311 results about "Optical distortion" patented technology

The invention belongs to the technical field of lens calibration, and particularly discloses and provides an optical lens production intelligent calibration system which comprises an environment coupling module, an optical detection module, a self-adaptive calibration decision module and an automatic focusing adjustment module. According to the invention, various environmental data are collected in real time through the environmental coupling module to form a time-space correlation parameter set, so that a basis is provided for suppressing environmental interference; the optical detection module generates a dynamic target sequence and synchronously acquires various parameters of the lens, so that a calibration path can be dynamically optimized; the adaptive calibration decision module not only can establish a mapping relation between environment and optical distortion, but also can calculate a focusing adjustment parameter based on multiple parameters when an error exceeds a threshold value; and the automatic focusing adjustment module controls the focusing device in real time according to the adjustment parameters and verifies the adjustment parameters, so that sorting and recalibration of qualified and unqualified lenses are realized, the calibration accuracy is comprehensively improved, and the scene adaptability of an AF algorithm is enhanced.

A method of identifying road distress on a road based on imagery of the road is disclosed. The method is performed by a processor and comprises the steps of: identifying a region of interest from road regions detected in the imagery of the road; detecting one or more road distresses present in the region of interest by identifying features associated with physical characteristics related to road distress in an original image comprising the region of interest; detecting one or more road distresses present in the region of interest by identifying features associated with physical characteristics related to road distress in a corrected image obtained by applying at least one of optical distortion correction and perspective distortion correction to the original image comprising the region of interest; and identifying one or more road distresses by combining the detection based on the original image and the detection based on the corrected image. Unlocking insights from Geo-Data, the present invention further relates to improvements in sustainability and environmental developments: together we create a safe and liveable world.

The invention belongs to the technical field of image data processing, and discloses a beverage package defect visual detection method and system, and the method comprises the steps: firstly, shooting a defect-free beverage package sample under a preset scene, and building a standard image library; then collecting and preprocessing a to-be-detected package image, obtaining a package model, and selecting a corresponding reference image from the standard image library; the detection image and the reference image are registered, difference is carried out to obtain a difference image, and enhancement processing is carried out on the difference image; and performing threshold processing on the enhanced image to extract an abnormal region, analyzing features of the abnormal region to determine the position and size of a defect, and generating a detection result report. According to the method, the optical distortion effect of the transparent package on the background pattern is analyzed, invisible defects are converted into detectable background changes, different enhancement strategies are adopted for different types of areas, the defect detection problem of the transparent package is effectively solved, and the detection sensitivity and accuracy are improved.

The invention relates to the field of microscopic imaging, and discloses a miniature microscopic system optical precision improvement and image calibration error optimization method, which comprises the following steps: establishing an optical distortion model and a mechanical disturbance model, and respectively describing a static error and a dynamic error; constructing a joint dynamic error model, and uniformly expressing a coupling relationship between optical distortion and mechanical disturbance; decoupling and separating the joint error through a space-time separation method to obtain a static error component and a dynamic error component; performing iterative optimization on the optical distortion parameter and the mechanical disturbance parameter based on an optimization algorithm to minimize a system calibration error; a real-time sensor is utilized to obtain dynamic disturbance data, and real-time dynamic compensation is performed on an image calibration error in combination with an optimization result, so that a high-precision calibration result is obtained. The method can effectively improve the calibration precision of the microscopic system in a dynamic environment, remarkably improves the imaging quality of the system, and has a wide application prospect.

The invention provides an underwater robot obstacle avoidance system based on object capture. The method comprises the steps of collecting spatial visual information in a target area where the underwater robot is located in real time; acquiring multi-modal environment data in a target area where the underwater robot is located; constructing polarized light data in the multi-modal environment data into a water body scattering model by adopting a Mueller matrix to correct optical distortion in spatial visual information; acquiring a real-time motion state of the underwater robot through an inertial measurement unit; acquiring water flow disturbance data of the underwater robot, and correcting position drift caused by water flow disturbance in a real-time motion state by combining a water body flow model with the water flow disturbance data acquired in real time; constructing a dynamic risk field corresponding to the target area based on the spatial visual information, the corrected real-time motion state and sonar ranging data in the multi-modal environment data; and generating an obstacle avoidance strategy of the underwater robot in a future preset time period based on the dynamic risk field so as to realize dynamic obstacle avoidance.

The invention discloses a deviation rectification control method and system for simulating shield excavation, and relates to the technical field of shield control. The deviation rectification control method and system for simulating shield excavation comprise the steps that S1, shield deviation rectification data are collected in real time, and the shield deviation rectification data are preprocessed; s2, extracting an attitude deviation component, comprehensively evaluating environmental drift and optical distortion influence of attitude deviation, and generating each calibrated attitude angle; s3, all the calibrated attitude angles are read, attitude correction required values in all directions are calculated in combination with the laser target deviation value, the dynamic fluctuation degree of the execution process is quantified, and the target stroke of the deviation correction oil cylinder is obtained; and S4, the target speed is calculated, a deviation rectification control instruction is generated and issued for execution, a deviation rectification execution data set is formed, and a deviation rectification control closed loop is completed. The problems that an existing system lacks an automatic calibration and anomaly recognition mechanism, sensing data distortion still participates in deviation correction control, PLC attitude calculation errors are accumulated, and false deviation correction is generated are solved.

The invention relates to an optical distortion test system and method. According to the method, a light source assembly is used for outputting projection light; the target assembly is fixed in front of the projection light output end of the light source assembly. The to-be-tested assembly is located on the side, away from the light source assembly, of the target assembly and connected with the adjusting assembly. The adjusting assembly comprises a pitching adjusting sub-assembly, a horizontal adjusting sub-assembly, a height adjusting sub-assembly and an inclined sub-assembly, the pitching adjusting sub-assembly is used for ensuring that the to-be-detected assembly is perpendicular to the projection optical axis, and the horizontal adjusting sub-assembly and the height adjusting sub-assembly are used for ensuring that the optical center of the to-be-detected assembly is coaxial with the projection optical axis and the lens center of the detection assembly; the inclined sub-assembly is used for adjusting a space angle between an optical central axis of the to-be-detected assembly and a projection optical axis of the light source assembly so as to detect edge distortion of the to-be-detected curved surface element; the detection assembly is located on the side, away from the to-be-detected assembly, of the adjusting assembly and used for shooting a projection image of the target assembly which generates distortion after being acted by the to-be-detected assembly.

The invention discloses an electric arc three-dimensional reconstruction system and method based on binocular vision. The system comprises a double-camera image acquisition module, a correction module, a boundary contour point extraction module and a three-dimensional reconstruction module. The dual-camera image acquisition module completes dual-camera parameter calibration and dual-vision arc image shooting operation at different positions; the correction module corrects an optical distortion area and a breakpoint area of the double-vision arc image to obtain a corrected double-vision arc image; the boundary contour point extraction module adopts a third-order Bezier curve to perform segmentation fitting on the boundary contour of the corrected double-vision arc image to obtain continuous double-vision arc boundary points; and the three-dimensional reconstruction module reconstructs a three-dimensional contour line of the electric arc through a triangulation method according to the camera calibration parameters and the double-vision electric arc boundary points, and generates a corresponding three-dimensional point cloud data set. According to the method, the distortion and breakpoint phenomena of the arc image can be repaired, and high-precision reconstruction of three-dimensional data of the arc is realized.

The prime lens comprises a front lens group, a diaphragm and a rear lens group which are sequentially arranged from an object side to an image side, the front lens group is sequentially provided with a first lens, a second lens and a third lens with negative focal power, negative focal power and positive focal power from the object side to the image side; the rear lens group is sequentially provided with a fourth lens, a fifth lens, a sixth lens and a seventh lens with positive focal power, negative focal power, positive focal power and positive focal power from the object side to the image side; wherein the fourth lens and the fifth lens are glued to form a doublet lens. The prime lens is composed of seven lens elements, the number of the lenses is reasonable, the structure is simple and compact, the focal power and the position of each lens element are reasonable, the environment adaptability is high, and the resolving power is high; due to the design of the large field angle and the large image height, the lens system has higher competitiveness in the market. The aperture number FNO of the prime lens is 2.50, the field angle is 138 degrees, the imaging height can be matched with a 1 / 1.8 inch chip, the total optical length is not larger than 24.0 mm, the optical distortion absolute value is smaller than 40%, and the requirement for ultra-high-definition imaging is met.

The invention provides an embedded image enhancement method and system for a large-target-surface image sensor. According to the method, temperature gradient distribution and environment humidity data of a large-target-surface image sensor are collected, and an environment parameter matrix and a temperature noise mapping model are constructed in an associated mode; and correcting optical distortion of the incident light signal by using the liquid crystal modulator array, and outputting an original image. Then through a double-path module, a main path extracts noise features, and an auxiliary path separates color shift features caused by humidity; and verifying the physical consistency of the characteristics based on a thermodynamic equation and screening effective data. And finally, dynamically optimizing the image contrast, the dynamic range and the target details by the embedded processor, and outputting an enhanced image. Through environmental parameter modeling, dual-path feature separation and physical verification, temperature and humidity interference is effectively suppressed, and detail enhancement and color fidelity of the large-target-surface image sensor are improved.

The invention relates to the technical field of industrial vision, in particular to an automobile part surface defect detection method and system based on machine vision, and the method comprises the steps: firstly loading a CAD three-dimensional model, and rendering an ideal fringe reflection map in a virtual environment; calculating an optical distortion correction matrix by comparing the phase distortion with the phase distortion of an actual initial reflection image, driving a programmable light source to project a compensation pattern, and generating a normalized reflection intensity image; signal object decoupling is achieved through multi-scale wavelet transform, and high-frequency components and low-frequency components are separated; homomorphic filtering is applied to the low-frequency component to construct a homogenized background model, the high-frequency component is reversely corrected, and a high-signal-to-noise-ratio defect signal image is output; generating a coarse segmentation mask by the high-frequency signal through an adaptive local threshold, generating a morphology anomaly mask by the low-frequency signal through Hessian matrix morphological analysis, and fusing to form a collaborative segmentation mask; and extracting multi-dimensional geometric attributes of connected domains in the masks, and inputting the multi-dimensional geometric attributes into a decision tree to realize accurate classification and confidence output of defects.

The invention discloses a design and implementation method of a near-infrared light-splitting super lens, and relates to the technical field of super lenses. The super lens is composed of a rotational symmetric structure, so that polarization insensitivity is achieved, incident broadband light can be dispersed to different positions of the same focal plane according to different wavelengths through ingenious optical design, an effective light splitting effect is achieved, and the polarization insensitivity of the super lens is improved by adjusting geometric parameters and shapes of the super lens nano structure units. The positions of light with different wavelengths on a focal plane can be accurately controlled; in the optimization process, a particle swarm optimization algorithm is adopted to reduce errors, and performance attenuation and optical distortion caused by dispersion can be effectively reduced by adjusting dispersion characteristics and geometric parameters of the nano-structure units, so that the precision and reliability of light splitting are improved, and the light splitting precision is improved. The identification capability of the laser detection system is greatly improved, and integration and miniaturization are realized.

The invention relates to the technical field of intelligent visual detection, in particular to visual field detection equipment, system and method based on extended reality (XR), and the method comprises the steps that an image feature extraction module collects image data in real time, extracts features and eliminates optical distortion; the fixation deviation correction module analyzes eye movement data in real time, quantifies fixation deviation and triggers visual prompt and correction; the adaptive stimulation generation module dynamically encrypts to generate a test point image and adaptively adjusts the test point image according to visual field analysis and test requirements; the dynamic adjustment image module predicts and optimizes a test point presentation sequence according to image features and fixation points, automatically encrypts a high-probability defect area and quickly jumps to a key screening area; and the visual field defect identification module extracts image features, calculates the defect probability of each region in real time by using a Bayesian network in combination with subject response data, and locates a high-risk region. The system provides an efficient and accurate visual field detection scheme through the synergistic effect of multiple modules.

The invention discloses a star point coordinate extraction and star sensor attitude optimization method based on deep learning. The whole process of pseudo star map generation, star point coordinate extraction and attitude calculation is optimized. Multi-factor interference such as spacecraft jitter and optical distortion is simulated through dynamic star point modeling, and a high-fidelity pseudo star map is generated; a noise adaptive detection network is designed to fuse denoising and key point detection, and star point positioning precision in a low signal-to-noise ratio environment is improved; and optimizing attitude solution, constructing a loss function based on star point coordinates, and performing back propagation to optimize attitude parameters to realize an algorithm closed loop. According to the method, real data can be expanded to realize effective training of the model, and the positioning precision is improved; the star point coordinate positioning precision is improved to a sub-pixel level (RMSElt; 0.3 pixel); an end-to-end optimization framework reduces error accumulation in a traditional assembly line, and the robustness of the system is improved by 40%.

The invention discloses an automatic focusing method and system based on a TFT liquid crystal panel, and particularly relates to the technical field of TFT liquid crystal panels. By acquiring image data of a shooting scene, calculating an optimal focal length adjustment parameter and applying a control voltage to dynamically adjust the refractive index of a liquid crystal panel, focus adjustment of an optical system is realized, an adjusted image is acquired, image quality is compared by using a definition evaluation algorithm, if the definition does not reach a preset threshold value, voltage control is iteratively optimized, and the image quality is improved. And after the focus is determined, the system maintains the current voltage state, and the focusing process is automatically optimized in combination with a scene change detection mechanism. The problems of optical distortion, halo, aberration and the like caused by the uniformity and response characteristics of liquid crystal molecules in the optical adjustment process of an existing liquid crystal panel are solved; the automatic focusing method and the automatic focusing device are particularly suitable for high-resolution and large-aperture application scenes, and stability and adaptability of automatic focusing are improved.

The invention discloses an ultra-wide thin-wall tunnel roof deformation monitoring device based on laser ranging, and relates to the technical field of laser measurement, the ultra-wide thin-wall tunnel roof deformation monitoring device comprises an industrial camera and a mounting seat, a laser is fixedly mounted on the mounting seat, a mounting bracket is mounted at the bottom of the mounting seat, and a protective shell is fixedly mounted on the mounting seat. A light beam collimator is fixedly installed on the laser device, and a beam splitting assembly is fixedly installed in the protective shell and used for equally dividing a light source emitted by the laser device into two laser beams. The tunnel section deformation monitoring method has the advantages that high-precision and high-efficiency deformation monitoring can be performed on the tunnel section, the problems of time desynchrony and optical distortion existing in a traditional method are effectively solved, and meanwhile, the adaptability and data reliability in a severe environment are remarkably improved; and reliable technical means and equipment support are provided for structural health assessment of the ultra-wide thin-wall tunnel top arch.

The invention provides a camera image display method and device, an augmented reality display system and a computer readable storage medium. The camera image display method comprises the following steps: acquiring a to-be-corrected original image through a live-action camera; an optical machine distortion grid representing optical machine distortion characteristics of the display optical machine is obtained, and the optical machine distortion grid is obtained by performing complementation, displacement, rotation and / or fixed-point processing on a preliminary distortion grid obtained through shooting according to the result of an optical machine calibration experiment; and processing the original image according to the optical machine distortion grid so as to generate a pre-corrected image, and obtaining a display image offsetting optical distortion at the rear end of the display optical machine. By performing complementation, displacement, rotation and / or fixed-point processing on the preliminary distortion grid calibrated by the experiment, the method can obtain a more accurate distortion grid to compensate for the distortion of the optical machine, thereby improving the quality of the display image and improving the user experience.

The invention discloses a single-pixel phase imaging method based on an untrained physical driving neural network, and belongs to the field of single-pixel imaging and computational optics. According to the method, by adding a physical diffraction layer and an Admn optimizer, direct reconstruction from a single-pixel detection intensity sequence to a phase object image is realized. According to the method, pre-training is not needed, and the dependency on a large data set is remarkably reduced; by introducing the total variation loss of the output phase, the influence of noise and optical distortion is effectively suppressed; and when the sampling rate is as low as 30%, the phase distribution can still be efficiently reconstructed, and the required sampling number is reduced.

The invention discloses a self-adaptive spatial transformation network for cross-medium optical distortion, and solves the problem that the existing spatial transformation network is difficult to consider both global transformation and local nonlinear optical distortion. The network is integrated in a target detection model, and the method comprises the steps that firstly, a parameter prediction network synchronously outputs affine transformation parameters and a water surface fluctuation physical parameter diagram; then, the local distortion grid generation network generates a distortion sampling grid based on the parameter diagram and a predefined water surface fluctuation physical model; meanwhile, the grid generator generates an affine sampling grid according to the affine transformation parameters; then, a grid fusion device fuses the two grids to generate a final sampling grid; and finally, the sampler samples the input image or the feature map according to the final sampling grid to obtain an output image or a feature map. Through a space transformation mechanism guided by physical prior, optical distortion caused by water surface fluctuation can be effectively relieved, and the accuracy and robustness of a target detection model in a cross-medium underwater scene are remarkably improved.

The invention discloses an in-situ harmful gas monitoring method for sewage treatment plant structures, and particularly relates to the field of in-situ harmful gas monitoring, and the in-situ harmful gas monitoring method comprises the following steps: collecting refractive index disturbance data of a local gas-liquid-gas interface caused by bubble release in a sludge tank or an anaerobic tank, and forming a refractive index distribution field changing along with time; and modeling an infrared light propagation path based on the refractive index distribution field, executing infrared absorption inversion operation, solving a first concentration result of the harmful gas, and establishing a mapping relationship between the first concentration result and the refractive index distribution field. Through coupling calculation of a refractive index distribution field caused by bubble disturbance and an infrared absorption inversion process, a reciprocating iteration and time sequence prediction chain is constructed so as to correct dynamic optical distortion and stably solve the real release intensity of harmful gas.

The invention belongs to the technical field of optical system aberration analysis, and discloses an experimental device for measuring and correcting image distortion of an optical imaging system, which comprises an optical axis testing device and an optical distortion testing platform, and the optical distortion test platform is used for testing optical distortion of the optical imaging system to be tested and integrating optical distortion data with optical axis deviation to obtain an image distortion fitting coefficient and a distortion correction model of the optical imaging system. According to the invention, the image distortion of the optical imaging device can be measured, the image distortion can be corrected, the imaging device can correct the deviation between the optical axis and the center of the target surface when the system is installed and adjusted, the optical distortion of the whole optical system can be corrected, and the method has guiding significance for the application of detecting and identifying the accurate position of a target by using the optical system.

The invention discloses a distortion correction method for intelligently identifying an image of a SWIT6 millimeter lens. The method comprises the following steps: S1, acquiring original image data through the SWIT6 millimeter lens; s2, calculating a distortion compensation factor in the original image data according to the optical system characteristics of the SWIT6 millimeter lens; s3, correcting geometric distortion by using the distortion compensation factor to obtain image data after geometric correction; s4, according to the optical system characteristics of the SWIT6 millimeter lens, carrying out geometric correction on the edge region of the image data after geometric correction to obtain corrected image data; s5, applying an adaptive denoising algorithm to the corrected image data, dynamically adjusting the noise suppression intensity according to the distribution condition of optical distortion, and performing detail enhancement processing; and S6, outputting the image data after distortion correction, denoising and detail enhancement. The method has the advantages of good detail retention, efficient real-time processing capability and the like.

Vehicle window glass and a vehicle. Vehicle window glass (100) comprises an information acquisition area (101); the information acquisition area (101) comprises an optical transmission area (103) and a shielding area (104); a first shielding layer (20) and at least one second shielding layer (30) are arranged in the shielding area (104); the material of the second shielding layer (30) is different from that of the first shielding layer (20); at least one transition area (105) is arranged between the first shielding layer (20) and the optical transmission area (103); and one part of each second shielding layer (30) covers the corresponding transition area (105), and the other part of each second shielding layer (30) covers part of the surface of the first shielding layer (20). The vehicle window glass not only can ensure the size range of an optical transmission area necessary for a sensor, but also implement isolation of optical distortion outside the optical transmission area, such that the diopter of the optical transmission area satisfies the use requirements of the sensor, the image acquisition quality of the sensor is effectively improved, the detection quality of the sensor is improved, and the use requirements of a camera having high precision and a narrow horizontal field of view can be satisfied.

The embodiment of the invention provides vehicle window glass and a vehicle, which can solve the problem of optical distortion when signal light is transmitted to sensing devices such as a camera and a radar through the vehicle window glass, and ensure that the signal transmission quality of the sensing devices such as the camera and the radar is good. The vehicle window glass comprises a glass substrate, a functional patch and a bonding layer, the functional patch is located on one side of the glass substrate in the thickness direction, the functional patch and the glass substrate are arranged in a spaced mode, and the bonding layer is connected between the glass substrate and the functional patch; the vehicle window glass is provided with a signal transmission area, and the projection of the functional patch covers the signal transmission area in the thickness direction of the glass substrate; wherein the functional patch comprises a patch layer and a functional layer, the patch layer is connected to the surface, away from the glass substrate, of the bonding layer and covers the surface, away from the glass substrate, of the bonding layer, the thickness h1 of the patch layer is smaller than or equal to the thickness h2 of the bonding layer, and the functional layer is connected to the surface, away from the bonding layer, of the patch layer and covers the surface, away from the bonding layer, of the patch layer.

The invention discloses a double-beam link vortex light correction system and method based on a model method, and the system comprises a double-beam common-path light path which is used for enabling vortex light and planar light to be transmitted in a common path, to pass through a turbulent flow or optical distortion region together, and to carry the same wavefront distortion information; the wavefront correction unit is used for dynamically compensating wavefront distortion information; the image acquisition and control unit is used for acquiring a corrected far-field light spot image after the planar light passes through a distortion area, and generating a driving instruction of the wavefront correction unit according to far-field light spot information to realize closed-loop control; and the topological charge detection module is used for carrying out topological charge detection on the corrected vortex light. According to the invention, indirect correction of the turbulence aberration of the common-path vortex light is realized, so that the correction efficiency and stability of the vortex light are improved.

The invention discloses a self-adaptive optical distortion compensation device and compensation method based on high-speed closed-loop control, and the device comprises an optical path front-end interface which is used for connecting a coupling wind tunnel or a laser emission system; the wavefront sensor is used for measuring a local wavefront slope by adopting a distributed array; the FPGA controller comprises a wavefront reconstruction processor and a closed-loop logic controller and is used for reconstructing wavefront and generating a control instruction; the MEMS deformable mirror array comprises a plurality of MEMS drivers and is used for correcting a wavefront phase; the feedback monitoring module is used for performing dual verification through deformation capacitance measurement and CCD image feedback; and the imaging / laser output end is used for converting the corrected optical signal into an image and outputting the image. The method can be widely applied to the fields of high-speed aircraft wind tunnel testing, laser communication, infrared imaging guide head calibration, high-energy laser beam shaping and the like, a programmable hardware platform, a high-speed parallel operation structure and a predictive control algorithm are introduced, and unprecedented sub-microsecond closed-loop compensation is achieved.

A system implements techniques for measurement and compensation of optical distortion by accessing a first image of a target object captured of via an imaging instrument, and repeating the process of moving the target object a known distance via an actuator and capturing other images of the target object after the target object has been moved a number of times until a plurality of images have been captured. A correspondence is then established between a feature of the first image and a corresponding feature of each of the other images to identify corresponding features in consecutive images and the coordinates of each pair of identified corresponding features is measured. The measured displacement vector between each pair of features is used to determine parameters for optical distortion of the imaging instrument which is then used to modify the first image to compensate for optical distortion, and output the modified image.

This invention discloses a machine vision-based method and system for dynamic screening and size detection of glass fiber particles, specifically relating to the field of glass fiber particle size detection. The method includes real-time monitoring of particle adhesion and dynamic adjustment of the vibration dispersing mechanism, further integrating vibration signals and image features for analysis, and correcting motion blur and refractive index distortion in the image to accurately measure the physical size of the particles. The machine vision-based method and system for dynamic screening and size detection of glass fiber particles achieves coordinated control of vibration and imaging by dynamically adjusting vibration parameters through the adhesion index, effectively solving the problem of lack of coordination between the vibration dispersing mechanism and the imaging mechanism. Through distortion correction algorithms, it compensates for motion blur caused by vibration and optical distortion caused by differences in glass fiber refractive index, reducing measurement distortion. Finally, through a reinforcement learning model, it minimizes size measurement errors while ensuring high dispersion.

The application provides an underwater robot obstacle avoidance system based on object capture. The method comprises the following steps: collecting spatial vision information of a target area where an underwater robot is located in real time; acquiring multi-modal environment data of the target area where the underwater robot is located; constructing a water body scattering model for correcting optical distortion in the spatial vision information by using Mueller matrix for polarization light data in the multi-modal environment data; acquiring real-time motion state of the underwater robot by using an inertial measurement unit; acquiring water flow disturbance data of the underwater robot, and correcting position drift in the real-time motion state caused by water flow disturbance by using a water flow model and the real-time collected water flow disturbance data; constructing a dynamic risk field corresponding to the target area based on the spatial vision information, the corrected real-time motion state and sonar ranging data in the multi-modal environment data; and generating an obstacle avoidance strategy of the underwater robot in a future preset period based on the dynamic risk field, so as to realize dynamic avoidance of obstacles.

The present invention discloses an autofocus method and system based on a TFT liquid crystal panel, specifically related to the technical field of TFT liquid crystal panels; by acquiring image data of a shooting scene, calculating the optimal focal length adjustment parameters, and then dynamically adjusting the refractive index of the liquid crystal panel by applying a control voltage to achieve the focus adjustment of the optical system, collecting the adjusted image, and using a sharpness evaluation algorithm to compare the image quality. If the sharpness does not reach the preset threshold, the voltage control is iteratively optimized until the optimal focus is obtained. When the focus is determined, the system maintains the current voltage state and combines a scene change detection mechanism to automatically optimize the autofocus process. The present invention overcomes the problems of optical distortion, halos, and aberrations caused by the uniformity and response characteristics of liquid crystal molecules in the existing optical adjustment process of liquid crystal panels, improves the focusing accuracy and imaging quality, is particularly suitable for high-resolution and large-aperture application scenarios, and enhances the stability and adaptability of autofocus.