eight / snaking pattern at a second speed that is slower than the predetermined speed; The parameter estimation system according to technique 3, which estimates the parameters of the motion model in the order of: With this configuration, by defining the estimation order according to the movement pattern, it becomes possible to estimate the parameters of the movement model with higher accuracy.

[0139] (Technology 5) The parameter estimation system according to any one of Technology 2 to Technology 4, wherein the estimation unit estimates the parameters of the motion model by repeating the same motion pattern while changing a gain. This configuration makes it possible to further improve the accuracy of parameter estimation.

[0140] (Technology 6) The parameter estimation system according to any one of Technology 2 to Technology 5, wherein the estimation unit estimates parameters of a motion model using a navigation log of a motion pattern in a predetermined direction and a navigation log of a motion pattern in a direction opposite to the predetermined direction. This configuration makes it possible to suppress the effects of external factors such as waves and wind, and further improve the accuracy of parameter estimation of the motion model for a straight-line motion pattern.

[0141] (Technology 7) The parameter estimation system according to any one of Technology 1 to Technology 6, wherein the estimation unit estimates a predetermined parameter among a plurality of parameters included in a motion model of the ship by using a navigation log corresponding to a predetermined motion pattern. With this configuration, it becomes possible to switch the target of parameter estimation depending on the motion pattern, for example, when turning at high speed or when turning at low speed.

[0142] (Technology 8) The navigation log includes self-position information and driving information, The self-position information includes at least one of a current position, a heading angle, and a speed of the ship, The parameter estimation system according to any one of Techniques 1 to 7, wherein the drive information includes at least one of a propeller rotation speed and a steering angle. With this configuration, it becomes possible to estimate parameters of a motion model specific to the ship using, for example, the ship's own position information and driving information during navigation.

[0143] (Technology 9) The parameter estimation system according to any one of Techniques 1 to 8, which estimates parameters of a nonlinear motion model using MHE (Moving Horizon Estimation). According to this configuration, for example, it is possible to estimate parameters of a more complicated motion model compared to a linear model, and it is also possible to improve the robustness of the parameter estimation.

[0144] (Technology 10) A recording unit (e.g., 202) for recording the navigation log of the ship; An instruction unit (e.g., 201, 205) that instructs manual steering of the ship based on the predetermined motion pattern; a determination unit (e.g., 201) that determines whether or not a navigation log of manual ship steering, which is performed in response to an instruction from the instruction unit and recorded in the recording unit, matches the predetermined motion pattern; having The parameter estimation system according to any one of Technology 1 to Technology 9, wherein the instruction unit instructs manual steering of the ship again based on the predetermined motion pattern when the determination unit determines that there is no match. According to this configuration, for example, it is possible to acquire a desired navigation log by performing manual navigation, and it is also possible to improve the operability of the operator performing manual navigation.

[0145] (Technology 11) The parameter estimation system according to any one of Technology 1 to Technology 10, wherein the ship navigation log is either a navigation log recorded during manual ship steering performed based on the predetermined motion pattern, or a navigation log recorded during automatic ship steering performed based on the predetermined motion pattern. With this configuration, it is possible to estimate parameters of a motion model specific to the ship by using a navigation log containing a predetermined motion pattern, which is a navigation log when the ship is navigated either automatically or by automatic steering.

[0146] (Technology 12) The parameter estimation system according to any one of Techniques 1 to 11, wherein the motion model estimation system is installed on the ship. This configuration makes it possible to, for example, perform real-time parameter estimation and automatic navigation.

[0147] (Technology 13) A parameter estimation method for estimating parameters of a ship motion model, comprising the steps of: an estimation step of estimating parameters of a motion model specific to the ship corresponding to the predetermined motion pattern indicated by a navigation log obtained when the ship navigates in a predetermined motion pattern; A parameter estimation method having the following structure: This configuration makes it possible, for example, to easily estimate parameters of a ship-specific motion model.

[0148] (Technology 14) A computer (e.g., 100), An estimation unit (e.g., 101) that uses a navigation log when a ship navigates in a predetermined motion pattern to estimate parameters of a motion model specific to the ship corresponding to the predetermined motion pattern indicated by the navigation log; A program to function as a This configuration makes it possible, for example, to easily estimate parameters of a ship-specific motion model. [Industrial Applicability]

[0149] The present invention is useful, for example, as an apparatus, a system, a method, and a program for estimating parameters of a motion model used during automatic steering of a ship. [Explanation of symbols]

[0150] 100...Parameter estimation system. 101...Control unit 102...Storage section 103...Input section 104...Output section 105…Communications Department 200…ship 201...Control unit 202...Storage section 203...Operation unit 204...Drive unit 205...Output section 206…Sensor section 207…Antenna section 208...Camera

Claims

1. A parameter estimation system for estimating parameters of a ship motion model, comprising: an estimation unit that uses a navigation log when the ship navigates in a predetermined motion pattern to estimate parameters of a nonlinear motion model specific to the ship corresponding to the predetermined motion pattern indicated in the navigation log by using MHE (Moving Horizon Estimation); having The parameter estimation system wherein the estimation unit determines the predetermined motion pattern indicated by the navigation log, and sets gains for parameters included in the motion model in accordance with the determined predetermined motion pattern.

2. The parameter estimation system according to claim 1 , wherein the predetermined movement patterns include a pattern of repeating stepwise acceleration and deceleration while moving straight, a steady circular turn, a figure-of-eight movement, and a meandering pattern.

3. The estimation unit is (1) A pattern of repeatedly accelerating and decelerating in stages while traveling in a straight line. (2) A steady circular / figure-eight / snaking pattern at a first speed that is faster than a predetermined speed; (3) A steady circular / figure-of-eight / snaking pattern at a second speed slower than the predetermined speed; The parameter estimation system according to claim 2 , wherein the parameters of the motion model are estimated in the order of:

4. The parameter estimation system according to claim 1 , wherein the estimator estimates the parameters of the motion model by repeating the same motion pattern while changing a gain.

5. The parameter estimation system according to claim 1 , wherein the estimator estimates the parameters of the motion model using a navigation log of a motion pattern in a predetermined direction and a navigation log of a motion pattern in a direction opposite to the predetermined direction.

6. 2. The parameter estimation system according to claim 1, wherein the estimation unit estimates a predetermined parameter from among a plurality of parameters included in the ship motion model by using a navigation log corresponding to a predetermined motion pattern.

7. The navigation log includes self-position information and driving information, The self-position information includes at least one of a current position, an azimuth angle, and a speed of the ship, The parameter estimation system according to claim 1 , wherein the drive information includes at least one of a rotation speed and a steering angle of a propeller.

8. 2. The parameter estimation system according to claim 1, wherein the ship's navigation log is either a navigation log recorded during manual steering performed based on the specified motion pattern, or a navigation log recorded during automatic steering performed based on the specified motion pattern.

9. The parameter estimation system according to claim 1 , wherein the parameter estimation system is installed on board the vessel.

10. A parameter estimation method for estimating parameters of a ship motion model, comprising the steps of: an estimation step of estimating parameters of a nonlinear motion model specific to the ship, which corresponds to the predetermined motion pattern indicated by a navigation log when the ship navigates in the predetermined motion pattern, by using MHE (Moving Horizon Estimation); having A parameter estimation method in which, in the estimation step, the predetermined movement pattern indicated by the navigation log is determined, and gains for parameters included in the movement model are set in accordance with the determined predetermined movement pattern.

11. Computer, an estimation unit that uses a navigation log when the ship navigates in a predetermined motion pattern to estimate parameters of a non-linear motion model specific to the ship corresponding to the predetermined motion pattern indicated in the navigation log by using MHE (Moving Horizon Estimation); Functioning as a The estimation unit determines the predetermined movement pattern indicated by the navigation log, and sets gains for parameters included in the movement model in accordance with the determined predetermined movement pattern.

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