[go: up one dir, main page]

CN112644646A - Underwater robot intelligent system for large-water-area fish resource investigation and working method - Google Patents

Underwater robot intelligent system for large-water-area fish resource investigation and working method Download PDF

Info

Publication number
CN112644646A
CN112644646A CN202011328163.4A CN202011328163A CN112644646A CN 112644646 A CN112644646 A CN 112644646A CN 202011328163 A CN202011328163 A CN 202011328163A CN 112644646 A CN112644646 A CN 112644646A
Authority
CN
China
Prior art keywords
fish
shore
unmanned
underwater
unmanned ship
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202011328163.4A
Other languages
Chinese (zh)
Inventor
陈刚
吕思源
卢裕旺
杨鑫
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang University of Technology ZJUT
Original Assignee
Zhejiang University of Technology ZJUT
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhejiang University of Technology ZJUT filed Critical Zhejiang University of Technology ZJUT
Priority to CN202011328163.4A priority Critical patent/CN112644646A/en
Publication of CN112644646A publication Critical patent/CN112644646A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
    • B63B35/00—Vessels or similar floating structures specially adapted for specific purposes and not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63C—LAUNCHING, HAULING-OUT, OR DRY-DOCKING OF VESSELS; LIFE-SAVING IN WATER; EQUIPMENT FOR DWELLING OR WORKING UNDER WATER; MEANS FOR SALVAGING OR SEARCHING FOR UNDERWATER OBJECTS
    • B63C11/00—Equipment for dwelling or working underwater; Means for searching for underwater objects
    • B63C11/34—Diving chambers with mechanical link, e.g. cable, to a base
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63G—OFFENSIVE OR DEFENSIVE ARRANGEMENTS ON VESSELS; MINE-LAYING; MINE-SWEEPING; SUBMARINES; AIRCRAFT CARRIERS
    • B63G8/00—Underwater vessels, e.g. submarines; Equipment specially adapted therefor
    • B63G8/001—Underwater vessels adapted for special purposes, e.g. unmanned underwater vessels; Equipment specially adapted therefor, e.g. docking stations
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63G—OFFENSIVE OR DEFENSIVE ARRANGEMENTS ON VESSELS; MINE-LAYING; MINE-SWEEPING; SUBMARINES; AIRCRAFT CARRIERS
    • B63G8/00—Underwater vessels, e.g. submarines; Equipment specially adapted therefor
    • B63G8/38—Arrangement of visual or electronic watch equipment, e.g. of periscopes, of radar
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63G—OFFENSIVE OR DEFENSIVE ARRANGEMENTS ON VESSELS; MINE-LAYING; MINE-SWEEPING; SUBMARINES; AIRCRAFT CARRIERS
    • B63G8/00—Underwater vessels, e.g. submarines; Equipment specially adapted therefor
    • B63G8/39—Arrangements of sonic watch equipment, e.g. low-frequency, sonar
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING 
    • B63B35/00—Vessels or similar floating structures specially adapted for specific purposes and not otherwise provided for
    • B63B2035/006—Unmanned surface vessels, e.g. remotely controlled
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
    • B63G—OFFENSIVE OR DEFENSIVE ARRANGEMENTS ON VESSELS; MINE-LAYING; MINE-SWEEPING; SUBMARINES; AIRCRAFT CARRIERS
    • B63G8/00—Underwater vessels, e.g. submarines; Equipment specially adapted therefor
    • B63G8/001—Underwater vessels adapted for special purposes, e.g. unmanned underwater vessels; Equipment specially adapted therefor, e.g. docking stations
    • B63G2008/002—Underwater vessels adapted for special purposes, e.g. unmanned underwater vessels; Equipment specially adapted therefor, e.g. docking stations unmanned
    • B63G2008/005—Underwater vessels adapted for special purposes, e.g. unmanned underwater vessels; Equipment specially adapted therefor, e.g. docking stations unmanned remotely controlled
    • B63G2008/007—Underwater vessels adapted for special purposes, e.g. unmanned underwater vessels; Equipment specially adapted therefor, e.g. docking stations unmanned remotely controlled by means of a physical link to a base, e.g. wire, cable or umbilical
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/30—Assessment of water resources

Landscapes

  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Ocean & Marine Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Life Sciences & Earth Sciences (AREA)
  • Geophysics (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)

Abstract

本发明属于水下机器人技术领域。目的是提供一种基于水下视觉辅助的大水域鱼类资源调查的水下机器人系统，以实现高精度、高效率、低破坏性的大水域鱼类资源调查，并显著降低了鱼类调查的人力成本。技术方案是：大水域鱼类资源调查的水下机器人智能系统，其特征在于：该系统包括置于岸边基地的岸基控制台和水下智能调查系统；所述岸基控制台包括岸基服务器以及与岸基服务器进行信息沟通的岸基无线通讯模块，用于对无人船传回的图像信息进行分类处理以及鱼群位置、深度和运动信息进行记录，并对获得的信息处理分析，从而计算鱼类数据；无线通讯模块还用于与无人船的实时通信。

Figure 202011328163

The invention belongs to the technical field of underwater robots. The purpose is to provide an underwater robot system based on underwater visual aids for fish resources survey in large waters, so as to realize high-precision, high-efficiency, and low-destructive fish resources survey in large waters, and significantly reduce the cost of fish surveys. Labor costs. The technical scheme is: an underwater robot intelligent system for fish resources survey in large waters, characterized in that: the system includes a shore-based console and an underwater intelligent survey system placed in a shore base; the shore-based console includes a shore-based console The server and the shore-based wireless communication module that communicates with the shore-based server are used to classify and process the image information returned by the unmanned ship, record the position, depth and motion information of the fish, and process and analyze the obtained information. Thereby calculating fish data; the wireless communication module is also used for real-time communication with unmanned ships.

Figure 202011328163

Description

Underwater robot intelligent system for large-water-area fish resource investigation and working method
Technical Field
The invention belongs to the technical field of underwater robots, and particularly relates to an underwater robot intelligent system for large-water-area fish resource investigation and a working method.
Background
The total ocean area is about 3.61 hundred million square kilometers, which is a huge resource treasury for human beings. The ocean contains abundant resources, and under the conditions of shortage of global living resources, huge energy gaps and rapid population growth, human beings develop ocean resources and learn to use the ocean resources, which is very important, particularly fish resources, and tens of thousands of fish organisms live in the ocean. How to explore and identify marine fishes is one of key technologies for exploring oceans and realizing marine economy and scientific research by utilizing the oceans. The existing marine fish identification mostly uses technologies such as sonar detection and fixed-point fishing, and although the technologies can achieve certain effects, the cost and the accuracy are all deficient, for example, the fixed-point fishing technology is a great challenge to technicians how to achieve fishing and counting, and the acquired data have certain errors. Therefore, it is urgently needed to design an intelligent system with the capability of autonomously surveying fish resources, which has higher accuracy and lower destructiveness compared with the traditional surveying method, and greatly reduces the labor cost.
Disclosure of Invention
The invention aims to overcome the defects of the background technology and provide an underwater robot system for large-water-area fish resource investigation based on underwater vision assistance, so that the large-water-area fish resource investigation with high precision, high efficiency and low destructiveness is realized, and the labor cost of the fish investigation is obviously reduced.
The technical scheme provided by the invention is as follows:
an underwater robot intelligent system for large-water-area fish resource investigation is characterized in that: the system comprises a shore-based control platform and an underwater intelligent investigation system, wherein the shore-based control platform is arranged at a shore base;
the shore-based control station comprises a shore-based server and a shore-based wireless communication module which is in information communication with the shore-based server and is used for classifying image information sent back by the unmanned ship, recording fish school position, depth and motion information, processing and analyzing the obtained information and calculating fish data; the wireless communication module is also used for real-time communication with the unmanned ship;
the underwater intelligent survey system comprises an unmanned ship and an unmanned underwater vehicle, wherein the unmanned ship is provided with a sonar navigation system, a Beidou navigation system, a speed instrument, an attitude sensor and a shipborne wireless communication module; the unmanned underwater vehicle carries an ultra-high-definition underwater camera, a depth sensor, a control circuit, an attitude adjusting module and a speed sensor, and a communication component of the unmanned underwater vehicle is communicated with the unmanned ship through an optical cable so as to transmit fish information detected underwater back to the unmanned ship; the shipborne wireless communication module on the unmanned ship transmits the signals to the shore-based server, and the shore-based server identifies and stores the fish information.
The shore-based control console realizes real-time control of position information of a detection point of the unmanned ship by the shore base through a Beidou navigation system on the unmanned ship; the unmanned ship realizes exploration of the movement position of the fish school through a sonar detector.
The unmanned underwater vehicle transmits shot fish information and the depth information of the position where the fish school is located back to the shore-based control console through the carried ultra-high-definition underwater camera, the depth sensor and the speed sensor.
A fish image recognition algorithm is adopted when the shore-based server calculates the fish data; the fish image identification algorithm adopts a deep convolution network with 5 network layers.
The control circuit, the attitude adjusting module and the communication assembly of the unmanned underwater vehicle are respectively placed in the two pressure-resistant sealed cabins; the ultra-high-definition underwater camera is arranged on a lower deck of the unmanned underwater vehicle and is respectively fixed with the lower deck through two fixing rings; the depth sensor is arranged right behind the ultra-high-definition underwater camera.
The working method of the underwater robot intelligent system for the investigation of the fish resources in the large water area comprises the following two steps:
one is the situation that the overall movement speed of the fish school is high, and the other is the situation that the whole fish school is relatively static;
when the underwater robot intelligent system for the large-water-area fish resource investigation surveys the fish swarm with high movement speed: the unmanned ship autonomously moves in a pre-surveying water area according to a track path planned in advance; meanwhile, a sonar carried on the unmanned ship starts to detect fish clusters in the surrounding water area; when fish or fish school is detected in a certain area, the information is transmitted to a shore-based control console through a shore-based wireless communication module; when the unmanned ship reaches a designated position, the unmanned underwater vehicle is put down and an underwater ultrahigh-definition camera is used for shooting fish shoals, and various sensors are started to work; when the integral movement speed of the fish school is found to be high, the shore-based control console controls the unmanned ship and the unmanned underwater vehicle to move together with the fish school, so that image information and activity information of the high-speed moving fish school are recorded, and the information is transmitted back to the shore-based server through the shipborne wireless communication module of the unmanned ship; classifying and identifying by a shore-based server using a fish image identification algorithm; if the test is repeated, the unmanned underwater vehicle is controlled to return to the initial position, and then the whole control process is started again.
When the underwater robot intelligent system for large-water-area fish resource investigation surveys relatively static fish schools: the unmanned ship autonomously moves in a pre-surveying water area according to a track path planned in advance, and simultaneously, a sonar carried on the unmanned ship starts to detect fish clusters in the surrounding water area; when fish or fish school is detected in a certain area, the information is transmitted to a shore-based control console through a shore-based wireless communication module; when the unmanned ship reaches a designated position, the unmanned underwater vehicle is put down and the ultrahigh-definition underwater camera is used for shooting fish shoals, and various sensors are started to work; when the whole fish school is in a relatively static state, the shore-based server firstly controls the unmanned ship to be static, the unmanned underwater vehicle shoots the fish schools with different water depth levels and transmits the fish schools to the unmanned ship, and then the unmanned ship shoots the fish schools around the fish school from different angles to obtain all-dimensional image information with different water depth levels; then the unmanned ship transmits the image information and the activity information obtained by the sensor back to a shore-based server through a shipborne wireless communication module on the unmanned ship; and classifying and identifying the fish by using a shore-based server fish image identification algorithm. If the test is repeated, the unmanned underwater vehicle is controlled to return to the initial position, and then the whole process is started again.
The activity information comprises the current fish school movement speed recorded by the speed sensor and the depth of the current fish school position recorded by the depth sensor.
The invention has the beneficial effects that:
1) according to the invention, sonar detection and the ultra-high-definition underwater camera are combined, so that the sonar detection of the appearance directions of fish in fish clusters is realized, the ultra-high-definition underwater camera collects fish image resources and transmits information back to the shore-based control console, and fish data are classified and identified by using a fish image identification algorithm, so that the investigation precision is effectively improved.
2) The invention uses the depth image recognition technology, avoids the damage of the traditional fixed-point fishing to the fishes, can realize the investigation of the large-water-area fish resources with high precision, high efficiency and low destructiveness, and obviously reduces the labor cost of the fish investigation.
3) The unmanned ship carries equipment such as a Beidou navigation system and a cruise instrument, can realize real-time positioning and determination of the unmanned ship and the fish school position by the shore base, and can realize the function of recording the frequent emergence area of the fish school position.
Drawings
FIG. 1 is a schematic diagram of an underwater robot intelligent system for surveying large water area fish resources.
Fig. 2 is an enlarged schematic structural diagram of the unmanned underwater vehicle in fig. 1.
FIG. 3 is a flowchart of a working method of the underwater robot intelligent system for surveying the fish resources in the large water area.
FIG. 4 is a second flowchart of the operation method of the underwater robot intelligent system for surveying the fish resources in the large water area according to the present invention.
In the figure, 101 is a shore-based server; 102. a shore-based wireless communication module; 201. a shipborne wireless communication module; 202. a Beidou navigation system; 203. sonar; 204. an unmanned ship deck; 205. the unmanned ship underwater vehicle is placed in the cabin; 206. an unmanned ship; 301. an upper cover plate of the underwater vehicle; 302. a pressure-resistant sealed cabin; 303. an ultra-high-definition underwater camera; 304. a depth sensor.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments.
As shown in figure 1, the invention consists of a shore-based control console and an underwater intelligent investigation system.
The shore-based control station is arranged on land and comprises a shore-based server 101 and a shore-based wireless communication module 102. The shore-based server 101 mainly completes classification processing of image information transmitted back by the unmanned ship and recording of depth and position information; the shore-based wireless communication module 102 is connected with the shore-based server 101 and is used for real-time communication with a shipborne wireless communication module of the unmanned ship.
The underwater intelligent survey system comprises an unmanned ship 206 and an unmanned underwater vehicle; the unmanned ship 206 carries a sonar 203, a Beidou navigation system 202, a shipborne wireless communication module 201, an unmanned ship deck 204, an unmanned underwater vehicle placing cabin 205 and an unmanned underwater vehicle;
the unmanned underwater vehicle cabin is located at the bottom of the unmanned ship, when a sonar on the unmanned ship detects that large-scale fish schools exist underwater, the cabin door of the unmanned underwater vehicle is opened, the unmanned underwater vehicle is lowered to the fish school depth, the depth sensor is used for recording the fish school depth information, the fish school depth information is transmitted to the unmanned ship through an optical cable by the communication assembly, and then the fish school depth information is transmitted back to the shore-based server through the shipborne wireless communication module on the unmanned ship.
The unmanned underwater vehicle drives a steering mechanism by using a large-torque waterproof steering engine to realize steering of the unmanned underwater vehicle, a control circuit, an attitude adjusting module and a communication component of the unmanned underwater vehicle are respectively placed in two pressure-resistant sealed cabins 302, and the unmanned underwater vehicle further comprises an upper cover plate 301 of the unmanned underwater vehicle, side cover plates and a bottom plate; the ultra-high-definition underwater camera 303 is arranged on a lower deck of the unmanned underwater vehicle and is fixed with the lower deck through two fixing rings respectively; the depth sensor 304 is installed right behind the ultra high definition underwater camera 303.
The working method of the invention is as follows:
the working method of the underwater robot system for the autonomous survey of the fishes in the large water area is divided into two types, wherein one type is when the integral moving speed of the fish swarm is high, and the other type is when the integral fish swarm is in a relatively static condition.
When the underwater robot intelligent system for large-water-area fish resource investigation surveys the high-speed moving fish swarm (the working method flow is shown in figure 3): after the detection is started, first, the unmanned ship 206 autonomously moves in the pre-surveyed water area along a previously planned trajectory path, and the unmanned underwater vehicle is stored in the unmanned ship cabin 205. Meanwhile, a sonar 203 carried by an unmanned ship 206 starts to detect fish clusters in surrounding water areas (preferably 100m square-circle water areas), and when the existence of fishes or fish schools with a certain scale is detected in a certain area, information recorded by the Beidou navigation system 202 is transmitted to the shore-based server 101 through the shipborne wireless communication module 201; when the unmanned ship reaches a specified position, the shore-based server sends an instruction, the unmanned underwater vehicle is placed to a specified depth, then the underwater ultrahigh-definition camera 303 is used for shooting a fish school, when the overall movement speed of the fish school is found to be high, the shore-based server 101 sets parameters of the unmanned ship and the unmanned underwater vehicle, the unmanned ship and the unmanned underwater vehicle move together along with the fish school so as to realize a follow-shooting function for the high-speed moving fish school (fish schools with different water depth levels are shot through the upward floating and the downward submerging of the unmanned underwater vehicle), then the current movement speed is recorded by the speed sensor, the depth of the current fish school position is recorded by the depth sensor 304, the communication component is transmitted back to the unmanned ship through an optical cable, and then the depth information, the speed information and the picture information of the fish school are transmitted back to the shore-based server 101 through the shipborne wireless communication module 201 of the unmanned ship; the shore-based server 101 performs classification and identification based on the feedback data using a fish asset identification algorithm that employs a network depth 5-tier deep convolution algorithm that can be run across multiple servers to identify large-scale fish asset depths. If the test is repeated, the unmanned underwater vehicle is controlled to return to the initial position, and then the whole process is started again.
When the underwater robot intelligent system for the investigation of the fish resources in the large water area surveys a relatively static fish swarm (the flow of the working method is shown in figure 4): after the detection is started, first, the unmanned ship 206 autonomously moves in the pre-surveyed water area along a previously planned trajectory path, and the unmanned underwater vehicle is stored in the unmanned ship cabin 205. Meanwhile, a sonar 203 carried by the unmanned ship 206 starts to detect fish clusters in the range of the surrounding water area (preferably a square 100m water area); when the existence of fishes or fish schools with a certain scale is detected in a certain area, information recorded by the Beidou navigation system 202 is transmitted to the shore-based server 101 through the shipborne wireless communication module 201; when the unmanned ship reaches a specified position, the shore-based server sends an instruction, the ultra-high-definition underwater camera 305 is used for shooting fish schools after the unmanned detector is placed to a specified depth, and when the whole fish schools are found to be in a relatively static state, the shore-based server 101 sets parameters of the unmanned ship 206 and the unmanned underwater vehicle so that the unmanned ship can be firstly static and the unmanned underwater vehicle starts to float up and descend, and fish schools of different water depth levels are shot; after shooting is finished, the unmanned ship 206 moves around the fish school, so that the ROV can record image information of the fish school in all directions and at different levels, the communication assembly transmits depth information, speed information and picture information of the fish school back to the unmanned ship 206 in real time through the optical cable, and then the shipborne wireless communication module 201 of the unmanned ship 206 transmits the information back to the shore-based server 101 of the shore-based control station; the shore-based server 101 classifies and identifies the fish data using a fish resource identification algorithm based on the fed back data. If the test is repeated, the unmanned underwater vehicle is controlled to return to the cabin 205, and then the whole process is started again.
The invention provides a fish resource investigation device with a submersible carried by an unmanned ship aiming at fish investigation operation and marine science research operation, which can collect fish information at different depths and different positions, recover the fish information and analyze the fish information to obtain more comprehensive fish resource data.

Claims (7)

1.大水域鱼类资源调查的水下机器人智能系统，其特征在于：该系统包括置于岸边基地的岸基控制台和水下智能调查系统；1. the underwater robot intelligent system of fish resources investigation in large waters, is characterized in that: this system comprises the shore-based console and the underwater intelligent investigation system placed on the shore base; 所述岸基控制台包括岸基服务器(101)以及与岸基服务器进行信息沟通的岸基无线通讯模块，用于对无人船传回的图像信息进行分类处理以及深度和位置信息进行记录，并对获得的信息处理分析，从而计算鱼类数据；无线通讯模块还用于与无人船的实时通信；The shore-based console includes a shore-based server (101) and a shore-based wireless communication module that communicates with the shore-based server, and is used for classifying and processing the image information returned by the unmanned ship and recording depth and position information, And the obtained information is processed and analyzed to calculate fish data; the wireless communication module is also used for real-time communication with unmanned ships; 所述水下智能调查系统，包括无人船(206)及无人潜航器，无人船上载有声呐(203)、北斗导航系统(202)、航速仪、姿态传感器以及船载无线通讯模块(201)；无人潜航器携带超高清水下摄像机、深度传感器(304)、控制电路与姿态调节模块以及速度传感器，无人潜航器的通信组件通过光缆与无人船通信，以将水下探测到的鱼类信息传回无人船；无人船上的船载无线通讯模块将信号传至岸基服务器，岸基服务器将鱼类信息识别并保存。The underwater intelligent investigation system includes an unmanned ship (206) and an unmanned underwater vehicle, and the unmanned ship is equipped with a sonar (203), a Beidou navigation system (202), a speedometer, an attitude sensor, and a ship-borne wireless communication module ( 201); the unmanned underwater vehicle carries an ultra-high-water underwater camera, a depth sensor (304), a control circuit, an attitude adjustment module and a speed sensor, and the communication component of the unmanned underwater vehicle communicates with the unmanned ship through an optical cable to detect underwater detection. The received fish information is sent back to the unmanned ship; the onboard wireless communication module on the unmanned ship transmits the signal to the shore-based server, and the shore-based server identifies and saves the fish information. 2.根据权利要求1所述的大水域鱼类资源调查的水下机器人智能系统，其特征在于：所述岸基控制台通过无人船上的北斗导航系统实现岸基对无人船检测点位置信息的实时掌控；所述无人船通过声呐探测器实现对鱼群运动位置的勘探。2. the underwater robot intelligent system of fish resources investigation in large waters according to claim 1, is characterized in that: described shore-based console realizes shore-based to unmanned ship detection point position by Beidou navigation system on unmanned ship Real-time control of information; the unmanned ship realizes the exploration of the movement position of the fish through the sonar detector. 3.根据权利要求2所述的大水域鱼类资源调查的水下机器人智能系统，其特征在于：所述无人潜航器,通过所搭载的超高清水下摄像机、深度传感器以及速度传感器，以将拍摄到的鱼类信息以及调查到的鱼群所处位置深度信息回传给岸基控制台。3. the underwater robot intelligent system of fish resources investigation in large waters according to claim 2, is characterized in that: described unmanned underwater vehicle, by carrying ultra-high water underwater camera, depth sensor and speed sensor, to Send the captured fish information and the depth information of the investigated fish schools back to the shore-based console. 4.根据权利要求3所述的大水域鱼类资源调查的水下机器人智能系统，其特征在于：所述岸基服务器计算鱼类数据时采用鱼类图像识别算法；鱼类图像识别算法采用网络层数为5层的深度卷积网络。4. the underwater robot intelligent system of fish resources investigation in large waters according to claim 3, is characterized in that: fish image recognition algorithm is adopted when described shore-based server calculates fish data; fish image recognition algorithm adopts network A deep convolutional network with 5 layers. 5.根据权利要求4所述的大水域鱼类资源调查的水下机器人智能系统，其特征在于：无人潜航器的控制电路与姿态调节模块、通讯组件分别放在两个耐压密封舱(302)中；超高清水下摄像机(303)安装在无人潜航器下甲板上并分别通过两个固定环与下甲板固定；深度传感器(304)安装在超高清水下摄像机303正后方。5. the underwater robot intelligent system of fish resources investigation in large water areas according to claim 4, is characterized in that: the control circuit of unmanned underwater vehicle and attitude adjustment module, communication assembly are respectively placed in two pressure-resistant sealed cabins ( 302); the ultra-high water underwater camera (303) is installed on the lower deck of the unmanned underwater vehicle and is respectively fixed to the lower deck through two fixing rings; the depth sensor (304) is installed directly behind the ultra-high water underwater camera 303. 6.权利要求1所述的大水域鱼类资源调查的水下机器人智能系统的工作方法，分为如下两种：6. the working method of the underwater robot intelligent system of the large water area fish resources investigation described in claim 1, is divided into following two kinds: 一种是鱼群整体运动速度较快的情况时，另一种是鱼群整体处于一个相对静止的情况时；One is when the overall speed of the fish school is relatively fast, and the other is when the fish school as a whole is in a relatively static situation; 大水域鱼类资源调查的水下机器人智能系统勘查运动速度较快的鱼群时：无人船先在预勘察水域内按照事先规划的轨迹路径自主运动；同时无人船上搭载的声呐开始对周围水域内的鱼类集群进行探测；当在某区域探测到鱼类或鱼群时，将信息通过岸基无线通讯模块传递给岸基控制台；当无人船到达指定位置时，下放无人潜航器并使用水下超高清相机拍摄鱼群，各类传感器也启动工作；发现鱼群整体运动速度较快时，岸基控制台控制无人船和无人潜航器一起跟随鱼群运动，从而实现对高速运动鱼群的图像信息和活动信息进行记录，并通过无人船的船载无线通讯模块将信息传回给岸基服务器；由岸基服务器使用鱼类图像识别算法进行分类和识别；如若要重复测试，则需先控制无人潜航器回到初始位置，然后再重新开始循环整个控制过程。When the underwater robot intelligent system for fish resources survey in large waters surveys fish schools with fast moving speed: the unmanned boat first moves autonomously according to the pre-planned trajectory in the pre-surveyed waters; Fish clusters in the waters are detected; when fish or fish groups are detected in a certain area, the information is transmitted to the shore-based console through the shore-based wireless communication module; when the unmanned ship reaches the designated position, the unmanned submarine is released and use the underwater ultra-high-definition camera to shoot the fish school, and various sensors also start to work; when the overall movement speed of the fish school is found to be fast, the shore-based console controls the unmanned ship and the unmanned submersible to follow the fish school movement together, so as to realize The image information and activity information of high-speed moving fish are recorded, and the information is sent back to the shore-based server through the on-board wireless communication module of the unmanned ship; the shore-based server uses the fish image recognition algorithm to classify and identify; To repeat the test, first control the UUV back to the initial position, and then start the cycle of the entire control process again. 大水域鱼类资源调查的水下机器人智能系统勘察相对静止的鱼群时：无人船先在预勘察水域内按照事先规划的轨迹路径自主运动，同时无人船上搭载的声呐开始对周围水域内的鱼类集群进行探测；当在某区域探测到鱼类或鱼群时，将信息通过岸基无线通讯模块传递给岸基控制台；当无人船到达指定位置时，下放无人潜航器并使用超高清水下摄像机拍摄鱼群，各类传感器也启动工作；发现鱼群整体处于一个相对静止的状态时，岸基服务器先控制无人船静止不动，无人潜航器对不同水深层次的鱼群进行拍摄并且传输至无人船，接着无人船环绕鱼群从不同角度拍摄，获得一个全方位，不同水深层次的图像信息；然后实时将图像信息与传感器获得的活动信息通过无人船上的船载无线通讯模块将信息传回岸基服务器；岸基服务器鱼类图像识别算法进行分类和识别。如若重复测试则需先控制无人潜航器回到初始位置，然后再重新开始循环整个过程。When the underwater robot intelligent system for fish resources survey in large waters surveys relatively static fish schools: the unmanned ship first moves autonomously according to the pre-planned trajectory in the pre-surveyed waters, and at the same time, the sonar carried on the unmanned ship begins to detect the surrounding waters. When the fish or fish group is detected in a certain area, the information is transmitted to the shore-based console through the shore-based wireless communication module; when the unmanned ship reaches the designated position, the unmanned submersible is lowered and the Using ultra-high-water underwater cameras to shoot fish, all kinds of sensors also start working; when the fish is found to be in a relatively static state, the shore-based server first controls the unmanned ship to stand still, and the unmanned submersible can respond to different water depths. The fish school is photographed and transmitted to the unmanned ship, and then the unmanned ship surrounds the fish school and shoots from different angles to obtain an all-round image information of different water depths; then the image information and the activity information obtained by the sensor are passed through the unmanned ship in real time. The ship-borne wireless communication module transmits information back to the shore-based server; the shore-based server fish image recognition algorithm performs classification and identification. If the test is repeated, it is necessary to control the UUV to return to the initial position, and then start the cycle again. 7.根据权利要求6所述的大水域鱼类资源调查的水下机器人智能系统的工作方法，其特征在于：所述活动信息包括速度传感器记录的当前鱼群运动速度、深度传感器记录的当前鱼群位置的深度。7. the working method of the underwater robot intelligent system of large water fish resources investigation according to claim 6, is characterized in that: described activity information comprises the current fish movement speed that speed sensor records, the current fish that depth sensor records The depth of the group location.
CN202011328163.4A 2020-11-24 2020-11-24 Underwater robot intelligent system for large-water-area fish resource investigation and working method Pending CN112644646A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011328163.4A CN112644646A (en) 2020-11-24 2020-11-24 Underwater robot intelligent system for large-water-area fish resource investigation and working method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011328163.4A CN112644646A (en) 2020-11-24 2020-11-24 Underwater robot intelligent system for large-water-area fish resource investigation and working method

Publications (1)

Publication Number Publication Date
CN112644646A true CN112644646A (en) 2021-04-13

Family

ID=75349748

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011328163.4A Pending CN112644646A (en) 2020-11-24 2020-11-24 Underwater robot intelligent system for large-water-area fish resource investigation and working method

Country Status (1)

Country Link
CN (1) CN112644646A (en)

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113575528A (en) * 2021-07-30 2021-11-02 海南福港远洋渔业有限公司 Far deep sea fishing method
CN114153003A (en) * 2021-11-08 2022-03-08 浙江海洋大学 Image acquisition processing device and acquisition method for ocean electronic information engineering
CN114185079A (en) * 2021-11-22 2022-03-15 武汉船舶通信研究所（中国船舶重工集团公司第七二二研究所） An underwater stereo detection system
CN114394202A (en) * 2021-12-28 2022-04-26 深圳潜行创新科技有限公司 Unmanned ship control system
CN115128690A (en) * 2022-09-01 2022-09-30 深圳潜行创新科技有限公司 Floating type underwater detection device with underwater rotary camera and method
CN115195959A (en) * 2022-08-12 2022-10-18 青岛科技大学 A marine surveying and mapping equipment based on intelligent unmanned ship
CN115305808A (en) * 2022-08-30 2022-11-08 武汉工程大学 Integrated application method and system of multi-type bridge detection equipment based on unmanned platform
CN117193304A (en) * 2023-09-20 2023-12-08 武汉理工大学 An unmanned ship cluster control method and related equipment
CN119142491A (en) * 2024-11-20 2024-12-17 上海交通大学三亚崖州湾深海科技研究院 High-anti-flow multi-point observation type fish school monitoring underwater robot based on multi-source data fusion

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003111533A (en) * 2001-10-02 2003-04-15 Mitsubishi Heavy Ind Ltd Method and facilities for oceanographic investigation
DE10310550A1 (en) * 2003-03-02 2004-09-30 Fred Hocker System for investigating inshore water bodies comprises at least one unmanned floating element and at least one unmanned submerged element, and a base station with remote control and data processing means
KR101199416B1 (en) * 2012-02-21 2012-11-09 (주)더모스트 Waterway Data Update System
KR20150000054A (en) * 2013-06-21 2015-01-02 (주)진우소프트이노베이션 u-AUV FOR MANAGING AQUACULTURE OF FISHES
US20170295759A1 (en) * 2011-03-17 2017-10-19 Liquid Robotics Inc. Autonomous wave-powered vessels and fleets for managing fish stock
CN111008794A (en) * 2019-12-31 2020-04-14 中国水产科学研究院黑龙江水产研究所 Multi-dimensional one-stop investigation method for spawning site of spawning fishes on large water area grass in rivers, lakes and reservoirs

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2003111533A (en) * 2001-10-02 2003-04-15 Mitsubishi Heavy Ind Ltd Method and facilities for oceanographic investigation
DE10310550A1 (en) * 2003-03-02 2004-09-30 Fred Hocker System for investigating inshore water bodies comprises at least one unmanned floating element and at least one unmanned submerged element, and a base station with remote control and data processing means
US20170295759A1 (en) * 2011-03-17 2017-10-19 Liquid Robotics Inc. Autonomous wave-powered vessels and fleets for managing fish stock
KR101199416B1 (en) * 2012-02-21 2012-11-09 (주)더모스트 Waterway Data Update System
KR20150000054A (en) * 2013-06-21 2015-01-02 (주)진우소프트이노베이션 u-AUV FOR MANAGING AQUACULTURE OF FISHES
CN111008794A (en) * 2019-12-31 2020-04-14 中国水产科学研究院黑龙江水产研究所 Multi-dimensional one-stop investigation method for spawning site of spawning fishes on large water area grass in rivers, lakes and reservoirs

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113575528A (en) * 2021-07-30 2021-11-02 海南福港远洋渔业有限公司 Far deep sea fishing method
CN114153003A (en) * 2021-11-08 2022-03-08 浙江海洋大学 Image acquisition processing device and acquisition method for ocean electronic information engineering
CN114185079A (en) * 2021-11-22 2022-03-15 武汉船舶通信研究所（中国船舶重工集团公司第七二二研究所） An underwater stereo detection system
CN114394202A (en) * 2021-12-28 2022-04-26 深圳潜行创新科技有限公司 Unmanned ship control system
CN115195959A (en) * 2022-08-12 2022-10-18 青岛科技大学 A marine surveying and mapping equipment based on intelligent unmanned ship
CN115195959B (en) * 2022-08-12 2023-09-19 青岛科技大学 Marine marine mapping equipment based on intelligent unmanned ship
CN115305808A (en) * 2022-08-30 2022-11-08 武汉工程大学 Integrated application method and system of multi-type bridge detection equipment based on unmanned platform
CN115128690A (en) * 2022-09-01 2022-09-30 深圳潜行创新科技有限公司 Floating type underwater detection device with underwater rotary camera and method
CN117193304A (en) * 2023-09-20 2023-12-08 武汉理工大学 An unmanned ship cluster control method and related equipment
CN117193304B (en) * 2023-09-20 2024-05-07 武汉理工大学 Unmanned ship cluster control method and related equipment
CN119142491A (en) * 2024-11-20 2024-12-17 上海交通大学三亚崖州湾深海科技研究院 High-anti-flow multi-point observation type fish school monitoring underwater robot based on multi-source data fusion
CN119142491B (en) * 2024-11-20 2025-01-28 上海交通大学三亚崖州湾深海科技研究院 A highly flow-resistant multi-point observation fish school monitoring underwater robot based on multi-source data fusion

Similar Documents

Publication Publication Date Title
CN112644646A (en) Underwater robot intelligent system for large-water-area fish resource investigation and working method
Agarwala Monitoring the ocean environment using robotic systems: Advancements, trends, and challenges
Zacchini et al. Forward-looking sonar CNN-based automatic target recognition: an experimental campaign with FeelHippo AUV
CN111637874B (en) Multi-AUV layered detection system and detection method for red tide sea area
CN111735922B (en) Aquaculture monitoring system based on underwater robot
CN109144105A (en) A kind of hull bottom intelligence underwater cleaning robot, control system and control method
Radeta et al. Deep learning and the oceans
KR101988963B1 (en) Discovery system using the deep-learning
Berkenpas et al. A buoyancy-controlled lagrangian camera platform for in situ imaging of marine organisms in midwater scattering layers
Okamoto et al. Visual and Autonomous Survey of Hydrothermal Vents Using a Hovering‐Type AUV: Launching Hobalin into the Western Offshore of Kumejima Island
Nishida et al. Benthos sampling by autonomous underwater vehicle equipped a manipulator with suction device
CN111323418A (en) Sea surface oil stain monitoring system based on unmanned ship
CN110333369A (en) UUV DVL Velocity Measurement System and Adaptive Noise Removal Method Based on Surface GPS Correction
CN113281823A (en) Magnetometer detection device of underwater autonomous platform
CN110412583B (en) Underwater unidentified moving target detection system based on multi-ROV cooperation
CN113050665A (en) Energy-saving underwater robot detection method and system based on SLAM framework
Ribas Romagós Underwater slam for estructured environments using and imaging sonar
KR102431452B1 (en) Underwater survey system using under water drone
TR2022013492A2 (en) FISH DETECTION SYSTEM AND ALGORITHM WITH DRON
Lowe et al. Use of autonomous vehicles for tracking and surveying of acoustically tagged elasmobranchs
TWM583606U (en) Marine mammal tracking system and carrier thereof
Massot-Campos et al. Assessing benthic marine habitats colonized with posidonia oceanica using autonomous marine robots and deep learning: A Eurofleets campaign
Babić et al. Design and development of a low-cost floater for sustainable fishing
Yasukawa et al. Development and Sea Trials of Vision-Based Control for Sampling-AUV
CN219957890U (en) Submarine cable inspection system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20210413

RJ01 Rejection of invention patent application after publication