Obstacle estimation system

Abstract

To provide an obstacle estimation system for improving estimation accuracy for an obstacle and to improve safety of a vessel.SOLUTION: The obstacle estimation system comprises a plurality of data acquisition means and a control unit for executing information processing, and estimates information on an obstacle when a vessel navigates. The control unit executes: own vessel information estimation processing for estimating own vessel position information and own vessel attitude information based on first data acquired from at least one data acquirement means; own vessel information compensation processing for compensating the own vessel position information and the own vessel attitude information based on second data acquired from at least one data acquirement means; obstacle information estimation processing for estimating a position and size of the obstacle based on the own vessel position information and the own vessel attitude information compensated in the own vessel information compensation processing as well as third data acquired from at least one data acquirement means; and output information generation processing for generating output information based on information of the position and size of the obstacle estimated in the obstacle information estimation processing.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an obstacle estimation system. [Background technology]

[0002] Conventionally, when a ship navigates, it is necessary to avoid obstacles such as floating objects on the water surface and other ships, and technology to do so is required. For example, Patent Document 1 discloses a system that integrates sensor data from multiple sensors to detect foreign objects present on the ship's travel path and assist the ship in avoiding collisions. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-036010 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, because ships are subject to rocking and swaying due to the effects of waves and wind and are affected by tidal currents while they are moving, the ship's position and attitude are unstable, making it difficult to ensure accuracy in estimating obstacles.

[0005] Therefore, the present disclosure has been made in consideration of the above problems, and has an object to provide an obstacle estimation system that improves the accuracy of obstacle estimation and enhances the safety of ships. [Means for solving the problem]

[0006] According to the present disclosure, there is provided an obstacle estimation system that includes a plurality of data acquisition means and a control unit that executes information processing, and estimates information about an obstacle when a ship is navigating, comprising: The control unit is a ship information estimation process for estimating ship position information and ship attitude information based on first data acquired from at least one data acquisition means; a ship information correction process for correcting the ship position information and the ship attitude information based on second data acquired from at least one data acquisition means; an obstacle information estimation process for estimating a position and a size of an obstacle based on the ship position information and ship attitude information corrected in the ship information correction process and third data acquired from at least one data acquisition means; and an output information generation process for generating output information based on information on the position and size of the obstacle estimated in the obstacle information estimation process. Effect of the Invention

[0007] According to the present disclosure, it is possible to provide an obstacle estimation system that improves the accuracy of obstacle estimation and enhances the safety of ships. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 illustrates an obstacle estimation system according to an embodiment of the present disclosure. [Diagram 2] 1 is a diagram showing a ship to which an example of an obstacle estimation system according to the embodiment is applied. FIG. [Diagram 3] 4 is a flowchart illustrating a series of controls in the obstacle estimation system according to the embodiment. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functional configurations are denoted by the same reference numerals, and redundant description will be omitted.

[0010] FIG. 1 shows an example of an obstacle estimation system (hereinafter, simply referred to as the "system") according to this embodiment. The system of this embodiment can be installed on any type of vessel, and is particularly suitable for relatively small vessels. Specifically, the system of this embodiment can be adopted in fishing boats, water taxis, small multipurpose vessels, recreational fishing boats, passenger boats, transportation boats, work boats, fireboats / patrol boats, pleasure yachts, pleasure motorboats, special work vessels, etc., and can also be adopted in large passenger ships, tankers, cargo ships, etc.

[0011] The system of this embodiment is an obstacle estimation system that has multiple data acquisition means and a control unit that performs information processing, and estimates information about obstacles when a ship navigates, and the control unit executes an own ship information estimation process that estimates own ship position information and own ship attitude information based on first data acquired from at least one data acquisition means, an own ship information correction process that corrects the own ship position information and own ship attitude information based on second data acquired from at least one data acquisition means, an obstacle information estimation process that estimates the position and size of an obstacle based on the own ship position information and own ship attitude information corrected by the own ship information correction process and third data acquired from at least one data acquisition means, and an output information generation process that generates output information based on the information on the position and size of the obstacle estimated by the obstacle information estimation process.

[0012] The system of this embodiment is an obstacle estimation system 1 for estimating obstacles when a ship navigates. The system 1 includes, for example, a data acquisition unit 10, a control unit 20, a storage unit 30, an input unit 40, an output unit 50, a communication unit 60, and a ship operation control unit 70. Each component is connected by wire or wirelessly and can communicate with each other. In this example, the control unit 20, the storage unit 30, the input unit 40, the output unit 50, and the communication unit 60 are implemented in an information processing device (computer), but this is not limited to the above and each component may be independent.

[0013] The data acquisition unit 10 includes a plurality of data acquisition means such as various sensors and cameras, and acquires various sensor data and image data. The data acquisition unit may include, for example, a camera, a radar device such as Lidar (Light detection and ranging), a marine radar, or a millimeter wave radar, an ultrasonic distance measurement sensor, a GNSS module, a QZSS module, or other positioning device, an AIS, an inertial measurement unit (IMU), an inertial sensor, a wind direction sensor, a wind speed sensor, a speed sensor (ground speed sensor, water speed sensor), a direction sensor, an acceleration sensor, a gyro sensor, a magnetic compass, a satellite compass, a temperature sensor, a humidity sensor, a pressure sensor, an altitude sensor, an infrared sensor, or the like. The data acquisition unit 10 can acquire information on the current position (coordinates), attitude (heading such as bow direction), moving speed, moving direction, bow direction, and turning amount of the ship, information on the surrounding environment, and information on obstacles such as other ships and people. The AIS is a system for transmitting and receiving various information between ships or between a ship and a land facility, and can exchange ship information such as the position, attitude (course), moving speed, and destination of each ship by wireless communication. The direction sensor may be a magnetic direction sensor that calculates the heading direction using geomagnetism, a gyrocompass, a GPS compass, or the like.

[0014] The control unit 20 includes a processor (arithmetic device) such as a CPU, and is configured to be able to execute various information processes based on programs stored in the storage unit 30. The control unit 20 can execute ship information estimation processing to estimate ship position information and ship attitude information based on data (first data) from the data acquisition unit 10. The ship position information can be estimated using coordinate information as positioning data acquired by the GNSS module as the current position. The ship position information may be estimated by a self-position estimation processing based on a comparison between map data (three-dimensional point cloud data) acquired from Lidar and map information stored in the storage unit. The ship position information may be expressed by two-dimensional or three-dimensional coordinate information on a specific coordinate system, and may be expressed by latitude and longitude. The attitude of the ship is expressed by orientation (angle) information in a specific two-dimensional or three-dimensional coordinate system. The attitude information may be expressed by east-west-north-south orientation.

[0015] The control unit 20 can execute a ship information correction process to correct the ship position information and the ship attitude information based on the data (second data) from the data acquisition unit 10. The control unit 20 can correct the ship position information and the ship attitude information based on speed data acquired from, for example, Lidar or a camera.

[0016] The control unit 20 can execute a speed estimation process to estimate the ship's speed based on data from the data acquisition unit 10. For example, the control unit 20 can calculate the distance traveled in a given time from position information from a given time ago (0.01 seconds, 0.1 seconds, 1 second, etc.) and current position information, and estimate the speed from the information on the distance traveled in the given time.

[0017] The control unit 20 can execute an obstacle information estimation process to estimate the position and size of an obstacle based on the ship's position information and ship's attitude information corrected by the ship's information correction process, and the data (third data) from the data acquisition unit 10. The control unit 20 can also estimate the type of obstacle based on the ship's position information and ship's attitude information corrected by the ship's information correction process, and the data (third data) from the data acquisition unit 10.

[0018] The control unit 20 can estimate the type of obstacle by, for example, selecting one of candidates of obstacle types stored in advance in the storage unit 30. The information on the type of obstacle can include type information such as ships, specific ship classifications (fishing boats, water taxis, small multipurpose boats, recreational fishing boats, passenger boats, transportation boats, work boats, fireboats / patrol boats, pleasure yachts, pleasure motorboats, special work boats, etc.), marine structures, people (including swimming, surfing, yachts, paddle boards, etc.), rocks, shores, driftwood, seaweed, marine life, etc. The information on the type of obstacle is stored in association with size information (area, height).

[0019] The control unit 20 can estimate the position, posture, type, and size of the obstacle by, for example, image analysis of image data acquired by the camera. The control unit 20 may estimate the position, posture, type, and size of the obstacle by using a machine learning technique using a learning model that has been trained in advance in the obstacle information estimation process. When the control unit 20 estimates the position of the obstacle based on the image data acquired by the camera, after estimating the three-dimensional position (coordinates) of the obstacle in the camera coordinate system, the control unit 20 can convert the camera coordinate system into a world coordinate system by a coordinate conversion process based on the position (coordinates) of the camera and the information on the shooting direction, and calculate the position (coordinates) of the obstacle on the world coordinate system. The control unit 20 can estimate the bow direction of the ship as an obstacle, the direction of a person's face (front direction), and the direction (traveling direction) of an object used such as a surfboard by image analysis of the image data from the camera or analysis of three-dimensional data (point cloud data, model data, etc.). The control unit 20 can estimate the three-dimensional position and attitude of an obstacle on or underwater based on sensor data from any one or a combination of sensors such as a radar device, Lidar, etc., not limited to image data from a camera as described above.

[0020] The storage unit 30 may store candidates for types of obstacles and values ​​of sizes (information on area and height in plan view) corresponding to each type, and size ranges (upper limit and lower limit) in association with each other in advance. For example, the range of the area of ​​a ship may be 3 m^2 or more and 9200 m^2 or less, and the range of the height of the ship (height above the water surface) may be 0.5 m or more and 100 m or less. The range of the area of ​​a person may be 0.2 m^2 or more and 5 m^2 or less, and the range of the height of a person (height above the water surface) may be 0.1 m or more and 3 m or less. The storage unit 30 stores information on the appropriate avoidance distance associated with obstacle information such as the position, type, and size of the obstacle. The storage unit 30 may also store information on a calculation formula for calculating the appropriate avoidance distance. For example, the appropriate avoidance distance may be calculated according to the size (area in plan view) of the ship as an obstacle. The parameters used in the calculation may include information on the type of obstacle, the moving speed, the moving direction, and the like. The memory unit 30 may contain information about a program that simulates movement of the ship along its navigation route (planned route) and whether or not it will come into contact with an obstacle. The memory unit 30 stores information about each data acquisition means. The information about the data acquisition means may be, for example, the position of the data acquisition means on the ship (e.g., a relative position with respect to a specific point such as the center or center of gravity of the ship), a relative attitude (e.g., a direction relative to the bow direction of the ship), etc., but is not limited to this.

[0021] The control unit 20 may estimate the moving speed, moving direction, and attitude of an obstacle based on the ship's position information and ship's attitude information corrected in the ship's information correction process, the ship's moving speed information, moving direction information, and data (third data) from the data acquisition unit 10. The control unit 20 can acquire moving speed information and moving direction information of obstacles such as other ships relative to the ship, based on data from Lidar. The control unit 20 can also acquire moving speed information, moving direction information, etc. of obstacles using data from a radar device.

[0022] In the obstacle information estimation process, the control unit 20 can analyze image data acquired by the camera to estimate information such as the type, size, position, shape, and color of the obstacle. The control unit 20 may estimate the information of the obstacle based on any information of the obstacle estimated from the image data and the obstacle-related information stored in advance in the storage unit. For example, the control unit 20 may estimate the size of the obstacle from the image data, and determine (estimate) an obstacle candidate associated with a size range that matches the size as the type of the obstacle by referring to the storage unit. The control unit 20 may also analyze image data acquired by the camera to estimate the type of the obstacle, and determine (estimate) a size candidate associated with the type as the size of the obstacle by referring to the storage unit. The control unit 20 may also estimate any one of the type, size, and position of the obstacle based on any one or a combination of detection data acquired from a radar device and detection data from Lidar, without being limited to image data acquired by the camera. For example, three-dimensional data of an obstacle can be generated from distance data to multiple points of the obstacle by Lidar, and the three-dimensional shape, type, size, position, etc. of the obstacle can be estimated based on the three-dimensional data of the obstacle. In this way, the control unit 20 can select from among the obstacle candidates by comparing the information of the obstacle candidates stored in the storage unit 30 with the data on the obstacle acquired from the data acquisition unit 10, and estimate the type, size, etc. of the detected obstacle. The control unit 20 can also estimate the position and size of the obstacle based only on the data from the data acquisition unit 10.

[0023] The control unit 20 can store various information such as generated information in the storage unit 30, update the information in the storage unit 30, output the information from the output unit 50, and transmit the information to an external device, another ship, etc. via the communication unit 60. The control unit 20 can also accept information acquired by the data acquisition unit 10, user operation information input via the input unit 40, and information received by the communication unit 60, and execute information processing based on the information.

[0024] The memory unit 30 can store various types of information stored in advance, information acquired from the data acquisition unit 10, information received from external devices or other ships via the communication unit 60, information generated by the control unit 20, information input via the input unit 40, etc., and is composed of a non-volatile memory, a hard disk, etc. The memory unit 30 can store information on various parameters indicating the shape of the ship (three-dimensional model data, etc.), characteristics (characteristics related to output, speed, and turning amount), information on obstacles, two-dimensional or three-dimensional map information, navigation history information, navigation plan information, tidal information, etc.

[0025] The input unit 40 receives input information based on operations from a user, etc. The input unit 40 is composed of mechanical buttons, switches, operation levers, touch panels, etc. The input unit 40 may also include a microphone that allows voice input.

[0026] The output unit 50 outputs various information as images (video), sounds, etc. The output unit 50 may include, for example, a display unit such as a liquid crystal monitor or a touch panel that displays images, an audio output unit such as a speaker that displays sounds, a vibration generating unit (vibration device) that generates vibrations, etc.

[0027] The communication unit 60 is connected to a network such as the Internet or wireless communication, and is capable of transmitting data to external devices (servers, control devices, etc.) and other ships, and receiving data from external devices.

[0028] The vessel operation control unit 70 may include an auto-rudder that controls steering, an auto-throttle that controls a power unit (engine, motor, etc.) for rotating a propeller or thruster, etc. The vessel operation control unit 70 controls the operation of the vessel 70 (movements such as forward movement, backward movement, left / right movement, turning, etc.) based on instruction information from at least one of the control unit 20, the memory unit 30, the input unit 40, and the communication unit 60, and can navigate the vessel along a predetermined route.

[0029] Fig. 2 shows an example of the present system installed on a ship 100. In the example of Fig. 2, the system includes a Lidar, a camera, a GNSS antenna, an AIS antenna, and a wind speed and direction meter as a data acquisition unit 10, a control unit as a control unit 20, a monitor as an output unit 50, and an auto-rudder and an auto-throttle as a ship operation control unit 70. In the example of Fig. 2, the Lidar and the camera are installed on the front side (bow side) and the rear side (stern side) of the ship 100, respectively, so that data around the ship 100, particularly the front and rear sides, can be detected with high accuracy. The configuration of the present system installed on a ship is not limited to the illustrated example, and other sensors and the like may be included.

[0030] FIG. 3 shows an example of a process flow relating to a method for estimating obstacle information in the system of this embodiment.

[0031] The control unit 20 executes an own ship information estimation process (S101) for estimating own ship position information and own ship attitude information based on first data acquired from at least one data acquisition means, an own ship information correction process (S102) for correcting own ship position information and own ship attitude information based on second data acquired from at least one data acquisition means, an obstacle information estimation process (S103) for estimating the position and size of an obstacle based on the own ship position information and own ship attitude information corrected in the own ship information correction process and third data acquired from at least one data acquisition means, and an output information generation process (S104) for generating output information based on the information on the position and size of the obstacle estimated in the obstacle information estimation process. The first data, the second data, and the third data may each include data acquired from a common data acquisition means. Also, the first data, the second data, and the third data may each include data acquired from one data acquisition means or from multiple data acquisition means.

[0032] In the ship information estimation process (S101), for example, the ship's three-dimensional position is estimated based on coordinate information from a GNSS antenna as a data acquisition means, and the ship's three-dimensional attitude information is estimated based on orientation data acquired from an inertial measurement unit. The ship information estimation process (S101) may be performed based on data acquired from only one data acquisition means, but from the viewpoint of improving estimation accuracy, it is preferable to perform the estimation process based on data acquired from multiple data acquisition means.

[0033] In the ship information correction process (S102), the ship position information and ship attitude information estimated in S101 are corrected based on, for example, speed information acquired from at least one of Lidar and a camera. The control unit 20 estimates the current position and attitude (a predetermined time after the time) using, for example, the position (coordinates), movement direction information, and movement speed information at a time point a predetermined time ago (0.01 seconds, 0.1 seconds, 1 second, etc.). The estimated position and attitude information is then compared with the ship position information and ship attitude information estimated in the ship information estimation process (S101). If they do not match, the ship position information and ship attitude information can be corrected by adopting the numerical value between the two as accurate current position and current attitude information. Note that the ship information correction process may be performed by another method, and for example, the ship position information and ship attitude information may be corrected using the position information and attitude information calculated by the ship position and attitude estimation process based on image data from a camera, or a combination of these. Moreover, from the viewpoint of increasing the accuracy of the correction process, it is preferable to execute the correction process based on data acquired from a plurality of data acquisition means.

[0034] Next, in the obstacle information estimation process (S103), for example, the position and attitude of the camera are estimated (the position and attitude of the camera in the ship's coordinate system) based on the ship's position information and ship's attitude information corrected in the ship information correction process, and the position of the obstacle in the world coordinate system is estimated by coordinate conversion using the relative position data of the obstacle in the camera coordinate system. In addition, the type and size of the obstacle are estimated by analyzing the image data of the camera. The position, type and size of the obstacle may be estimated using detection data acquired from the radar device alone or in combination.

[0035] Then, in the output information generation process (S104), for example, image data or audio data including information on the position and size of the obstacle is generated as output information, and the position of the obstacle can be displayed on a map on a monitor, the type and size of the obstacle can be displayed in text or images, or audio can be output from a speaker to warn the driver.

[0036] Here, the content of the output information is not particularly limited, and for example, navigation route information for avoiding obstacles and navigating the vehicle may be generated and displayed on a monitor or applied to an autopilot system for automatic navigation.

[0037] The output information may include information on the distance (appropriate avoidance distance) to be kept away from the obstacle. For example, if the size of the obstacle is small (such as 1 m^2 or less), the appropriate avoidance distance may be set small (5 m, 10 m, etc.), and the larger the size of the obstacle (such as 10 m^2 or more), the larger the appropriate avoidance distance may be set (20 m, 50 m, etc.). For example, if the obstacle is a person, the appropriate avoidance distance may be set large (20 m, 50 m, etc.), and if the obstacle is a floating object such as a buoy, driftwood, or seaweed, the appropriate avoidance distance may be set small (5 m, 10 m, etc.). The appropriate avoidance distance may be determined based on appropriate avoidance distance information pre-stored in the storage unit according to at least one of the type and size of the obstacle. In this case, information on the type and size of the obstacle and information on the appropriate avoidance distance are pre-stored in association with each other. If the obstacle is another ship, the appropriate avoidance distance may be calculated based on the moving speed and moving direction of the other ship.

[0038] As described above, in the system of this embodiment, the control unit 20 executes an own ship information estimation process (S101) for estimating own ship position information and own ship attitude information based on the first data acquired from at least one data acquisition means, an own ship information correction process (S102) for correcting own ship position information and own ship attitude information based on the second data acquired from at least one data acquisition means, an obstacle information estimation process (S103) for estimating the position and size of an obstacle based on the own ship position information and own ship attitude information corrected in the own ship information correction process and the third data acquired from at least one data acquisition means, and an output information generation process (S104) for generating output information based on the information on the position and size of the obstacle estimated in the obstacle information estimation process. In this way, by correcting the own ship information estimated in the own ship information correction process in the own ship information correction process before executing the obstacle information estimation process, the estimation accuracy of the obstacle can be improved, and as a result, it becomes easier to avoid contact with the obstacle, and the safety of the ship can be improved. Furthermore, according to this embodiment, the above process is repeatedly executed at predetermined intervals such as 0.01 seconds, 0.1 seconds, etc., so that obstacle information can be estimated with high accuracy substantially in real time. Note that the obstacle type may be estimated by the obstacle information estimation process, and in this case, information on the obstacle type may be output as an image, text, sound, or the like, as output information.

[0039] In the system of this embodiment, the obstacle information estimation process may include a data correction process for correcting the third data based on the ship's position information and ship's attitude information corrected in the ship information correction process. That is, for example, the detection data of the radar device, the image data from the camera, the data from Lidar, etc. as the third data are corrected based on the corrected ship's position information and ship's attitude information, thereby further improving the estimation accuracy of the obstacle. The correction process may include a so-called clustering process, etc.

[0040] In the system of the present embodiment, the output information may include information on the distance that the vessel should keep away from the obstacle based on the information on the position and size of the obstacle. With this configuration, the vessel can navigate while safely and efficiently avoiding the obstacle.

[0041] In the system of this embodiment, the information on the size of the obstacle may include information on the height from the water surface to the top of the obstacle. With this configuration, for example, it is possible to determine the distance to avoid the obstacle depending on its height, and to improve the accuracy of estimating the type of the obstacle.

[0042] In the system of this embodiment, the obstacle information estimation process may include a process for determining whether the type of obstacle is another ship or a person. With this configuration, for example, it is possible to inform the user that the obstacle is another ship or a person that requires special attention, urge the user to be careful, or allow the user to avoid the obstacle safely.

[0043] In the system of the present embodiment, the first data may include positioning data received from a positioning satellite and data acquired from an inertial measurement unit. With this configuration, the own ship information estimation process can be performed quickly and efficiently.

[0044] In the system of the present embodiment, the second data may include speed data acquired from at least one of the Lidar and the camera. With this configuration, even if the positioning data received from the positioning satellite cannot be acquired, the ship information correction process can be performed with high accuracy.

[0045] In the system of the present embodiment, the third data may include data acquired from Lidar. With such a configuration, for example, the position, size, shape, and other information of an obstacle can be estimated with high accuracy using the 3D point cloud data acquired from Lidar.

[0046] In the system of the present embodiment, the third data may include image data acquired from a camera. With this configuration, for example, the relative position, size, shape, and other information of the obstacle can be estimated with high accuracy by image analysis of the image data.

[0047] In the system of this embodiment, in environments where signals from positioning satellites cannot be received or signal interference occurs, such as under a bridge, in other words, where GNSS and the like do not function, self-position estimation processing can be performed based on data from at least one of the Lidar and the camera.

[0048] When the control unit 20 determines based on the signal from the data acquisition unit 10 that a signal from a positioning satellite has not been received, the control unit 20 may notify the fact that a signal from a positioning satellite has not been received by using an image or sound from the output unit 50, or may automatically switch the method of ship's position estimation processing. The switching process of the ship's position estimation processing method may be, for example, switching from self-position estimation processing based on data such as GNSS to self-position estimation processing based on data from Lidar and a camera. Then, when it determines that a signal from a positioning satellite has been received again, the method of ship's position estimation processing may be returned to the original method based on data from the positioning satellite.

[0049] In the system of this embodiment, the control unit 20 may determine the type of data to be used in each process based on priority information previously stored in the storage unit 30. For example, in the obstacle information estimation process, the priority can be set in advance such that the combination of camera image data and Lidar data is given the highest priority, followed by camera image data only, Lidar data only, and radar device data only. The priority can be set, for example, taking into consideration high estimation accuracy and low information processing load.

[0050] In the system of this embodiment, the control unit 20 may repeatedly determine whether each data acquisition means is functioning properly based on the presence or absence of a signal from the data acquisition means, and may determine the type of data to be used for each process based on the determination result. For example, if it is determined that GNSS data cannot be acquired, the control unit 20 may execute a ship information estimation process using data acquired by Lidar to estimate the position information and attitude information of the ship.

[0051] Information on the determination result as to whether each data acquisition means is functioning properly or not may be output from the output unit 50 as an image, sound, signal, or the like.

[0052] The system of this embodiment can be installed when a new ship is manufactured, but it can also be implemented on an existing ship by installing various components such as various sensors, cameras, drive devices, power sources, and information processing devices.

[0053] The system of this embodiment can be installed in a newly constructed ship, but can also be installed (retrofitted) in an existing ship. That is, the data acquisition unit 10, control unit 20, storage unit 30, input unit 40, output unit 50, communication unit 60, and ship operation control unit 70 may be entirely or partially formed as a system unit, and the system unit may be installed later in an existing ship.

[0054] In the system of this embodiment, for example, meteorological information and ocean current information may be acquired via the data acquisition unit 10 or the communication unit 60. In this case, for example, by using the meteorological information and ocean current information in at least one of the above-mentioned ship information estimation process, ship information correction process, and obstacle information estimation process, the estimation accuracy of the ship or obstacle can be further improved.

[0055] In the system of this embodiment, output information regarding obstacles generated by the control unit, and information such as weather information, ocean current information, and tide information acquired via the data acquisition unit 10 or the communication unit 60 may be transmitted to other ships. In this case, for example, other ships can be notified of emergencies such as natural disasters and accidents. Information may also be shared with rescue teams and the coast guard to respond to marine distress and emergencies.

[0056] In the system of this embodiment, the current position and attitude of the ship may be predicted based on speed data of the ship at a specific point in time in the past, as described above, or the accuracy of estimating the ship's position information and attitude may be improved by predicting the ship's movement using machine learning or the like from information such as parameters indicating the ship's characteristics and navigation history.

[0057] In the system of this embodiment, the control unit may delete unnecessary obstacle information when the obstacle information acquired from the multiple data acquisition means is duplicated. That is, the control unit may perform a duplication determination process to determine whether the multiple obstacle information estimated (detected) by the multiple data acquisition means is the same obstacle or not, and when it is determined that there are two or more obstacle information for one obstacle, it may delete the obstacle information other than one and leave only one obstacle information in the storage unit. The duplication determination process may determine that the position information (coordinates) of another ship acquired by the first data acquisition means (AIS, etc.) and the position information of another ship (obstacle) estimated from the data of the second data acquisition means (camera, Lidar, radar device) are the same, or that the value (distance) indicating the difference between these two points (coordinates) is within a predetermined threshold range. On the other hand, when it is determined that the value (distance) indicating the difference between the two points (coordinates) is outside the predetermined threshold range (exceeds the threshold), it may determine that the two obstacles are different, and the two obstacle information may be maintained without being deleted. The first data acquisition means and the second data acquisition means may be only one data acquisition means or a combination of multiple data acquisition means. The first data acquisition means and the second data acquisition means are assumed to be different data acquisition means, but some of them may be the same data acquisition means.

[0058] In the system of this embodiment, the control unit 20 can further determine the appropriate avoidance distance based on the attitude (direction) of the obstacle. For example, when the attitude (bow direction) of a ship as an obstacle is facing the own ship, the parameters can be set so that the appropriate avoidance distance is larger than when the bow direction is the same as that of the own ship. When the obstacle is a person using a surfboard or paddle boat, the parameters can be determined in the same manner according to the direction (the direction of an object used by a person such as a surfboard, canoe, yacht, or paddle board) and the direction of the person's face. Such information on the attitude of the obstacle and information on the parameters may be stored in advance in association with each other in the storage unit.

[0059] In the system of this embodiment, the control unit 20 can execute a navigation route generation process that generates navigation route information for avoiding obstacles and navigating to a destination based on an appropriate avoidance distance (parameter). The navigation route generation process generates navigation route information that is the appropriate avoidance distance away from an obstacle based on position information (coordinates) of a start position (e.g., the ship's current position), position information (coordinates) of a destination, 3D map information including the seabed topography, and obstacle information including parameters. At this time, the appropriate avoidance distance is determined based on not only the position information of the obstacle but also the type information and size information of the obstacle, thereby enabling safe and efficient navigation without taking a detour longer than necessary.

[0060] In the system of this embodiment, the control unit 20 may generate a navigation route using a route search algorithm stored in the storage unit. For example, a cost (numerical value) may be set for each node, which is the smallest unit area obtained by dividing a map (nautical chart), and a search may be performed so that the cost from the start node to the destination node is minimized, thereby generating a navigation route. In setting the cost, a parameter based on the appropriate avoidance distance may be used. For example, the closer a node is to an obstacle, the higher the cost value is, and the cost of a node that is more than the appropriate avoidance distance is set to be equal to or less than a predetermined value. In this way, the cost value may be a parameter related to the appropriate avoidance distance. In this case, the predetermined value may be 0 or any value that is set in advance. A search is performed so that the cost from the departure point to the destination is minimized, using an estimated value of the cost (distance) from each node to the destination. The cost of each node used in the route search may be set using any other information in addition to obstacle information and map information (including water depth information and unnavigable area information). For example, the cost may be determined based on meteorological information (including wind direction, wind speed, etc.), ocean current information, wave size information, etc. For example, the higher the wind speed, the higher the cost, the higher the cost of a node where the wind is blowing in the opposite direction to the direction of travel, the higher the cost of a node where there is an ocean current in the opposite direction to the direction of travel, and the higher the waves, the higher the cost.

[0061] The control unit 20 may generate a navigation route using a simulation program in the storage unit. For example, when the ship moves along a planned navigation route (planned travel route) at a preset speed (constant speed or preset variable speed), the control unit 20 may determine the timing when the ship approaches each obstacle closest to the obstacle, whether the ship will come into contact with the obstacle, the distance to the obstacle when the ship approaches the obstacle closest, and whether the ship approaches the obstacle by more than the appropriate avoidance distance (possibility of appropriate avoidance). By repeatedly executing the simulation program while changing the planned travel route and the ship's speed, the ship can navigate at an appropriate distance from the obstacle and generate (search) a navigation route (including speed information) that can reach the destination in the shortest time. Machine learning based on a predetermined learning model may be used in generating such a navigation route.

[0062] Although the preferred embodiment of the present disclosure has been described in detail above with reference to the attached drawings, the technical scope of the present disclosure is not limited to such examples. It is clear that a person having ordinary knowledge in the technical field of the present disclosure can conceive of various modified or amended examples within the scope of the technical ideas described in the claims, and it is understood that these also naturally belong to the technical scope of the present disclosure.

[0063] The device described in this specification may be realized as a single device, or may be realized by a plurality of devices (e.g., cloud servers) partially or entirely connected via a network. For example, the control unit and the storage unit may be realized by different servers connected to each other via a network.

[0064] The series of processes performed by the device described in this specification may be realized using any of software, hardware, and a combination of software and hardware. A computer program for realizing each function of the control unit according to this embodiment may be created and implemented in a PC or the like. A computer-readable recording medium in which such a computer program is stored may also be provided. The recording medium may be, for example, a magnetic disk, an optical disk, a magneto-optical disk, a flash memory, or the like. The above computer program may also be distributed, for example, via a network, without using a recording medium.

[0065] In addition, the processes described herein using flowchart diagrams do not necessarily have to be performed in the order shown. Some process steps may be performed in parallel. Additional process steps may be employed, and some process steps may be omitted.

[0066] In addition, the effects described in this specification are merely descriptive or exemplary and are not limiting. In other words, the technology according to the present disclosure may achieve other effects that are apparent to a person skilled in the art from the description of this specification, in addition to or in place of the above effects.

[0067] Note that the following configurations also fall within the technical scope of the present disclosure. (Item 1) An obstacle estimation system comprising a plurality of data acquisition means and a control unit that executes information processing, and which estimates information regarding an obstacle when a ship is navigating, The control unit is a ship information estimation process for estimating ship position information and ship attitude information based on first data acquired from at least one data acquisition means; a ship information correction process for correcting the ship position information and the ship attitude information based on second data acquired from at least one data acquisition means; an obstacle information estimation process for estimating a position and a size of an obstacle based on the ship position information and ship attitude information corrected in the ship information correction process and third data acquired from at least one data acquisition means; and an output information generation process for generating output information based on information on the position and size of the obstacle estimated in the obstacle information estimation process. (Item 2) The obstacle estimation system of claim 1, wherein the obstacle information estimation process estimates the type of obstacle based on the ship's position information and ship's attitude information corrected in the ship's information correction process, and third data acquired from at least one data acquisition means. (Item 3) 2. An obstacle estimation system as described in item 1, wherein the obstacle information estimation process includes a data correction process that corrects the third data based on the ship's position information and ship's attitude information corrected in the ship's information correction process. (Item 4) 3. The obstacle estimation system according to claim 2, wherein the output information includes information on the distance that the vessel should keep away from the obstacle based on information on the position, type, and size of the obstacle. (Item 5) 3. The obstacle estimation system according to item 1 or 2, wherein the information on the size of the obstacle includes information on the height from the water surface to the top of the obstacle. (Item 6) 3. The obstacle estimation system according to item 2, wherein the obstacle information estimation process includes a process for determining whether the type of the obstacle is another ship or a person. (Item 7) 3. The obstacle estimation system according to claim 1, wherein the first data includes positioning data received from a positioning satellite and data acquired from an inertial measurement unit. (Item 8) 3. The obstacle estimation system according to item 1 or 2, wherein the second data includes speed data acquired from at least one of a Lidar and a camera. (Item 9) 3. The obstacle estimation system according to item 1 or 2, wherein the third data includes data acquired from a Lidar. (Item 10) 3. The obstacle estimation system according to claim 1, wherein the third data includes image data acquired from a camera. (Item 11) 3. The obstacle estimation system according to claim 1, wherein the third data includes data acquired from a radar device. [Explanation of symbols]

[0068] 1 Obstacle Estimation System 10 Data Acquisition Section 20 Control section 30 Storage section 40 Input section 50 Output section 60 Communications Department 70 Ship motion control unit

Claims

1. An obstacle estimation system comprising a plurality of data acquisition means and a control unit that executes information processing, and which estimates information regarding an obstacle when a ship is navigating, The control unit is a ship information estimation process for estimating ship position information and ship attitude information based on first data acquired from at least one data acquisition means; a ship information correction process for correcting the ship position information and the ship attitude information based on second data acquired from at least one data acquisition means; an obstacle information estimation process for estimating a position and a size of an obstacle based on the ship position information and ship attitude information corrected in the ship information correction process and third data acquired from at least one data acquisition means; and an output information generation process for generating output information based on information on the position and size of the obstacle estimated in the obstacle information estimation process.

2. The obstacle estimation system of claim 1, wherein the obstacle information estimation process estimates the type of obstacle based on the ship's position information and ship's attitude information corrected by the ship information correction process, and third data acquired from at least one data acquisition means.

3. 2. The obstacle estimation system according to claim 1, wherein the obstacle information estimation process includes a data correction process for correcting the third data based on the ship's position information and the ship's attitude information corrected in the ship information correction process.

4. The obstacle estimation system according to claim 2 , wherein the output information includes information on a distance that the vessel should keep away from the obstacle, based on information on a position, a type, and a size of the obstacle.

5. The obstacle estimation system according to claim 1 or 2, wherein the information on the size of the obstacle includes information on a height from a water surface to a top of the obstacle.

6. The obstacle estimation system according to claim 2 , wherein the obstacle information estimation process includes a process of determining whether the type of the obstacle is another ship or a person.

7. The obstacle estimation system according to claim 1 or 2, wherein the first data includes positioning data received from a positioning satellite and data acquired from an inertial measurement unit.

8. The obstacle estimation system according to claim 1 or 2, wherein the second data includes speed data acquired from at least one of a Lidar and a camera.

9. The obstacle estimation system according to claim 1 or 2, wherein the third data includes data acquired from a Lidar.

10. The obstacle estimation system according to claim 1 or 2, wherein the third data includes image data acquired from a camera.

11. The obstacle estimation system according to claim 1 or 2, wherein the third data includes data acquired from a radar device.

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