2278 results about "Underwater robot" patented technology

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 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 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 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 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 proposes an underwater target intelligent recognition system based on multi-sensor fusion, and relates to the technical field of underwater target recognition, and the system comprises an underwater robot which is provided with an optical sensor, an acoustic sensor, a three-dimensional laser sensor, and a water quality environment sensor; the data acquisition module is used for synchronously acquiring original multi-modal data and water quality parameters from the underwater robot; the data preprocessing module is used for generating preprocessed multi-modal data; the multi-modal feature fusion module is used for extracting each modal feature from the preprocessed multi-modal data and generating a fusion feature; the target recognition and positioning module is used for processing the fusion features by adopting a target detection network and outputting the category, the position and the confidence of the underwater target; and the intelligent analysis output module is used for comprehensively analyzing the information of the underwater target and generating an analysis result and visual data. According to the invention, the limitation of a single sensor can be overcome, and the underwater target can be accurately and stably identified by combining an intelligent algorithm.

The invention relates to the technical field of underwater robots and high-precision positioning, and particularly discloses a high-precision positioning system for collaborative operation of an underwater robot cluster. The system comprises a multi-source fusion positioning base station network module, a cross-medium cooperative positioning engine module, a cluster relative positioning subsystem module, a dynamic environment perception compensation module, an elastic positioning fault-tolerant system module and a cooperative positioning decision center module. An absolute positioning reference is constructed through a multi-source fusion positioning reference station network, a cross-medium cooperative positioning engine is combined to realize accurate pose calculation, a cluster relative positioning subsystem is utilized to establish a dynamic topological relation between robots, an environment perception compensation and elastic fault-tolerant mechanism is introduced, and finally resource configuration is optimized through a cooperative decision center. The method solves the problem of high-precision positioning of robot cluster collaborative operation in a complex underwater environment, and can be widely applied to the fields of ocean exploration, underwater engineering and the like.

The invention relates to the technical field of intelligent monitoring, in particular to an underwater robot monitoring device and method based on muon imaging and navigation positioning, and the device comprises a transmission and control subsystem which is used for driving an underwater robot to complete a target action task in an underwater pipeline; the muon imaging positioning subsystem is used for acquiring high-energy imaging information and a three-dimensional coordinate position of the underwater robot so as to assist the underwater robot in completing a target action task; the underwater scanning, monitoring and early warning subsystem is used for evaluating a water sample of the underwater pipeline to generate a water quality evaluation report and acquiring surrounding terrain and geological feature information of the underwater pipeline to generate an underwater three-dimensional image; and the multi-source data fusion transmission base station is used for fusing the water quality evaluation report, the high-energy imaging information and the underwater three-dimensional image to generate a state evaluation report. Therefore, the problems of insufficient penetrating power, low resolution, signal interference and the like of the existing underwater monitoring technology and the like under the conditions of deep water, high turbidity or complex terrains are solved.

The invention relates to a low-illumination underwater image enhancement method based on double-domain adaptive collaboration, and the method employs a multi-scale mixed attention mechanism to collaboratively integrate the spatial domain and frequency domain information of an image, and obtains the key feature information of the image. And on the basis of the obtained image key feature information, adaptive parametric convolution is used, convolution kernel parameters are dynamically adjusted by using a multi-branch convolution structure, and image dynamic key information is obtained. And a dynamic content perception Markov discriminator is used to cooperatively perceive space and frequency characteristics, and the authenticity of the enhanced image is discriminated, so that the fidelity of the texture is improved. And finally, optimizing the generator and the discriminator by using adversarial training, and finally outputting an enhanced underwater image by using the optimized generator. The method can be embedded into an underwater robot platform, image quality enhancement is achieved with fewer computing resources in a low-illumination complex water environment, image definition, contrast and color consistency are improved, the enhanced image is closer to human eye visual perception, and the visual perception capability and operation reliability of an underwater robot are remarkably improved.

The invention provides a multi-mode underwater detection robot. The robot comprises a body section assembly formed by connecting a plurality of cabin pipe assemblies and power cabin assemblies in series. Joints between the cabin pipe assemblies are connected through joint connecting pieces (7); a steering engine joint piece (3) is arranged at the joint connecting piece, a propeller propelling device (4) is arranged at the power cabin assembly, and when the underwater posture and the propelling working condition of the robot are adjusted, a steering engine of the steering engine joint piece applies force to the joint connecting piece to change the included angle of the joint connecting piece, so that the body section assembly is twisted, and the posture of the robot is converted into different modes; the propelling direction of the propeller propelling device is changed; the problems that an existing underwater robot is single in mode, incapable of adapting to complex environments, low in energy efficiency, difficult in structure maintenance and poor in function expansion capacity can be solved.

The invention discloses a method for improving channel traffic volume based on an underwater map, and belongs to the technical field of water transportation traffic, and the method comprises the following steps: S1, constructing an underwater high-precision map, deploying an unmanned ship and an underwater robot, and collecting underwater topographic data by using a multi-beam sounding technology to construct a high-precision underwater map; s2, establishing a dynamic channel planning model, collecting hydrological data and ship traffic data of different time and places of a channel by using a big data analysis and machine learning algorithm, and generating a dynamic channel use scheme; and S3, integrating a ship navigation and management system, developing ship navigation terminal equipment, and integrating the dynamic channel planning model with a monitoring system of a channel management department. According to the invention, channel resource utilization is optimized, intelligent dynamic planning is realized, ship passing efficiency, navigation autonomy, navigation safety and system stability and reliability are improved, channel management scientificity is enhanced, and cooperation of ships and management departments is enhanced.

The invention discloses an underwater robot real-time three-dimensional map reconstruction system and method fused with an SLAM algorithm, and belongs to the technical field of three-dimensional map reconstruction. By constructing a confidence coefficient system of three-dimensional points, a spatial trajectory fluctuation index and an inter-frame texture change rate are introduced as dynamic feature evaluation indexes; and a regression model is adopted to score and grade the severity of the false points, and differential processing of different grades of point clouds is realized in combination with a dynamic suppression mechanism, so that an unstable structure is effectively eliminated, and the stability and reliability of the sparse three-dimensional map are remarkably improved. Therefore, the positioning precision, the path planning capability and the task execution safety of the underwater robot in a complex environment are enhanced.

The invention discloses a multi-mode water-air-land cross-medium cooperative sensing system and method based on an MEMS (Micro Electro Mechanical System). The system comprises an underwater robot, a buoy station, an unmanned aerial vehicle and a ground control station, each node is provided with an MEMS sensor integrating acoustics, optics, magnetism, inertia and other modes, and data transmission and relay are achieved through acoustics, optical communication and radio links. And the ground control station carries out fusion processing, target identification and decision control on multi-source data through time synchronization and space registration, and issues a cooperative instruction to each node to realize a perception-decision-re-perception closed loop. The method comprises five steps of node deployment and calibration, multi-modal data acquisition, hierarchical transmission and sharing, adaptive weighted fusion and closed-loop cooperative control. According to the invention, global coverage, high-precision and multi-mode environment and target perception can be provided in a complex water-air-land environment, and the detection reliability and the communication efficiency are significantly improved.

The invention relates to a robot under-actuated motion control method under the condition of failure of partial propellers. The robot under-actuated motion control method comprises the following steps: acquiring multi-source sensor data of an underwater robot; based on the multi-source sensor data, a health state model of the propellers constructed in real time is adopted, the state of each propeller is monitored in real time, and fault information of the propellers is further obtained; based on the fault information of the thruster, regularly checking the state of the thruster, and further judging whether the thruster can move at six degrees of freedom or not, if so, obtaining a thrust output scheme without coupling torque through an improved particle swarm optimization algorithm to complete the under-actuated motion control process of the robot, and if not, obtaining a thrust output scheme without coupling torque through an improved particle swarm optimization algorithm to complete the under-actuated motion control process of the robot. If yes, the robot under-actuated motion control process is completed by coordinating the sine fluctuating motion of the joints of the robot. Compared with the prior art, the invention provides a fault-tolerant control scheme under various fault conditions, and has the advantages of higher fault-tolerant control precision and the like.