3084 results about "Underwater robot" patented technology

The present disclosure provides an underwater detection method for contact leakage of a tunnel joint of a dam culvert, including: obtaining an underwater image sequence of the culvert by an underwater robot; preprocessing and registering the underwater image sequence; extracting particle information appearing in the underwater image sequence based on the registered underwater image sequence; constructing a three-dimensional fluid velocity distribution map based on the particle information, and determining leakage situation according to the three-dimensional fluid velocity distribution map; and superimposing the three-dimensional fluid velocity distribution map on a preconfigured three-dimensional culvert model, and rendering and displaying it. The present disclosure can adapt to the complex and changeable underwater environment inside the culvert, it has a high sensitivity to fine leakage in the deep layer, it can realize the accurate measurement and trend prediction of leakage, and it can automate the detection process to reduce manual dependence.

The invention discloses an underwater robot autonomous obstacle avoidance and path planning system based on a multi-modal sensor, particularly relates to the field of underwater robot navigation, solves the problems of multi-modal sensing and path planning in a complex environment, and unifies the feature space of a multi-source heterogeneous sensor based on a physical field correction mode of an acousto-optic fluctuation rule. Fusion deviation caused by physical property difference of sonar and visual data is overcome, and obstacle characterization precision and dynamic environment adaptability are remarkably improved; a dynamic confidence decision-making mechanism is combined with a path curvature-moment constraint model, the environmental perception credibility and the robot motion performance are synchronously fused into a path generation process, the feasibility of motion control is ensured while the geometric collision risk is avoided, and the contradiction between the safety and the performability in path planning is solved; the global path optimization eliminates the hidden danger of local path sudden change through iterative smoothing under double constraints of physical field and dynamics, and forms an optimal navigation scheme considering obstacle avoidance efficiency, energy consumption and motion stability.

The invention discloses an autonomous navigation method for an underwater robot based on energy consumption perception, which comprises the following steps of: acquiring underwater environment parameters and robot state parameters by fusing multi-sensor data, constructing a factor graph model containing pose nodes and energy consumption nodes by adopting a graph-based SLAM (Simultaneous Localization and Mapping) algorithm; a local area environment energy consumption map is obtained by fusing maximum posteriori estimation of poses and energy consumption with robot state parameters, the local energy consumption map is updated in real time according to extension of a robot exploration area, if the current local energy consumption map covers a global target position, a global energy consumption optimal path is calculated according to the path length and energy consumption, and the optimal energy consumption is calculated according to the path length and the energy consumption. And if the current local energy consumption map does not cover the global target position, triggering local path re-planning, generating an energy consumption compensation strategy, and if the current path is invalid due to major change of the environment, re-executing global planning.

The invention provides a comprehensive and intelligent mariculture net cage management and control system. The system integrates a multi-parameter sensor module, an underwater robot module, an underwater camera module, a central control module, a data storage and analysis module, an early warning module, a remote communication module and an automatic execution module. By monitoring multiple environmental parameters such as water temperature, salinity, dissolved oxygen and the like in real time and utilizing the underwater robot and the underwater camera to carry out autonomous inspection and fish behavior observation, the system can accurately master the culture environment condition. The AI algorithm and the intelligent model are combined, the system dynamically adjusts the bait casting amount, the oxygenation frequency and the net cage position, and the breeding benefits are effectively improved. Meanwhile, the early warning module carries out graded early warning on risk events such as typhoon and diseases, and the breeding safety is ensured. The remote communication and visual human-computer interface further enhances the remote monitoring and management capability of the system.

The invention discloses a battery energy recycling method for an underwater robot, and the method comprises the steps: integrating the equipment state and environment data of the underwater robot, screening the data through a particle filtering algorithm, capturing the depth information of an underwater environment in real time, collecting the material attribute of a battery and an energy transmission efficiency parameter, and recognizing the parameter through a k-means clustering algorithm. The method comprises the following steps: constructing constraint conditions of an energy recovery network, constructing an energy recovery network topology model according to energy loss information and node layout, obtaining an optimal path by applying an Euleran path algorithm, determining an arc curvature by adopting a non-dominated sorting genetic algorithm, dynamically updating topology model parameters, obtaining an optimized energy recovery arc, and constructing an arc optimization mechanism. A logistic regression algorithm is used for scoring arcs and identifying efficient nodes, an Apriori association rule mining algorithm is used for simplifying a network topology structure, calculating structural differences and updating a model, a fitness function algorithm is used for monitoring the network state and energy loss in real time, and the transmission efficiency is evaluated.

The invention relates to a coastal wetland ecological restoration effect evaluation method and system, and belongs to the technical field of ecological monitoring and restoration. Aiming at the problems of static evaluation index lag, insufficient data fragmentation integration and lack of causal diagnosis mechanism in the prior art, multi-source time sequence ecological data are acquired by constructing a three-dimensional monitoring network consisting of satellite remote sensing, an unmanned aerial vehicle, an Internet of Things sensor and an underwater robot; a fusion data set is generated based on space-time alignment and tidal phase marking, dynamic evolution characteristics are extracted by using an LSTM network, and a spatial distribution difference chart of ecological parameters before and after restoration is generated in combination with a GAN; and furthermore, through hot area clustering and historical data association mining, a degradation driving factor is positioned, and an optimization suggestion is generated. The method breaks through the space-time limitation of a traditional evaluation method, remarkably improves the degradation diagnosis precision and the regulation and control efficiency of restoration engineering, and is suitable for various ecological restoration scenes such as estuary delta and coral reefs.

The invention relates to an underwater robot navigation positioning method and system. The method comprises the following steps: S1, acquiring angular velocity and acceleration signals through an inertial measurement unit; s2, resolving a three-dimensional velocity observation value according to the beam radial velocity vector signal in combination with the angular velocity signal, and extracting environment feature point cloud data according to the acoustic image signal; s3, multi-source data time synchronization is carried out, and a fusion input signal with time-space alignment is generated; s4, constructing an adaptive factor graph optimization model, and dynamically adjusting an inertial navigation solution node based on a real-time weight coefficient; inputting the environment feature point cloud data into a closed-loop detection module to generate a loopback factor node, and adaptively correcting the weight of the node according to the feature matching degree; and S5, solving the adaptive factor graph optimization model through a nonlinear optimization algorithm. According to the underwater robot navigation positioning method and system, the problem that the fusion positioning precision of a multi-source heterogeneous sensor is insufficient in an underwater GPS-free environment can be solved.

The invention discloses a multi-underwater-robot cooperative control system and method based on predictive control, and relates to the technical field of cooperative control. During operation of the system, underwater environment data are collected through sensor equipment, an underwater three-dimensional dynamic environment model is generated by using a data fusion technology, and the underwater three-dimensional dynamic environment model is established based on task requirements; tasks are decomposed and distributed to all the robots, through an optimization algorithm, optimal paths of the robots and the mechanical arms are planned, the motion trails of the underwater robot mechanical arms are dynamically optimized based on model predictive control MPC, a real-time control strategy is provided for task division among the multiple mechanical arms, and the real-time control strategy of the underwater robot mechanical arms is provided based on environment modeling and the real-time state. Future motion states of the robot and the mechanical arm of the robot are predicted, an optimization objective function including task completion time, energy consumption and mechanical arm operation precision is constructed, a rolling optimization method is utilized, a control instruction is updated in real time, and real-time data sharing among multiple underwater robots is supported based on an acoustic communication technology.

The invention provides a multi-scale underwater fish school detection system and detection method based on an attention module, relates to the technical field of underwater detection, and performs multi-scale fusion on sonar signals and image information. The depth of a fish school is determined through a sonar, a sound wave feature vector is generated, an unmanned underwater robot is used for collecting a low-illumination image, edge features are generated in a grey-scale image, color features are generated in an HSV color space, and the edge features and the color features are corrected. Weighted fusion is carried out on the sound wave features, the edge features and the color features through a feature alignment and attention module, and a comprehensive feature vector is generated. And finally, constructing a fish school detection model by using a deep learning network based on the deep feature vector, and realizing real-time detection of fish school categories and quantity. According to the method, multi-scale information and an attention mechanism are utilized, and the accuracy and reliability of fish school detection are improved.

The invention discloses a high-flow-resistance multi-point observation type fish school monitoring underwater robot based on multi-source data fusion. The high-flow-resistance multi-point observation type fish school monitoring underwater robot comprises a shell, a self-adaptive ocean current resistance system and an energy system. The self-adaptive ocean current resistance system comprises an ocean current information detection module and a PID control algorithm real-time regulation and control propeller module; the ocean current information detection module is used for collecting ocean current information in real time, including water velocity, direction and turbulence intensity; the control algorithm real-time regulation and control thruster module regulates and controls the power and direction of a thruster in real time by utilizing a PID control algorithm according to ocean current changes, and it is ensured that the underwater robot keeps stable in complex ocean currents; the telescopic multi-sensor fusion system collects multi-dimensional data of a fish school by combining a plurality of sensors, and performs fusion analysis on the data by using a deep learning algorithm, thereby realizing high-precision fish school identification and tracking. And an integrated ocean current-solar energy system enables the underwater robot to have long-time cruising ability.

The invention discloses a rescue underwater robot based on multi-mode drowning recognition and a rescue method. The rescue underwater robot is provided with a multi-mode recognition module, a rescue launching device module and a diving mask auxiliary rescue module. The multi-modal recognition module obtains images through a high-definition camera and a sonar, the recognition precision is improved through the combined calibration of direction angles and the feature fusion technology, and accurate detection of a drowning target is achieved; the rescue launching device module adopts a spring launching device to quickly release a rescue device, the rescue device is provided with a high-elasticity silica gel strip and a built-in inflatable bag, the silica gel strip is provided with an anti-skid texture structure and can quickly surround and fix the waist of a drowning person, and the inflatable bag is automatically started to be inflated after it is confirmed that the inflatable bag is stably contacted with the drowning person through a magnetic delay mechanism; the diving mask auxiliary rescue module is provided with a heart rate sensor, a motion sensor, an emergency help button and a black box module, and the state of a diver is monitored in real time.

The invention relates to the technical field of AUVs (Autonomous Underwater Vehicles), in particular to a real-time communication and positioning data fusion processing method for AUV (Autonomous Underwater Vehicle) collaborative operation, which comprises the following steps of: deploying a multi-modal sensor, acquiring communication data, kinematics data, acoustic positioning data and visual data required by an AUV, and preprocessing the data; the method comprises the following steps: fusing multi-modal data by using an extended Kalman filtering algorithm, calculating three-dimensional position and attitude information of the AUV in real time, carrying out dynamic path planning by using an ant colony optimization algorithm based on fused positioning data, optimizing a collaborative operation path between the AUVs, and sharing the positioning data and a path planning result in real time through an underwater communication network. And dynamically adjusting a task allocation strategy by using an improved task allocation algorithm, optimizing the cooperation efficiency, and finally, storing all data, path planning records and task allocation schemes in a database. According to the invention, the accuracy and stability of AUV collaborative operation are improved.

The invention discloses an end-to-end underwater three-dimensional reconstruction method and system based on an underwater imaging model, and belongs to the technical field of underwater image processing. According to the method, deep learning pose estimation is combined with an underwater imaging model; firstly, a multi-frame underwater image sequence is collected as input, a deep neural network is constructed, and the network mainly comprises two core sub-modules: a pose estimation network; secondly, a three-dimensional reconstruction network is adopted, dense point cloud or voxel reconstruction is completed according to the predicted pose and image content, pose estimation and the three-dimensional reconstruction process are integrated in the same system, and overall joint optimization is achieved; and in combination with a self-adaptive underwater imaging model, modeling is performed on physical processes such as underwater illumination attenuation and scattering, so that the reality sense and the accuracy of a reconstruction result are improved. According to the method, high-quality three-dimensional reconstruction of images in a complex underwater environment is realized, and the method can be widely applied to ocean engineering, underwater robots, submarine topography surveying and mapping and underwater cultural relic protection.

The invention discloses an underwater robot vision sharpening method based on a multi-modal fusion network, and belongs to the technical field of underwater image processing, and the method mainly comprises the steps: collecting a turbid underwater image and a corresponding clear underwater image, and constructing an underwater polarization image data set which comprises underwater polarization images, polarization degree images and polarization angle images of different angles; constructing an underwater robot vision clearness model based on the multi-modal fusion network, wherein the underwater robot vision clearness model comprises the multi-modal fusion network and an image enhancement network; training the multi-modal fusion network based on an underwater polarization image data set, updating RGB information and polarization information by using pixel multi-scale fusion during training, and generating fusion features; training the image enhancement network by using an underwater polarization image data set to obtain an image enhancement-based model; and obtaining a to-be-processed fusion feature with turbidity, and inputting the fusion feature into the network-based image enhancement model, thereby obtaining a clear underwater image.

The present disclosure relates to the field of underwater robots, and in particular to a controllable sinking and floating swimming pool robot and a sinking and floating control method for a swimming pool robot. The controllable sinking and floating swimming pool robot of the present disclosure includes a sinking and floating control unit configured to control a swimming pool robot to float and sink; a waterline detection unit configured to detect a positional relationship between the swimming pool robot and a waterline of a liquid surface of a swimming pool where the swimming pool robot is located; and a main control unit configured to control a working state of the sinking and floating control unit to enter a floating working state based on detection results to realize a floating of the swimming pool robot.

The invention discloses an underwater robot dynamic environment sensing and navigation device and method, and relates to the technical field of underwater robos.The device comprises an underwater robot, a sensor system, a data processing system, a control system, a navigation system and a power system, and the sensor system, the data processing system, the control system, the navigation system and the power system are arranged on the underwater robot; the surrounding environment can be comprehensively sensed in real time, and the optimal path is calculated through the path planning module according to the real-time environment data; performing obstacle detection according to the environment image to obtain an obstacle detection result; when an obstacle is detected, the control system sends out an obstacle avoidance decision instruction, after the path planning module receives the obstacle avoidance decision instruction, an adaptive algorithm is used for adjusting the optimal path according to the information of the obstacle to be detected, the adjusted path is obtained, and autonomous navigation for a complex underwater environment and autonomous navigation are achieved. And the autonomous navigation and operation capabilities of the underwater robot are obviously improved.

The invention relates to an image processing method for an underwater robot heterogeneous imager array, and the method comprises the steps: S1, collecting an original underwater image, and carrying out the brightness adjustment, and obtaining a first image with balanced brightness; s2, analyzing pixel distribution of the first image, and judging and executing de-scattering processing to obtain a second image; s3, performing multi-scale detail enhancement on the second image to obtain a third image with richer details; s4, evaluating color distribution of the third image, and performing color correction to obtain a fourth image; s5, performing adaptive denoising processing on the noise features of the fourth image to obtain a fifth image; s6, according to the contrast characteristic of the fifth image, contrast adjustment is carried out to ensure that a preset threshold value is met, and a sixth image is obtained; s7, edge enhancement processing is carried out on the sixth image, and a seventh image with the clear edge is obtained.By means of illumination compensation, scattering removal and multi-scale detail enhancement, the influence of complex optical conditions of the underwater environment on the image quality is effectively overcome.

The invention discloses a deep and far sea cage culture typhoon disaster prevention and after-disaster rapid recovery method, which comprises the following steps of: carrying a high-definition camera by using an unmanned aerial vehicle to aerially photograph a cage water surface structure before a disaster, acquiring an underwater image by an underwater robot through sonar hierarchical scanning and the camera, and generating structure data and fish school data before the disaster; weak points such as frames, nettings and anchor chains are analyzed through three-dimensional modeling and are repaired and reinforced, the stocking density is optimized in combination with typhoon information, the risk of facility damage and fish loss is reduced, structural data and fish school data are repeated after a disaster, and the pre-disaster standard serves as a reference to compare and evaluate the frame damage degree, the nettings damage degree, the anchor chain breakage degree and the fish school escape or death degree; and generating a graded repair scheme and a disaster relief plan. According to the method, the detection precision and the evaluation efficiency are improved through multi-device cooperation and data fusion, the damaged part is rapidly positioned, the recovery strategy is optimized, and an efficient disaster prevention and reduction and after-disaster rapid recovery solution is provided for deep and far sea cage culture.

The invention discloses an underwater robot submarine cable inspection method and system based on two-dimensional image sonar, and relates to the field of submarine cable inspection. The existing submarine cable inspection method has the problems of insufficient detection precision, lack of autonomy, dynamic obstacle avoidance defect and the like. The method comprises the steps of submarine cable feature recognition model construction, underwater robot sensing system configuration, image processing, path planning, obstacle avoidance path generation and detouring. According to the technical scheme, the underwater robot carries the electromagnetic induction sensor, the two-dimensional image sonar and the ultra-short baseline positioning device, and an image processing technology and a path planning algorithm are combined, so that efficient inspection of the submarine cable is realized; when the robot encounters an obstacle, the robot can generate an obstacle point cloud through image processing in combination with prior obstacle information, and performs obstacle avoidance in combination with a local path planning algorithm, so that safe and smooth proceeding of an inspection task is ensured; the detection precision is effectively improved, automatic and efficient inspection is realized, and a powerful guarantee is provided for long-term stable operation of the submarine cable.

The invention discloses an underwater robot multi-target dynamic resource scheduling method, and relates to the technical field of robot resource scheduling. The method comprises the following steps: constructing an underwater robot resource scheduling problem model, and establishing a target optimization model which comprises the steps of minimizing task maximum execution time, minimizing total power consumption and balancing load; generating reference points and distributing the reference points in a target space; a population is coded and initialized, a scheduling scheme is represented by adopting multi-segment chromosome coding, the scheduling scheme comprises a task allocation sequence and tasks allocated by a robot, and an initial parent population is generated in a random mode; a non-dominated solution set is obtained through evolutionary iteration, and the non-dominated solution set is obtained through reference point niche selection and combined evolutionary iteration of crossover and mutation operation based on an improved NSGA-III algorithm; and obtaining an optimal scheduling scheme, and screening an optimal compromise solution from the non-dominated solution set as the optimal scheduling scheme. According to the invention, a data-driven intelligent scheduling scheme is provided for collaborative operation of underwater robots in a complex marine environment.

The invention provides a hydro-junction water level adjusting method and system. Wherein the sediment deposition space-time atlas containing the sedimentary gradient is constructed and periodically corrected through scanning of an underwater robot and synchronous acquisition of satellite remote sensing data. A radar array is deployed at a bend section of a flood discharge channel, and vector distribution of a three-dimensional sediment flow velocity field is analyzed by using multi-frequency pulse signals. Through correlation analysis of the dynamic coupling sedimentary gradient and the flow velocity field, a correlation area of flow velocity sudden change and sediment deposition is accurately identified, and a constraint condition set including coordinate positioning and a flow-sediment matching rule is established. And in combination with real-time water level monitoring data, calculating and generating a dynamic adjustment parameter sequence of the opening degree of the flood discharge gate by using a constraint condition set, thereby realizing accurate regulation and control of the water level. According to the technical scheme, the flood discharge parameters are intelligently optimized, the water level of the hydro-junction can be accurately regulated and controlled, the sediment deposition problem of a high-sediment-content water area is effectively relieved, and safe operation and flood control efficiency of the junction are guaranteed.

The invention discloses an underwater robot inspection obstacle avoidance control method and system, and relates to the technical field of robots, an event camera is introduced to construct a two-dimensional event response distribution diagram, local feature vectors acquired by multiple sensors are fused, a semantic point cloud is formed, and a geometric, semantic and dynamic residual triple optimization mechanism is constructed in combination with a historical environment map. According to the method, depth alignment of a current state and a historical map is realized, the dynamic obstacle identification precision and the adaptive ability of obstacle avoidance path planning are further improved, risk level division can be carried out on an updated environment map through calculation of a dynamic confidence coefficient C and a color coding mechanism, high-dynamic-risk, medium-risk and low-risk areas are distinguished, and the accuracy of obstacle avoidance is improved. According to the method, the intelligent decision-making capability of path selection is effectively enhanced, and on the basis, the data in the red area is preferentially uploaded by combining a return priority scheduling mechanism, so that the consistency matching of the task risk level and the data uploading priority is realized, and redundant data transmission is reduced.

The invention relates to the technical field of structure inspection, in particular to a bridge pier underwater structure inspection system based on an unmanned underwater robot, which comprises an inspection period adjustment module, an anomaly recognition module, an automatic supplementary shooting module, a damage evaluation module and a bridge pier anomaly evaluation module. According to the invention, bridge pier underwater structure inspection is executed through the unmanned underwater robot, the inspection period is dynamically adjusted according to the traffic flow, fine management of inspection work is realized, the inspection frequency can be adjusted according to actual use conditions and external influence factors, potential structure problems are effectively prevented and found, and the inspection efficiency is improved. The damage area can be quickly and accurately calibrated by image acquisition and automatic anomaly recognition performed by the unmanned robot, supplementary shooting is performed when necessary, the image quality is improved, the data reliability is ensured, and the influence of damage on the structural safety can be accurately evaluated by comparing the positions and overlap ratios of the damage area and the key bearing area of the bridge pier, so that the safety of the bridge pier is improved. And a scientific basis is provided for maintenance decision.

The invention provides an underwater robot intelligent navigation and environment sensing system based on a multi-sensor fusion collaborative technology. The system integrates a plurality of sensors such as sonar, optical, electromagnetic and the like, and realizes comprehensive data acquisition and real-time perception of an underwater environment. By applying advanced algorithms such as Kalman filtering and a neural network, the system performs synchronization, preprocessing and deep fusion on multi-source data, and the consistency and accuracy of information are remarkably improved. In addition, the system also has adaptive navigation and environment perception capabilities, can dynamically adjust a navigation path and a perception strategy according to fused data, and adapts to a complex and changeable underwater environment. And the intelligent decision support system provides decision assistance for an operator in combination with an environment perception result and a task target. And due to the design of a user interaction and monitoring interface, the usability and real-time monitoring capability of the system are ensured. According to the implementation of the invention, the precision and efficiency of the underwater robot in tasks such as monitoring and exploration are greatly improved.

The invention discloses an energy consumption optimization path planning method for an underwater robot. According to the method, an ocean current model is established by using a Navier-Stokes equation, and complex water flow in the ocean is simulated; a mountain peak model is used for simulating complex submarine topography, and a sphere model is used for simulating random obstacles in the ocean; the outer layer of the path planner adopts a particle swarm optimization algorithm, the inner layer of the path planner adopts a sequential quadratic programming algorithm, and the optimal speed of each section of path can be obtained while path points are obtained; fitting path points by using a B-spline curve to generate a smooth path; and a special fitness function calculation mode is adopted, and a re-planning strategy is combined, so that the calculation efficiency of the algorithm is improved. According to the method, the optimal navigation speed of the robot in different environments can be calculated, the energy consumption of the planned path is reduced on the basis of ensuring the navigation time and safety of the robot, and the efficiency and robustness of path planning are effectively improved through a multi-algorithm combined double-layer path planner and a dynamic re-planning mechanism.

Provided in the present application is an underwater robot, including a robot body and a trigger mechanism. The trigger mechanism includes a sealed cabin, a driving mechanism, and a sensing structure, where the sealed cabin is disposed in the robot body, and the sensing structure is disposed in the sealed cabin and electrically connected to the driving mechanism. The sensing structure is configured to detect whether the underwater robot enters water, and trigger the driving mechanism to work, so that the underwater robot moves in the water and performs cleaning.

The invention discloses an underwater multi-degraded image enhancement and target recognition joint optimization method based on a genetic algorithm, and relates to the field of underwater image enhancement and underwater target recognition, and the method comprises the steps: building an underwater robot target recognition system, obtaining underwater event camera data, and processing the underwater event camera data to obtain a sample data set; initializing by adopting a genetic algorithm to obtain a primary population, namely an initial enhancement parameter; performing initial enhancement on the environment information by adopting the initial enhancement parameter to obtain an initial enhanced image data set; taking YOLOv5 as a basic framework, constructing an underwater target recognition algorithm model, and obtaining underwater target detection average precision mAP; the underwater target detection average precision mAP is used as a genetic algorithm fitness value, a genetic algorithm is adopted to optimize enhancement parameters of an underwater multi-degraded image enhancement module, then target enhancement parameters are obtained to enhance environment information to obtain a target enhanced image, and the purposes of image enhancement and effective recognition are achieved at the same time.

The invention discloses a cable underwater robot trajectory tracking control method for coping with ocean current disturbance, and belongs to the technical field of underwater robot trajectory tracking, and the method comprises the following steps: S1, constructing a kinematics and dynamics model of a cable underwater robot, and simplifying the kinematics model of the cable underwater robot; s2, combining speed information of a Doppler velocimeter sensor, designing a super-spiral expansion state observer, and compensating a cable underwater robot system; designing a self-adaptive super-spiral expansion state observer by combining a self-adaptive law; and S3, designing a self-adaptive super-spiral integral terminal sliding mode controller based on the self-adaptive super-spiral expansion state observer. The real-time dynamic performance and stability of the underwater robot in sliding mode control are improved, the buffeting problem existing in sliding mode control is solved, it is ensured that under the condition of ocean current disturbance, the ROV can still achieve accurate trajectory tracking, and the robustness is very high.

The invention discloses a drilling-grouting integrated underwater robot and aims to meet the requirement for precise operation in a complex underwater environment. The robot integrates the fin antenna, the hydraulic telescopic crawler belt, the hydrodynamic force wings, the bionic mechanical arm and the integrated drilling and injecting system, and has the multi-terrain adaptation, efficient navigation and autonomous operation capacity; through modular design and a high-strength pressure-resistant structure, the robot can complete tasks such as pipeline repair, resource exploration and infrastructure construction in a deep sea high-pressure environment; the core technology comprises a multi-mode propulsion system, intelligent sensing and navigation, AI optimization operation and dual-mode operation switching. Typical application scenes include submarine pipeline damage repair, deep sea mining area reinforcement sampling, cross-sea bridge pile foundation grouting and the like. The limitation that a traditional underwater robot is single in function and high in energy consumption is broken through, and the safety and efficiency of complex underwater engineering are remarkably improved.

The invention discloses a crack detection and grouting repair system for underwater concrete, which comprises a visual operation system and an underwater robot controlled by the visual operation system, the underwater robot comprises a bearing plate, a multifunctional converter arranged below the edge of the bearing plate, and a power assembly, a camera shooting assembly, a detection assembly, a crack repairing assembly and a control circuit which are arranged in corresponding areas of the bearing plate. The detection assembly comprises an ink jet head arranged on the multifunctional converter, the ink jet head is used for carrying out ink jet treatment on the suspected crack area, and the ink jet head is connected with a corresponding ink storage box; the crack repairing assembly comprises a high polymer spray head arranged on the multifunctional converter and a pinhole grouting head arranged below the base, the high polymer spray head and the pinhole grouting head are communicated with a micro grouting machine, the high polymer spray head is used for narrow crack grouting repairing, and the pinhole grouting head is used for wide crack grouting repairing. The invention aims to realize crack detection and repair of underwater concrete.