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 PDFInfo
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- 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
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- 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
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- 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
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- 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
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- 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
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- 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
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- 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
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- 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
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- 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
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- 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
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- 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
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Abstract
The invention belongs to the technical field of underwater robots. The underwater robot system for the large-water-area fish resource investigation based on underwater vision assistance is provided, 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 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.
Description
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. 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 (101) and a shore-based wireless communication module which is in information communication with the shore-based server and is used for carrying out classification processing on image information returned by the unmanned ship, recording depth and position information, processing and analyzing 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 (206) and an unmanned underwater vehicle, wherein the unmanned ship is provided with a sonar (203), a Beidou navigation system (202), a navigational speed instrument, an attitude sensor and a shipborne wireless communication module (201); the unmanned underwater vehicle carries an ultra-high-definition underwater camera, a depth sensor (304), 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.
2. The underwater robot intelligent system for large-water-area fish resource investigation according to claim 1, wherein: 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.
3. The underwater robot intelligent system for large-water-area fish resource investigation according to claim 2, wherein: 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.
4. The underwater robot intelligent system for large-water-area fish resource investigation according to claim 3, wherein: 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.
5. The underwater robot intelligent system for large-water-area fish resource investigation according to claim 4, wherein: the control circuit, the attitude adjusting module and the communication assembly of the unmanned underwater vehicle are respectively arranged in two pressure-resistant sealed cabins (302); the ultra-high-definition underwater camera (303) is arranged on the lower deck of the unmanned underwater vehicle and is respectively fixed with the lower deck through two fixing rings; the depth sensor (304) is installed right behind the ultra-high-definition underwater camera 303.
6. The working method of the underwater robot intelligent system for the investigation of the fish resources in the large water area as claimed in claim 1 is divided into the following two types:
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 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 image information and the activity information obtained by the sensor are transmitted back to a shore-based server in real time 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.
7. The working method of the underwater robot intelligent system for the large-water-area fish resource investigation, according to claim 6, is characterized in that: 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.
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Cited By (6)
| 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 |
| 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） | Underwater three-dimensional detection system |
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| CN117193304A (en) * | 2023-09-20 | 2023-12-08 | 武汉理工大学 | Unmanned ship cluster control method and related equipment |
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