50 results about "Pedestrian navigation" patented technology

The invention discloses a pedestrian inertia / vision / satellite integrated navigation method based on a handheld terminal PDR. The pedestrian inertia / vision / satellite integrated navigation method comprises the following steps: calculating to obtain inertial navigation pose information based on strapdown inertial navigation; when the pedestrian is static, constructing an observation constraint of zero-speed motion for correction, and updating inertial navigation position information based on step length information when a new step is carried out; obtaining visual pose information of the pedestrian based on an inertia / visual fusion odometer, obtaining satellite position information of the pedestrian based on satellite positioning, and carrying out coordinate system alignment and step length coefficient correction factor estimation; a pedestrian multi-source factor graph optimization model with a handheld terminal PDR as a core is constructed, inertial navigation pose information and step length information are used as local state constraints, visual pose information and satellite position information are used as global state constraints, and a target optimization function is constructed to obtain a final pose of a pedestrian. The method is applied to the field of pedestrian navigation, has full-scene robust and continuous positioning capability, and can effectively realize high-precision navigation positioning under long endurance.

Methods, apparatuses, and computer-readable media for providing a pedestrian-oriented navigation app for a mobile device. Destination information is received from a pedestrian using a mobile device. The mobile device retrieves pedestrian-oriented mapping data and routing for the navigation of the pedestrian to the destination, determines a current location and direction of the pedestrian based upon GPS data and compass data retrieved from the device, and displays the current location and direction of the pedestrian along with a route for the pedestrian to the destination on the user interface of the mobile device based on the pedestrian-oriented mapping data and routing. If the mobile device detects that the pedestrian has deviated from the route, the mobile device alters the display on the user interface to alert the pedestrian to the deviation.

Methods, apparatuses, and computer-readable media for providing a pedestrian-oriented navigation app for a mobile device. Destination information is received from a pedestrian using a mobile device. The mobile device retrieves pedestrian-oriented mapping data and routing for the navigation of the pedestrian to the destination, determines a current location and direction of the pedestrian based upon GPS data and compass data retrieved from the device, and displays the current location and direction of the pedestrian along with a route for the pedestrian to the destination on the user interface of the mobile device based on the pedestrian-oriented mapping data and routing. If the mobile device detects that the pedestrian has deviated from the route, the mobile device alters the display on the user interface to alert the pedestrian to the deviation.

The invention belongs to the technical field of mobile wireless positioning, and particularly relates to a Bluetooth and UWB fusion positioning method and system based on Kalman filtering, and the method comprises the steps: taking a UWB distance measurement value and a distance converted by a Bluetooth signal distance conversion model as an observation vector through combining the low power consumption characteristic of a Bluetooth signal and the high precision advantage of UWB; according to the real-time position of a detected target, a Kalman filtering algorithm (Kalman filtering algorithm) is adopted to carry out data fusion processing, so that real-time positioning of an observation target is realized. According to the algorithm, a positioning service area is divided into a high-precision positioning area, a common-precision positioning area and a connection area according to the positioning precision requirement, and UWB positioning anchor point equipment and BLE positioning anchor point equipment are arranged in different positioning areas at the same time. And an indoor fixed person navigation positioning model is formed by adopting UWB and BLE pedestrian navigation constraints for the connection area, so that the requirements of relatively high precision and relatively low cost are met.

The invention discloses a pedestrian navigation method and system based on intelligent fusion of optical signals and inertia. The method comprises the following steps: calculating the distance between a receiving end and a transmitting end according to the positions of a visible light transmitting end and a receiving end and visible light original data collected by the receiving end; calculating the collected inertial data by adopting a pedestrian dead reckoning method to obtain position information of a receiving end; and carrying out tight combination fusion on the distance between the receiving end and the transmitting end and the position information of the receiving end based on a particle filtering algorithm to obtain a predicted pedestrian position. According to the method, the pedestrian dead reckoning positioning result and the visible light ranging information are fused, the defects of a single positioning technology are overcome, the method has good performance on a fusion positioning system of visible light and other signals susceptible to environmental interference and inertial and other high-noise signals, the adverse effect of environmental noise on the fusion system is weakened, and the positioning accuracy is improved. And the migration capability and the adaptive capability of the fusion system are effectively improved.

The invention belongs to the technical field of pedestrian navigation and positioning, and relates to a pedestrian inertial navigation method based on action recognition. The method comprises the following steps: collecting IMU data and muscle electricity data by using a wearable device; in a static state, calculating an Euler angle and solving a coordinate rotation matrix by means of IMU data, converting an acceleration in a carrier coordinate system into a navigation coordinate system, and obtaining speed information after integration; after the muscle electricity data is subjected to preprocessing and feature extraction, an SVM model based on statistics and an action correction algorithm is used for recognizing the motion state of the human body in a mixed motion mode, and an action recognition result is obtained; the action recognition result is used for self-adaptively adjusting threshold detection of the zero speed interval, finally, the zero speed is corrected in the zero speed interval through a speed correction method based on the EKF, integration is conducted on the corrected speed, and therefore position information is obtained. According to the method, high positioning precision, small positioning error and good robustness can be realized in a mixed motion mode, and an accurate track can be drawn.

The invention relates to the technical field of positioning and navigation, in particular to a multi-modal recognition pedestrian positioning and navigation method. The method comprises the following steps: firstly, respectively acquiring data in six motion modes of walking reading, walking telephone calling, walking swinging, walking pocket, jogging telephone calling and jogging pocket, and extracting 30-dimensional motion features; thirdly, constructing a multi-mode recognition model of a PCA-GWO-KELM (principal component analysis and grey wolf algorithm optimization kernel extreme learning machine) based on the PCA-GWO-KELM; inputting the motion features into a multi-mode recognition model for training to obtain recognition accuracy rates under different motion modes; then, step number detection is carried out by combining a peak value detection method with a self-adaptive acceleration upper threshold value and a self-adaptive dynamic time threshold value, the step length is calculated by adopting a multi-feature-based self-adaptive step length estimation algorithm, and the course is calculated by adopting a method of fusing direction sensor data and gyroscope data; finally, continuous dead reckoning is carried out on pedestrian displacement, and low-cost and high-robustness pedestrian navigation positioning is achieved.

Method for processing users' cellphone data, the method comprising using a hardware processor for analyzing at least accelerometer (IMU) data provided by cellphones of at least a threshold number of users in a given location including recognizing at least one urban feature at said given location each time at least the threshold number of users, known to be present at the given location, exhibit a given motion pattern known by the processor to be characteristic of said urban feature; and / or generating a map including a stored representation of said at least one urban feature which is associated in memory with said given location at which the accelerometer data indicative of the urban feature was collected.

The application discloses a rescue navigation method, device and equipment based on a three-dimensional road network, the method comprising: constructing a three-dimensional road network of a target area, the three-dimensional road network comprising a first layer constructed based on stake number line information and a second layer constructed based on grid data; monitoring a rescue request sent by an intelligent safety helmet in the target area; generating a rescue strategy based on the rescue request in response to the rescue request; generating a navigation route based on the rescue strategy and the three-dimensional road network; and performing rescue navigation based on the navigation route, wherein the navigation route comprises a vehicle navigation route and a pedestrian navigation route, the vehicle navigation route is generated based on the first layer of the three-dimensional road network, and the pedestrian navigation route is generated based on the second layer of the three-dimensional road network, so that the three-dimensional road network can effectively adapt to different rescue navigation scenarios, the rescue response speed is greatly improved, rescue personnel and vehicles can timely arrive at a rescue position, and the problem that an unreasonable navigation plan leads to an incorrect best rescue window is effectively avoided.

The present invention relates to the technical field of autonomous navigation of mobile robots and pedestrian collision avoidance, and provides a safe pedestrian navigation method and system based on spatio-temporal constrained velocity obstacles. The method includes: obtaining the motion state of pedestrians according to laser information; constructing a velocity obstacle region in the velocity space according to the motion state of pedestrians; adaptively adjusting the time factor according to the pedestrian density, and adjusting the velocity obstacle region according to the time factor, and performing velocity sampling by using the velocity obstacle method under time constraint according to the velocity obstacle region under time constraint, and judging whether to perform velocity resampling through a velocity resampling criterion; performing integral processing on the sampled velocity to generate a candidate trajectory, and designing an evaluation function to select the optimal trajectory. The present invention uses the spatio-temporal constrained velocity obstacle method to guide the robot to generate a safe velocity, and improves the safety and motion efficiency of the robot navigation by designing an adaptively adjustable time factor and a velocity resampling mechanism.

The invention discloses a pedestrian navigation method based on self-adaptive search interval zero-speed detection. The pedestrian navigation method comprises the following steps: S1, periodically collecting acceleration data and angular velocity data output by an inertial sensor; s2, judging whether the navigation system is initialized or not, if the navigation system is not initialized, initializing the navigation system, and entering S1 to recollect acceleration data and angular velocity data; if so, entering the step S3; s3, performing adaptive interval zero-speed point search based on the acceleration data and the angular velocity data, obtaining an inertia factor and a zero-speed factor based on an adaptive search interval, and constructing an optimization equation to predict inertia information according to the inertia factor and the zero-speed factor; and S4, predicting the pose change from the previous zero speed point to the current moment based on the inertial information, and outputting carrier navigation information. According to the method, accumulative error divergence can be effectively restrained by combining a self-adaptive zero-speed point detection technology with a graph optimization framework, and pedestrian positioning information is obtained.

The present invention relates to an adaptive zero-speed detection algorithm based on interval search under variable speed motion conditions, and belongs to the field of pedestrian navigation technology. It includes: 1) zero-speed interval proportion analysis; 2) gait cycle extraction; 3) preliminary screening of zero-speed intervals; 4) fine determination of zero-speed intervals. The present invention determines the search interval of the gait cycle by performing SWA filtering on the modulus of angular velocity, and preliminarily determines a zero-speed interval based on the statistical characteristics of the zero-speed interval in the gait cycle under different speeds, and sets a new threshold based on the 3σ criterion to achieve adaptive zero-speed detection. The present invention not only provides a new, efficient and accurate positioning solution for wearable devices and location services, but also provides a valuable reference for pedestrian navigation research under complex motion patterns.

The present invention discloses a navigation method based on an inelastic boundary constraint integrated multi-dimensional factor combination. First, environmental magnetic fingerprint data is collected in an offline stage to obtain a geomagnetic fingerprint library; and step length, heading angle, GNSS positioning data and magnetic fingerprint measurement values ​​are collected in real time through pedestrian navigation; step length factor, differential heading angle factor, magnetic fingerprint factor, GNSS factor are calculated and a factor graph model is constructed: a sliding window optimization strategy is adopted to only retain the state nodes of the most recent several moments in the preliminary factor graph model for optimization; the optimized factor graph model is applied to obtain the optimal navigation trajectory. This method improves positioning accuracy and robustness in complex environments. It addresses the problems that traditional PDR systems are susceptible to single-step abnormal estimation, magnetic fingerprint positioning is susceptible to local magnetic interference, and GNSS positioning has poor stability in blocked areas.

The present application relates to a kind of pedestrian collaborative navigation method based on distance and angle, the collaborative navigation method includes: S1, by MIMU output each pedestrian respective three-axis accelerometer and three-axis gyroscope data, and carry out strapdown inertial navigation solution, again by the state of zero speed detection to the data of inertial navigation solution is carried out zero speed correction by extended Kalman filtering;S2, by UWB ranging angle measurement obtains the relative distance and angle between pedestrians as observation, then with the position information and heading angle information of N pedestrians as state quantity, carries out Kalman filtering, obtains the correction data of the position information and heading angle information of each pedestrian;S3, according to the position information and heading angle information of each pedestrian after correction collaborative navigation is carried out.The present application uses distance and angle as observation to correct pedestrian navigation after ZUPT auxiliary, solves the current pedestrian navigation heading angle drift and the problem of large amount of calculation of centralized filtering.

The present invention discloses a visually assisted gait feature constrained pedestrian navigation method, which comprises the following steps: firstly, using the data collected by the inertial measurement unit to analyze the gait characteristics of the pedestrian and calculate the zero-speed interval; then, calibrating the inertial measurement unit and the camera to obtain corresponding internal and external parameters, solving the position and attitude data of the six-degree-of-freedom of the visual inertial odometer, and obtaining the relative posture information of the pedestrian's movement; then adopting the strapdown inertial navigation calculation method to perform initial alignment and inertial navigation solution to obtain the pedestrian's instantaneous attitude, speed and position information; finally, establishing a Kalman filter model, using the speed difference and angular velocity difference in the zero-speed interval, the attitude error and position error when the visual signal is valid as observation quantities for measurement and update; using the current corrected state quantity as the initial quantity for the next inertial navigation solution, and repeating the navigation correction process. The present invention can constrain the divergence of navigation errors in an environment where GNSS signals fail, and improve the accuracy of pedestrian navigation positioning.

The invention relates to a self-adaptive zero-speed detection algorithm based on interval search under variable-speed motion conditions, and belongs to the technical field of pedestrian navigation. Comprising the following steps: 1) analyzing a zero-speed interval proportion; 2) gait cycle extraction; 3) preliminary screening of zero-speed intervals; and 4) finely determining a zero-speed interval. According to the method, SWA filtering processing is carried out on the mode of the angular speed, the search interval of the gait cycle is determined, a zero-speed interval is preliminarily determined according to the statistical characteristics of the zero-speed interval in the gait cycle at different speeds, a new threshold value is set based on the 3 sigma criterion, and self-adaptive zero-speed detection is achieved. The invention not only provides an efficient and accurate new positioning scheme for the fields of wearable equipment and location services, but also provides valuable reference for pedestrian navigation research in a complex motion mode.

The invention discloses a rescue navigation method, device and equipment based on a three-dimensional road network, and the method comprises the steps: constructing the three-dimensional road network of a target area, the three-dimensional road network comprises a first layer constructed based on stake mark line information and a second layer constructed based on raster data, monitoring a rescue request sent by an intelligent safety helmet in the target area, in response to the rescue request, generating a rescue strategy based on the rescue request, generating a navigation route based on the rescue strategy and the three-dimensional road network, and performing rescue navigation based on the navigation route, the navigation route including a vehicle navigation route and a pedestrian navigation route, the vehicle navigation route being generated based on a first layer of the three-dimensional road network, and the pedestrian navigation route being generated based on a second layer of the three-dimensional road network; the pedestrian navigation route is generated based on the second layer of the three-dimensional road network, so that the three-dimensional road network can effectively adapt to different rescue navigation scenes, the rescue response speed is greatly improved, rescue workers and vehicles are ensured to arrive at rescue positions in time, and the problem that the optimal rescue window is wrong due to unreasonable navigation planning is effectively avoided.

The following generally relates to using Augmented Reality (AR) to enhance pedestrian navigation. In some examples, AR techniques are applied to provide AR indications of a location of a group member that includes two or more AR devices. In these examples, AR techniques may be applied to determine a relative position of the group member and / or provide navigational guidance to the group member. In other examples, AR techniques are applied to provide AR-assisted pedestrian guidance. In these examples, AR techniques may be applied to present an AR display that includes information for a point of interest along a route.

The present disclosure relates to a pedestrian navigation heading constraint method, device, electronic equipment, storage medium and program product. The method comprises: obtaining inertial data of a target pedestrian; based on the inertial data, extracting the heading of the target pedestrian at the current time; in response to the heading of the target pedestrian within a first sliding window satisfying a first preset straight line condition, based on the difference information between the heading at the current time and the heading of the target pedestrian within the first sliding window, and / or the error distribution of the heading of the target pedestrian within a second sliding window, performing heading constraint processing on the target pedestrian at the current time, wherein the right boundaries of the first sliding window and the second sliding window are both the current time, and the length of the second sliding window is greater than the length of the first sliding window.

The application relates to the technical field of pedestrian navigation, in particular to a pedestrian positioning method and system based on building structured information assistance, which comprises the following steps: initializing a track angle through a dynamic window self-adaptive track angle initialization method according to pedestrian motion structured features; judging straight movement and turning according to the pedestrian motion structured features and the initial track angle; performing multi-dimensional error collaborative correction through an improved self-adaptive Kalman filter; performing multi-dimensional collaborative correction through a flexible constraint model and a state-by-state Kalman filter when turning; dynamically compensating state quantities after straight movement correction and state quantities after turning correction according to environmental interference structured features; obtaining compensated state quantities; and positioning the pedestrian through the compensated state quantities. The application can fully exploit multi-dimensional structured information, dynamically optimize correction strategies for different motion states, and realize adaptive compensation of environmental interference for pedestrian positioning.

The present invention belongs to the technical field of micro-electromechanical systems, and specifically discloses a badge-type consumer-grade IMU pedestrian navigation method, including: determining whether a pedestrian is in a static state; obtaining the pedestrian's motion parameters at the current moment, correcting the gyroscope and accelerometer, clearing the pedestrian's speed and performing S5; obtaining the angular velocity measured by the corrected gyroscope, and projecting the acceleration measured by the corrected accelerometer to a navigation system, and updating the pedestrian's motion parameters at the current moment according to the acceleration under the navigation system; compensating and updating the gyroscope correction according to the acceleration calculation under the navigation system obtained in S3, and performing S5; the method has the following advantages: the inertial navigation method based on the MEMS inertial measurement unit (MIMU) has the advantages of high-precision positioning effect in a short-flight scenario, is independent of external information, and is not easily affected by interference, which makes up for the shortcomings of radio positioning and is combined with the radio positioning method to improve the accuracy of pedestrian navigation positioning in an indoor environment.

The invention relates to an indoor pedestrian navigation positioning method under a multi-constraint condition, and belongs to the field of indoor pedestrian navigation positioning. According to the method, on the basis of a foot zero-speed correction algorithm, a Kalman filtering correction algorithm based on limb course change consistency is provided by combining a constraint condition that a difference value between a foot course variation and a waist course variation is relatively small in a movement process of each step; meanwhile, in consideration of stability of relative information output characteristics of building same-floor air pressure height measurement and stability constraint of a building geometric structure in an indoor environment, a constraint algorithm based on air pressure relative height change and an improved heuristic course drift elimination algorithm based on a building structure are provided. According to the invention, an improved hierarchical zero-speed interval detection algorithm is designed for stationary motion and non-stationary motion, and the recognition accuracy of a single zero-speed detection interval is improved. And meanwhile, through an improved multi-constraint condition algorithm, relatively high navigation and positioning precision can be provided for indoor pedestrians in a relatively long time, accumulated errors of pedestrian navigation and positioning are reduced, and a high-precision navigation and positioning function is provided for the pedestrians in a three-dimensional space environment.

The invention relates to a pedestrian navigation course constraint method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: acquiring inertial data of a target pedestrian; based on the inertial data, extracting the course of the target pedestrian at the current moment; in response to the situation that the course of the target pedestrian in the first sliding window meets a first preset straight going condition, the first straight going condition is determined based on difference information between the course of the current moment and the course of the target pedestrian in the first sliding window and / or error distribution of the course of the target pedestrian in a second sliding window; course constraint processing is conducted on the target pedestrian at the current moment, the right boundaries of the first sliding window and the second sliding window are the current moment, and the length of the second sliding window is larger than that of the first sliding window.

The invention discloses a path navigation method and device for a mobile robot in a dense crowd environment and a medium, and the method comprises the steps: recognizing things in the dense crowd environment, and constructing semantic map information based on the things; carrying out semantic information analysis on the object, and describing human-machine-object by utilizing a unified interaction space method so as to construct an interaction space model; constructing a sampling path tree by using a plurality of sampling path grafting modes, and providing sampling paths with reasonable density based on dense crowd environment requirements; different sampling path time distribution is adopted based on different navigation modes so as to simulate different navigation behaviors of pedestrians; performing collision detection and comfort evaluation on the sampling path; setting evaluation indexes, comprehensively evaluating and screening the sampling paths through the evaluation indexes, and obtaining the sampling path corresponding to the optimal evaluation index as the optimal navigation path. The motion trail of the pedestrian is predicted in real time, path planning is rapidly updated, and safe navigation of the mobile robot in a dynamic environment is ensured.

The invention relates to a binary imbalance method-based group entrance and exit detection method, which comprises the following steps of: 1, constructing a sample, cutting a group boundary footprint into equidistant line segments, taking a midpoint as a sample point, and marking positive and negative samples; 2, extracting internal feature data reflecting the shape, size and spatial layout attributes of the cluster; step 3, extracting external feature data of each sample point according to an association relationship between the sample point and the context of the space where the sample point is located and interaction with the pedestrian; 4, normalizing the data set of the internal features and the data set of the external features and dividing the data set into a training set and a test set; 5, oversampling the positive sample, and undersampling the negative sample; step 6, predicting a group entrance and exit; and step 7, embedding the entrance and exit of the group into the community road network. According to the method, the position information of the entrance and the exit of the group is accurately deduced and positioned by utilizing the structural characteristics and the spatial context characteristics of the group, the accuracy of micro-scale path planning of the community is improved, and the navigation experience of pedestrians is optimized.

The invention discloses a navigation method based on inelastic boundary constraint integrated multi-dimensional factor combination, which comprises the following steps: firstly, acquiring environmental magnetic fingerprint data in an offline stage to obtain a geomagnetic fingerprint database; a step length, a course angle, GNSS positioning data and a magnetic fingerprint measurement value are collected in real time through pedestrian navigation; a step length factor, a difference course angle factor, a magnetic fingerprint factor and a GNSS factor are obtained through calculation, and a factor graph model is constructed; a sliding window optimization strategy is adopted, and only state nodes at a plurality of latest moments in the preliminary factor graph model are reserved for optimization; and applying the optimized factor graph model to obtain an optimal navigation track. According to the method, the positioning precision and robustness in a complex environment are improved. The problems that a traditional PDR system is prone to being influenced by single-step abnormal estimation, magnetic fingerprint positioning is prone to being influenced by local magnetic interference, and GNSS positioning is poor in stability in an occlusion area are solved.

The invention discloses a DTW-based pedestrian navigation method and device and a storage medium, and relates to the technical field of pedestrian navigation, and the technical scheme is characterized in that the method comprises the following steps: S1, obtaining triaxial accelerometer data of an inertial sensor, carrying out secondary processing on the triaxial accelerometer data, and regenerating a new modulus value of a triaxial accelerometer by using an exponential function; s2, performing matching item construction on the regenerated new module value of the triaxial accelerometer by using a DTW algorithm, and performing zero-speed state detection in a gait cycle; and S3, performing position recursion of pedestrian navigation by using a Kalman filter according to a zero-speed state detection result in the gait cycle. According to the invention, the adaptability and flexibility of navigation are improved, the cost is reduced, and more accurate pedestrian navigation is realized.

The present invention claims protection for a three-dimensional indoor positioning method that uses ranging information to assist zero-velocity correction and altitude calculation, mainly including the following steps: (1) According to the distance between the foot and the ground output by the ranging information sensor, incorporate this distance into the data output by the inertial measurement unit to divide the gait intervals and perform zero-velocity correction; (2) When walking on a flat surface, the ranging data changes continuously in distance, while it exhibits jumps when going up and down stairs. Utilize this characteristic to identify the gait of going up and down stairs. The difference before and after the ranging jump is the height of one step; (3) Three types of information can be obtained from the ranging data: the height of the shoe from the ground, the vertical velocity of the shoe, and height information such as steps, stairs, and floors. Design a Kalman filter using these three states to perform altitude calculation, and finally obtain the pedestrian's height information to achieve high-precision three-dimensional indoor positioning of the pedestrian. The present invention not only assists zero-velocity correction to improve the horizontal positioning accuracy of pedestrian navigation, but also performs altitude calculation to improve the vertical positioning accuracy.

The invention provides a progressive optimization pedestrian enhanced autonomous navigation system based on sparse reference information. The navigation enhancement model construction module is used for carrying out frequency reduction representation on high-frequency navigation information output by the integrated navigation system to obtain navigation position representation based on two-dimensional vector mileage; according to error characteristics of direction and distance increment in the two-dimensional vector mileage, establishing a progressive pedestrian navigation enhancement model, and outputting enhanced autonomous navigation information; the abnormality diagnosis module performs abnormality diagnosis on the external position reference information; in the normal stage of the external position reference information, the enhanced navigation module carries out parameter identification and online updating on the pedestrian navigation enhanced model; and in the abnormal stage, a parameter identification process is not carried out, and enhanced navigation output is obtained by directly using the current pedestrian navigation enhancement model. According to the invention, the positioning precision can be improved.

The invention provides a traffic pedestrian navigation method and system based on multi-source information fusion, and relates to the technical field of navigation and positioning. Inputting the traffic scene multi-source information and the pedestrian historical movement data into a pedestrian intention prediction model, and estimating the potential destination or path selection tendency of the pedestrian; based on a pedestrian intention prediction result, dynamically distributing and adaptively adjusting a fusion weight of each piece of multi-source information through a fuzzy evaluation model, and carrying out fusion processing on the multi-source information by utilizing the adjusted fusion weight to generate comprehensive navigation data; and inputting the integrated navigation data and the pedestrian intention prediction result into a path planning model based on reinforcement learning to generate a personalized navigation path. According to the invention, by introducing a pedestrian intention prediction mechanism, the dynamic optimization of the multi-source information fusion weight is realized, and the accuracy and adaptability of pedestrian navigation in a complex urban environment are effectively improved.