188 results about "Navigation model" patented technology

A query server of a mobile search engine system for searching content items accessible online, is arranged to send at least a first screenview of search results (63) to a browser of a mobile device (10), and send instructions (69, 74) in a scripting language to the browser for a background process to fetch further search results to the mobile device for presentation later. The further search results can then be viewed as desired without the need for a further round trip delay across the wireless network. The user can be presented with a simpler navigation model. The first screenview can be sent in the form of a page formatting template, and results data. The formatting information can be reused for other results, to reduce formatting overhead in the downloads. The instructions can also be used for showing information while waiting for downloads, or downloading information during entry of search queries.

A method of processing vehicle navigation information for use in autonomous vehicle navigation is provided. The method includes receiving, by a server, navigation information from a plurality of vehicles. The navigation information from the plurality of vehicles is associated with a common road segment. The method also includes storing, by the server, the navigation information associated with the common road segment. The method also includes generating, by the server, at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information from the plurality of vehicles. The method further includes distributing, by the server, the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating the one or more autonomous vehicles along the common road segment.

The invention discloses a GPSINS combination navigation method and system utilizing a neural network algorithm to realize compensation and correction. The method comprises steps that a combination navigation model based on a GPS and an inertial navigation module is constructed, a Kalman filter is designed to filter combination navigation data of the combination navigation model, and navigation error data of the inertial navigation module is outputted; in a normal GPS signal state, inertial navigation data is taken as input data of a training sample of a neural network model, output data of the navigation data after filtered by the Kalman filter is taken as output data of a training sample of a neural network module, and the neural network model is trained; in a GPS signal loss state, the trained neural network model is utilized to predict an output error of the inertial navigation module, and the predicted output error is further utilized to compensate and correct inertial navigation. The method is advantaged in that the GPSINS combination navigation model is compensated and corrected through utilizing the neural network algorithm, and the inertial navigation system is assisted by the neural network algorithm to output the accurate navigation data in the GPS signal loss state.

Systems and methods are provided for distributing a crowdsourced sparse map for autonomous vehicle navigation. In one implementation, a method of generating a road navigation model for use in autonomous vehicle navigation may include receiving navigation information associated with a common road segment from a plurality of vehicles; storing the navigation information associated with the common road segment; generating at least a portion of an autonomous vehicle road navigation model for the common road segment based on the navigation information; and distributing the autonomous vehicle road navigation model to one or more autonomous vehicles for use in autonomously navigating along the common road segment. The autonomous vehicle road navigation model may include at least one line representation of a road surface feature extending along the common road segment, and each line representation may representing a path along the common road segment substantially corresponding with the road surface feature.

Systems and methods are provided for anonymizing navigation data and generating an autonomous vehicle road navigation model with the anonymized data. A navigation system may receive data relating to a road section from a vehicle. The system may determine one or more motion representations associated with the vehicle and one or more road characteristics associated with the road section. The system may assemble navigation information relative to a first portion and relative to a second portion of the road section. The first and second portions may be spatially separated by a third portion. The system may transmit the navigation information relating to the first and second portions and forego transmitting information relating to the third portion. A server may receive the transmitted navigation information and assemble an autonomous vehicle road navigation model. The server may transmit the navigation model to one or more vehicles for use in autonomous navigation.

The invention discloses a tightly coupled INS/UWB integrated navigation system and method adopting fixed-interval CRTS smoothing. The navigation system comprises an inertial navigation system (INS), a UWB radio tag, UWB wireless reference nodes, a reference system and a data processing system, wherein the inertial navigation system (INS) and the UWB radio tag are arranged on shoes of a pedestrian; the UWB wireless reference nodes and the reference system are arranged at a set position; the inertial navigation system (INS), the UWB radio tag and the reference system are connected with the data processing system respectively; the data processing system comprises a local data fusion filter, a Cubature Kalman Filter (CKF), a pseudo-distance data processing module, an RTS smoothing module and an average filtering module. The tightly coupled INS/UWB integrated navigation system and method has the benefits that the possibility of introducing truncation errors due to omitting of higher terms of Taylor expansion in a conventional tightly coupled integrated navigation model is effectively decreased.

The invention relates to the field of GIS (Geographic Information System) three-dimensional visualization, and in particular relates to a three-dimensional visualized indoor navigation method oriented to a large shopping center. The method comprises the following steps of: carrying out extraction and classification on navigation elements, network structure elements and geometric elements of the shopping center from the perspective of function and visualization according to the characteristics of geographical elements in the existing large shopping centers, wherein similar elements are subjected to a same detail level grade description; and constructing a data model and a network structure according to the elements obtained through extraction and classification, and based on the data model and the network structure, carrying out indoor navigation based on three-dimensional visualization. According to the method, the achievements in the aspects of building the expression model of indoor three-dimensional navigation geographic elements, indoor three-dimensional navigation data logical models, indoor three-dimensional navigation models and the like not only create a novel LBS (Location Based Service) application mode, but also enrich the connotation of the indoor navigation technology, thereby providing a beneficial reference for the indoor three-dimensional navigation application of large shopping centers.

An electric vehicle rapid charging demand scheduling method based on load space transfer comprises the steps of dynamically selecting a path of an urban road network and sequentially establishing a road section dynamic travel time model and a dynamic path selection model; establishing a charging navigation scheme considering the congestion degree of the charging station, wherein a user charging navigation model, a charging station group service capability optimization model and a charging selection model considering vehicle decision dynamic evolution are sequentially established; and establishing an ordered rapid charging strategy based on the interaction between the charging station and the electric vehicle, including formulating the cost of the charging station and establishing a master-slave game model of the charging station and the electric vehicle. Factors such as interaction influence of multi-vehicle charging selection and non-uniform facility utilization rate of the urban fastcharging station are considered in the electric vehicle fast charging demand scheduling process; the interactive influence of charging station selection and path selection between vehicles and the interactive game strategy between stations and vehicles are fully considered, and a more scientific and effective scheduling scheme can be provided for quick charging of electric vehicles.

The embodiment of the invention discloses a semi-physical test method and system for an aircraft avionics system. The system comprises: a test management subsystem for managing test projects, models and data through preset test management; a real-time simulation subsystem performing real-time simulation calculation on n aircraft avionics system and states of the subsystems of an aircraft; and a signal acquisition and output subsystem which is used for data interaction between a simulation system and real airborne equipment, wherein the airborne equipment is real airborne equipment, simulationexcitation equipment is avionics equipment operation environment simulation equipment, and the real-time simulation subsystem comprises an aerodynamic model, a kinetic model, an undercarriage model, amass characteristic model, a motion equation, an atmospheric data model, a GPS model and an inertial navigation model. According to the embodiment of the invention, through closed-loop crosslinking of testing environments of hardware system excitation, the real-time simulation system and the real airborne equipment, various effective ways are provided for the aircraft avionics system testing, andthe invention is close to an external field test.

The invention relates to a GPS/INS integrated navigation method based on unscented Kalman filtering. The method is mainly characterized in that the method comprises the following steps that INS data and corresponding GPS data are combined together, and an unscented Kalman filtering method is adopted to build a GPS/INS integrated navigation model to obtain the online optimal value of a GPS; the INS data are used as training data and are combined with the online optimal value of the GPS as a training target to build an SVM regression model, and the SVM regression model is used for predicting the off-line navigation data of the GPS. According to the method, the precision of the GPS is usually combined with the reliability of an inertial navigation system to achieve the information fusion of the filtering, the GPS and an INS, and when the GPS and the INS are used together, a precise filtering result can be obtained; an SVM is adopted to train INS data obtained when GPS signals are lost, the parameters of a kernel function and a penalty function in an SVM algorithm are optimized through a simulated annealing algorithm, and the precision of the off-line GPS is kept close to that of the online GPS.

The invention discloses an SLAM method based on a rodent model and an RTAB-Map closed-loop detection algorithm. Spatial positioning can be performed by means of hippocampal neurons of the rodent model. A new bionic navigation model is constructed according to an existing closed-loop detection RTAB-MAP algorithm. On the condition that high real-time performance of the system is ensured, correction of a long-term accumulated error in a macroenvironment can be realized, and furthermore low navigation stability caused by indoor light change to a certain extent.

The invention relates to a deep space explorer acquisition phase celestial navigation method based on target object ephemeris correction. According to the method, firstly, a Martian explorer state model, a startlight angle navigation sub system measuring model and an X-ray pulsar navigation sub system measuring model are built; then, the startlight angle and the X-ray pulsar quantity measurements are respectively obtained; filtering estimation is performed to obtain the position and the speed of a detector in a heliocentric inertia coordinate system and a target object center inertia coordinate system; on the basis, a state model and a measuring model of target object ephemeris error are built; the quantity measurement about the target object ephemeris error is obtained through estimation state vectors of the startlight angle navigation sub system and the X-ray pulsar navigation sub system; a Kalman filtering method is used for estimating the target object ephemeris error; the target object ephemeris error is fed back into a navigation system model; the position of a target object in the navigation model is corrected. The deep space explorer acquisition phase celestial navigation method belongs to the technical field of aerospace navigation, can be used for estimating the object ephemeris error and correcting the model error of the navigation system on line, and is applicable to the explorer acquisition phase.

A system for mapping a lane mark for use in autonomous vehicle navigation is provided. The system includes at least one processor programmed to: receive two or more location identifiers associated with a detected lane mark; associate the detected lane mark with a corresponding road segment; update an autonomous vehicle road navigation model relative to the corresponding road segment based on the two or more location identifiers associated with the detected lane mark; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

The invention provides a method and a device for intercepting a navigation model. The navigation model interception device comprises a launching device, an interception net and a launching missile, wherein steel corners of the interception net is connected with the launching missile, the interception net can be launched along with the launching missile and expanded, so that the targeted navigation model can be captured by the interception net. The method and the device fill up the blank of the navigation model interception method and device in the prior art, and the device is simple and easy to operate.

Systems and methods are disclosed for mapping lanes for use in vehicle navigation. In one implementation, at least one processing device may be programmed to receive navigational information from a first vehicle and a second vehicle that have navigated along a road segment including a lane split feature; receive at least one image associated with the road segment; determine, from the first navigational information, a first actual trajectory of the first vehicle and a second actual trajectory of the second vehicle; determine a divergence between the first actual trajectory and the second actual trajectory; determine, based on analysis of the at least one image, that the divergence between the first actual trajectory and the second actual trajectory is indicative of the lane split feature; and update a vehicle road navigation model to include a first target trajectory and a second target trajectory that branches from the first target trajectory after the lane split feature.

Methods and systems for navigating a mobile robot through a crowded pedestrian environment by selecting and following a particular pedestrian are described herein. In one aspect, a navigation model directs a mobile robot to follow a pedestrian based on the position and velocity of nearby pedestrians and the current and desired positions of the mobile robot in the service environment. The mobile robot advances toward its desired destination by following the selected pedestrian. By repeatedly sampling the positions and velocities of nearby pedestrians and the current location, the navigation model directs the mobile robot toward the endpoint location. In some examples, the mobile robot selects and follows a sequence of different pedestrians to navigate to the desired endpoint location. In a further aspect, the navigation model determines whether following a particular pedestrian will lead to a collision with another pedestrian. If so, the navigation model selects another pedestrian to follow.