CN108521626A - A kind of search and rescue localization method waterborne based on more sensing networks - Google Patents
A kind of search and rescue localization method waterborne based on more sensing networks Download PDFInfo
- Publication number
- CN108521626A CN108521626A CN201810188711.4A CN201810188711A CN108521626A CN 108521626 A CN108521626 A CN 108521626A CN 201810188711 A CN201810188711 A CN 201810188711A CN 108521626 A CN108521626 A CN 108521626A
- Authority
- CN
- China
- Prior art keywords
- node
- sensor node
- distance
- sensor
- fictitious force
- 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.)
- Granted
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Testing Or Calibration Of Command Recording Devices (AREA)
Abstract
The invention discloses a kind of search and rescue localization method waterborne based on more sensing networks, belongs to multiple-sensor network technical field.The present invention includes：The acquisition of sensor node position is obtained by GPS and wireless communication and exchanges self-position coordinate information in real time；Sensor node stress model is established, sensor node is abstracted into the particle in force field, the moving direction and distance of the effect control sensor node of power between analyte sensors node；Based on the multiple-sensor network region overlay for improving fictitious force algorithm.The present invention can make multiple-sensor network realize the seamless coverage in region, and carry out data collection to overlay area；Photo electric imaging system determines search target using gray scale and temperature difference, and simultaneously feedback target co-ordinate position information is determined using three side location algorithms.
Description
Technical field
The invention belongs to multiple-sensor network technical fields, and in particular to a kind of search and rescue waterborne based on more sensing networks are fixed
Position method.
Background technology
Multiple-sensor network combines sensor technology, embedding assembly technology, micro-electromechanical technology and wireless communication technique,
It is made of a large amount of sensor nodes being deployed in monitoring region, can synergistically complete to monitor, sense and acquire target in real time
The information of object, and it is handled, send the user for needing information to.With MEMS, wireless communication technique and
Integrated, micromation and networking are moved towards in the development of large scale integrated circuit technology, the acquisition of sensor information technology gradually
Direction, multiple-sensor network are also considered as one of this century most important technology, its development and extensive use will be to people
Social life and industry transformation bring strong influence.
The advantages that at low cost, low in energy consumption, miniature due to the sensor node in multiple-sensor network, it is possible to reduce arrangement net
The time of network and cost, can carrying platform it is extensive, can adapt to severe condition, be therefore widely used in military battlefield, dagger-axe
The regions such as wall desert, universe space, seabed depths.The present invention proposes a kind of positioned with improvement fictitious force algorithm and three sides and calculates
Multiple-sensor network is applied to the unmanned method for searching and rescuing positioning of the water surface by method.
Invention content
It is an object of the invention to using the control sensor node distribution of fictitious force algorithm is improved, multiple-sensor network be made to cover
Lid searches and rescues waters, and comprehensive collection information, positions and feedback target position, realization position the unmanned search and rescue of waterborne target.
The object of the present invention is achieved like this：
A kind of search and rescue localization method waterborne based on more sensing networks, which is characterized in that comprise the steps of：
The acquisition of step 1 sensor node position；
The characteristics of sensor node is according to its carrying platform chooses the position for obtaining its own positioning in real time by GPS modes
Set coordinate, and mode and other node switching location informations by radio communication；
Step 2 establishes sensor node stress model；
Sensor node is abstracted into the particle in force field, some sensor node is to ambient sensors node strong
Effect, gravitation and repulsion are distinguished as according to the size of distance；When the distance of two sensor nodes is less than distance threshold, the two
Between there are repulsion, distance increases between the two；When the distance of two sensor nodes is more than distance threshold, between the two then
Show as gravitation, Distance Shortened between the two；
Stress relationship F between sensor nodeij：
In formula, wAIndicate gravitational coefficients；wRIndicate repulsion coefficient；dijIndicate the Euclidean distance between node；dthIndicate away from
From threshold values；aijIt is the azimuth of sensor node；RcIndicate the communication radius of node；
If FijFor repulsion, then
Fxij=| Fij|(xi-xj)/dij
Fyij=| Fij|(yi-yj)/dij
If FijFor gravitation, then
Fxij=| Fij|(xj-xi)/dij
Fyij=| Fij|(yj-yi)/dij
Stress relationship between two sensor nodes, FijFor：
Fij=Fxij+Fyij
The fictitious force of horizontal direction and it is：
Fx=∑ Fxij
The fictitious force of vertical direction and it is：
Fy=∑ Fyij
The size of horizontal direction and vertical direction resultant force is：
If F in formulaxij, FyijFor negative, show the component of horizontal direction to the left, the component of vertical direction is downward；
The stress details of wireless sensor node is obtained according to the above analysis, according to the stressing conditions of sensor node
The direction moved when determining sensor node by fictitious force and distance：
In formula, (xi yi) it is the initial position of sensor node；(xi',yi') be it is mobile after position；FthFor fictitious force
The threshold value of component, when the component for the fictitious force being subject to is less than the value, sensor node does not move on the component direction；step
For the maximum distance of sensor node movement；
Step 3 is based on the multiple-sensor network region overlay for improving fictitious force algorithm；
Improve fictitious force algorithm：
To reduce fictitious force algorithm iteration number, added on the stress model of sensor node and apart from relevant system
Number；For node when distance is closer, fictitious force is sufficiently large, it is made quickly to spread；When euclidean distance between node pair tends to distance threshold, fictitious force
It is sufficiently small, so that node is easily reached balance；Fictitious force equation between improved node is：
In formula, d (si,sj) it is Euclidean distance between node i and node j；U1To be in node i communication range
Node set；
Step 4 positions unknown position target；
Photoelectronic imaging search system searches for determining searching target using the difference of gray scale and temperature；After determining target,
The sensor node for knowing self-position coordinate positions unknown position target by three side location algorithms；
Target location is solved according to following equation：
In formula, (x, y) is target location coordinate；(x1,y2)、(x2,y2)、(x3,y3) be respectively three known nodes seat
Mark；d1、d2、d3Respectively target between three nodes at a distance from.
Compared with prior art, the beneficial effects of the invention are as follows：
1, the present invention is completed to specifying unmanned searching and rescuing for the task of the water surface of target, using the mobility of sensor node,
It is automatically performed the covering to reconnoitring waters, collects and analyze information, simultaneously feedback target position coordinates is determined, has reached unmanned search and rescue
Purpose；
2, the present invention is overcome original using the distribution of movement in improved fictitious force algorithm control sensor node region
The slow problem of the fictitious force algorithm speed of service so that sensor node disperses rapidly and stablizes in corresponding position, reduces energy consumption, increases
The stability of strong multiple-sensor network, and extend the survival duration of multiple-sensor network；
3, the present invention is handled the monitoring water surface imaging of collection by photoelectronic imaging search system, determines unknown mesh
Mark.It is not necessarily to the self-contained sensor node of target in this way, reduces the requirement to target itself, the target scope of application can be expanded.
4, the present invention completes covering of the multiple-sensor network to the prospecting water surface by improving fictitious force algorithm, passes through three sides
Location algorithm determines and feedback target position, realizes search and rescue unmanned to the water surface of target and positions.
Description of the drawings
Fig. 1 is inventive sensor joints model；
Fig. 2 is that the present invention is based on the sensor node moving process simulation results for improving fictitious force algorithm；
Fig. 3 is the schematic diagram of three side location algorithms of the invention.
Specific implementation mode
The new concept of the present invention is subtracted below in conjunction with the accompanying drawings and shakes drag reduction ship and makes following detailed description：
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, with reference to Fig. 1 to Fig. 3 and tool
The present invention is described in further detail for body embodiment, wherein Fig. 1 is sensor node stress model；Fig. 2 is to be based on changing
Into the sensor node moving process simulation result of fictitious force algorithm；Fig. 3 is the schematic diagram of three side location algorithms；
Specific embodiment one
The purpose of the present invention is realized according to the following steps：
1. establishing sensor node stress model
Sensor node is abstracted into the particle in force field, some sensor node is to ambient sensors node strong
Effect, can be distinguished as gravitation and repulsion according to the size of distance.When the distance of two sensor nodes is less than distance threshold,
There is repulsion between the two, distance increases between the two；When the distance of two sensor nodes be more than distance threshold when, the two it
Between then show as gravitation, Distance Shortened between the two.Accordingly, sensor node stress model is established, as shown in Figure 1.
Stress relationship F between sensor nodeij：
In formula, wAIndicate gravitational coefficients；
wRIndicate repulsion coefficient；
dijIndicate the Euclidean distance between node；
dthIt indicates apart from threshold values；
aijIt is the azimuth of sensor node；
RcIndicate the communication radius of node.
If FijFor repulsion, then
Fxij=| Fij|(xi-xj)/dij
Fyij=| Fij|(yi-yj)/dij
If FijFor gravitation, then
Fxij=| Fij|(xj-xi)/dij
Fyij=| Fij|(yj-yi)/dij
Stress relationship between two sensor nodes, FijFor
Fij=Fxij+Fyij
The fictitious force of horizontal direction and it is：
Fx=∑ Fxij
The fictitious force of vertical direction and it is：
Fy=∑ Fyij
The size of horizontal direction and vertical direction resultant force is：
If F in formulaxij, FyijFor negative, show the component of horizontal direction to the left, the component of vertical direction is downward.
The stress details that wireless sensor node can be obtained according to the above analysis, according to the stress of sensor node
The direction and distance that situation moves when determining sensor node by fictitious force：
In formula, (xi yi) it is the initial position of sensor node；
(xi',yi') be it is mobile after position；
FthIt is uploaded in the component direction for the threshold value of fictitious force component when the component for the fictitious force being subject to is less than the value
Sensor node does not move；
Step is the maximum distance of sensor node movement.
2. improving fictitious force algorithm, and controls sensor node seamless coverage using it and reconnoitre waters
(1) fictitious force algorithm is improved
To reduce fictitious force algorithm iteration number, added on the stress model of sensor node and apart from relevant system
Number.For node when distance is closer, fictitious force is sufficiently large, it is made quickly to spread；When euclidean distance between node pair tends to distance threshold, fictitious force
It is sufficiently small, so that node is easily reached balance.Fictitious force equation between improved node is：
In formula, d (si,sj) it is Euclidean distance between node i and node j；
U1For the set of the node in node i communication range.
(2) fictitious force algorithm operational process is improved
Fictitious force algorithm is iterated as follows：Original state is that sensor node is randomly dispersed in monitoring section
Domain, sensor node are acted on by other nodal forces, then according to the size and Orientation by power determine mobile distance and
Direction is moved after being moved to new position further according to new stress size and Orientation, next time until reaching satisfied covering
It is required that.Its carrying out practically process is as follows：
Step 1：Sensor node is randomly dispersed in monitoring region；
Step 2：Sensor node calculates at a distance from surroundings nodes and relative position, calculates size and the side of fictitious force
To, and displacement distance and direction are determined with this；
Step 3：Calculate coverage rate；
Step 4：When coverage rate is met the requirements, stopping algorithm iteration exporting result.
Fig. 2 reflects sensor node and is gradually moved to the state of water surface seamless coverage from random distribution state, and utilizes
Curve graph reflects the relationship between coverage rate and algorithm iteration number.
3. sensor collection waters information determines target location based on three side location algorithms
Sensor node is obtained by GPS and wireless communication and exchanges own coordinate position with adjacent node in real time, by passing
Sensor collects information in communication context, and simultaneously feedback target position coordinates are determined using three side location algorithms.
Three side location algorithm principles are as shown in figure 3, target location is solved according to following equation：
In formula, (x, y) is target location coordinate；
(x1,y2)、(x2,y2)、(x3,y3) be respectively three known nodes coordinate；
d1、d2、d3Respectively target between three nodes at a distance from.
4. the search and rescue localization method waterborne based on more sensing networks
Search and rescue localization method design procedure waterborne based on multiple-sensor network is as follows：
Step 1：Sensor node is randomly dispersed in monitoring waters；
Step 2：Waters is scouted using improved fictitious force algorithm control sensor node seamless coverage；
Step 3：Sensor node obtains and exchanges in real time self-position coordinate by GPS and wireless communication, and collects and cover
Information in cover area looks for target using the determination of photoelectronic imaging search system；
Step 4：Using three side location algorithms, at a distance from sensor node determines target between three known nodes, calculate
And feedback target location information.
Specific embodiment two
A kind of search and rescue localization method waterborne based on more sensing networks, it is characterised in that：This method utilizes fictitious force algorithm
The sensor node with maneuvering characteristics is controlled, it is made to be moved by initial random distribution state, realizes the nothing to specifying waters
Seam covering, is collected simultaneously data in overlay area, is analyzed and determined on sea using photo electric imaging system and Digital Image Processing
Target, take three side location algorithms to determine and feedback target position, the search and rescue to target and positioning may be implemented.
(1) acquisition of sensor node position
The characteristics of sensor node can be according to its carrying platform is chosen and obtains its own positioning in real time by modes such as GPS
Position coordinates, and mode and other node switching location informations by radio communication.
(2) sensor node stress model is established
Sensor node is abstracted into the particle in force field, establishes sensor node stress model, passes through sensor section
The effect control sensor node moving direction and distance of power between point.
(3) based on the multiple-sensor network region overlay for improving fictitious force algorithm
It is randomly dispersed in region under sensor node original state, sensing region is overlapped, passes through power between node
Effect, control node moving direction and distance, algorithm successive ignition can be to the area of coverage until realizing seamless coverage to region
Domain carries out data comprehensive collection.Often due to original fictitious force algorithm iteration, the consumption of sensor node energy can be increased,
The present invention is directed to this problem, proposes by way of addition on the stress model in sensor node and apart from relevant coefficient,
Carry out boosting algorithm speed, reduces energy consumption.
(4) unknown position target is positioned
Photoelectronic imaging search system searches for determining searching target using the difference of gray scale and temperature.After determining target,
The sensor node for knowing self-position coordinate positions unknown position target by three side location algorithms.
Sensor node is abstracted into the particle in force field, some sensor node is to ambient sensors node strong
Effect, can be distinguished as gravitation and repulsion according to the size of distance.When the distance of two sensor nodes is less than distance threshold,
There is repulsion between the two, distance increases between the two；When the distance of two sensor nodes be more than distance threshold when, the two it
Between then show as gravitation, Distance Shortened between the two.Accordingly, sensor node stress model is established：
Stress relationship F between sensor nodeij：
In formula, wAIndicate gravitational coefficients；
wRIndicate repulsion coefficient；
dijIndicate the Euclidean distance between node；
dthIt indicates apart from threshold values；
aijIt is the azimuth of sensor node；
RcIndicate the communication radius of node.
If FijFor repulsion, then
Fxij=| Fij|(xi-xj)/dij
Fyij=| Fij|(yi-yj)/dij
If FijFor gravitation, then
Fxij=| Fij|(xj-xi)/dij
Fyij=| Fij|(yj-yi)/dij
Stress relationship between two sensor nodes, FijFor
Fij=Fxij+Fyij
The fictitious force of horizontal direction and it is：
Fx=∑ Fxij
The fictitious force of vertical direction and it is：
Fy=∑ Fyij
The size of horizontal direction and vertical direction resultant force is：
If F in formulaxij, FyijFor negative, show the component of horizontal direction to the left, the component of vertical direction is downward.
The stress details that wireless sensor node can be obtained according to the above analysis, according to the stress of sensor node
The direction and distance that situation moves when determining sensor node by fictitious force：
In formula, (xi yi) it is the initial position of sensor node；
(xi',yi') be it is mobile after position；
FthIt is uploaded in the component direction for the threshold value of fictitious force component when the component for the fictitious force being subject to is less than the value
Sensor node does not move；
Step is the maximum distance of sensor node movement.
To reduce fictitious force algorithm iteration number, added on the stress model of sensor node and apart from relevant system
Number.For node when distance is closer, fictitious force is sufficiently large, it is made quickly to spread；When euclidean distance between node pair tends to distance threshold, fictitious force
It is sufficiently small, so that node is easily reached balance.Fictitious force equation between improved node is：
In formula, d (si,sj) it is Euclidean distance between node i and node j；
U1For the set of the node in node i communication range.
Fictitious force algorithm is iterated as follows：Original state is that sensor node is randomly dispersed in monitoring section
Domain, sensor node are acted on by other nodal forces, then according to the size and Orientation by power determine mobile distance and
Direction is moved after being moved to new position further according to new stress size and Orientation, next time until reaching satisfied covering
It is required that.
Target location is solved according to following equation：
In formula, target location coordinate is (x, y)；
The coordinate of three known nodes is respectively (x1,y2)、(x2,y2)、(x3,y3)；
It is respectively d that target seems distance with three nodes1、d2、d3。
Search and rescue localization method design procedure waterborne based on multiple-sensor network is as follows：
Step 1：Sensor node is randomly dispersed in monitoring waters；
Step 2：Waters is scouted using improved fictitious force algorithm control sensor node seamless coverage；
Step 3：Sensor node obtains and exchanges in real time self-position coordinate by GPS and wireless communication, and collects and cover
Information in cover area looks for target using the determination of photoelectronic imaging search system；
Step 4：Using three side location algorithms, at a distance from sensor node determines target between three known nodes, calculate
And feedback target location information.
Claims (1)
1. a kind of search and rescue localization method waterborne based on more sensing networks, which is characterized in that comprise the steps of：
The acquisition of step 1 sensor node position；
The characteristics of sensor node is according to its carrying platform chooses the position seat for obtaining its own positioning in real time by GPS modes
Mark, and mode and other node switching location informations by radio communication；
Step 2 establishes sensor node stress model；
Sensor node is abstracted into the particle in force field, some sensor node work strong to ambient sensors node
With being distinguished as gravitation and repulsion according to the size of distance；When the distance of two sensor nodes be less than distance threshold when, the two it
Between there are repulsion, distance increases between the two；When the distance of two sensor nodes is more than distance threshold, then table between the two
It is now gravitation, Distance Shortened between the two；
Stress relationship F between sensor nodeij：
In formula, wAIndicate gravitational coefficients；wRIndicate repulsion coefficient；dijIndicate the Euclidean distance between node；dthIt indicates apart from valve
Value；aijIt is the azimuth of sensor node；RcIndicate the communication radius of node；
If FijFor repulsion, then
Fxij=| Fij|(xi-xj)/dij
Fyij=| Fij|(yi-yj)/dij
If FijFor gravitation, then
Fxij=| Fij|(xj-xi)/dij
Fyij=| Fij|(yj-yi)/dij
Stress relationship between two sensor nodes, FijFor：
Fij=Fxij+Fyij
The fictitious force of horizontal direction and it is：
Fx=∑ Fxij
The fictitious force of vertical direction and it is：
Fy=∑ Fyij
The size of horizontal direction and vertical direction resultant force is：
If F in formulaxij, FyijFor negative, show the component of horizontal direction to the left, the component of vertical direction is downward；
The stress details of wireless sensor node is obtained according to the above analysis, is determined according to the stressing conditions of sensor node
The direction moved when sensor node is by fictitious force and distance：
In formula, (xi yi) it is the initial position of sensor node；(xi',yi') be it is mobile after position；FthFor fictitious force component
Threshold value, when the component for the fictitious force being subject to be less than the value when, sensor node does not move on the component direction；Step is to pass
The maximum distance of sensor node movement；
Step 3 is based on the multiple-sensor network region overlay for improving fictitious force algorithm；
Improve fictitious force algorithm：
To reduce fictitious force algorithm iteration number, added on the stress model of sensor node and apart from relevant coefficient；Section
For point when distance is closer, fictitious force is sufficiently large, it is made quickly to spread；When euclidean distance between node pair tends to distance threshold, fictitious force is enough
It is small, so that node is easily reached balance；Fictitious force equation between improved node is：
In formula, d (si,sj) it is Euclidean distance between node i and node j；U1For the section in node i communication range
The set of point；
Step 4 positions unknown position target；
Photoelectronic imaging search system searches for determining searching target using the difference of gray scale and temperature；After determining target, it is known that from
The sensor node of body position coordinates positions unknown position target by three side location algorithms；
Target location is solved according to following equation：
In formula, (x, y) is target location coordinate；(x1,y2)、(x2,y2)、(x3,y3) be respectively three known nodes coordinate；d1、
d2、d3Respectively target between three nodes at a distance from.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810188711.4A CN108521626B (en) | 2018-03-08 | 2018-03-08 | Overwater search and rescue positioning method based on multiple sensor networks |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810188711.4A CN108521626B (en) | 2018-03-08 | 2018-03-08 | Overwater search and rescue positioning method based on multiple sensor networks |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108521626A true CN108521626A (en) | 2018-09-11 |
| CN108521626B CN108521626B (en) | 2020-09-25 |
Family
ID=63433578
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810188711.4A Active CN108521626B (en) | 2018-03-08 | 2018-03-08 | Overwater search and rescue positioning method based on multiple sensor networks |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108521626B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115015839A (en) * | 2022-08-10 | 2022-09-06 | 中国海洋大学 | Passive positioning system for underwater target in shallow sea |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101051973A (en) * | 2007-05-17 | 2007-10-10 | 浙江大学 | Method and device for layout mobile radio sensor network node based on virtual force |
| CN102438252A (en) * | 2011-12-23 | 2012-05-02 | 无锡虹业自动化工程有限公司 | Node path smooth control method for wireless sensor network |
| CN104333866A (en) * | 2014-10-24 | 2015-02-04 | 北方信息控制集团有限公司 | Wireless sensor network coverage optimization method and system based on fictitious force algorithm |
| CN105611555A (en) * | 2015-12-31 | 2016-05-25 | 北京科技大学 | Energy saving coverage control method of sensor network based on virtual force orientation |
| US20170337831A1 (en) * | 2016-05-18 | 2017-11-23 | Converge Industries, Co. | Method and system for collision avoidance and environment sensing for a robotic system |
-
2018
- 2018-03-08 CN CN201810188711.4A patent/CN108521626B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101051973A (en) * | 2007-05-17 | 2007-10-10 | 浙江大学 | Method and device for layout mobile radio sensor network node based on virtual force |
| CN102438252A (en) * | 2011-12-23 | 2012-05-02 | 无锡虹业自动化工程有限公司 | Node path smooth control method for wireless sensor network |
| CN104333866A (en) * | 2014-10-24 | 2015-02-04 | 北方信息控制集团有限公司 | Wireless sensor network coverage optimization method and system based on fictitious force algorithm |
| CN105611555A (en) * | 2015-12-31 | 2016-05-25 | 北京科技大学 | Energy saving coverage control method of sensor network based on virtual force orientation |
| US20170337831A1 (en) * | 2016-05-18 | 2017-11-23 | Converge Industries, Co. | Method and system for collision avoidance and environment sensing for a robotic system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115015839A (en) * | 2022-08-10 | 2022-09-06 | 中国海洋大学 | Passive positioning system for underwater target in shallow sea |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108521626B (en) | 2020-09-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106931961B (en) | Automatic navigation method and device | |
| US9927814B2 (en) | System and method for localization of robots | |
| KR101913332B1 (en) | Mobile apparatus and localization method of mobile apparatus | |
| CN107817798A (en) | A kind of farm machinery barrier-avoiding method based on deep learning system | |
| CN104517289B (en) | A kind of indoor scene localization method based on hybrid camera | |
| Nain et al. | Localization techniques in underwater wireless sensor network | |
| Manjanna et al. | Efficient terrain driven coral coverage using gaussian processes for mosaic synthesis | |
| Capi et al. | Neural network based guide robot navigation: an evolutionary approach | |
| CN111144208A (en) | Automatic detection and identification method for marine vessel target and target detector | |
| CN108521626A (en) | A kind of search and rescue localization method waterborne based on more sensing networks | |
| Son et al. | Synthetic deep neural network design for lidar-inertial odometry based on CNN and LSTM | |
| Wei et al. | MM-Loc: Cross-sensor indoor smartphone location tracking using multimodal deep neural networks | |
| Yeh et al. | Remote control realization of distributed rescue robots via the wireless network | |
| CN110919644A (en) | Method and system for positioning interaction by using camera equipment and robot | |
| CN113758487A (en) | Underwater robot positioning method based on 5G technology and machine learning assistance | |
| Alatise et al. | Pose estimation of a mobile robot using monocular vision and inertial sensors data | |
| Asami et al. | Visual navigation system based on evolutionary computation on FPGA for patrol service robot | |
| Mishra et al. | An architecture for virtual tethering of rovs | |
| Jeong et al. | OrigamiBot-II: An amphibious robot with reconfigurable origami wheels for locomotion in dynamic environments | |
| Kim et al. | Multi-robot team outdoor localization using active marker and high frequency signal sources | |
| Greenberg et al. | Efficient optical localization for mobile robots via Kalman filtering-based location prediction | |
| Oleari et al. | Issues in high performance vision systems design for underwater interventions | |
| Wang et al. | Mobile robot SLAM methods improved for adapting to search and rescue environments | |
| Kumar et al. | Energy Aware Node deployment using Ant Lion optimization algorithm in underwater acoustic sensor Network | |
| Grejner-Brzezinska et al. | Cooperative navigation in transitional environments |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |