38 results about "Spatial code" patented technology

The invention discloses a city-level CIM scene streaming rendering method based on multi-modal fusion, and the method comprises the following steps: S1, collecting city data, and carrying out the preprocessing of the city data; s2, establishing a cross-modal entity alignment relationship, and constructing a city object structure body; s3, dividing a space by adopting a quadtree method, generating rendering sub-blocks and distributing a unique space code; s4, binding the rendering sub-blocks with the urban object structure body, constructing a multi-modal fusion network, and generating a multi-modal rendering unit set; s5, constructing an inter-frame rendering cost function, and scheduling and sequencing the multi-modal rendering unit set to form an inter-frame scheduling sequence; s6, loading the rendering units according to the inter-frame scheduling sequence to form a city-level three-dimensional view of continuous frames; and S7, updating the scheduling sequence, dynamically adjusting the loading sequence, and realizing stable and efficient streaming rendering of the city-level CIM scene. According to the method, the fusion efficiency and rendering performance of the urban large-scale three-dimensional data are improved, and the method has remarkable engineering applicability and popularization value.

The invention relates to the technical field of intelligent traffic, in particular to an intelligent scheduling method and device for unmanned taxis, and the method comprises the steps: constructing a spatial topological structure for connecting a target unmanned taxi, passengers and a charging station based on the received vehicle data, passenger data and environment data; capturing a spatial dependency relationship among the target unmanned taxi node, the passenger node and the charging station node to generate a spatial coding feature and a time coding feature, and combining the spatial coding feature and the time coding feature with corresponding weights to generate a spatial-temporal feature of the target unmanned taxi; and generating a passenger matching result and / or a path plan and / or a charging decision of the target unmanned taxi based on the spatial-temporal characteristics. Therefore, the problems that a traditional unmanned taxi scheduling method does not fully consider complex factors in an actual driving scene, scheduling decisions are still mostly single-target guiding, dynamic adaptability is lacked, and the increasing travel requirements of passengers cannot be met are solved.

The invention discloses a voice-driven speaking portrait generation method and electronic equipment. The method comprises the following steps: acquiring an audio feature, a spatial feature and an image feature; inputting the audio features and the spatial features into an audio-spatial coding module, and aligning the audio features with the spatial features by dynamically adjusting the spatial positions of the audio features and the face region to obtain spatially perceived lip features; inputting the audio features and the image features into an audio-guided dynamic fusion module, and calculating audio-perceived channel attention and space attention by using a dynamic linear layer to obtain dynamic fusion features; obtaining reference key points, inputting the reference key points and the audio features into an expression optimization module, and fusing the reference key points and the audio reference points to obtain key point features; and inputting the lip sensing feature, the dynamic fusion feature and the key point feature into a trained generative network to generate a video frame. According to the method, the higher-quality, more natural and stable voice-driven portrait synthesis effect is achieved.

The embodiment of the invention discloses an AI generative model training method, an image generation method and electronic equipment, and the method comprises the steps: obtaining a plurality of training data sets used for training an artificial intelligence AI generative model, and the plurality of training data sets comprise a plurality of condition images corresponding to a plurality of different control types; respectively carrying out feature extraction on the condition image and the text content of the control instruction through an adapter network of an AI generative model so as to obtain control information; and injecting the control information into a backbone network of the AI generative model in a cross attention mode, introducing the spatial coding information of the condition image into the backbone network, and completing training of the AI generative model. Therefore, the AI generative model can be uniformly controlled through the condition images of various different control types. According to the embodiment of the invention, unified control on the model by various different types of control signals can be realized.

The invention discloses a real-scene three-dimensional system geographic entity space-time coding method. According to the method, the dynamic sensing capability of the geographic entity state is remarkably improved through an evolution prediction mechanism. Traditional coding mostly focuses on current state records, but the method depends on a state transition probability model of time decay weighting, can accurately capture recent change trends of entities, generate evolution prediction codes and dynamically bind the evolution prediction codes with space codes and time codes, so that the coding can not only reflect current positions, time and attributes of the entities, but also can reflect current state records of the entities. And the state trend of 1-3 months in the future can be pre-expressed. According to the method, the subsequent stage of a construction road can be pre-judged in advance, an emergency department can quickly recognize potential risk entities, the problem that geographic information lags behind actual change is effectively solved, more prospective data support is provided for collaborative decision making of multiple departments, the suitability and long-term reliability of coding in multiple scenes are enhanced through full-process closed-loop design, and the method is suitable for popularization and application. And a stable basic support is provided for efficient application of live-action three-dimensional geographic information.

The invention provides a time domain mapping encryption imaging method and system based on an event camera, and belongs to the field of computer vision hardware encryption imaging. The method comprises the steps that a receiver builds an asynchronous time domain mapping imaging system and constructs a space coding secret key sequence, then obtains an SLM modulation pattern sequence, obtains a noise SLM modulation pattern sequence and sends the SLM modulation pattern sequence to a sender; and the receiver carries out calibration based on the SLM modulation pattern sequence to obtain a space decoding secret key sequence. And the sender obtains the imaging event information and the encrypted time decoding secret key sequence based on the noise SLM modulation pattern sequence and sends the imaging event information and the encrypted time decoding secret key sequence to the receiver. And the receiver obtains a fragmented grey-scale map based on the spatial decoding secret key sequence and the received information, and then obtains a dense and complete grey-scale image through a video completion network based on the fragmented grey-scale map. According to the invention, real-time encryption can be realized, and the leakage risk before encrypted information transmission is reduced; moreover, the method is not sensitive to the collection environment, is high in decoding efficiency, and is low in implementation difficulty.

Embodiments feature families of rate allocation and rate control methods that utilize advanced processing of past and future frame / field picture statistics and are designed to operate with one or more coding passes. At least two method families include: a family of methods for a rate allocation with picture look-ahead; and a family of methods for average bit rate (ABR) control methods. At least two other methods for each method family are described. For the first family of methods, some methods may involve intra rate control. For the second family of methods, some methods may involve high complexity ABR control and / or low complexity ABR control. These and other embodiments can involve any of the following: spatial coding parameter adaptation, coding prediction, complexity processing, complexity estimation, complexity filtering, bit rate considerations, quality considerations, coding parameter allocation, and / or hierarchical prediction structures, among others.

The invention discloses a method for establishing an entity object relationship of urban governance elements. The method comprises the following steps of: firstly, dividing urban governance multi-source data into spatial data and non-spatial data; giving spatial codes to the spatial data according to a spatial grid where a central point of the spatial data is located; especially for the planar elements, a tolerance calculation mechanism is introduced, when spatial overlay analysis is carried out, only when the geometric overlapping relation between the planar elements and other spatial elements meets the preset tolerance calculation condition, it is judged that the planar elements have the inclusion relation and correlation is established, and therefore boundary overflow errors caused by surveying and mapping precision are corrected. And for non-spatial data, accurately mounting the non-spatial data to the established spatial entity through address standardization matching of place name address objects or keyword analysis. And finally, on the basis of a unique space code formed by combining the professional identification code, the space identification code and the time identification code, constructing an urban governance element entity object. According to the method, the problems of inaccurate spatial logic judgment and difficult association of non-spatial data in traditional data fusion are effectively solved, and accurate fusion and efficient indexing of urban governance data are realized.

Consistent with an aspect of the present disclosure, an exemplary digital communication system is provided that includes redundant or spare transceivers to handle failure events. In one example, if one of the first N+r transceivers experience a failure, spatial FEC codewords can correct the resulting bit errors and, as previously mentioned, prevent post-FEC errors from occurring. In embodiments, if a primary transceiver fails, a redundant transceiver may be activated to take its place.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive one or more channel state information (CSI) reference signals (CSI-RSs). The UE may select a first spatial domain (SD) basis from a spatial codebook based at least in part on a measurement of the one or more CSI-RSs. The UE may select remaining SD bases within a same orthogonal oversampling group as the first SD basis, where a size of the orthogonal oversampling group is N1 by N2 of the spatial codebook, and N1 and N2 are dimensions representing a quantity of CSI-RS ports. The UE may transmit an indication of the selected first SD basis and the selected remaining SD bases in a CSI report. Numerous other aspects are described.

The invention relates to the technical field of aviation safety monitoring, provides a flight personnel operation state identification method and system based on multi-modal data fusion, and solves the problems of high misjudgment rate and poor environmental adaptability in the prior art. The method comprises the following steps: synchronously acquiring electroencephalogram signals of a flight personnel, angular velocity of a head inertial measurement unit, an eye movement track and pitch angle and roll angle parameters of an aircraft; dynamically segmenting the electroencephalogram signal to construct an electroencephalogram dynamic topological graph, and generating a head stability index; extracting wave persistence features of the forehead lobe brain region, and performing weighted fusion on the wave persistence features and the head stability index to generate a cognitive conflict feature vector; the eye movement track coordinates are converted into a cabin three-dimensional coordinate system to generate space codes, and space-time feature bodies are constructed through space-time convolution kernel fusion space distribution and track density gradients; and identifying the operation state to be normal, early-warning or out-of-control three levels. According to the invention, accurate grading early warning of the operation state of the flight personnel is realized, and the real-time performance and the accuracy of flight safety monitoring are remarkably improved.

The invention discloses a land full-process approval management method, particularly relates to the technical field of land intelligent management, and realizes full-period run-through, cross-system collaboration and intelligent decision by constructing a dynamic space code mechanism. A land parcel is taken as a core, a static sequence (GeoSOT grid code) is adopted to guarantee spatial position consistency, a dynamic sequence (business state code / timestamp / serial number) maps an examination and approval state in real time, and code updating and associated business synchronization are automatically triggered when the land parcel is changed; based on a national project code and a space code series tax, municipal and financial department system, external data is called through a government affair data sharing platform, and one application and full sharing are realized; spatial conflicts between land and permanent basic farmland and ecological red lines are automatically identified and early warned by utilizing GIS topological overlay analysis, a full-process structured data link (WKT / JSON format) is constructed in combination with fuzzy retrieval, the problems of stage splitting and data islands are solved, and approval accuracy and collaborative efficiency are improved.

The present invention provides a method for constructing a target association tracking dataset based on self-reported position data. Scenario parameters are set based on the sensor sources of the multi-source target tracks to be constructed. The desired tracks are extracted from publicly available civilian AIS data, and the target density and maneuverability within the spatial grid are statistically analyzed. This data is used as a basic database for track simulation and stored in CSV format as an AIS spatial coding index file. Based on the target density and maneuverability within the spatial grid, AIS track data for the desired grid is extracted from the AIS spatial coding index file. Based on the extracted real tracks, a multi-sensor target track dataset that meets the set scenario parameters is constructed through coordinate translation, random batching, systematic error generation, random error generation, and track association mapping. This method constructs a unified, standardized, large-scale, high-quality dataset based on publicly available data, providing a fundamental guarantee for training deep learning neural networks for multi-source track association.

The embodiment of the invention relates to the technical field of three-dimensional graphic rendering, and discloses a mixed rendering method based on voxel coding. According to the method, for a three-dimensional scene in which multiple rendering strategies coexist, voxel-level division is carried out through the scene, space coding of nodes is calculated based on finite element grids, and ordered arrangement and linear coding of the nodes in the three-dimensional space are achieved. And by using the codes, constructing a code-driven scene block scheduling mechanism, and binding corresponding rendering strategies (such as neural rendering, point cloud rendering and traditional graphic rendering) to different coding areas. In the rendering stage, a proper rendering mode can be selected according to observation positions, equipment capabilities or application requirements, and unified management and mixed scheduling of multiple rendering modes are realized by means of a unified spatial coding index. The method is suitable for meta-universe construction, digital twinborn visualization and scene organization in a complex three-dimensional graphic system, and the scheduling efficiency and space consistency in a large-scale environment are improved.

The application discloses a speech-driven talking portrait generation method and electronic equipment, wherein the method comprises the following steps: acquiring audio features, spatial features and image features; inputting the audio features and the spatial features into an audio-spatial coding module, aligning the audio features and the spatial features by dynamically adjusting the spatial position of the audio features and the facial region, and obtaining spatially perceived lip features; inputting the audio features and the image features into an audio-guided dynamic fusion module, calculating audio-perceived channel attention and spatial attention by using a dynamic linear layer, and obtaining dynamic fusion features; acquiring reference key points, inputting the reference key points and the audio features into an expression optimization module, fusing the reference key points and the audio reference points, and obtaining key point features; and inputting the lip perception features, the dynamic fusion features and the key point features into a trained generation network to generate video frames. The method realizes a higher-quality, more natural and stable speech-driven portrait synthesis effect.

The application discloses a depression evaluation method based on audio-visual multi-modal data fusion, comprising the following steps: step 1, obtaining the facial video of a subject and the audio of the subject; step 2, obtaining the low-level visual features and low-level audio features of the subject; step 3, inputting the low-level visual features and low-level audio features obtained in step 2 into a parallel multi-scale bridge fusion depression evaluation PMBFN network for processing and obtaining a depression rating; by constructing a spatial coding module of a visual and audio branch, a parallel multi-scale dynamic convolution module and a space-time attention pooling module, multi-scale deep features are quickly and efficiently extracted from audio-visual multi-modal data, dynamic performance of depression behavior is comprehensively captured, and under the adjustment of a multi-modal bridge fusion module, data between modes is fully interacted, the utilization rate of multi-modal data is improved, and therefore the accuracy and efficiency of automatic depression evaluation are improved.

Disclosed is a hierarchical spatial resolution codec that adaptively adjusts the representations of immersive audio content as the target bandwidth for delivering the audio content changes. The audio content may be represented by an adaptive number of content types such as channels / objects, higher-order ambisonics (HOA), and encoded by adaptive spatial coding techniques to support the target bitrate of a transmission channel or user. Adaptive spatial coding techniques may include adaptive channel / object spatial encoding techniques to generate an adaptive number of channels / objects, and adaptive HOA spatial encoding or HOA compression techniques to generate an adaptive order of the HOA. The adaptation may be a function of the target bitrate that is associated with a desired quality, and an analysis that determines the priority of the channels, objects, and HOA. High priority channels / objects may be encoded into a high quality bit-stream while low priority channels / objects may be converted and encoded as HOA.

The invention relates to the technical field of deep learning and meteorological science crossing, in particular to a deep learning rainfall prediction enhancement method fusing a graph structure and frequency domain characteristics and an integration framework, and the method comprises the steps: obtaining rainfall data of a historical time-space sequence as input data; inputting the input data into a spatial coding module to extract initial spatial features; inputting the initial spatial features into a graph frequency fusion enhancement module to generate enhanced features; wherein the graph-frequency fusion enhancement module is used for enhancing the expression capability of a local space structure and multi-scale frequency domain features of a precipitation field by combining Fourier frequency domain feature extraction and spatial topology modeling of a graph neural network; and inputting the enhanced features into a backbone network module of a rainfall prediction model, carrying out spatio-temporal evolution modeling, and outputting a rainfall prediction result of a future spatio-temporal sequence. According to the method, the accuracy and reliability of heavy rainfall prediction can be improved, and more powerful technical support is provided for weather forecast and disaster early warning.

The embodiment of the invention discloses a space-time unified coding method and device, computer equipment and a storage medium. The method comprises the steps of obtaining space information, time information and equipment information corresponding to target equipment; encoding the spatial information to obtain a spatial code corresponding to the target equipment; encoding the time information to obtain a time code corresponding to the target equipment; encoding the equipment information to obtain an equipment code corresponding to the target equipment; generating a space-time coding identifier corresponding to the target equipment according to the space code, the time code and the equipment code; initial data collected by the target device are obtained, target data are generated according to the combination of the space-time coding identifier and the initial data, and the space-time coding identifier is used for indexing the initial data contained in the target data and / or conducting data alignment between the target data and other data containing the preset space-time coding identifier. Therefore, the space-time coding identification can be used for indexing and aligning the data.

The invention provides a land resource information monitoring and management system, and the system comprises a three-dimensional spatio-temporal data collection module which collects overground and earth surface spatio-temporal data, integrates spatio-temporal data of different spatial scales and time scales, and forms a three-dimensional spatio-temporal data set; the data fusion module is used for preprocessing the three-dimensional space-time data set and carrying out multi-source fusion on the three-dimensional space-time data set; the spatial code data association module is used for generating spatial codes according to the multi-source data fused by the data fusion module in combination with geographic coordinates, timestamps, resource types and region identifiers, and associating different service data through the spatial codes to form a data network; the space tent tracking module is used for calculating the total resource amount and the resource variation amount according to the three-dimensional spatio-temporal data, analyzing the resource flow direction according to space codes and dynamically tracking the city-county-rural three-level resource state; and the visualization module is used for carrying out visualization display on data and analysis results of all the modules.

The invention discloses a wiring-free Carplay reversing image wireless transmission method and a wiring-free Carplay reversing image wireless transmission system, and belongs to the technical field of video coding. When a reversing mode is started, a wireless transmission link monitoring thread is started, a wireless transmission link performance index is acquired, and an acceptable target code rate of a current reversing image frame is given; after acquiring each frame of image, the reversing image acquisition equipment analyzes to obtain an initial block-level coding precision matrix, performs inter-frame smoothing and variation amplitude constraint on the coding precision of each spatial position in the matrix, and performs differential coding on each spatial coding block according to a final block-level coding precision matrix to obtain a final block-level coding precision matrix; the method comprises the following steps: generating a coding data stream adaptive to the bearing capacity of a current link, sending the coding data stream to a CarPlay terminal through a wireless transmission link, obtaining a monitoring result in a transmission process, dynamically and finely adjusting the target code rate and block-level precision distribution of a subsequent frame, and reducing the impact of queue backlog and frame-level loss of a sending end on the real-time performance and accuracy of a reversing image from the source.

The application provides a cross-domain flood prediction system based on spatial coding and coupled bidirectional LSTM, relates to the technical field of flood prediction, and constructs a three-layer collaborative architecture of a perception node, an edge gateway and a cloud engine. The perception node collects multi-modal hydrological data and pre-processes; the edge gateway generates a basin grid through spatial interpolation of discrete sensor data, extracts multi-scale spatial features through spatial pyramid pooling and reduces dimension to a spatial coding vector; the cloud engine initializes the vector as a cell state of a forward long short-term memory network, and injects the forward hidden state into each gating unit of a reverse long short-term memory network through a coupling matrix in real time, realizes forward and reverse information collaboration, and finally outputs a future runoff prediction value. The application can retain the spatial heterogeneity structure of the basin, fully utilize future weather forecast information, and significantly improve the cross-region prediction accuracy and system disaster resistance.

The invention belongs to the technical field of data processing, is applied to medical scenes and financial scenes, and discloses a resource scheduling method, device, equipment and medium based on a multi-level thermodynamic map, and the method comprises the following steps: obtaining business data of each level of an administrative region, the business data comprises spatial position information and resource state indexes of each level of the administrative region; converting the spatial position information of each level of the administrative region into geographic coordinate information through a spatial coding engine, and constructing a spatio-temporal data set of each level of the administrative region based on the geographic coordinate information; a map of each level of the administrative region is loaded, hierarchical rendering is performed on the map of each level of the administrative region according to the resource state indexes in the spatio-temporal data set, and a thermodynamic distribution diagram of each level of the administrative region is generated; and the resource state of each level of the administrative region is identified based on the generated thermodynamic distribution diagram, and the corresponding resource scheduling configuration instruction is generated based on the identified resource state, so that the resource scheduling efficiency of the service scene is effectively improved.

The application discloses an automatic driving space planning enhancement method based on semantic region focusing, comprising the following steps: acquiring input information, including images of an automatic driving scene and texts of a space planning problem; designing a dynamic text library and constructing cross-modal correlation mapping of the text library and the images to generate a region-activated attribution graph; performing spatial visual coding on the images and fusing the attribution graph to construct an explicit spatial coding prompt, constructing a geometric feature enhancement prompt and combining the explicit spatial coding prompt to generate a structured prompt; inputting the input information and the structured prompt into a multi-modal large model to obtain an answer to the space planning problem; and introducing region attention prior through the explicit visual prompt and the text prompt, improving the attention degree of an automatic driving model to a key semantic region in a complex automatic driving scene, thereby enhancing the space planning capability of the automatic driving system.

The present invention relates to a power grid modeling and scheduling method, device, and medium for a graph computing platform, and relates to the technical field of power grid scheduling analysis. The method comprises: step S1: constructing a power grid structure diagram, generating spectral position codes, and extracting three-dimensional scattering features; step S2: concatenating the physical quantities, spectral position codes, three-dimensional scattering features, and spatial codes on the nodes to obtain a composite vector; step S3: constructing a similarity matrix based on the composite vector and further generating a multi-scale graph dataset; step S4: constructing feature perturbation views and structural perturbation views based on the multi-scale graph to generate a multi-scale perturbation view set, performing view coding, minimizing representation differences, and constructing a fused embedding vector; and step S5: solving the power flow state, generating a first feature based on the fused embedding vector, and obtaining node scheduling instructions based on the first feature. Compared with the existing technology, the present invention has the advantages of improving the efficiency and safety of power grid scheduling.

The invention discloses a complex action detection method and device based on space-time fusion and a storage medium, and the method comprises the steps: obtaining a monitoring video stream of a target scene, marking key frames and continuous frames of a shot RGB video, respectively inputting the key frames and continuous frames into a space coding branch and a time sequence coding branch, and extracting a multi-layer feature map; inputting the extracted feature map into a feature fusion network constructed by a feature pyramid to carry out multi-scale feature fusion; in order to effectively fuse double-branch features and enhance spatio-temporal features, the invention provides a fusion module based on spatio-temporal attention, and the representation capability of video features is enhanced from time and space dimensions through a simplified multi-head attention mechanism, 3D time sequence convolution and depth separable convolution with residual errors. And finally, the category, duration and coordinate information of the target behavior in the video are obtained by decoupling the detection head. According to the invention, the detection accuracy is improved on the premise of ensuring real-time detection.

This invention relates to altitude coding, specifically to an altitude segment coding system based on true altitude. The system includes an altitude benchmark coding module, which determines the core benchmark for altitude coding and ensures compatibility with mainstream international aviation altitude standards; a multi-level altitude coding management module, which divides altitude segments and constructs corresponding coding systems based on the regulatory needs and operational characteristics of low-altitude flight; an altitude coding principle and administrative authority control module, which formulates altitude coding principles and establishes matching rules between administrative levels and altitude segments to ensure the scientific and practical nature of the coding system; and an integrated air-space-ground altitude coding fusion module, responsible for the application and implementation of the coding system, deeply integrating altitude coding with planar spatial coding and integrating it into relevant systems to improve the safety and management efficiency of low-altitude flight. The technical solution provided by this invention can effectively overcome the difficulties in airspace supervision and the high risks associated with low-altitude flight in existing technologies.

The invention discloses an intelligent campus operation and maintenance management system based on digital twinning, and relates to the technical field of campus operation and maintenance management, and the system comprises a homologous filing module which is used for establishing a space code and an object set, establishing an acquisition dictionary and completing source instantiation, generating an event tuple, and establishing upstream mapping; the credibility evaluation module is used for writing continuous measurement of the object into a twinning side recording time sequence according to the acquisition dictionary, calculating a rolling standard deviation and a consistency distance and generating a twinning credible account book; the evidence chain order distribution module is used for calculating an object priority order, constructing an evidence chain set according to upstream mapping, selecting a main chain, determining a primary positioning object, generating a work order set and distributing the work order set; and the closed-loop verification module is used for respectively generating twin trusted account books before and after disposal, comparing and verifying the twin trusted account books, updating twin side records and writing the twin side records into a disposal record library when the twin side records pass the verification, generating supplementary work orders when the twin side records do not pass the verification, and circularly verifying the supplementary work orders, so that the focusing degree of disposal resources is improved, and the operation and maintenance closed-loop verifiability and management normalization are enhanced.

The present invention discloses a patterned wafer defect detection system and method based on dual-comb spatio-temporal coding. The system includes: a dual-comb light source module, a spatial coding illumination module, a time programming control module, a signal acquisition and processing module, and a data analysis and processing module. The data analysis and processing module receives the restored three-dimensional topography information of the surface of the wafer to be measured, analyzes it, extracts defect-related features, establishes a mapping relationship between spectral features and defects, and identifies the surface defects of the wafer to obtain corresponding defect types and position information. The present invention adopts a wafer defect detection technology based on dual-comb spatio-temporal coding, uses dual-comb interference technology to achieve fast scanning and parallel detection, and greatly improves the detection efficiency. The present invention can obtain the absolute distance information of the wafer surface, and feeding this result back to the precision air-bearing motion platform can eliminate the autofocus optical path system and the feedback control part, improve the detection efficiency, and reduce the volume, complexity and cost of the entire wafer detection system.

The invention discloses an intelligent library double-sided book taking and returning system and a book taking and returning method, and relates to the technical field of library artificial intelligence, the system comprises a double-sided bookshelf unit design, one side of a bookshelf is a robot operation area, the other side of the bookshelf is a manual operation area, and mutual interference is avoided; the multi-level spatial coding positioning system can accurately position the position of each book through three positioning codes; a vertical partition and book taking and returning grid opening interaction unit is designed, a bookshelf is vertically divided into an upper area and a lower area through the vertical partition and book taking and returning grid opening interaction unit, the lower area is a manual book taking and returning area, and the upper area is a robot book taking and returning area; according to the design that the robot clamps the book material box, the robot can clamp the material box with the fixed size through the two designed clamping arms, and book taking and returning operation is conducted by recognizing the two-dimensional code for positioning; the method has remarkable technical advantages in the aspects of improving the safety, accuracy, efficiency and the like of the library automation system.