433 results about "Visual observation" patented technology

The present disclosure provides a system for generating motor control commands for a humanoid robot, comprising an alpha model with over 1 billion parameters that processes visual observations and language instructions at a first frequency to generate contextual embeddings, and a beta model operating at a higher second frequency. The beta model includes an embodiment-specific state encoder projecting robot state information into a shared embedding space, a diffusion transformer module generating denoised action sequences through iterative flow-matching that cross-attends to the alpha model's contextual embeddings, and an embodiment-specific action decoder converting denoised sequences into motor control commands. The beta model generates action chunks comprising future action sequences over a predetermined time horizon in a single inference step, with the complete system having less than 5 billion parameters.

The invention relates to the technical field of decorative materials, in particular to a decorative material with a 3D texture structure and a preparation method and application of the decorative material. The method comprises the following steps: carrying out digital printing on a pretreated substrate to obtain a 2D pattern layer on the surface of the substrate; coating the surface of the 2D pattern layer with a photocuring coating, carrying out preliminary curing, and then carrying out ink-jet printing of a texture developing solution on the surface subjected to preliminary curing to carry out secondary curing, so as to obtain a cured coating; the cured coating comprises a hardened part and an unhardened part; and after an unhardened part in the cured coating is removed through polishing and wire drawing, a surface coating is coated, and the decorative material with the 3D texture structure is obtained. The textures with different widths and depths can be obtained in a manner of combining primary curing of the coating with ultraviolet absorption of the developing solution, and then a microcosmic coarse and visual smooth form is obtained through polishing and wire drawing treatment, so that the obtained 3D texture structure is closer to natural textures.

The invention provides a robot control method based on a visual language action model and related equipment thereof, and relates to the technical field of intelligent robots, and the method comprises the steps: obtaining visual observation information, a target language instruction and robot body state information of a target robot; reasoning the visual observation information, the target language instruction and the robot body state information through a pre-trained visual language action model to obtain a predicted low-dimensional potential vector; reconstructing the predicted low-dimensional potential vector into a robot action instruction through a pre-trained high-dimensional action reconstruction module; wherein the dimension of the robot action instruction is matched with the action space dimension of the target robot; and the target robot is driven to execute the high-dimensional robot action instruction. According to the method, the limitation of the existing visual language action model on the action output dimension can be solved, so that the high-degree-of-freedom robot is effectively controlled.

The invention provides a road inspection target positioning method based on multi-source data fusion, and relates to the field of road daily inspection and infrastructure performance monitoring, and the method comprises the following steps: obtaining multi-source data based on a preset multi-source sensor; through deep coupling of satellite positioning carrier double-difference observation and inertial navigation solution of an inertial sensor, error correction is carried out in combination with Kalman filtering recursion, and fusion navigation data is determined; according to the fused navigation data, carrying out fusion processing on the two-dimensional visual observation data and the three-dimensional space point cloud data to obtain a forward view depth map; determining the national geodetic coordinates of the disease by combining a depth value back calculation method and utilizing a forward view depth map; and obtaining a starting kilometer pile number in a road inspection process, and determining a mileage pile number of the disease by combining the national geodetic coordinate of the disease and utilizing a Gaussian positive algorithm. According to the invention, centimeter-level geographic coordinate positions of diseases and corresponding mileage stake numbers can be output.

The invention discloses a manifold perception-based large model navigation method guided by a historical topological graph, and relates to a computer vision technology. The method aims at solving the challenges that in the navigation process, long-distance reasoning experience is insufficient, instruction fragments and dynamic visual observation are difficult to align, and large model reasoning is prone to illusion interference. Firstly, a large model based on an encoder-decoder structure is used for supplementing historical information coding for a visual observation sequence, and therefore global topological information guidance is provided for long-distance reasoning. And secondly, in order to effectively solve the problem that large model reasoning is subjected to illusion interference, significant space-time differences in a visual observation sequence are mined by using a multi-curvature manifold, so that the large model can accurately describe the current environment and make a decision according to a visual reference object in thinking. Besides, in order to strengthen the perception capability of the large model to the space structure and establish a graph self-attention mechanism, the node distance embedded in the constructed historical topological graph is combined with the visual similarity so as to model the space relationship between the nodes.

The invention discloses a VLA model autonomous generalization method, system and device and a medium, and belongs to the technical field of robot control. The method comprises the steps of obtaining visual observation data and natural language task description of a current environment of a robot, generating an action sequence and controlling the robot to execute tasks; track data in the task execution process are collected, and token-level dense rewards and structured reflection information are output; storing the trajectory data, the token-level dense reward and the structured reflection information into a double-memory block; extracting task priori from the long-term memory by using an experience-driven generator, and generating trajectory data containing a sub-target chain; updating the VLA strategy model by using a reinforcement learning algorithm based on the token-level dense reward; and updating the VLA strategy model by using a supervised fine tuning algorithm based on the high-quality track data set. According to the method, the technical problem of autonomous generalization of the VLA model is solved.

The invention provides an inertia / satellite / vision adaptive integrated navigation method and system. The method comprises the following steps: carrying out inertia measurement and navigation calculation to obtain inertia data; calculating satellite navigation observed quantity according to the satellite navigation data and the inertial data, and constructing a satellite observation model; calculating visual navigation observed quantity according to the visual navigation data and the inertial data, and constructing a visual observation model; aiming at a satellite and a visual observation model, respectively adopting an innovation-based adaptive covariance estimation method to obtain satellite and visual observation noise covariance updated values; constructing a satellite and visual navigation health degree, and calculating a satellite and visual fusion weight according to the satellite and visual navigation health degree; controlling updating of satellite and visual navigation observed quantity according to the satellite and visual fusion weight; and calculating a weighted equivalent observation matrix and a noise covariance, and carrying out filtering estimation. According to the method, an adaptive noise estimation and sensor health degree evaluation mechanism is introduced, dynamic weighted fusion of multi-sensor data is realized, and the robustness and precision of a navigation system in complex environments such as satellite signal lock losing and visual feature missing are improved.

The invention belongs to the technical field of artificial intelligence and robot autonomous navigation, and discloses an open vocabulary topology semantic graph construction and navigation method and system for an unknown environment. A topological map composed of nodes and edges is constructed in an online incremental mode, the nodes represent key positions in the environment, and the edges represent passable connection between the positions; for each node in the topological map, coding the corresponding visual observation image into a semantic feature vector by using a pre-trained visual language model; performing graph neural network fusion on the semantic feature vectors, executing cross-modal alignment with a natural language instruction, and generating global map representation; and based on the global map representation, generating a navigation action, and driving an intelligent agent to move towards the target. According to the method, an environment representation which deeply fuses spatial topology and semantic information is constructed, and intelligent decision making is carried out according to the environment representation.

The invention belongs to the technical field of oil and gas drilling well control equipment, and particularly relates to a ram blowout preventer state confirmation method with a locking indication window, which comprises the following steps: arranging a transparent observation window on a blowout preventer shell, and calibrating the alignment position of the end face of a locking shaft and an inner side reference scribed line; after the locking action is executed, the alignment state is confirmed through multi-angle visual observation; a switchable auxiliary light source is integrated to eliminate visual interference; an industrial camera is used for collecting images, displacement deviation is recognized through an edge detection algorithm, and an alarm is given if the displacement deviation exceeds the limit; and generating an encrypted digital report containing a timestamp and equipment information, uploading the encrypted digital report to a monitoring platform, and supporting real-time check and electronic signature of a mobile terminal. Through three layers of mechanisms of standardized vision-mechanical mapping, optical enhancement and digital perception, high-reliability, high-compatibility and traceable locking state confirmation is realized.

The invention discloses a bidirectional visible narrow rectangular flow channel CHF test device and test method, and belongs to the field of nuclear power. The bidirectional visible narrow rectangular flow channel CHF test device comprises a pressure-bearing module and a transparent heating module, the pressure-bearing module comprises a pressure-bearing frame, a rectangular flow channel is arranged in the pressure-bearing frame, and through observation windows are arranged on the two sides of the pressure-bearing frame; the transparent heating module comprises a transparent heating assembly and a power supply module, the transparent heating assembly is installed on the observation window in a sealed mode and defines a test space, the transparent heating assembly comprises an ITO transparent conducting film plated on an ITO transparent conducting film substrate, and the transparent heating assembly provides heat input and a visible observation area in the CHF test. The test device can provide bidirectional visible CHF test conditions and effectively improve the test observation precision.

The embodiment of the invention relates to the technical field of robot moving trajectory planning, and provides a robot moving trajectory optimization control method and device, electronic equipment and a medium, and the method comprises the steps: obtaining visual observation data and a natural language task instruction when a robot executes a current moving trajectory; joint reasoning is carried out on the visual observation data and the natural language task instruction, a discrete action sequence is generated, smooth optimization is carried out, and a first continuous running track is generated; the robot is controlled to be converted from the current moving track to execute the first continuous moving track, and the visual observation data and the natural language task instruction of the robot executing the first continuous moving track continue to be obtained; and smooth transition processing is carried out on the newly generated second continuous moving track and the first continuous moving track, and the robot is controlled to be transited to the second continuous moving track from the first continuous moving track. Therefore, smooth trajectory generation meeting dynamic constraints, continuous trajectory transition under dynamic instructions and safety control in an abnormal state are realized.

The utility model relates to the field of batteries, and discloses a battery in-situ test sample cell, which comprises a first shell and a second shell, a first accommodating cavity with one closed end is arranged in the first shell, the first accommodating cavity is used for accommodating a sample to be tested, and the second shell covers the first shell so that the other end of the first accommodating cavity is closed. The top of the second shell is provided with an observation window, the observation window can observe the to-be-tested sample in the first containing cavity through the observation channel, an annular second containing cavity is formed outside the first containing cavity, and a semiconductor temperature control chip is installed in the second containing cavity. The device can be combined with synchrotron radiation analysis and gas product detection, has a lateral visual observation function, is reasonable in whole structural design and high in compatibility, can stably operate in a temperature range of-20 DEG C to 70 DEG C, and is adaptive to various in-situ characterization platforms.

The application discloses a safe decision-making agent of a large language model driven by safe reinforcement learning, and the decision-making agent comprises: a high-level semantic planner, which is used for receiving target and constraint instructions in a text form, receiving language or visual observation signals of an environment, and outputting safe risk information and a suggestion action plan in a text format; a low-level action executor, which is used for receiving low-dimensional observation and semantic encoding of the environment, wherein the semantic encoding is output by the high-level semantic planner after text embedding conversion; a strategy network of the low-level action executor, which outputs a final safe action; a training alignment module, which is used for optimizing the strategy network and a value network; reward and cost signals collected through environment interaction are fed back to the high-level semantic planner, and parameters of the strategy network and the value network are trained through a safe reinforcement learning algorithm. The application is convenient for realizing the decision-making of a given text target while ensuring that the decision-making does not violate a given text safety constraint.

The invention discloses a visual sparse observation and physical model fused flexible body deformation tracking method, which comprises the following steps of: firstly, constructing a flexible body co-rotation finite element model considering geometric nonlinearity, and establishing a low-dimensional flexibility coupling model for describing a mechanical transfer relationship between a virtual actuating source and a characteristic observation point by utilizing a static condensation technology; in the real-time tracking process, a binocular vision system is used for collecting images and resolving three-dimensional coordinates of sparse feature points in a real physical world; constructing and solving a reverse optimization problem based on the low-dimensional flexibility coupling model, and calculating a virtual correction force vector capable of minimizing an observation error; and applying the virtual correction force vector to the finite element model to drive the finite element model to deform, and updating a full-field geometric node position and a tangent stiffness matrix in real time. Through deep fusion of a physical model and sparse visual observation, the problems of visual occlusion and virtual-real model deviation in flexible body assembly are effectively solved, and online real-time full-field high-precision deformation state estimation is realized.

The invention discloses an unmanned aerial vehicle visual language navigation method and system based on an asynchronous collaborative architecture and a target constraint decision. The method comprises the following steps: analyzing a natural language instruction into a structured subtask set by utilizing a large language model; constructing an asynchronous architecture in which a main control thread is separated from a decision reasoning thread, wherein the reasoning thread extracts visual observation based on the latest frame; constructing a multi-source spatio-temporal context tensor fusing vision, semantics and historical actions; generating a navigation strategy by using the visual language large model; for large-amplitude maneuvering, defining a macro action output open-loop control sequence; and introducing a termination judgment model based on geometric features, and judging the completion state of the subtasks by calculating inequality constraints of the target center deviation degree and the view field ratio. According to the method, the problem of control lag caused by large model reasoning delay of a traditional serial navigation architecture and the problem of misjudgment of a probability model in a complex scene are solved, and the navigation real-time performance and robustness of the unmanned aerial vehicle in a real environment are remarkably improved.

The invention provides a VLA-based agaricus bisporus autonomous picking method and system, and relates to the technical field of cultivation, and the method comprises the steps: obtaining picking task description information and visual observation data, and coding the visual observation data to obtain a visual feature sequence; constructing a multi-scale visual feature map based on the visual feature sequence, and generating an object-level visual mark sequence; encoding the picking task description information into a text marking sequence, mapping the text marking sequence and the object-level visual marking sequence to a unified semantic space, and splicing the text marking sequence and the object-level visual marking sequence to form a joint semantic sequence; and inputting the joint semantic sequence into a pre-trained VLA model, performing autoregression prediction to generate an action mark sequence, decoding according to the action mark sequence to obtain a picking control instruction, and driving a picking device to complete picking, so as to improve the key visual information extraction capability and enhance the accuracy and robustness of action generation in a complex unstructured cultivation scene.

The invention is suitable for the technical field of heat pipe experiment systems, and provides a heat pipe experiment system and method based on visual visualization and dual-seal temperature control, and the system comprises a visual heat pipe, a temperature adjustment module, a data collection module, a liquid injection module and a glass temperature monitoring feedback module. The visual heat pipe adopts an aluminum alloy cover plate, visual glass and a copper substrate to form a double-sealing structure. The system integrates a glass temperature monitoring and feedback mechanism, prevents the observation window from fogging, prevents the temperature of the observation window from being too high, and guarantees high-definition visual observation. And the data acquisition module synchronously records the thermal parameters and the dynamic image of the condensed liquid drop, and quantitatively analyzes the behavior of the liquid drop through an image processing technology. The system can realize high-definition observation, high-precision temperature control and quantitative analysis of the internal condensation process of the flat heat pipe at different inclination angles and under different working conditions, and is suitable for in-depth research of a phase-change heat exchange mechanism and heat pipe performance.

The invention relates to the technical field of vehicle electric control suspensions, in particular to a chassis prediction control system and method based on binocular vision and multi-domain cooperation, and constructs the chassis prediction control system based on binocular vision and multi-domain cooperation based on an ADAS binocular camera. IMU data of a binocular camera is obtained by using a data acquisition module of the chassis prediction control system, visual observation data of a vehicle body is obtained by using a binocular visual processing module, and then the IMU data and the visual observation data are fused and converted into a three-dimensional image by using modules such as an extended Kalman filtering fusion module and a motion conversion module. The sprung mass vertical acceleration and sprung mass vertical speed of the vehicle four-corner suspension provide accurate suspension four-corner vertical motion state input for an electric control suspension controller, and the accuracy and real-time performance of the electric control suspension for vehicle body posture control are guaranteed. Meanwhile, the problems that a special IMU is difficult to arrange, high in cost and insufficient in precision and IMU resources of an ADAS system are wasted are solved.

The invention relates to the technical field of aircraft navigation, and discloses an aircraft return path construction method based on visual intelligence. According to the method, a flight environment multi-view image sequence is collected through an airborne vision sensor, and vision observation data with a unified timestamp and space coordinates are generated through space-time alignment processing; calculating a motion vector field of the aircraft relative to a ground reference object based on continuous inter-frame optical flow characteristics in the data, and establishing a three-dimensional environment kinematics model by combining attitude data of the inertial measurement unit; reversely deducing a current flight path by using the model, extracting a historical path key waypoint set, and constructing a return path initial topology network according to the spatial distribution density of the historical path key waypoint set; carrying out dynamic weight distribution on a network node connection relationship, and generating a wind disturbance resistance candidate return path set in combination with a real-time meteorological wind field intensity parameter; and evaluating the candidate set by using a multi-objective optimization algorithm, and outputting an optimal return path meeting a fuel consumption threshold value and a flight time constraint.

The invention relates to the technical field of submarine optical cable burying, in particular to a submarine optical cable curve burying ship position line planning method and system based on parameterization calculation. The method comprises the following steps: setting a routing point and a steering point, determining the radius of an internally tangent turning circle, and enabling the internally tangent turning circle to be respectively tangent to the point; calculating the horizontal towing distance of the burying plough; respectively extending from the tangent points along the extension direction of the route to obtain the stern position at the beginning of steering and the stern position at the end of steering, and calculating the radius of the ship position circle; and calculating a ship head direction change angle arc length, a ship true course, a ship relative azimuth angle and a ship moving distance when the ship moves in the true azimuth angle each time when the ship moves each time, and finally completing the calculation of the embedded ship position when the ship steers. The technical problems that in the prior art, submarine optical cable steering and burying depend on visual observation and past experience of an operator, so that precision is poor, and the burden of the operator is heavy are effectively solved.

The invention discloses a power transmission line icing sag thickness measurement method and system based on machine vision, and belongs to the technical field of visual observation, and the method comprises the steps: obtaining a first power transmission line image and a second power transmission line image, and obtaining the point cloud data of a center line of a wire according to the second power transmission line image; catenary fitting is carried out based on the conductor center line point cloud data to obtain a conductor catenary model, and sag estimation is carried out according to the conductor catenary model to obtain conductor sag distribution data; performing icing area extraction on the first power transmission line image, and performing icing thickness inversion mapping in combination with the second power transmission line image to obtain conductor icing thickness distribution data; and performing correlation fitting on the conductor sag distribution data and the conductor icing thickness distribution data to obtain a fitting function, and obtaining an icing sag thickness distribution increment based on the fitting function to obtain the icing sag thickness. The technical problem that the accuracy of the icing sag thickness is low due to the fact that the dynamic coupling relation between the icing thickness and the conductor sag is not considered in the prior art is solved.

The invention relates to the field of bionic vision, in particular to a visual observation image quality evaluation device and method based on a visual bionic structure, and aims to accurately simulate the independent refraction adjustment process of left and right eyes and truly restore imaging changes under refraction abnormities such as myopia / hyperopia. The consistency and fusion quality of binocular preconceived acquisition are improved by establishing an image fusion model, an evaluation system based on a deep integrated multi-modal fusion network model is established, a binocular vision bionic structure of a human eye refraction state is effectively simulated, focusing, image acquisition and fusion processing of left and right eyes are realized, and the human eye refraction state is effectively simulated. Therefore, the real evaluation of the visual bionic structure viewing effect by the human visual characteristic difference is realized.

The invention provides a smart operation teaching data set acquisition method and device based on visual observation, and the method comprises the steps: preliminarily estimating the three-dimensional poses of a human hand and an object in each frame of a human hand teaching video according to a color image and a depth image in the human hand teaching video; and taking the initial pose estimation result as an initial value, performing joint optimization on the pose tracks of the human hand and the objects by utilizing an optimization objective function, and outputting the three-dimensional pose tracks of the human hand and the objects. And performing heterogeneous mapping on the three-dimensional posture track of the hand to generate a dexterous hand action sequence. And performing spatial transformation on the original track teaching data set by using the three-dimensional attitude track of each object to obtain a dexterous operation teaching data set. The dexterous hand operation teaching data is automatically extracted without an external wearable device, the teaching data acquisition efficiency is remarkably improved, and the method is suitable for various complex operation tasks.

The invention relates to the technical field of medical apparatus and instruments, and discloses an abdominal cavity wound PRP treatment drainage tube visual observation system, which comprises an intelligent imaging module used for collecting multispectral image data of an abdominal cavity wound; the multi-mode sensing module is used for synchronously acquiring various physiological parameter data of a wound surface target area; the spatial memory mapping module is used for establishing a three-dimensional spatial memory model of the wound surface through dynamic light field reconstruction according to the multispectral image data; and a treatment decision analysis module. And the treatment decision analysis module performs semantic segmentation on the three-dimensional space memory model to identify a wound area, fuses the physiological parameter data, and calculates and outputs an optimal PRP treatment site three-dimensional coordinate through a preset optimization algorithm. According to the method, the three-dimensional shape, the spectral characteristics and the multi-dimensional physiological parameters of the wound surface are deeply fused in the data level, so that objective and quantitative decision-making of the PRP treatment site is realized, and the treatment accuracy is improved.

This invention relates to the technical field of fire hydrants and discloses an intelligent fire hydrant with water consumption monitoring function, comprising: a hydrant end cap at the upper end of the hydrant body assembly, and an equipment assembly installed inside the hydrant end cap; a transparent detection window on the hydrant body assembly, a rod inside the transparent detection window, a central rotating shaft installed on the inner side of the transparent window assembly, and a rotating scraper on the central rotating shaft; the rod can detect the water level in the hydrant body in real time, and the rotating scraper can clean the dirt on the surface of the transparent window assembly; this invention, through the coordinated linkage structure of the float, rod, and float plate inside the transparent detection window, combined with the visual observation slot design of the transparent window assembly, realizes real-time accurate monitoring and intuitive visual feedback of water consumption in the fire hydrant, effectively solving the technical pain points of traditional fire hydrants lacking convenient monitoring methods and having difficulty in accurately controlling water consumption.

A driving assistance device is provided with: a detection means for detecting, on the basis of information about the surroundings of a vehicle, an object to be notified, which is an object to be notified to a driver of the vehicle; an estimation means that estimates the direction of sight of the driver; a first control means that, on the basis of the line-of-sight direction, when the driver visually observes the object to be notified, controls to open a visual observation mark indicating whether or not the driver visually observes the object to be notified; a second control means that, when the visual observation mark is set to be on, controls a recognition mark indicating whether or not the driver is recognizing the notification object to be on; and a suppression mechanism.

The invention provides a moving trolley device for semiconductor appearance inspection and an operation method, and belongs to the technical field of semiconductor appearance inspection. Comprising a bottom frame, moving wheels and telescopic sleeves, the moving wheels are arranged at the bottom of the bottom frame, and the tops of the moving wheels are fixedly connected with the telescopic sleeves. By arranging the appearance residue detection module, when debris or metal particles or other sundries exist on the appearance surface of a semiconductor, the debris or metal particles or other sundries on the semiconductor can be directly sucked away by the appearance residue detection module according to the negative pressure suction principle; whether sundries exist on the appearance surface of the semiconductor or not can be judged by detecting the air inflow during air suction, and manual observation with human eyes is not needed in the whole process, so that the possibility of eyestrain caused by long-term observation with the eyes of workers is reduced to a certain extent; and the fatigue and the body discomfort of the worker caused by sitting beside the visual observation instrument for working for a long time are reduced to a certain extent.

The invention relates to a mobile robot motion estimation method based on pose decoupling. The method comprises the following steps: multi-sensor synchronization and decoupling state modeling; performing attitude-position decoupling pre-integration based on an IMU (Inertial Measurement Unit); visual observation modeling and reprojection constraint construction are carried out; carrying out pose optimization solution based on the decoupling factor graph; pose recovery, motion track output and local re-initialization are carried out; compared with the prior art, the method has the advantages that independent modeling and decoupling estimation are carried out on the pose rotation component and the translation component, the propagation effect of rotation errors to translation solution in traditional visual motion estimation is effectively inhibited, and the stability of translation estimation is remarkably improved. Under visual degradation scenes of weak texture, low parallax, illumination variation, motion blur and the like, estimation drift can be reduced, track continuity and consistency can be improved, and robustness of the system to abnormal matching and noise disturbance can be enhanced; besides, the decoupling mechanism provided by the invention has good universality, can be integrated with various types of visual SLAM or visual-inertial fusion frames, and provides more reliable motion estimation capability for stable autonomous navigation of the mobile robot in a complex environment.

The invention discloses a different-diameter wafer edge detection alignment mechanism and an alignment method, and relates to the field of semiconductors. According to the different-diameter wafer edge detection alignment mechanism and alignment method, a user can control a rodless cylinder to drive a connecting block and a connecting plate to move, the moving direction of the connecting block is limited through a linear guide rail, the moving connecting plate drives a linear sensor to move through a right-angle support, and after the linear sensor moves to the position of a wafer, the linear sensor is driven to move. Compared with a traditional clamping and centering mechanism, the wafer edge alignment device can achieve alignment operation of wafers of different diameter specifications, and compared with a traditional wafer edge alignment structure observed visually, the wafer edge alignment device has the advantages that the wafer edge alignment device is simple in structure and convenient to operate. The structure of the device is more compact, and the alignment function of wafers with different diameter specifications can be realized in a smaller space.

The invention relates to the technical field of biological detection, in particular to an HClO near-infrared fluorescent probe as well as a preparation method and application thereof. The structure of the HClO near-infrared fluorescent probe is shown in the specification. The emission wavelength of the near-infrared fluorescent probe developed by the invention is 750nm, and the near-infrared fluorescent probe has high selectivity, high sensitivity (the detection limit is as low as 49 nM) and quick response capability to HClO, and has low cytotoxicity and excellent in-vivo imaging capability, so that visual observation of HClO in a living Parkinson's disease model mouse body is successfully realized, and the near-infrared fluorescent probe has a wide application prospect. The method has great potential in the aspect of tracking HClO related pathological states in real time.