126 results about "Space perception" patented technology

The invention discloses a campus green space ownership perception assessment method and system based on multi-modal learning, and the method specifically comprises the steps: inputting the output results of a visual feature coding network and an auditory feature coding network into an audio-visual modal feature fusion module for fusion processing, and obtaining an environment joint representation; inputting the physiological response data set and the psychological assessment data set into a physiological and psychological collaborative encoder for processing to obtain a physiological and psychological joint representation; inputting the environment joint characterization and the physiological and psychological joint characterization into a global fusion module for deep fusion to obtain a final fusion feature; and inputting the final fusion feature into a multi-task prediction channel for processing, and training and optimizing in combination with a loss function to obtain an environment comfort comprehensive scoring result and an explanatory decision basis. According to the invention, comprehensive assessment of campus green space perception is realized, the accuracy and scientificity of assessment are improved, and decision support is provided for optimization of campus space design.

The invention discloses an efficient open vocabulary-oriented panoramic segmentation method. The method comprises the following steps of S1, performing visual feature extraction and aggregation based on a multi-scale feature extractor and a lightweight aggregator; s2, encoding any category of vocabularies by using a text encoder to obtain text embedding # imgabs0 # S3, improving semantic understanding of visual aggregation features based on a vocabulary perception selection module, and reducing feature interaction burden of a mask decoder; s4, on the basis of bidirectional dynamic embedding experts, generating instance embedding with semantic perception and spatial perception by dynamically distributing expert weights; s5, based on a lightweight decoder, using the object kernel to perform mask prediction and refinement layer by layer, and using the object kernel and text embedding to perform dot product as category prediction; the method aims at reducing the model calculation overhead and increasing the reasoning speed while achieving considerable performance, and has remarkable practical value and application prospect.

The invention discloses a VR teaching experience enhancement system and method, and belongs to the technical field of virtual teaching, and the method specifically comprises the steps: collecting the position data and posture data of a trainee in a VR environment, building a multi-user coordination interaction model based on the position data and posture data of the trainee in the VR environment, and carrying out the interaction of the multi-user coordination interaction model. The method comprises the following steps: acquiring training participants, identifying an interaction relationship and an interaction event among the training participants, generating tactile feedback data corresponding to the interaction event based on the interaction event, performing calibration processing on the tactile feedback data, and synchronously sending the calibrated tactile feedback data to VR equipment of the training participants, the calibration processing comprises adjusting the tactile feedback data based on the spatial propagation difference quantity and the tactile feedback time offset value of the trainees; according to the invention, when multiple trainees cooperatively operate the same virtual object or scene, consistent and real-time tactile response and spatial perception can be obtained, and the teaching experience in a multi-person cooperation scene is improved.

The invention relates to the technical field of artificial intelligence, and particularly discloses a visual space description method, system and product based on depth information fusion, and the method comprises the steps: obtaining an image and a corresponding object text; performing vision-plane position feature extraction on the image to obtain a vision feature and a plane position feature, and performing depth feature extraction on the image to obtain a depth feature; performing text coding on the object text to obtain text features; performing feature fusion on the visual features, the plane position features, the depth features and the text features to obtain fusion features; performing spatial relationship classification on the fusion features to obtain a spatial relationship; and inputting the instruction language, the spatial relationship and the object text into a large language model to obtain a natural statement describing the spatial relationship of the object. According to the method, the spatial relationship between the objects in the image can be accurately described, the spatial perception capability of artificial intelligence is improved, and meanwhile, the increase of redundant manual annotation workload is avoided.

The invention provides a method and device for realizing visual and auditory synchronous perception, and the method comprises the steps: obtaining the relative position information between a played video image and an audience and the type of a room where the audience is located under the condition that a video application is started; determining a volume adjustment gain based on the acquired relative position information and the type of the room where the audience is located; adjusting the sound to be played of the video application according to the volume adjustment gain; when the video is played, the relative orientation and distance between the image and the audience can be obtained, the type of the room can be judged, the audio signal to be played is dynamically adjusted according to the orientation and distance between the audience and the image and the type of the room, and the virtual sound image synchronously changing with the image is generated. The audience can obtain the same spatial perception in auditory sense and visual sense, and the immersion of video application is increased.

The invention discloses a robust point cloud registration method and system based on global spatial perception and multistage filtering. The method comprises the following steps: respectively obtaining point cloud initial features and spatial structure features of global spatial perception based on point cloud information; inputting the point cloud initial features and the spatial structure features into a transform network for feature enhancement, and obtaining enhanced features; and performing up-sampling processing and multi-stage filtering on the enhanced features to obtain a transformation matrix, and completing point cloud registration. According to the method, global spatial perception and multi-stage filtering are introduced, so that abnormal values can be effectively eliminated while feature matching is completed finally, and the precision and efficiency of point cloud registration are improved.

The invention discloses a visual language action large model design method for enhancing spatial perception ability, which comprises the following steps of: acquiring a plurality of frames of task scene images, inputting the images into a two-dimensional image encoder and a visual geometry guidance Transformer VGGT encoder, extracting image features and performing time sequence spatial embedding, encoding a natural language instruction into language embedding representation, and extracting a visual language action large model. Image features and language embedding are fused through a cross attention mechanism, a pre-training large model is input to generate cross-modal representation, the fusion features are input into an action expert module to output an action control sequence in combination with robot body state information, and a robot is driven to execute an operation task. Therefore, damage of additional information to an original pre-training model is avoided, and compared with an original combined structure of a pre-training visual language model and an action expert, utilization of multi-view picture information is enhanced, so that higher understanding ability on space depth is achieved in the task execution process, the task success rate is increased, and the task execution efficiency is improved. And a more efficient and more robust robot sensing and decision-making integrated system is realized.

The invention discloses a real-time rendering method for a three-dimensional scene based on spatial perception, and the method comprises the steps: obtaining an initial sparse point cloud of a scene image, carrying out the denoising of the initial sparse point cloud, then extracting a spatial boundary of the scene, carrying out the voxelization of the denoised point cloud, taking the center of each voxel as an anchor point, randomly selecting a camera pose, and carrying out the recognition of the spatial boundary of the scene. The method comprises the following steps: generating a rendered image according to a current anchor point and a neural Gaussian attribute thereof, calculating loss and carrying out back propagation, cutting an original anchor point, generating a new anchor point based on spatial perception, finally terminating iteration after an iteration termination condition is reached, and generating the rendered image according to the current anchor point and the neural Gaussian attribute thereof. According to the method, it is guaranteed that anchor point growth only occurs in a reasonable space range, the anchor points can effectively cover an under-reconstruction region, prediction of neural Gaussian related attributes is optimized, and the processing capacity for complex geometrical shapes and details is enhanced while the reconstruction quality is guaranteed.

The invention relates to the field of robot navigation, and particularly discloses a spatial perception observation information quality evaluation method and system, a terminal and a medium, and the method comprises the steps: converting the measurement information of each dimension into a normalization probability according to the measurement target of each dimension; according to the concept of entropy in the information theory, the normalized probability of each dimension is converted into a computable entropy value; a downstream task weight coefficient is introduced for the entropy value of each dimension, the multi-dimensional entropy value after the downstream task weight coefficient is introduced is mapped into a physical interpretable confidence coefficient in a [0, 1] interval through an exponential attenuation function, and the confidence coefficient explicitly represents the uncertainty of observation information of each dimension. According to the method, a space perception quality evaluation system with mathematics interpretability, scene adaptation and real-time calculation is formed, multi-source uncertainty is mapped into executable confidence, and multi-dimensional accurate evaluation of intelligent agent space perception observation information is achieved.

The invention discloses an underground coal mine goaf gap space sensing method based on a multiple detection technology, and the method comprises the steps: obtaining a three-dimensional dielectric constant body through a ground penetrating radar, and determining the space position of a goaf gap; resistivity tomography is carried out through the optimally arranged electrode network, and a three-dimensional resistivity body is inverted; constructing a three-dimensional wave velocity body by adopting sound wave detection, and identifying a velocity low-value region; a dielectric constant body, a resistivity body and a wave velocity body obtained by the three technologies are uniformly registered to a cubic grid with a preset resolution and normalized, a caving zone void probability body is constructed by adopting adaptive weighted fusion based on information entropy and a Bayesian maximum posteriori estimation framework, and finally a three-dimensional void model is generated and the total volume is calculated. Through multi-source data fusion of ground penetrating radar, resistivity tomography and sound wave detection, the limitation of a single technology in goaf space detection is solved, the precision of gap detection is improved, and the method is suitable for goaf space perception and treatment.

The invention provides a universal and controllable radiation field enhancement method based on spatial perception. The method comprises the following steps: step 1, obtaining training data; 2, light rays and sampling points are generated according to the training data; 3, constructing a neural radiation field hybrid model; 4, inputting the coordinates of the sampling points and the direction of the light into the neural radiation field hybrid model constructed in the step 3, and calculating the volume density and color of each sampling point; 5, calculating an RGB color value of a pixel corresponding to each light ray; step 6, according to the volume density and color of each sampling point and the RGB color value corresponding to each light, training the neural radiation field hybrid model constructed in the step 3 to obtain a trained neural radiation field hybrid model; and step 7, using the trained neural radiation field hybrid model to render a two-dimensional picture under the view angle according to the camera pose of the new view angle, and completing universal and controllable radiation field enhancement based on spatial perception.

The invention discloses a method, a device and a system for identifying personnel under a crane jib and related equipment. Inputting the original image into a segmentation network model to segment personnel and suspension arms, and obtaining personnel suspension arm mask data; inputting the original image into the depth estimation network to obtain depth data of the image; combining the personnel suspension arm mask data and the depth data of the image to obtain personnel suspension arm depth data; according to the depth data of the lifting arm of the person, the overlapping degree of the person and the lifting arm in the horizontal direction, the vertical direction and the depth direction is judged, and the first probability that the person is located below the lifting arm is determined; inputting the position coding information of the depth data of the suspension arm of the person and the model cue word into the large language model to obtain a second probability that the person is located below the suspension arm; and according to the first probability and the second probability, obtaining a comprehensive judgment result of the personnel in the dangerous area below the suspension arm. The personnel under the suspension arm can be accurately identified, the equipment deployment cost is low, the space perception capability is high, and the identification process is more efficient and convenient.

The invention provides a pump room scene abnormal state recognition system and method based on video monitoring, and relates to the field of monitoring or monitoring activities, in particular to the field of space perception. The system comprises a synchronous trigger device which is used for synchronously triggering the collection of video data and audio data in a pump room in the same monitoring time interval; and the state identification device is used for intelligently identifying a pump room scene abnormity type by adopting an intelligent scene abnormity identification model on the basis of basic contents obtained by analyzing the video data in the pump room and the audio data in the pump room. According to the invention, in order to solve the technical problem that the recognition precision and efficiency of various specific pump room scene abnormal states cannot be considered at the same time, different intelligent scene abnormal recognition models can be designed for different pump room scenes and multi-modal basic contents screened in a targeted manner are introduced; and various specific pump room scene abnormal state identification is completed, so that the technical problem is solved.

The invention provides a dexterous manipulator fused with an ontology visual perception function, and belongs to the technical field of electromechanical control. The depth camera is arranged in the palm, the size of the device is remarkably reduced, the size of the device is closer to the size of a human hand, and therefore flexibility and naturalness are improved, the depth camera and a control system are highly integrated, the structure is simplified, synchronism of visual data and hand actions is improved, operation precision is improved, the dexterous manipulator has 16 degrees of freedom, and the flexibility and the reliability of the device are improved. The system is completely driven by a steering engine, the operation flexibility and the fine action execution capability are greatly improved, the requirements of complex tasks are met, the production and maintenance cost is effectively reduced through optimization design and reduction of external accessories, multiple objects are positioned at the same time through a developed instance-level multi-target positioning method and by using a neural network, pre-training is not needed, and the operation efficiency is improved. The space perception capability of the dexterous hand is further improved, and the autonomous operation capability of the dexterous hand in a complex environment is enhanced.

The invention discloses a stroke motion cognition evaluation system and method based on spatial perception nerve enhancement. The stroke motion cognition evaluation system comprises a data acquisition module, a preprocessing module, a feature extraction module, a weight coefficient generation module, a motion cognition evaluation module and a visualization module. Extracting information of different frequency bands of the brain through a feature extraction module, and obtaining power spectral density, a phase locking value and cross-frequency coupling features; meanwhile, a weight coefficient generation module is used for obtaining weight coefficients for performing weight fusion on different features, and the features extracted by a feature extraction module are fused through a motion cognition evaluation module to completely describe complex brain network interaction, so that cognition and spatial perception state evaluation of the subject in the motion imagination process is completed. In addition, threshold adjustment and personalized feedback are performed based on the real-time change of the evaluation result, so that the quality and efficiency of motor imagery training can be remarkably improved.

The invention discloses a robot action generation method integrating multi-layer feature bridging and world knowledge prediction. The method comprises the following steps: extracting multi-layer middle layer visual features and action query hidden variables by utilizing a pre-trained visual language model; an initialization strategy based on robot body sensing state guidance is adopted, real-time pose priori is injected for action query, and traditional all-zero initialization is replaced; a spatial perception vector gating mechanism is introduced into the bridging attention module, and fine-grained selection of specific image region features is achieved; meanwhile, a world knowledge prediction task is integrated, and physical common knowledge is enhanced through explicit modeling environment depth, semantics and a dynamic region; and finally, replacing a traditional L1 regression action head with a diffusion model architecture, and generating an optimal action sequence under multi-modal distribution through an iterative denoising process. According to the method, the operation precision of the robot in a long-range complex task is improved, and the problem of control failure caused by an action'averaging effect 'is solved while the light weight of the model is kept.

The invention discloses a directional floor vibration feedback method and system. The directional floor vibration feedback method comprises the steps of obtaining spatial information and audio information of a virtual object and state information of a target user; obtaining distribution parameters according to the spatial information and the state information, and performing overall frequency scaling on the audio information to obtain vibration waveform data; distributing the vibration waveform data according to the distribution parameters to obtain vibration intensity distribution information; and performing vibration feedback on the target user according to the vibration intensity distribution information. According to the invention, space sound rendering and floor vibration feedback can be driven at the same time, synchronous transmission of sound and vibration is realized, and the space perception and immersion of virtual reality are improved.

The invention discloses a direction selection method and device based on spatial perception positioning, equipment and a medium. The method comprises the following steps: acquiring a current area and a specific position of a user; when the pointing information of the user is detected, a pointing axis is determined according to the pointing information, and a virtual elliptic cone area with an axial angle is constructed around the pointing axis; obtaining an object set covered by the virtual elliptic cone region in the region where the user is located, and determining priorities of all objects in the object set; and pushing subscription information corresponding to the object with the highest priority in the object set to the user, and / or selecting a target object from the object set according to an instruction given by the user and executing corresponding operation. The invention provides a sensing technology for user position and user pointing selection so as to accurately identify the operation intention and the target object of the user, thereby realizing more intuitive operation execution and simplifying instruction input. The method is of great significance in promoting highly intelligent development in the fields of industry, smart home and the like.

A binocular visual field (VF) testing system and a method employing spherical (non-Euclidean) geometric modeling and eye-tracking technology to generate cyclopean visual field maps are disclosed. The system projects dichoptic stimuli to each eye independently at controlled fixation distances and dynamically records vergence responses using eye tracking. A non-Euclidean spatial encoding model based on logarithmic spirals and Jacobian analysis is applied to the resulting binocular data, enabling three-dimensional topographic field mapping. This approach extends traditional monocular field testing by accounting for retinal curvature, binocular integration, and fixation depth effects, resulting in volumetric visual field models more representative of real-world spatial perception. The system includes hardware (BINOSCOPE) and software modules that implement real-time depth encoding, topological mapping, and boundary detection of peripheral visual fields.

The invention discloses a wheat lodging region recognition model establishment method and application, and mainly solves the technical problems of low processing efficiency, high cost and low segmentation recognition precision of a traditional recognition method. Through the UssNet model combining context and space perception, the advantages of semantic segmentation of UNet and global context perception of State Space Models (SSM) are brought into full play, and the method can be well applied to a wheat lodging semantic segmentation task. And a local auxiliary mechanism is combined with SSM, and feature mapping is selectively scanned from different directions, so that a long sequence can be linearly calculated, and global context image information can be extracted. In addition, a Focal loss function is introduced to solve the problems of wheat lodging category imbalance and lodging small region identification. In order to solve the dead ReLu phenomenon, GeLu is adopted as an activation function, and the over-fitting suppression capability of ReLu is reserved, so that the optimal recognition effect can be achieved. By paying attention to image global information, the UssNet model can effectively improve the recognition precision of the wheat lodging region.

The invention discloses a cross-domain multi-modal dynamic reasoning and generating method and system for space sensing equipment linkage, a terminal and a storage medium, and the method comprises the steps: carrying out the weighted fusion and space-time alignment of multi-source heterogeneous equipment sensing data, and forming a cross-domain space sensing data flow with a unified reference; based on real-time spatial topology and business constraints, dynamically dividing semantic collaboration areas and establishing visual mapping; for each region, fusing spatial semantics, text and visual information, and generating a region cooperative control strategy; rendering the visual content in parallel according to the mapping relation and synchronizing the equipment state; and outputting a result through area-level quality reflection evaluation, if all the data reach the standard, carrying out protocol adaptation and linkage output, otherwise, starting a local regeneration protocol for an area which does not reach the standard, re-calibrating data, updating a strategy and rendering. According to the invention, multi-device collaborative millisecond response, cross-protocol non-stop adaptation and anomaly localization repair are realized.

The application provides a kind of space perception teaching auxiliary method, device, equipment and storage medium, wherein, the method comprises: determining target value for training, and recording the first starting point of first user action;When triggering end instruction, determine the critical point of first user action;The difference between first starting point and critical point is used as measurement value;According to the comparison result between target value and measurement value, determine the guidance information, feedback guidance information in the form that visual impaired person can perceive.The space perception teaching auxiliary method, device, equipment and storage medium provided by the embodiment of the application, the user makes first user action with the help of mobile terminal, realizes the perception of specified length or angle, and does not need teaching aid throughout;And, each time triggering end instruction, mobile terminal will compare the result of measurement value and target value to user in real time, and does not need the feedback of naked eye person.Provide the efficiency of teaching, also reduce economic cost.

The invention discloses an intelligent exhibit guide system and method integrating multi-dimensional space perception and user intention judgment, and belongs to the technical field of indoor positioning and navigation. The method comprises the following steps: acquiring real-time state information of a user; according to the user coordinates, preliminarily screening the plurality of exhibits in a preset candidate radius to obtain a candidate exhibit set; for any candidate exhibit, executing physical visibility constraint verification based on a preset visual range polygon corresponding to the candidate exhibit, so as to update the candidate exhibit set; calculating a comprehensive matching score of each candidate exhibit in the candidate exhibit set based on the user orientation, the user coordinate and the exhibit center coordinate corresponding to the candidate exhibit; and determining a unique target exhibit according to the comprehensive matching score, and pushing guide information associated with the target exhibit. According to the method and the device, the problems of false triggering, confusion of affiliations of adjacent exhibits and dislocation explanation under abnormal positioning caused by only depending on distance judgment in the prior art are solved.

The invention discloses a flight personnel space orientation capability assessment method based on holographic eye movement characteristics, and belongs to the technical field of flight personnel capability assessment. Extracting multi-dimensional eye movement characteristics such as pupil contraction / expansion tracks, iris stability parameters and proportional change rate; aligning and matching the eye movement characteristics with real-time flight attitude and environmental stimulation data; carrying out collaborative analysis on the features, and generating a fusion eye movement feature vector insensitive to ambient light interference; and finally, inputting the spatial orientation capability into a pre-trained spatial orientation capability evaluation model, and outputting quantitative evaluation values of spatial perception acuity, environmental adaptability and stress response level. According to the method, the problems that an existing evaluation method is high in subjectivity, prone to being interfered by the environment and difficult to comprehensively reflect the complex physiological cognitive state of the pilot are solved, and more objective, stable and comprehensive quantitative analysis on the spatial orientation capacity is achieved.

The invention discloses an automatic driving method with cross-domain data fusion and double-space perception enhancement. The automatic driving method comprises the following steps: extracting multi-modal features; constructing a cross-domain data fusion strategy; establishing a double-space perception enhancement module; and performing end-to-end trajectory planning and reasoning. Through dynamic weight distribution based on data set difference and dynamic fine adjustment based on loss feedback, the training weights of conventional and long-tail scenes are balanced, the basic capability of the conventional scene and the generalization capability of the edge scene are cooperatively improved, and the robustness of the system is remarkably improved; according to the invention, a double-space perception enhancement mechanism is provided, and a bird's-eye view global structure and look-around local details are decoupled and fused; according to the method, the characteristics of a long-distance small target are accurately captured by utilizing a self-adaptive cutting technology guided by a multi-modal pre-training model based on comparative learning, so that the problem of information loss caused by insufficient spatial resolution of a single aerial view is solved, and the sensing precision of key targets such as traffic signs is improved.

The invention relates to the technical field of intelligent interactive design, and discloses an intelligent public space interactive design method and system based on spatial awareness, and the method comprises the steps: collecting data in real time through a multi-source sensor in a public space, and carrying out the fusion through employing an LIO-SAM algorithm, and obtaining multi-source fusion data; performing semantic segmentation on the multi-source fusion data by adopting a MaskR-CNN model, and constructing a three-dimensional dynamic space model; a behavior prediction model is constructed on the basis of a Social-STGCNN-Transform network, the future behavior trend of the personnel is predicted on the basis of the multi-source fusion data, and a user behavior analysis result is obtained; generating an intelligent interaction strategy according to the three-dimensional dynamic space model and the user behavior analysis result, and executing the intelligent interaction strategy through interaction equipment in the public space; feedback data is obtained, and the intelligent interaction strategy is evaluated and optimized by adopting a multi-target Bayesian optimization algorithm based on the feedback data; according to the invention, dynamic interaction optimization of the public space is realized.

The application provides a city resident population distribution trend prediction method based on a geographic detector, comprising the following steps: acquiring panoramic street view data of a research area; performing semantic segmentation to obtain visual perception elements and establish visual perception factors; establishing spatial perception factors through the accessibility of different facility types under different travel modes; using the geographic detector to calculate the explanation rate of the visual perception factors and the spatial perception factors on the resident population distribution density; obtaining several high-explanation-rate perception factors, obtaining corresponding weights based on a judgment matrix, establishing a resident intention index, and predicting the city resident population distribution trend. The prediction method is based on the perception of people to the real city environment, takes into account the subjectivity and objectivity of evaluation, and has high reference value for city planning related to city resident population distribution.

The invention belongs to the technical field of natural language processing, and particularly discloses a method for constructing a geographic knowledge graph alignment model, which comprises the following steps of: constructing a geographic knowledge graph structure containing multi-dimensional spatial information; creating a corresponding reverse link for the relation link between each geographic entity by using a reverse link generation strategy; distributing corresponding weights to different neighbor entities of each geographic entity by using a spatial perception attention mechanism, and calculating an output feature of each geographic entity by combining an orthogonal transformation matrix of the relationship and the spatial distance; and generating a negative sample through the adversarial network, training a pre-constructed deep learning network by using the negative sample, performing error calculation by using a combination of vector loss and geographic loss as total loss in the training process, and updating a corresponding weight parameter according to an error result until network convergence reaches an expected target, thereby completing training. According to the method and the device, the accuracy of geographic entity alignment in the geographic knowledge graph can be improved.

The present application discloses a unilateral visual spatial perception parameter acquisition device based on picture description and reading test, which relates to the field of human-computer interaction technology. The device includes: a picture description test device, a reading test device and a parameter acquisition device; the picture description test device is used to perform a picture description test, and obtain picture description parameters according to the eye focus point movement trajectory and the cumulative gaze time; the reading test device is used to perform a reading test, and obtain reading parameters according to eye gaze, gestures and voice input; the visual spatial perception parameter acquisition device is used to obtain the target unilateral visual spatial perception parameters according to the picture description parameters and the reading parameters. The present application provides a data basis for a comprehensive assessment of the unilateral visual spatial perception ability of a subject, accurately obtains visual spatial perception data, and uses this comprehensive data to accurately identify the bias or deficiency or unilateral neglect of visual spatial perception ability.

The application relates to a blind guiding method and system based on semantic Gaussian mapping and multi-source fusion navigation. In the method, color images, depth images and inertial data are acquired first, and visual-inertial odometer processing is performed to output blind guiding stick pose data; key frames are determined, and target detection frames are obtained through asynchronous semantic estimation; the depth distribution in the detection frame is subjected to double-component probability modeling based on the depth image to generate a three-dimensional Gaussian candidate pair, then the Gaussian candidate pair is updated to a world coordinate system to construct a dense semantic instance map; pose data are fused to generate a cost map containing semantic weights and obstacle inflation information, and then path planning and dynamic obstacle avoidance are performed based on a preset target point, the cost map and the pose data, a navigation vector instruction is output, and blind guiding is completed. Compared with the prior art, the application has the advantages of improving the reliability of space perception and obstacle avoidance, realizing intelligent guiding with space perception and safe obstacle avoidance, and the like.