1952 results about "Navigation path" patented technology

The invention relates to the technical field of navigation, and particularly provides a quadruped robot autonomous navigation method and system for a special environment, and the method comprises the steps: generating a semantic tag for depth point cloud data corresponding to a depth image through employing a recognition result of a target detection network for the depth image; calculating local odometer information according to the laser point cloud data and the inertial sensor data by using a laser radar mileage calculation method; fusing the depth point cloud data with the semantic label, the laser point cloud data with the semantic label and the local speedometer information to obtain positioning data in a pre-constructed point cloud map; constructing a multi-layer cost map according to the pre-constructed point cloud map, the newly acquired depth image, the laser point cloud data and the inertial sensor data by using a sensing method of a region planner; and generating navigation path information according to the positioning data and the multi-layer cost map by using a global path planning algorithm and a local path planning algorithm. The method improves the navigation precision.

An autonomous robotic vehicle with dynamic path planning capabilities, including: a dynamic path planning module configured to generate and adapt navigation paths in real time based on environmental changes and mission objectives; a sensor fusion module that integrates data from multiple sensors, including LiDAR, radar, cameras, ultrasonic sensors and GPS, to create a comprehensive environmental model; an obstacle avoidance module capable of detecting and predicting both stationary and moving obstacles and modifying the navigation path to avoid collisions; an artificial intelligence-based decision-making module for analyzing environmental data and learning from past navigation scenarios for improved performance; a decentralized control module that enables the independent operation of the vehicle in areas with interrupted or no connection to a central server; an energy management module configured to optimize battery usage by dynamically adjusting operating parameters based on real-time data and mission requirements; a cooperation module that enables communication and coordination between multiple autonomous robot vehicles for fleet management or the synchronized execution of tasks; a fail-safe module to ensure uninterrupted operation and data security in the event of communication failures or hardware malfunctions.

The invention provides an autonomous navigation path planning method, device and equipment for a humanoid robot in a complex environment. A navigation task is determined by obtaining the current position and path requirement of the robot; constructing a constraint preposition map based on body size constraint, joint motion constraint and dynamic balance constraint, and calculating a feasible motion space of the robot in advance; acquiring environment sensing data for variation trend analysis, and predicting a future movement track of the dynamic obstacle to generate a dynamic environment prediction sequence; establishing a bidirectional planning mechanism, performing forward and reverse path search at the same time, and generating a plurality of candidate path hypotheses through meeting point detection and path fusion; analyzing a human behavior pattern to identify a potential passage conflict area, establishing a social negotiation strategy, and taking an intermediate meeting point as a social key node to adaptively adjust a candidate path; the optimal safety path is determined through multi-dimensional safety evaluation of the falling risk, the collision risk and the energy consumption risk, and intelligent autonomous navigation of the humanoid robot in a complex environment is achieved.

The invention belongs to the technical field of medical robots, and particularly relates to a mammary gland puncture surgical robot navigation system and device based on multi-modal image fusion. The multi-mode image data are registered and fused, high-precision three-dimensional reconstruction of the mammary gland tissue is achieved, more visual and accurate surgical navigation information is provided for doctors, the position of the puncture needle is tracked in real time, space registration is conducted on the puncture needle and the image data, and therefore the precision and safety of the surgery are improved, and the operation efficiency is improved. Meanwhile, puncture force feedback information of a puncture needle in the needle moving process is collected in real time, the implementation effectiveness of a puncture navigation path is evaluated, when it is found that the puncture path has risks, dynamic adjustment is conducted immediately, a new puncture path bypassing an obstacle area and reaching a focus is planned again, and the risk of the puncture path is avoided. And if the safe path cannot be obtained, the system automatically stops needle insertion and gives an acousto-optic early warning prompt, so that the surgical risk caused by manual misoperation in the traditional surgery is avoided.

The invention discloses a building robot multi-machine linkage construction method and system based on intelligent scheduling, electronic equipment and a storage medium, and relates to the technical field of construction control. The method comprises the following steps: acquiring design drawing information and landform environment information of a to-be-constructed area; based on the design drawing information and the landform environment information, constructing a BIM model of the to-be-constructed area; determining process stages of a plurality of construction points in the to-be-constructed area, and matching building robot selection schemes corresponding to the construction points based on the process stages; for each construction point, according to the position of the construction point in the target BIM model, determining navigation paths of a plurality of different types of building robots in the building robot selection scheme; and receiving preset operation tasks corresponding to the different types of building robots, and controlling the different types of building robots to construct the construction site in combination with the navigation paths and the preset operation tasks. By implementing the technical scheme provided by the invention, the effect of improving the building construction efficiency is achieved.

The invention relates to the technical field of image processing, and discloses an AR technology-based precise positioning method and system for minimally invasive surgery of hepatobiliary surgery. The method comprises the steps that blood vessel network data are extracted through a medical image sequence, a three-dimensional structure diagram is generated, operation target points are marked, and a coordinate system is established; collecting dynamic data for mapping matching, and establishing a real-time tracking model; constructing an augmented reality scene and implanting a navigation path; acquiring an instrument position calculation track, and comparing with a navigation map to generate an instruction; constructing a projection interface to display the key area; recording the whole process and evaluating the operation quality. By establishing the real-time tissue deformation tracking model, a multi-source data fusion accurate positioning mechanism and an intelligent operation quality evaluation system, the accuracy and reliability of operation navigation are effectively improved.

The invention discloses an ophthalmologic operation real-time navigation system and method based on dynamic visual field tracking, and relates to the technical field of medical systems. Comprising the following steps: matching operation data closest to a current operation from a database, and generating standard operation navigation of the current operation; the real-time image of the operation process is compared with the image of the standard operation navigation in real time, the step of the current operation is determined, and meanwhile subsequent image navigation of the operation of the patient is displayed; generating a spatial mapping matrix between an eyeball movement track and a target region by combining target region boundary data of preoperative OCT image segmentation and an intra-operative navigation coordinate system; the virtual navigation path of the surgical instrument is dynamically corrected according to the real-time eyeball movement track, so that the surgical instrument is aligned with the target area, the spatial relation between the instrument and the target area can be visually mastered through the overlapping display of the three-dimensional virtual path and the real-time image, unconscious displacement or physiological tremor of a patient in an operation is actively adapted, and the operation accuracy is improved. And the continuous accuracy of the navigation path is ensured.

The invention relates to the technical field of robot navigation, and discloses a robot automatic navigation and homeward voyage method, device and equipment and a storage medium, and the method comprises the steps: carrying out the multi-scale environment feature extraction of environment image data collected by a walking replacing robot, and obtaining environment feature data; constructing an initial navigation path; performing target detection and feature re-identification on the real-time environment image to obtain a real-time environment perception result; performing extended Kalman filtering fusion processing on the multi-sensor data to obtain robot-environment interaction state features; according to robot-environment interaction state characteristics, carrying out linear section and turning section trajectory analysis, and constructing a smooth navigation trajectory; continuously updating the environment characteristic data and the working state data of the walking-instead-of-walk robot in the navigation process, and constructing a dynamic environment map; and when a return flight signal is received, quickly planning an automatic return flight path based on the dynamic environment map. The autonomy and the working efficiency of the walking-replacing robot can be improved.

The invention provides a mobile robot motion planning method and device for an indoor dynamic scene, and the method comprises the steps: generating an indoor environment map and the positioning information of a mobile robot according to environment perception data obtained in real time, and carrying out the denoising and classification of the environment perception data, static obstacle points and dynamic obstacle points are extracted according to the recognition features; constructing a comprehensive environment model of static obstacles and dynamic obstacles; identifying and marking the current position and the predicted position of the dynamic obstacle by utilizing a machine learning model based on the track prediction information of the dynamic obstacle in the comprehensive environment model, and further identifying potential navigation path key points of the mobile robot; constructing a multi-criterion preference function based on the navigation path key points, and measuring and serializing the navigation path key points to obtain local optimal navigation path key points; and determining a planned path by applying a branch and bound method.

The present invention generally relates to a virtual reality (VR) navigation system using artificial intelligence (AI), thus enabling providing of individualized and context-aware navigation experience in VR environments. It consists of an AI-inclusive central processing unit (CPU) that receives and processes real-time data from multiple hardware sensors deployed in a wearable VR headset, e.g., inertial measurement units (IMUs), eye-tracking sensors, biometric ones. This is AI-driven CPU that dynamically changes the navigation path and sensory outputs such as visual, audio, haptic based on user input / interaction & environmental context. It consists of a hand-held controller with numerous input interfaces and a wireless communication module, enabling it to be easily linked or integrated into several VR applications.

The invention discloses an intelligent traffic signal device and a remote control method, and relates to the technical field of intelligent traffic control. The method is used for solving the problems of low emergency traffic efficiency and global and local control imbalance under sudden traffic events. The method comprises the following steps: firstly, fusing an emergency vehicle navigation path, accident point vehicle motion abnormal parameters and pedestrian aggregation distribution data, constructing a multi-dimensional event evolution feature vector through a space-time encoder, and accurately describing a traffic situation; an event influence domain boundary is delimited based on vehicle trajectory and flow direction consistency analysis, a dynamic evolution model is constructed in combination with an acceleration abrupt change propagation path, and a space-time conflict probability matrix is generated; then executing a hierarchical control strategy, dynamically adjusting an intersection signal period starting time difference in a global level to form an emergency green wave coordination band, and inserting an adaptive full red phase in a local level according to a balance relation between a vehicle arrival rate and a dissipation rate; and finally, reversely correcting model parameters through an actual pass error, updating a conflict probability generation rule, and forming a closed-loop feedback mechanism.

The invention discloses an unmanned ship navigation path obstacle avoidance method and system, and particularly relates to the technical field of unmanned ships. The method comprises the following steps: acquiring information of a fixed obstacle, a dynamic target and environmental factors, predicting the motion track of the dynamic target by using a deep learning algorithm, improving the track prediction accuracy, calculating an optimal obstacle avoidance path in real time based on a Dijkstra algorithm in combination with the navigation state of the unmanned ship and hydrodynamic environmental factors, and obtaining the optimal obstacle avoidance path. The trajectory prediction deviation is evaluated through a hydrodynamic disturbance factor and a motion inertia deviation factor; when the deviation exceeds a threshold value, the system adaptively adjusts a path, preferentially adopts a minimum steering angle strategy and an energy consumption optimization strategy, ensures the navigation stability of the unmanned ship, and meanwhile, continuously optimizes the strategy in combination with historical obstacle avoidance data, so that the intelligent obstacle avoidance capability, the navigation stability and the energy consumption efficiency of the unmanned ship in a complex dynamic water area can be improved; the system is suitable for application scenes such as water area patrol, environment monitoring and ocean detection.

The invention discloses a ship motion prediction method and device, electronic equipment and a readable storage medium. The ship motion prediction method comprises the steps of obtaining current motion information and current environment information of a target ship; the current motion information and the current environment information are processed through a ship motion prediction model obtained through pre-training, output future motion information is obtained, the ship motion prediction model is constructed based on a motion sub-model and a prediction sub-model obtained through training, the motion sub-model is used for representing physical motion characteristics of the ship, and the prediction sub-model is used for predicting the physical motion characteristics of the ship. The prediction sub-model adopts a gating circulation unit as a model framework and adopts historical ship motion information as a training sample, and the historical ship motion information comprises various parameters which are respectively collected by various sensors arranged on a ship and are related to representing ship motion; determining a future motion track of the target ship by using the future motion information; and adjusting the planned advancing path of the target ship based on the future movement track. By applying the method, the intelligent level of a ship navigation system can be improved, the ship navigation path is optimized, and the safety of sailing on the sea is guaranteed.

A system and method for latent hyperspace navigation in spatiotemporal media using hierarchical and Lorentzian autoencoders. The system compresses spatiotemporal media into navigable latent representations while preserving geometric and semantic relationships through tensor structure maintenance. A latent hyperspace manager organizes compressed representations as geodesic trajectories within a geometric manifold structure based on differential geometry principles. A geodesic trajectory mapper computes optimal navigation paths through the high-dimensional space, while symbolic anchors positioned at semantically significant locations serve as persistent reference points. Spatiotemporal routing protocols manage navigation decisions across multiple temporal scales. A strategy caching system preserves successful navigation patterns for reuse, enabling continuous learning. The system generates synthetic content during navigation to support infinite zoom capability, allowing exploration beyond original media boundaries. Cross-modal fusion combines diverse input modalities into unified representations, applicable to immersive media exploration, scientific visualization, and surveillance analysis.

The invention relates to the technical field of intelligent robots and old-age care, and discloses a target navigation method and device based on environmental context, a robot and a medium, which can be applied to a household auxiliary robot intelligent medicine delivery scene, and the method comprises the following steps: receiving multi-modal input of a user, preprocessing the multi-modal input, and generating preprocessed multi-modal data; reading the current time and the environment state, and performing perceptual analysis based on a pre-constructed tetrad map, the current time and the environment state to generate a candidate search area list; determining a target candidate area from the candidate search area list; generating a target navigation path based on the SLAM map and the target candidate area, and moving the robot to the target candidate area according to the target navigation path; and obtaining a target candidate region image, and performing visual semantic verification based on the target candidate region image and the target object label in the structured text instruction. According to the invention, the robot navigation accuracy and the user experience are improved.

The invention discloses a wounded rescue life detection and positioning method based on deep learning. The method comprises the steps that S1, multi-view RGB-D images, laser radar point clouds, millimeter wave vital sign radar data and infrared thermal image data are collected and subjected to time synchronization; s2, outputting a pixel-level semantic mask; s3, generating a semantic point cloud of the wounded; s4, forming a metric-semantic double-map data set; s5, generating vital sign scores and writing the vital sign scores into a metric-semantic double-map data set; s6, updating wounded dynamic anchor point attributes in the measurement-semantic double-map data set; and S7, based on the updated metric-semantic double-map data set, calculating the three-dimensional coordinate and rescue priority sequence of each wounded dynamic anchor point, and generating an obstacle avoidance optimized navigation path for avoiding the risk semantic region. The rescue efficiency and safety are effectively improved.

The invention relates to the technical field of smart bracelet positioning, and discloses a smart bracelet position tracking and navigation method, device and equipment and a storage medium, and the method comprises the steps: collecting multi-source positioning data through a built-in multi-sensor system of a smart bracelet, and carrying out the preprocessing, thereby obtaining the preprocessed multi-source data; performing feature extraction and space-time embedding processing to obtain an embedded multi-source feature sequence; inputting the embedded multi-source feature sequence into a multi-source information fusion model for processing to obtain an initial position estimation result and position uncertainty; constructing an adaptive pose map based on the initial position estimation result and the position uncertainty, and optimizing the adaptive pose map to obtain optimized position information; and a multi-level environment map is generated according to the optimized position information, and dynamic path planning is performed to obtain a navigation path and a navigation instruction, so that high-precision and low-power-consumption position tracking and navigation functions are realized, and smooth user experience is provided at the same time.

The invention discloses an unmanned aerial vehicle airport multi-target constraint planning and site selection method and system and electronic equipment. The planning and site selection method comprises the following steps: S1, obtaining geographic information of a target site selection area; s2, determining performance parameters of the unmanned aerial vehicle, and obtaining a flight coverage range of the unmanned aerial vehicle in combination with geographic information; s3, constructing a dynamic task point model, and determining an unmanned aerial vehicle task point set through the dynamic task point model; s4, obtaining an optimization target of airport site selection, establishing a target function according to the optimization target, constructing a site selection optimization model through the target function, and setting constraint conditions for the site selection optimization model; and S5, performing multi-target optimization calculation based on the site selection optimization model by adopting a heuristic algorithm to obtain a target layout of the unmanned aerial vehicle airport. According to the technical scheme disclosed by the invention, the navigation path can be precisely planned, the accurate navigation of the unmanned aerial vehicle in a communication limited or silent environment is realized, and the navigation reliability and the operation capability of the unmanned aerial vehicle are improved.

The invention discloses an unmanned ship navigation path intelligent optimization system and method based on ocean data, and particularly relates to the technical field of unmanned ship navigation. The accuracy of monitoring data of the sensor in a marine environment is continuously evaluated through a series of steps of preliminary calibration, data acquisition, filtering processing, abnormal marking, feature extraction and the like of the unmanned ship sensor, and real-time evaluation and time period division of the quality of the monitoring data are realized through comprehensive analysis of abnormal features of sound velocity and conductivity. The abnormal degree is predicted in the abnormal monitoring time period, and for the condition of high abnormal degree, a safety avoidance strategy is automatically set through a path planning system, and the route and the navigational speed of the unmanned ship are dynamically optimized, so that a risk area is avoided, the navigation precision and safety are improved, the reliability of sensor data is remarkably improved, and the safety of the unmanned ship is improved. The influence of data deviation on path planning is reduced, and the task success rate and the navigation safety of the unmanned ship in a complex marine environment are enhanced.

The invention discloses a path planning and obstacle avoidance method for an unmanned ship formation, and relates to the technical field of formation path planning. Decoding the quantum chromosome into an actual path by using a quantum genetic algorithm, screening out an optimal path, and discretizing the optimal path to obtain a global navigation path; a follower navigation path is constructed according to formation characteristics and a reference formation, the initial formation is adjusted when the follower starts, a communication link with a navigator is established at the same time, and the follower carries out local obstacle avoidance by using an improved artificial potential field method to carry out local formation adjustment; when a dynamic obstacle is detected, the stress is recalculated by using an improved potential field method, and the local path of the re-planned road section is optimized; and judging whether a target point is reached or not, if so, ending, and if not, circularly executing until the target point is reached. According to the invention, the formation system keeps stable formation in a dynamic unknown environment, and the targets of safe obstacle avoidance and optimal path are achieved.

The invention discloses an electric vehicle charging station ordered charging method based on intelligent queuing, which comprises the following steps: acquiring a remote charging queue adding request, and extracting a vehicle identifier and current position information; a sliding window mechanism is adopted, a fixed time interval is set, charging station traffic flow and charging pile state change data are collected, and the estimated waiting time is used for updating queuing information; according to the distance between the vehicle and the charging station, the priority queue algorithm is adopted to allocate the charging pile position in combination with the predicted waiting time, and it is ensured that the closer vehicle preferentially obtains the charging opportunity; acquiring position information of a plurality of vehicles entering the range of the charging station at the same time, processing the requests by using a timestamp sorting algorithm based on vehicle entering time, and determining a guiding sequence of each vehicle; and generating a navigation path from the current position to the specified charging pile position according to the guiding sequence and the distributed charging pile position, and sending path information to the vehicle-mounted navigation system. The charging efficiency can be remarkably improved.

The invention discloses an autonomous collision avoidance method and system for an unmanned ship in a mixed traffic mode, and the method comprises the following steps: obtaining the current position coordinate information, course information and surrounding environment information of the unmanned ship in real time through a ship positioning system and a ship recognition system on the unmanned ship; combining the target point, constructing a path plan and calculating the energy consumption of a navigation path, selecting a first navigation path, identifying and classifying static obstacles and dynamic obstacles, monitoring the static obstacles in real time, calculating and evaluating a detour difference, adjusting the path according to a collision avoidance rule, and generating a second navigation path; predicting the movement direction of the surrounding dynamic obstacles, and judging whether a collision risk exists or not; predicting a future position and adjusting the course to generate a third navigation path; and respectively evaluating the electric quantity threshold, the energy consumption threshold, the battery electric quantity and the energy consumption value, and adjusting an energy use strategy in real time. According to the invention, the accuracy of the navigation path is improved, and the safety of the unmanned ship in a complex environment is improved.

The invention relates to the technical field of visual navigation, in particular to a robot navigation method based on vision, which comprises the following steps: acquiring a grayscale image to extract dynamic point locations, screening boundary features to reconstruct a feature set, calculating gradient change to generate candidate guide points, converting coordinates to construct a path track set, and outputting a navigation planning path. According to the method, rapid elimination of static backgrounds is realized through difference threshold selection, dynamic region extraction accuracy is effectively improved, combined screening of boundary line feature point frequency and average feature density is combined, key feature stability is enhanced, and the identification capability of image local structure mutation is enhanced by using a variance change rate of a gradient amplitude sequence. Robustness of path guide point extraction is improved through judgment of an abnormal section, dynamic construction of a path track is realized by means of continuous time integration of image coordinates, path identification precision and spatial positioning continuity are optimized, and continuity, precision and real-time performance of navigation path planning are improved.

The invention discloses an automatic control method and device for a thermal management system of an electric vehicle, relates to the field of intelligent control, and realizes multi-step prediction of battery and motor heat production and thermal load change in the future by fusing external information such as a navigation path and weather forecast, plans a thermal management strategy in advance, and improves the response perspectiveness of the system. A multi-source disturbance dynamic structured correlation equalization technology is adopted, the coupling relation between heat sources is modeled, cross disturbance is compensated through a joint state function, and multi-heat-loop cooperative control is achieved. On the basis of a model predictive control (MPC) framework, temperature tracking errors and energy consumption penalty are optimized, the energy consumption of actuators such as a compressor and a water pump is reduced while a safe temperature interval is met, and the endurance is prolonged. And in combination with a state estimator fusion model and observation data, the control precision and robustness under a complex working condition are enhanced, and finally global optimal thermal management considering the service life of parts, the comfort of passengers and the energy efficiency is realized.

The invention provides a cross-domain multi-dimensional query feature index selection method, which comprises the following steps of: judging a query field and a query purpose of a user through query subject classification and query intention identification according to historical query behavior data of the user, and obtaining a field tag and an intention tag of the query; a navigation path of knowledge links is optimized, semantic correlation between nodes and small world index algorithm characteristics are comprehensively considered, an optimal knowledge navigation path is recommended for a user, and an optimization strategy is dynamically adjusted according to query historical behaviors and feedback of the user; a knowledge navigation result is presented in a visual interaction mode, a multi-dimensional attribute screening and sorting function is provided, exploration type browsing and deep mining of a user are supported, and personalized knowledge recommendation service is provided according to a query scene and preference of the user.

The invention relates to the technical field of robots, and discloses an SLAM navigation-based inspection robot inspection track self-correction method, which comprises the following steps: S1, acquiring environmental data through a 2D laser radar, an attitude sensor and an odometer sensor, and generating an initial environmental map and a navigation path by using an SLAM mapping algorithm; s2, fusing the laser radar pose data, the odometer pose data and the pose sensor pose data to obtain real-time pose information, comparing the current pose with the target path pose, and calculating a path error; s3, a robot motion instruction is adjusted through a compensation control algorithm based on the path error, and the path deviation is corrected; s4, continuously monitoring path errors and correcting the path errors in real time; and S5, storing the corrected track as a navigation path file. According to the invention, by introducing the robot remote controller, complex functions such as mapping, navigation, navigation point marking, path storage, motion control and the like are modularized, and the operation process is greatly simplified.

The invention provides a GNSS (Global Navigation Satellite System) anti-interference receiver system based on radio frequency front end-INS (Inertial Navigation System) combined assistance, which adopts a dual-core ARM Cortex-A9 and a programmable logic unit for layered decoupling, and realizes real-time receiving and processing of a high-bandwidth data stream, closed-loop control of an interference suppression link and quick response of a navigation path and a strategy decision. All the modules efficiently cooperate through AXI-Lite register mapping, interrupt signals, a shared state buffer area and a timer synchronization mechanism. By controlling bus and state buffer mapping to keep consistency and supporting a module-level independent debugging and system-level soft reset mechanism under hot start, the expandability of subsystem cascade debugging, fault module positioning and online updating is realized. In the aspects of module architecture, data channels and cooperation mechanisms, the structure order, efficient communication and control closed loop are realized, and an embedded multi-module cooperation anti-interference platform which is suitable for a high-interference environment, multi-channel fusion processing and navigation task real-time response is constructed.

The invention relates to an indoor robot navigation method based on multi-modal feature fusion. The method comprises the following steps: constructing a semantic map based on visual observation environment information; the method comprises the following steps: acquiring an RGB image of an indoor scene object, converting the RGB image into point cloud data, and preprocessing the RGB image and the point cloud data; image multilayer semantic features and point cloud features in the RGB image and the point cloud data are extracted respectively, and initial fusion is carried out; performing weighted fusion on the multi-layer semantic features and the point cloud features of the image by adopting space-channel-cross-modal multi-attention dynamic cooperation; and predicting a long-term target in a map space from top to bottom based on the fused feature map and the semantic map, and performing navigation path planning based on the current position and the long-term target. Under low-cost hardware configuration, the robustness of environment perception, the real-time performance of decision response and the usability of system integration in a dynamic complex environment are comprehensively improved, and the method is particularly suitable for application scenes such as indoor service robots.

The invention provides a robot navigation method and system based on visual identification, and relates to the technical field of computer vision, firstly, a continuous visual information set of the surrounding environment of a robot is obtained, the continuous visual information set comprises environment visual images of different directions of the advancing direction of the robot, and the object appearance features and the spatial arrangement relation are recorded; then establishing association mapping between the continuous visual information set and a preset navigation area to obtain a double-association mapping result; generating a semantic anchor point navigation path based on a double-correlation mapping result, wherein the semantic anchor point navigation path comprises a semantic anchor point sequence from the current position to the target position; real-time visual semantic features in the navigation process are obtained through a real-time visual collection module, and a semantic anchor navigation path is dynamically updated; finally, a final navigation execution path is output according to the updated path, the robot is driven to complete navigation operation, and the navigation capability and the intelligent level of the robot in a complex dynamic environment are improved.

The invention provides an airway navigation system and method based on a bronchoscope view, and the system comprises a reconstruction module which obtains a bronchial tree 3D mask through CT image reconstruction; the model building module is used for obtaining a three-dimensional virtual map model comprising a 3D bronchial tree according to the 3D mask of the bronchial tree; the path extraction module is used for extracting all possible navigation paths from the bronchus entrance to the target part based on the 3D bronchus tree; the path selection module is used for selecting one navigation path as a target navigation path; the navigation module is used for guiding the bronchoscope to move along a target navigation path in the three-dimensional virtual map model based on a visual guide path; and the navigation auxiliary module maps the identified real-time part corresponding to the bronchoscope to the 3D bronchial tree for matching so as to realize dynamic synchronization of the real-time part corresponding to the bronchoscope and the target navigation path. According to the invention, reliable and convenient navigation in a complex airway network can be realized, misoperation is effectively avoided, time is saved, and operation difficulty is reduced.