CN106017473B - A kind of indoor social navigation system - Google Patents
A kind of indoor social navigation system Download PDFInfo
- Publication number
- CN106017473B CN106017473B CN201610338026.6A CN201610338026A CN106017473B CN 106017473 B CN106017473 B CN 106017473B CN 201610338026 A CN201610338026 A CN 201610338026A CN 106017473 B CN106017473 B CN 106017473B
- Authority
- CN
- China
- Prior art keywords
- location
- terminal
- node
- model
- server
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
- G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Navigation (AREA)
Abstract
The present invention provides a kind of indoor social navigation system, the system comprises: location-server, the second alignment sensor data that the location-server is used to receive the first alignment sensor data of terminal transmission and target good friend's terminal is sent, the first geometric coordinate that the terminal is calculated according to the first alignment sensor data calculates the second geometric coordinate of the target terminal according to the second alignment sensor data；And first geometric coordinate and second geometric coordinate are stored in location database；Location server constructs interior space topological network for obtaining interior space model data；The navigation requests that the terminal is sent are received, determine geometric coordinate to location-server acquisition first geometric coordinate and described second according to the navigation requests；Optimal guidance path is calculated in the interior space topological network using path search algorithm.
Description
Technical field
The invention belongs to indoor location service technology field more particularly to a kind of indoor social navigation system.
Background technique
With the development of mobile Internet and location aware technology, location-based mobile social networking service is raw for people
Work brings many convenience.Mobile social networking is extended to reality by position attribution therein, reduces virtual world and line on line
The gap of lower real world, improves the service effectiveness of social networks, and people can be registered (check-in) with position, be shared each other
Multimedia content (geo-tagging content) with location tags etc.；Meanwhile user may be based on the space pass of position
Connection expands social relationships.
Currently, the location information in location-based mobile social networking mainly pass through global positioning system (GPS,
Global Position System), mobile base station, the positioning methods such as Wi-Fi obtain, the corresponding precision that services is arrived at 10 meters
100 meters are differed, and location-based mobile social networking service precision is in building building rank mostly.And due to being averaged everyone
Up to 90% time is in interior daily, and people, which service indoor location, also to be had between great demand, such as good friend
Indoor navigation.But the location information in mobile social networking and service relevant to position be not fine in the prior art
Change the functional space to indoor more floors, and location-based mobile social networking service belongs to the quiet of user's on-demand mostly
State service lacks the real-time actively updated, causes accurately plan guidance path in real time when social navigation indoors.
Based on this, a kind of social navigation system in the interior with high-precision, strong real-time is needed at present.
Summary of the invention
In view of the problems of the existing technology and the deficiency of application, the embodiment of the invention provides a kind of indoor social navigation
System, for solve indoor social connections navigation in the prior art seek friendly function cannot in real time, plan to dynamic, accuracy and lead
The technical issues of bit path.
The present invention provides a kind of indoor social navigation system, the system comprises:
Location-server, the first alignment sensor data and target good friend's terminal for receiving terminal transmission send the
Two alignment sensor data calculate the first geometric coordinate of the terminal according to the first alignment sensor data, according to institute
State the second geometric coordinate that the second alignment sensor data calculate the target terminal；And by first geometric coordinate and described
Second geometric coordinate is stored in location database；
Location server constructs indoor for obtaining indoor location model data according to the interior space position data
The space topological network of each level of position model；
The navigation requests that the terminal is sent are received, obtain described the to the location-server according to the navigation requests
One geometric coordinate and second geometric coordinate, and calculated in the space topological network using path search algorithm optimal
Guidance path.
In above scheme, the space topological network of each level of indoor location model includes: fine granularity level AEGVG
Figure, outlet level illustraton of model and position level illustraton of model.
In above scheme, the location server constructs the thin of indoor location model according to the interior space position data
Granularity level AEGVG figure specifically includes:
One-dimensional skeleton is extracted according to indoor floor plan, forms the one-dimensional Voronoi diagram in interior space elongated zones；
The open area is subjected to grid dividing with default side length and forms grid chart, the grid chart is added to described
In Voronoi diagram；
Sampling node is carried out by the sampling interval of the average step length of pedestrian, generates the AEGVG figure.
In above scheme, the location server constructs going out for indoor location model according to the interior space position data
Mouth hierarchical model figure specifically includes:
The Egress node of the coarser grained layers is determined according to the outlet port in the fine granularity layer AEGVG figure；
The outlet level illustraton of model is constructed using the reachable path between adjacent position as side.
In above scheme, the location server constructs the position of indoor location model according to the interior space position data
Hierarchical model figure is set to specifically include:
The nodes of locations of the coarser grained layers is determined according to the character position in the fine granularity layer AEGVG figure；
The position level illustraton of model is generated according to the adjoining between the nodes of locations, connected relation.
In above scheme, the location-server is used to calculate the terminal according to the first alignment sensor data
First geometric coordinate, specifically includes:
When the location-server detects the anchor point signal in the first alignment sensor data, the anchor point is believed
Number carrying out fingerprint matching with location fingerprint database determines the initial position of the terminal；
The anchor point signal is detected with preset period timing again, if detecting the anchor point signal, utilizes particle filter
Fusion location algorithm fusion pedestrian's dead reckoning PDR method, the anchor point signal and interior space information determine the terminal
First geometric coordinate.
In above scheme, after the space topological network of location server building each level of indoor location model,
Specifically it is also used to:
Receive the impact factor in every bar navigation path in the space topological network；
Each impact factor is received to the weighing factor of current navigation path；
The synthesis weight of each path is calculated according to the weighing factor.
In above scheme, the impact factor is specifically included: indoor pedestrian's reach distance, up to the time, density of personnel and
Road width.
In above scheme, interior pedestrian's reach distance is by formula
It is calculated；Wherein, the OiFor the corresponding first movement object of the terminal；The OjIt is corresponding for the target good friend terminal
The second mobile object；(the xx,yk) it is first movement object O described in distance in fine granularity layeriNearest node nkSeat
Mark；The m is integer.
In above scheme, the evaluation function of the path search algorithm are as follows: f (n)=g (n)+h (n)；Wherein, the f (n)
It is start node via the evaluation function of node n to destination node；The g (n) is start node described in state space to section
The actual cost of point n；The h (n) is actual cost of the node n to the best guidance path of the destination node.
The present invention provides a kind of indoor social navigation system, the system comprises: location-server, the positioning service
The second alignment sensor data that device is used to receive the first alignment sensor data of terminal transmission and target good friend's terminal is sent,
The first geometric coordinate that the terminal is calculated according to the first alignment sensor data, according to the second alignment sensor number
According to the second geometric coordinate for calculating the target terminal；And first geometric coordinate and second geometric coordinate are stored in
In location database；Location server constructs interior space topological network for obtaining interior space model data；Receive institute
The navigation requests for stating terminal transmission obtain first geometric coordinate and institute to the location-server according to the navigation requests
State the second geometric coordinate；Optimal guidance path is calculated in the interior space topological network using path search algorithm；In this way,
The location server can obtain the geometric coordinate of navigation both sides from location-server；Construct each layer of interior space position model
Secondary topological network, and geometric coordinate mapped in the fine granularity layer of the spatial position model, it determines every in topological network
The impact factor in bar navigation path, each impact factor calculate every road according to weighing factor to the weighing factor of guidance path
The synthesis weight of diameter determines optimal guidance path according to comprehensive weight；It thus can in real time, dynamically, accurately plan navigation road
Diameter.
Detailed description of the invention
Fig. 1 is the overall structure diagram for the indoor navigation system that the embodiment of the present invention one provides；
Fig. 2 is the interior space position model HiSeLoMo frame construction drawing that the embodiment of the present invention one provides；
Fig. 3 is the one-dimensional skeleton drawing for the indoor plane figure that the embodiment of the present invention one provides；
The fine granularity layer AEGVG figure that Fig. 4 is the HiSeLoMo that the embodiment of the present invention one provides；
Position level position model schematic diagram in the coarser grained layers that Fig. 5 provides for the embodiment of the present invention one；
Fig. 6 is the coarser grained layers middle outlet hierarchical position model schematic that the embodiment of the present invention one provides；
Fig. 7 is the mobile object dynamic relationship of topology schematic diagram that the embodiment of the present invention one provides；
Fig. 8 is the interior space position model HiSeLoMo interlayer relation schematic diagram that the embodiment of the present invention one provides
Attribute Association relationship between each layer of interior space position model HiSeLoMo that Fig. 9 provides for the embodiment of the present invention one
Schematic diagram.
Specific embodiment
In order in real time, dynamic, accuracy plan the guidance path under indoor environment between good friend, the present invention is provided
A kind of indoor social navigation system, the system comprises: location-server, the location-server is for receiving terminal transmission
The first alignment sensor data and target good friend's terminal send the second alignment sensor data, according to it is described first positioning pass
Sensor data calculate the first geometric coordinate of the terminal, calculate the target terminal according to the second alignment sensor data
The second geometric coordinate；And first geometric coordinate and second geometric coordinate are stored in location database；Position
Server constructs interior space topological network for obtaining interior space model data；According to the navigation requests to described fixed
Position server obtains first geometric coordinate and second geometric coordinate；Using path search algorithm in the interior space
Optimal guidance path is calculated in topological network.
Technical solution of the present invention is described in further detail below by drawings and the specific embodiments.
Embodiment one
The present embodiment provides a kind of indoor social navigation system, as shown in Figure 1, the system comprises: terminal 1, target are good
Friendly terminal 2, location-server 3, location server 4, social application server 5；Wherein,
Before the terminal 1 is wanted to carry out good friend's real-time navigation function, the location server 4 is for calculating the terminal
The distance between 1 and each good friend's terminal；The social application server 5 is also used to according to the far and near that the good friend is whole of distance
End is shown on the interface of the terminal 1 (with tabular form).
Here, for example the terminal 1 selects to send navigation requests to target good friend terminal 2, and the navigation requests are permitted
Can after, the navigation requests are forwarded to the location server 4 by the terminal 1.
After the navigation requests obtain the license of the target good friend terminal 2, the location-server 3 is used for first
The preset period receives second that the first alignment sensor data that the terminal 1 is sent and the target good friend terminal 2 are sent
Alignment sensor data, to calculate the first real-time geometric coordinate and second of the terminal 1 and the target good friend terminal 2 in real time
Geometric coordinate.Wherein, the described first preset period was 1HZ.
Specifically, when the location-server 3 determines the first of the terminal 1 according to the first alignment sensor data
When geometric coordinate, it is first determined whether the anchor point signal in the first alignment sensor data is detected, if detecting that anchor point is believed
Number when, according to the received signal strength indication of the anchor point signal, using arest neighbors matching algorithm by the anchor point signal and position
Fingerprint database carries out location fingerprint matching, calculate between signal strength indication and each finger print data of location fingerprint database away from
From the corresponding finger print data of minimum range therefrom being chosen, using the geometric coordinate representated by it as the initial bit of the terminal 1
It sets；If anchor point signal is not detected, the blind area point of GPS/ base station signal, the terminal 1 are successively selected according to priority
Alignment sensor data are presented the characteristic point of special state and interact that (two dimensional code is swept in map reconnaissance with the terminal 1
Deng) mode determine initial position.Wherein, the characteristic point of the special state is that the variation of the alignment sensor data is big
Data when preset threshold.
Here, after location-server 3 determines the initial position of terminal 1, initial position data is stored to positional number
According in library.Wherein, the signal strength indication is provided by the WiFi/ Bluetooth signal receiving module measurement of the terminal 1；It is described
First alignment sensor data may include: acceleration, angular speed and direction；The anchor point signal may include: Wi-Fi signal
Or Bluetooth signal.
After location-server 3 determines the initial position of terminal 1, pedestrian's dead reckoning (PDR, Pedestrain are utilized
Dead Reckoning) method carries out the real-time geometric coordinate of terminal 1, while being believed with the second preset period timing detection anchor point
Number, utilize characteristic point, the interior space information (indoor map) and first of particle filter fusion location algorithm fusion anchor point signal
The multi-source informations such as the characteristic point of alignment sensor data, further to correct the positioning accumulated error during PDR method, thus
Determine the real-time geometric coordinate of the terminal 1.Wherein, the described second preset period can depending on the configuration of terminal 1, one
As be set as 10~20HZ, it is preferable that be 11HZ, 12HZ, 15HZ, 18HZ or 19HZ；The characteristic point of the anchor point signal is institute
State anchor point signal strength indication when anchor point signal mutates.The indoor map includes: the Interior Spaces such as wall, room, corridor, door
Between elements position and its structure.
Specifically, the location-server 3 utilizes particle filter fusion location algorithm PDR method, anchor point signal and interior
The multi-source informations such as spatial information determine that the first real-time geometric coordinate of the terminal 1 specifically includes:
The state vector for holding the mobile target object to be positioned of terminal 1 is denoted as X by the location-server 3i=(xi,
yi,αi)T, i=1,2 ..., N, wherein (xi,yi) indicates coordinate, aiFor the parameter of Weinberg step-length model.Then, particle is filtered
Wave merges shown in the sensor model such as formula (1) of location algorithm, shown in motion model such as formula (2):
Wherein, in formula (1), akFor the acceleration of kth step, the acceleration akIt can be measured by the acceleration in terminal 1
It measures out；θk' it is the direction that kth walks, the direction can be obtained by the lining of terminal 1,For kth step angular speed,
The angular speedIt can be obtained by the gyroscope measurement in terminal 1；η indicates Gaussian random process.
Wherein, in formula (2),Be by parameter be aiWeinberg step-length model
It is calculated.The direction that i-th of particle is walked for kth, can be calculated by formula (4):
Wherein, in formula (4),The knot being calculated for Kalman filter according to compass and gyroscope measured value
Fruit.The specific calculating step of particle filter fusion location algorithm can be described as follows:
A) it initializes: calculating the initial position of target according to signal strength indication, mesh is determined according to the measured value of compass
Target direction.
B) it predicts: the state of k moment N number of particle is obtained according to the motion model of target
C) it weight computing: needs to recalculate weight there are two types of situation.The first situation, across wall or the particle of barrier
Weight is assigned to 0；Second situation, when encountering characteristic point, particle weights will be counted again according at a distance from characteristic point
It calculates, distance is closer, and weight is bigger.In the present invention, by assigning bigger weight, Ji Nengda to the closer particle of distance feature point
To the effect of amendment position error, while being also able to maintain good user experience.The calculation formula of weight is such as shown in (5).
Wherein, in formula (5),It is characterized coordinate a little, σ is corresponding standard deviation.
In addition, when there are when wireless signal (Wi-Fi, bluetooth), and location-server 3 is by resolving the terminal in environment
1 alignment sensor data capture characteristic point (characteristic point of some not distinguishing marks, such as earth magnetism present in finger ring border
Abnormal point and corner etc.), then the location information obtained to characteristic point and wireless fingerprint is weighted and averaged, and more new particle is weighed
Value；If only perceiving wireless signal, the location updating weight of wireless fingerprint acquisition is utilized；When only capturing characteristic point,
The position then generated based on characteristic point updates weight.Wherein, the wireless fingerprint is signal strength indication described above；Institute
Stating location information is real-time geometric coordinate；After calculating the weight of particle, need to carry out normalizing to weight according to formula (6)
Change processing:
Wherein, in formula (6),Indicate the weight of i-th of particle of k moment,Indicate the weight of all particles
The sum of.
D) state estimation: the probability distribution over states p of filtered mobile targetk(xk|y1:k) can approximate representation are as follows:
And it can thus be concluded that out position state estimation, as shown in formula (8):
E) resampling: the basic thought of resampling is the particle small with the big particle replacement weight of weight.When due to eliminating
Invalid particle and when leading to sample number deficiency, need to carry out resampling according to the information of previous moment, do not need at this time more
New Weinberg step-length model parameter ai。
F) it corrects.According to the measured value of each sensor, judge whether target reaches near characteristic point.If reaching certain
Region near a characteristic point, just according to the characteristic point to the position of target and towards being modified, circulation executes (b)-
(f)。
And when the location-server 3 does not detect the anchor point signal with the second preset period, then according to the PDR
Method determines the real-time geometric coordinate of terminal, specifically: the location-server 3 is determining the current geometric coordinate of user terminal
On the basis of, the walking event of user is captured, the step-length of pedestrian's walking is calculated according to accelerometer, pedestrian's direction is determined according to compass,
It is constrained by interior space information (indoor map), calculates user's next step position, and then determine the first of the terminal 1
Real-time geometric coordinate, when the location-server 3 detects the anchor point signal, to the end of pedestrian's dead reckoning method estimation
The real-time position information at end 1 is corrected, to reduce the accumulated error of pedestrian's dead reckoning PDR method.
Here, the location-server 3 determines the target good friend terminal 2 according to the second alignment sensor data
When the second geometric coordinate, identical with the method for the first geometric coordinate of terminal 1 is determined, details are not described herein.
Further, when the location-server 3 determines the first reality of the terminal 1 and the target good friend terminal 2
When geometric coordinate and the second real-time geometric coordinate after, the location server 4 is for obtaining interior space position model data, root
According to the space topological network of interior space position data building each level of indoor location model.
Specifically, the space topological network of each level of interior space position model includes: fine granularity level AEGVG
Figure, outlet level illustraton of model and position level illustraton of model.The location server 4 is constructed according to the interior space position data
The space topological network of each level of indoor location model specifically includes:
According to enclosed spatial characteristic and mobile target object motion feature, the interior is constructed based on indoor floor plan
The fine granularity layer AEGVG of spatial position model HiSeLoMo schemes, and determines the geometric coordinate of interior space object, character position, opens up
Flutter relationship and time-space relationship semantic information.Wherein, institute's semantic information can be with specifically: the connected relation in room and corridor, room
Between between proximity relations, mobile object the attributes such as geometric coordinate, character position (room number), function, space-time restriction.Its
In, the frame of the interior interior space position model HiSeLoMo is as shown in Figure 2.
Specifically, the fine granularity layer AEGVG figure of the HiSeLoMo includes: the one-dimensional Voronoi in interior space elongated zones
Figure and open area two dimension rule coverage grid chart.In general, interior space elongated zones are expressed by one-dimensional Voronoi diagram,
And open area is then expressed using grid chart.Wherein, when the width of interior space unit is less than or equal to certain value (such as 3m)
Region is known as elongated zones, such as corridor etc.；When the width of interior space unit is open greater than the region of certain value (such as 3m)
Region, such as hall etc..
Here, the fine granularity layer AEGVG map generalization of the HiSeLoMo specifically includes:
Firstly, extracting one-dimensional skeleton according to the indoor floor plan, Voronoi diagram, the one-dimensional skeleton are formed
As shown in Figure 3；Open area is subjected to grid dividing with default side length and forms grid chart, the grid chart is added to described
In Voronoi diagram；Sampling node is carried out by the sampling interval of the average step length of pedestrian, creates the AEGVG figure, the AEGVG
Figure is as shown in Figure 4.Wherein, sampling node is carried out using the average step length of pedestrian as side length, meets the motion feature of pedestrian, it can
The number of nodes in model is utmostly reduced, pedestrian's step-length is 1m or so.Simultaneously, it is contemplated that the step-length of people's walking is in 1m
Left and right.Therefore, open area is then divided with side length for the square net of 1m, constructs open area figure based on this
Model.
Here, the fine granularity layer AEGVG graph model of the HiSeLoMo can carry out formal definitions according to formula (9):
Gfine=(Vfine,Efine) (9)
In formula (9), Vfine={ vi, it is the set of the AEGVG figure interior joint；It is institute
State the set on side in AEGVG figure；Each edge is made of two nodes, by shown in formula (10).
E=(Vi,Vj) (10)
Wherein, each nodeEach node describes a certain discrete location of the interior space, and there is geometry to sit
The attributes such as mark, state, label；In general, the attribute information of the node can pass through < vid,xv,yv,cv,sv,lv,fv,bv> carry out table
Show.The vidIt is the number ID of the node；(the xv,yv) be node geometric coordinate；The cvFor the space of the node
Type, the cv∈{room,corridor,door,vertical,passage}；The svFor the physical state of the node,
The sv∈ { free, occpuied }, the lvFor the tag attributes of node, the fvFor floor identification locating for the node, institute
State bvFor the mark of building locating for the node.
Further, the side e ∈ Efine, expressing the connected relation of each node in AEGVG figure, the attribute on side is <
eid,vi,vj,fe,be,we>, wherein vi,vjIndicate two end nodes on side, feAnd beIndicate the character position attribute on side, i.e. side
Corresponding floor and building information.While there may be one-to-many subordinate relation, i.e., a line have passed through multiple functions
Space cell.The weThe weight for indicating side, usually using the Euclidean distance of two nodes as weighted value.
Secondly, building position hierarchical model；Specifically, coarseness is taken out on the basis of fine granularity layer AEGVG graph model
Position hierarchical model.Here, position level is by the organizational form of level a kind of, to express the topological relation between object
The semantic informations such as (such as adjacent, inclusion relation) and time-space relationship (time-space matrix, space-time restriction).In general, position is divided into three
Major class: room (Room), vertical lift space (Vertical Passage), including stair, elevator etc.；Corridor
(Corridor).Here level refer to the adjoining between position up to ordinal relation, such as: successively passing through from some entry position
Which adjoining position, child node of these adjoining positions as entry position in hierarchy chart；Sky either between position
Between inclusion relation, such as: certain floor include which position, child node of these positions as hierarchy chart.
AEGVG graph model based on fine granularity layer will have same label attribute lvNode aggregation be a sign bit
It sets.The nodes of locations of the coarser grained layers is determined according to the character position；After the nodes of locations formed in coarser grained layers,
According to the adjoining between nodes of locations, connected relation, so that it may form complete position hierarchical model in coarser grained layers.Position level
For model usually with node on behalf character position, side indicates the hierarchical graph model of position adjoining or inclusion relation, can be such as formula
(11) shown in.
Gloc=(Vloc,Eloc) (11)
In formula (11), Vloc={ vi, indicate the set of all character positions；Indicate AEGVG
The set of position adjoining or inclusion relation in figure；Each edge eloc=(vi,vj∈Eioc).Meanwhile each character position vi=<
locid,cloc,lloc,floc,bloc, adj_loc >, the locidFor the number of abstract position space, clocFor abstract position space
Classification, the cloc∈ { room, corridor, vertical passage }, llocIndicate the symbol language of abstract position space
Adopted information；flocIndicate floor locating for abstract position space；blocIndicate the building of abstract position space；MeanwhileIt is all location sets that there are neighbouring relations with notional position.
In practice, by taking certain engineering Lou Silou as an example, abstract forming position node is carried out to four buildings fine granularity floor AEGVG figures,
As shown in figure 5, room location is indicated with circular node, vertical lift spatial position is indicated that corridor is then by triangle by square nodes
Shape node indicates.For example, vertical space VP2 in fine granularity layer, the fine granularity node difference in the section HW4 and room RM12 of corridor
Nodes of locations VP2, HW4 and the RM12 being abstracted into coarser grained layers.After the nodes of locations formed in coarser grained layers, according to position
Set the relationship between node, forming position level, as shown in the lower left Fig. 5.Such as nodes of locations VP2 and corridor section node HW4
It is connected, HW4 is connected with corridor node HW5, and HW5 is connected or abuts with nodes of locations such as RM14, HW6.Pass through position
Adjoining, connected relation between node, so that it may form complete position hierarchical model in coarser grained layers.
Then, the Egress node of the coarser grained layers is determined according to the outlet port in the fine granularity layer AEGVG figure；It will
Reachable path between adjacent position constructs the outlet hierarchical model as side.
Specifically, in conjunction with the position hierarchical model of HiSeLoMo coarser grained layers, in order to support coarseness position spacing
It is expressed from topology, the outlet hierarchical model of coarseness is taken out on the basis of fine granularity layer model.Here, outlet level passes through
A kind of organizational form of level, express outlet port between topological relation (such as connected relation, ordinal relation), distance, constraint
Etc. semantic informations.Wherein, outlet refers to two tie points up to locational space in communication chamber, including practical outlet and virtual outlet
Two classes.Practical outlet is the reachable entrance of two spaces unit, usually room door；And virtually exporting is according to subspace list
Connected relation between member and artificially defined entrance in structure and are not present indoors.One outlet can only be connected to two
Locational space, a space cell may include multiple outlets, and outlet is to connect the unique channel of different spaces unit.And level is then
It points out the connected relation (such as some outlet port has been connected to two spaces position) between mouth, or points to up to certain outlet port mistake
Pass through the ordinal relation of outlet in journey (as reached the sequence pass that some position exports passed through outlet from certain floor exit
System).
Outlet level corresponds to the Egress node set being connected between different spaces unit in fine granularity layer, and the set is according to thin
The category attribute c in space in granularity layers AEGVG modelvIt is obtained for the Node extraction of outlet.Egress node is according to the adjoining in space
Relationship (arrival sequence) forms hierarchical structure, and wherein top-most node indicates entry into the entrance in the space, down from top mode,
The node of different layers indicates reachable hierarchical sequence relationship.As shown in fig. 6, the region VP2 is corresponding in certain engineering Lou Silou plan view
Egress node DR57 be top mode, reach DR55 and DR20 two outlets, therefore two Egress nodes of DR55 and DR20
Child node as DR57.
By the way that position outlet to be abstracted as to the Egress node of coarseness, the reachable path between adjacent position is as side, structure
Build outlet hierarchical model.The outlet hierarchical model can be indicated by formula (12).
Gexit=(Vexit,Eexit) (12)
In formula (12), Vexit={ viBe all outlet ports node set, the Egress node can be by formula (13)
It indicates.
vi=< exid,lex,loci,locj,parentex> (13)
In formula (13), exidThe number for indicating Egress node, the node serial number for being door with fine granularity sheaf space type
It is consistent, lexIndicate the semantic locations information of Egress node, the functional attributes in the space as represented by node.Outlet port is usual
It is connected to the position of two connections, the position of two connections passes through (loci,locj) indicate.lociAnd locjRespectively correspond position
Two positions in level, described two positions refer to any two node in the level of position.The parentexIndicate Egress node
Father node number in outlet hierarchical tree structure,And Eexit=Vexit×VexitIt is all reachable paths
Set, each path can be indicated by formula (14):
eexit=vi×vi (14)
Wherein, eexit∈Eexit。
Further, the mobile object layer model of the interior space position model HiSeLoMo is constructed.Specifically, because
In mobile computing environment, there are a large amount of mobile object (such as personnel, mobile asset).It for convenience, can be by the shifting
Dynamic object is expressed as<MovingObjID, (x, y, t), and objsemantic>；Wherein,
The MovingObjID is the number of the mobile object, and (x, the y, t) is the geometry of t moment mobile object
Coordinate, the objsemantic are the semantic information of mobile object.
Here, if ∑ objsemantic={ ∑ person ∪ Σ asset },
Then objsemantic ∈ Σ objsemantic={ person_id, asset_id }.
In order to simplify the dynamic relationship of topology between mobile object, the topological diagram G based on HiSeLoMo fine granularity layerfine,
The topological relation of mobile object MovingObject t at a certain moment is mapped to the topological diagram G of fine granularity layerfine-sub, such as Fig. 7 institute
Show.Specific expression way are as follows: according to the position (x, y) of mobile object MovingObject t at a certain moment, in fine granularity
Etale topology figure GfineThe middle inquiry node NearestNode nearest apart from the position；The mobile object MovingObject exists
The topological relation of moment t is the fine granularity etale topology subgraph G being represented by where NearestNodefine-sub.Wherein,Then MovingObjecti,tWith NaerestNodeiPhase mapping, mapping relations can be indicated by formula (15).
f:MovingObjecti,t→NearestNodei (15)
Finally, determining the interlayer relation of the interior space position model HiSeLoMo.
Specifically, position hierarchical model can polymerize from fine granularity layer and obtain in coarser grained layers, and outlet hierarchical model can be from
It exports to come in fine granularity layer, can also mutually export and between position level and outlet layer time, as shown in Figure 8.Out due to one
Mouthful be connected to two adjacent spaces, contained in position level and outlet level it is this be connected to or proximity relations, so out
It can mutually be exported between mouth layer and site layer.Relation on attributes such as Fig. 9 institute in fine granularity layer and position level and outlet level
Show, the attribute of node, side in outlet layer and site layer is all to export to come from fine granularity layer.
Further, after the location server 4 builds the space topological network of each level of indoor location model,
Specifically it is also used to the impact factor in every bar navigation path in reception space topological network figure；Each impact factor is received to working as
The weighing factor of preceding guidance path；The synthesis weight of each path is calculated according to the weighing factor.Wherein, the impact factor
It specifically includes: indoor pedestrian's reach distance, reachable time, density of personnel and road width.
Specifically, mainly optimal guidance path is carried out using indoor pedestrian's reach distance as impact factor in the present embodiment
It calculates, therefore, the reach distance of indoor road is the weight in path, then the room based on constructed indoor location model
One skilled in the art's reach distance can be calculated by formula (16):
Wherein, in formula (16), the IOD (Oi, Oj) it is indoor pedestrian's reach distance；The OiIt is right for the terminal 1
The first movement object answered；The OjFor corresponding second mobile object of the target good friend terminal 2；(the xx,yk) it is particulate
Spend first movement object O described in distance in layeriNearest node nkCoordinate；The m is integer.
Here, the same of the space topological network of each level of indoor location model is constructed in the location server 4
When, Xiang Suoshu location-server 3 obtains the first real-time geometric coordinate and second of the terminal 1 and the target good friend terminal 2
Real-time geometric coordinate calculates optimal guidance path in the space topological network using path search algorithm, wherein described
Optimal guidance path is the shortest path of indoor pedestrian's reach distance, the evaluation function of the path search algorithm are as follows: f (n)
=g (n)+h (n)；Wherein, the f (n) is evaluation function of the start node via node n to destination node；The g (n) is shape
Actual cost of the start node described in state space to node n；The h (n) is that node n most preferably navigates road to the destination node
The actual cost of diameter.It is using node n to the Euclidean distance between the destination node as weighted value, path in the present embodiment
Specific step is as follows for search:
(1) in real time by described in the described first real-time geometric coordinate of the terminal 1 for two sides of navigating and target good friend terminal 2 second
The geometry left side is mapped to the fine granularity layer node in the indoor location model, and start node and goal node are all respectively vstart
And vgoal。
(2) by the start node vstart(the f value and g value of the open list are all 0) is put into open list OPEN.
(3) in vstartLocation unitary space locstartStart Path extension search, searching in OPEN has most
The node of small value, and using the node found as current node.
(4) current node is deleted from OPEN, closing list CLOSE is added in current node.
(5) each node adjacent to current node successively executes step (6)-(8), as goal node vgoalIt is added into
When to open list as node to be tested, expression has searched path, at this time end loop；Or work as locstartIt is corresponding go out
Mouth node vexit-sWhen being put into open list as node to be tested, indicate in current location element space locstartIt does not search
Rope is switched to outlet layer from fine granularity layer at this time and carries out Path extension search to path, will export node vexit-sIt is deleted from OPEN
It removes, is put into closing list CLOSE, and execute step (9).
(6) if the neighborhood of nodes impassabitity or in CLOSE, continue to extend next node.
(7) if the neighborhood of nodes is not in OPEN, which is added in OPEN, and by the father of the neighborhood of nodes
Node is set as current node, while saving the g value and f value of the neighborhood of nodes.
(8) if the neighborhood of nodes is in OPEN, if judgement via current node reach the neighborhood of nodes g value whether
Less than the g value saved originally, if being less than, father's node of the neighborhood of nodes is set as current node, and reset the phase
The g value and f value of adjacent node.
(9) with vexit-sStep (6)-(8) are executed to each of which adjacent outlets node in outlet layer for current node, work as end
Point node vgoalLocation unitary space locgoalCorresponding outlet node vexit-gOpen list is added into as to be checked
When testing node, fine granularity layer is switched to from outlet layer and carries out Path extension search, will export node vexit-gIt deletes, puts from OPEN
Enter to close list CLOSE, and executes step (10).
(10) with vexit-gFine granularity layer is returned to for current node, and step is executed to each of which adjacent fine granularity layer node
(6)-(8), as goal node vgoalWhen being added into open list OPEN as node to be tested, expression has searched path,
End loop at this time；Or when being sky, show without the new node that can be added, and there is no goal node in the node examined
vgoalThen mean that path can not be found, at this time also end loop.
So far, the optimal guidance path determines that the location server 4 shows the optimal guidance path described
On the interface of terminal 1, meanwhile, during the navigation process, terminal 1 and target good friend terminal 2 can also be looked for by text chat increase
Interaction and connection during people, to supplement the information lacked in map navigation procedure.
Indoor navigation system provided in this embodiment, binding hierarchy indoor location model and path search algorithm determine optimal
When guidance path, the complexity of algorithm can be reduced, improves search efficiency and navigation accuracy.
Embodiment two
Corresponding to embodiment one, after the real-time geometric coordinate of terminal 1 can determine, so that it may be sat according to the geometry
It is marked in the social networks and issues content of registering；Specifically, terminal 1, which receives, registers when requesting, the location server 4
According to the language in the character position and the interior space position model database of 1 sign-in desk of the terminal in the geometric coordinate
Adopted information is matched, and the semantic locations information of the sign-in desk is obtained；The dynamic text record content of registering that will be received
And image content is uploaded；Meanwhile it showing the semantic locations of sign-in desk and showing position on map.Here, terminal 1
Social networks can be entered by the wireless network that Wi-Fi is established, society can also be entered by the 3G/4G network of mobile operator
Hand over network.
Here, visible permission can also be arranged before content is registered in publication in terminal 1, i.e. register content and the position pair
Which good friend as it can be seen that and it is invisible to which good friend, to protect the privacy of user.
In practical application, people often will record the activity dynamic of special meaning in daily life, such as weekend goes
Cuisines have been tasted in certain delicious dining room, or go Conference Hall to listen to report, or have purchased material benefit certain clothes shop
Clothes etc..Position dynamic of registering features people's authentic activity information in somewhere at a moment in time in real world, and indoor thin
The position granular information of granularity can more really reflect the locating space operation of people.User, which registers these positions, dynamically to share
After in mobile social networking, vivid label of the user in mobile social networking is gradually constructed, user is met
Wish in the in the eyes of impression building demand of good friend.For example, user library, bookstore issue position register dynamic it is more,
So the good friends of the user just have labels and the impression such as " scholar-tyrant, one who exercises autocratic control in academic and educational circles ", " having deep love for learning " to the user in the heart.
In the present embodiment, acquisition alignment sensor data, location-server 3 utilize hybrid positioning technology to terminal 1 in real time
The real-time geometric coordinate of (PDR method, Wi-Fi and bluetooth) computing terminal 1, when ensure that user's publication is registered, point geometry of registering
The dynamic and high precision of coordinate.
Embodiment three
Corresponding to embodiment one, the location server 4 go out calculate between the terminal 1 and each good friend's terminal away from
From；Good friend's terminal (with tabular form) is shown in the terminal 1 according to the distance of distance by the social application server 5
Interface on after, the terminal 1 be also used to by instant communication server 6 to target good friend terminal 2 send tracking request.
When carrying out good friend's tracking, due to being related to the access authority of user location, therefore tracking request mechanism, i.e. institute are introduced
It states terminal 1 and good friend's tracking request is sent to target good friend's terminal by the instant communication server 6, when good friend tracking is asked
It asks after obtaining license, the good friend is tracked request and is sent to the location server 4 by the terminal 1；The location server 4
After receiving good friend's tracking request, request is tracked according to the good friend and is obtained with the third preset period to the location-server 3
Take the second geometric coordinate of the target good friend terminal 2, and by second geometric coordinate and the interior space position model
Fine granularity layer node matches to obtain most similar node in database, and the position for obtaining the corresponding site layer of the node is semantic
Information；The terminal 1 shows the position semantic information of the target good friend terminal 2 on interface.Wherein, the matching process
It is complete with the building process of interior space position model and matching process, the building process of interior space position model of embodiment one
Exactly the same, details are not described herein；The third preset period can be 1~3HZ, it is preferable that can for 1HZ, 1.5HZ or
2HZ。
Here, after tracking request is confirmed, terminal 1 and target good friend terminal 2 can check mutually other side
Location information, with understand between mutual distance.
And when target good friend is specific group, tracking request mechanism needs are forced to allow or are arranged to fair in advance
Perhaps；Wherein, the specific group may include: children, old man or patient etc..
Further, the terminal 1 can also receive the geography fence of the preset target good friend terminal 2, when described
When location server 4 determines that the position of the target good friend terminal 2 exceeds the geography fence, the social application server 5
For pushing reminder message to the terminal 1.Wherein, the geography fence is specially the motor area of the target good friend terminal 2
Domain.
In practical application, when A and B indoors go window-shopping by market, not due to crowded in market and two people's focus
It is identical to the greatest extent, therefore two people are likely to respectively be buried in the stream of people, are broken up by the stream of people.So A and B can use good friend's dynamic to chase after
Track comes the position of real time inspection other side, while prompting range is arranged, and when there is a side to walk out the range, another party can receive this
Good friend walks remote reminder message, and then the user can quickly recognize to go to find good friend.
In addition, if caregiver is limited in indoor spaces such as home for destitute, kindergarten, hospitals, then to track accordingly
Object is equipped with special terminal positioning device, and caregiver can recognize the position of tracking object by terminal 1 in real time.When having
Tracking object is negligent of concern when walking out a certain range, and caregiver will pull up a horse and receive prompting message.
In the present embodiment, acquisition alignment sensor data, location-server 3 utilize hybrid positioning technology to terminal 1 in real time
The real-time geometric coordinate of (Wi-Fi, bluetooth and PDR method) computing terminal 1, when ensure that user carries out good friend's tracking, Hao Youshi
When geometric coordinate dynamic and high precision.
Example IV
Corresponding to embodiment one, the location server 4 can also realize the message push of fine position information, specific mistake
Journey the following steps are included:
Step a: the terminal 1 sends geography fence service request to the location server 4；
Step b: after the location server 4 confirms the request, 4 open position of location server tracks function
Can, 1 timing of terminal sends alignment sensor data to the location-server 3；
Step c: the location-server 3 determines that the real-time geometry of the terminal 1 is sat according to the alignment sensor data
Mark, is sent to location server 4 for the real-time geometric coordinate；Here, the location-server 3 is according to the alignment sensor
Data determine that the real-time geometric coordinate of the terminal 1 positions the real-time geometric coordinate of 1 good friend of terminal with embodiment one
Method it is identical, details are not described herein.
Step d: when the location server 4 receives the real-time geometric coordinate of the terminal 1, judge that the real-time geometry is sat
Whether mark meets the trigger condition of preset PUSH message, if satisfied, corresponding service message then is pushed to the terminal 1, when
When terminal 1 has read the reading mark information of service message to the location server 4 transmission, then the service is completed, otherwise again
Corresponding service message is pushed to location server 4.If not satisfied, then continuing to obtain the real-time several of terminal 1 from location-server 3
What coordinate repeats the above deterministic process.Wherein, the trigger condition be preset geography fence range, may include: 10m,
20m etc..
When practical application, when user A has subscribed the message push service of certain point of interest (certain brand shop) after entering market.
When Alice is strolled near certain brand shop, the message with brand shop such as preferential activity, the new product in the shop will be automatically received.
Different from the perimeter query function of embodiment one kind, which is to need to subscribe to specific interest point information and leaned on according to position
Nearly relationship receives the service of subscription automatically.Certainly, interest point information is not limited to the Business Information mentioned in the present embodiment, also wraps
Include museum exhibition position, office building department, airport duty-free shop etc..
Embodiment five
Corresponding to embodiment one, the terminal 1 is also used to send inquiry request and query argument to location server 4；Institute
Location server 4 is stated for meeting the object of the query argument according to inquiry request search, and query argument will be met
The geometric coordinate of query object be back to the terminal 1.Here, the query argument includes: query object classification, inquiry model
Enclose, point of interest category and inquiry quantity；The query object classification includes: periphery good friend inquiry and the inquiry of periphery point of interest.Institute
Stating point of interest category includes: digital product, clothes, cuisines etc..The query context may include: 10m, 20m, 50m or 100m
Deng.
After the location server 4 receives inquiry request and query argument, the query object classification is judged；When true
When the fixed query object classification is that periphery good friend inquires, Xiang Suoshu social application server 3 sends inquiry request, the social activity
Application server 5 sends the friend information of terminal 1 according to the inquiry request to the location server 4；When the position takes
After business device 4 receives the friend information, institute is obtained to the location-server 3 with the 4th preset period according to friend information
State the real-time geometric coordinate of each good friend of terminal 1.Wherein, the side of the real-time geometric coordinate of each good friend is obtained in the present embodiment
Method is identical with the acquisition method of the real-time geometric coordinate of terminal 1 in embodiment one, and details are not described herein.The friend information can
To include: good friend's head portrait, title and good friend's social networks etc..Wherein, the 4th preset period is 1Hz.
After the location-server 3 determines the real-time geometric coordinate of each good friend of the terminal 1, by each good friend's
Real-time geometric coordinate is stored into location database, and will be corresponding good according to the friend information that the location server 4 is sent
The real-time geometric coordinate information of friend is sent to location server 4, and the location server 4 receives the corresponding good friend's of terminal 1
After real-time geometric coordinate information, by the fine granularity layer of the real-time geometric coordinate information MAP to interior space position model.Its
In, the real-time geometric coordinate cannot intuitively be shown by terminal, and the semantic locations information is can intuitively to be shown by terminal
Show.The interior space position model is made of fine granularity layer, outlet layer and site layer.Fine granularity layer is by node and side
The adaptivity graph model of composition, node represent interior space specific location point, while illustrating the connection between each location point
Relationship.Then from the abstract obtained outlet diagram and semantic locations figure of fine granularity layer, outlet diagram indicates outlet knot for outlet layer and site layer
Point and its topological relation, semantic locations figure then indicate indoor each sub-spaces and its topological relation.Wherein, the Interior Space meta position
The building process for setting model is identical with the building process of interior space position model in embodiment one, no longer superfluous herein
It states.
When the real-time geometric coordinate information MAP of the corresponding good friend of terminal 1 is to the fine granularity layer in interior space position model
Afterwards, the location server 4 also determines the real-time geometric coordinate of the terminal 1 using same localization method, and utilizes periphery
Search algorithm searches for the object for meeting the query argument, and the geometric coordinate of the query object for meeting query argument is believed
Breath is back to the terminal 1.In the present embodiment, the detailed process of the perimeter query algorithm based on level indoor location model is such as
Under:
(1) it inquires the geometric coordinate of moving reference point (initiating the terminal 1 of inquiry request) and obtains its corresponding network
Node；
(2) by hierarchical network extension acquisition first time search tree as a result, and being obtained in the range of the network extends
Meet the mobile object of condition；
(3) if reference point does not move, network expanded search tree will not change, and can directly obtain the condition of satisfaction
Mobile object；
(4) if reference point moves, the root node of web search tree is updated, root node is current reference point mapped
Network node；
(5) boundary node is next obtained according to the inquiry based on previous moment position, judges the boundary node whether
Overrun threshold value, if continuing network extension in range threshold；Wherein, the range threshold is preset removable
Dynamic range, for example, 10m, 20m etc..
(6) if the boundary node is not in range threshold, its father node of backward tracing deletes institute along father node pointer
There is distance value to be greater than the node of range threshold values, obtains updated network expanded search tree；
(7) it finally traverses updated network expanded search tree and obtains the mobile good friend for meeting condition.
Further, hierarchical network extended method detailed process involved in step (2) is as follows:
(a) reference point present position unitary space name identification is obtained according to reference point, in the corresponding fine granularity of the mark
Network extension is carried out in layer figure, the stopping when expanding to the outlet node of position units space connection.
(b) network extension is switched to outlet layer and is extended, to moving reference point present position space cell it is all go out
Mouth node carries out network extension, and the outlet node that all distances to reference point are less than or equal to range threshold in the process all will
It is added in network expanded search tree.
(c) leaf node for the network expanded search tree that step 2 obtains is outlet node, empty according to the position of its connection
Between unit obtain corresponding fine granularity layer figure, and carry out network extension in fine granularity layer.When by extension node to reference point away from
Stop extension from when being greater than range threshold.
In addition, the location server 4 is specifically also used to when the query object classification is that periphery point of interest is inquired:
Read interest point information in (connected reference) described interior space model；The point of interest knot is calculated using perimeter query algorithm
Fruit.And point of interest result is back to terminal 1.Wherein, the process for inquiring point of interest and the query process of inquiry periphery good friend are complete
Complete the same, details are not described herein.
Peripheral position query function provided in this embodiment merges location algorithm using particle filter, in conjunction with the interior space
Position model positions periphery friend location and point of interest, improves positioning accuracy and dynamic；It is calculated using perimeter query
Method calculates the query result of periphery good friend and point of interest, improves the accuracy of query result, improves user experience.
The foregoing is only a preferred embodiment of the present invention, is not intended to limit the scope of the present invention, it is all
Made any modifications, equivalent replacements, and improvements etc. within the spirit and principles in the present invention, should be included in protection of the invention
Within the scope of.
Claims (6)
1. a kind of indoor social navigation system, which is characterized in that the system comprises:
Location-server, it is fixed for receiving the first alignment sensor data that terminal is sent and second that target good friend's terminal is sent
Level sensor data calculate the first geometric coordinate of the terminal according to the first alignment sensor data, according to described
Two alignment sensor data calculate the second geometric coordinate of the target terminal；And by first geometric coordinate and described second
Geometric coordinate is stored in location database；
Location server constructs indoor location according to the interior space position data for obtaining indoor location model data
The space topological network of each level of model；The space topological network of each level of indoor location model includes: fine granularity
Level AEGVG figure, outlet level illustraton of model and position level illustraton of model；
The navigation requests that the terminal is sent are received, obtain described more than the first to the location-server according to the navigation requests
What coordinate and second geometric coordinate, and optimal navigation is calculated in the space topological network using path search algorithm
Path；Wherein,
After the space topological network of location server building each level of indoor location model, specifically it is also used to:
The impact factor in every bar navigation path in the space topological network is received, the impact factor specifically includes: indoor
Pedestrian's reach distance, reachable time, density of personnel and road width；
Each impact factor is received to the weighing factor of current navigation path；
The synthesis weight of each path is calculated according to the weighing factor；
Interior pedestrian's reach distance is by formulaIt is calculated；Wherein, institute
State OiFor the corresponding first movement object of the terminal；The OjFor corresponding second mobile object of the target good friend terminal；Institute
State (xx,yk) it is first movement object O described in distance in fine granularity layeriNearest node nkCoordinate；The m is integer.
2. the system as claimed in claim 1, which is characterized in that the location server is according to the interior space position data
The fine granularity level AEGVG figure of building indoor location model specifically includes:
One-dimensional skeleton is extracted according to indoor floor plan, forms the one-dimensional Voronoi diagram in interior space elongated zones；
Open area is subjected to grid dividing with default side length and forms grid chart, the grid chart is added to the Voronoi
In figure；
Sampling node is carried out by the sampling interval of the average step length of pedestrian, generates the AEGVG figure.
3. the system as claimed in claim 1, which is characterized in that the location server is according to the interior space position data
The outlet level illustraton of model of building indoor location model specifically includes:
The Egress node of coarser grained layers is determined according to the outlet port in the fine granularity layer AEGVG figure；
The outlet level illustraton of model is constructed using the reachable path between adjacent position as side.
4. the system as claimed in claim 1, which is characterized in that the location server is according to the interior space position data
The position level illustraton of model of building indoor location model specifically includes:
The nodes of locations of coarser grained layers is determined according to the character position in the fine granularity layer AEGVG figure；
The position level illustraton of model is generated according to the adjoining between the nodes of locations, connected relation.
5. the system as claimed in claim 1, which is characterized in that the location-server is used for according to first orientation sensing
Device data calculate the first geometric coordinate of the terminal, specifically include:
When the location-server detects the anchor point signal in the first alignment sensor data, by the anchor point signal with
Location fingerprint database carries out the initial position that fingerprint matching determines the terminal；
The anchor point signal is detected with preset period timing again, if detecting the anchor point signal, is merged using particle filter
Location algorithm fusion pedestrian's dead reckoning PDR method, the anchor point signal and interior space information determine the first of the terminal
Geometric coordinate.
6. the system as claimed in claim 1, which is characterized in that the evaluation function of the path search algorithm are as follows: f (n)=g
(n)+h(n)；Wherein, the f (n) is evaluation function of the start node via node n to destination node；The g (n) is state
Actual cost of the start node described in space to node n；The h (n) is node n to the best guidance path of the destination node
Actual cost.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610338026.6A CN106017473B (en) | 2016-05-19 | 2016-05-19 | A kind of indoor social navigation system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610338026.6A CN106017473B (en) | 2016-05-19 | 2016-05-19 | A kind of indoor social navigation system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106017473A CN106017473A (en) | 2016-10-12 |
| CN106017473B true CN106017473B (en) | 2019-04-23 |
Family
ID=57095229
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610338026.6A Active CN106017473B (en) | 2016-05-19 | 2016-05-19 | A kind of indoor social navigation system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106017473B (en) |
Families Citing this family (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106643724B (en) * | 2016-11-16 | 2019-07-05 | 浙江工业大学 | Particle filter indoor orientation method based on cartographic information and position adaptive correction |
| CN108072371B (en) * | 2016-11-18 | 2021-05-11 | 富士通株式会社 | Positioning method, positioning device and electronic equipment |
| CN107449426B (en) * | 2017-07-14 | 2020-05-05 | 厦门市礼小签电子科技有限公司 | Navigation logic method and indoor AR navigation system thereof |
| CN107478229A (en) * | 2017-07-28 | 2017-12-15 | 谢荟 | A kind of indoor navigation system |
| CN107741235A (en) * | 2017-09-05 | 2018-02-27 | 浙江吉利控股集团有限公司 | Navigation route planning system and method |
| CN108121871B (en) * | 2017-12-21 | 2021-05-25 | 中国科学院遥感与数字地球研究所 | Method and device for generating reachable range of indoor space |
| CN108398131A (en) * | 2018-03-02 | 2018-08-14 | 李思远 | A kind of positioning and tracing method and system |
| CN108933990B (en) * | 2018-07-23 | 2021-04-20 | 车未来（天津）网络信息技术有限公司 | Navigation method and system |
| CN109084752B (en) * | 2018-10-18 | 2022-04-08 | 西北工业大学 | Geomagnetic navigation positioning method based on full connectivity constraint |
| CN109506653A (en) * | 2018-11-12 | 2019-03-22 | 上海理工大学 | Based on the indoor positioning pedestrian's method for improving particle filter under NLOS environment |
| CN113518304A (en) * | 2021-03-18 | 2021-10-19 | 深圳云里物里科技股份有限公司 | Indoor positioning method and device |
| CN113360987B (en) * | 2021-06-16 | 2023-09-12 | 北京建筑大学 | Indoor navigation-oriented spatial topological relation data organization model and construction method |
| CN114061585B (en) * | 2021-11-10 | 2023-09-19 | 哈尔滨工程大学 | Indoor pedestrian positioning and navigation path planning method based on two-dimension code |
| CN116184312B (en) * | 2022-12-22 | 2023-11-21 | 泰州雷德波达定位导航科技有限公司 | Indoor crowdsourcing fingerprint library construction method based on semantic Wi-Fi |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104919281A (en) * | 2012-12-13 | 2015-09-16 | Lg电子株式会社 | Method of calculating route, and method or device for obtaining route |
| CN105119800A (en) * | 2015-07-07 | 2015-12-02 | 卫小会 | Communication method and system for sharing navigation information |
| CN105357640A (en) * | 2015-11-17 | 2016-02-24 | 小米科技有限责任公司 | Positioning method and device |
| CN105352493A (en) * | 2015-10-22 | 2016-02-24 | 广东欧珀移动通信有限公司 | Navigation route generation method and user terminal |
| CN105444753A (en) * | 2014-09-30 | 2016-03-30 | 宇龙计算机通信科技(深圳)有限公司 | Method and device for planning navigation route and terminal |
-
2016
- 2016-05-19 CN CN201610338026.6A patent/CN106017473B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104919281A (en) * | 2012-12-13 | 2015-09-16 | Lg电子株式会社 | Method of calculating route, and method or device for obtaining route |
| CN105444753A (en) * | 2014-09-30 | 2016-03-30 | 宇龙计算机通信科技(深圳)有限公司 | Method and device for planning navigation route and terminal |
| CN105119800A (en) * | 2015-07-07 | 2015-12-02 | 卫小会 | Communication method and system for sharing navigation information |
| CN105352493A (en) * | 2015-10-22 | 2016-02-24 | 广东欧珀移动通信有限公司 | Navigation route generation method and user terminal |
| CN105357640A (en) * | 2015-11-17 | 2016-02-24 | 小米科技有限责任公司 | Positioning method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106017473A (en) | 2016-10-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106017473B (en) | A kind of indoor social navigation system | |
| CN105931124A (en) | Indoor social network service system | |
| Renaudin et al. | Evaluating indoor positioning systems in a shopping mall: The lessons learned from the IPIN 2018 competition | |
| JP5746378B2 (en) | Method and apparatus for mobile location determination | |
| CN104736968B (en) | Mass-rent indoor positioning | |
| Hazas et al. | Location-aware computing comes of age | |
| Shin et al. | Unsupervised construction of an indoor floor plan using a smartphone | |
| CN111123198B (en) | User positioning and navigation method and system in building | |
| Zeinalipour-Yazti et al. | Internet-based indoor navigation services | |
| CN107110652A (en) | Handle space characteristics | |
| Monnot et al. | Inferring activities and optimal trips: Lessons from Singapore’s National Science Experiment | |
| Belka et al. | BLE-based indoor tracking system with overlapping-resistant IoT solution for tourism applications | |
| Peng et al. | Indoor floor plan construction through sensing data collected from smartphones | |
| Huang et al. | Wearable indoor localisation approach in Internet of Things | |
| Elhamshary et al. | Justwalk: A crowdsourcing approach for the automatic construction of indoor floorplans | |
| Prentow et al. | Towards indoor transportation mode detection using mobile sensing | |
| Alakhras et al. | Location fixing and fingerprint matching fingerprint map construction for indoor localization | |
| Hightower | The location stack | |
| Stook | Planning an indoor navigation service for a smartphone with Wi-Fi fingerprinting localization | |
| Prentow et al. | Estimating common pedestrian routes through indoor path networks using position traces | |
| CN106021490A (en) | Indoor peripheral position query system | |
| Yan et al. | Navigation network derivation for QR code‐based indoor pedestrian path planning | |
| Alamri et al. | Multi-user routing algorithm for indoor spaces–Adapted for social distancing | |
| Ye et al. | Infrastructure-free floor localization through crowdsourcing | |
| Merkel | Building evacuation with mobile devices |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |