CN107273881A - A kind of anti-terrorism SEEK BUS, wearable device and virtual reality detection system - Google Patents
A kind of anti-terrorism SEEK BUS, wearable device and virtual reality detection system Download PDFInfo
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- CN107273881A CN107273881A CN201710724530.4A CN201710724530A CN107273881A CN 107273881 A CN107273881 A CN 107273881A CN 201710724530 A CN201710724530 A CN 201710724530A CN 107273881 A CN107273881 A CN 107273881A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2203/00—Indexing scheme relating to G06F3/00 - G06F3/048
- G06F2203/01—Indexing scheme relating to G06F3/01
- G06F2203/012—Walk-in-place systems for allowing a user to walk in a virtual environment while constraining him to a given position in the physical environment
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Abstract
A kind of anti-terrorism SEEK BUS, wearable device and virtual reality detection system, anti-terrorism SEEK BUS includes exploring vehicle main body, sensor assembly, at least four cameras and processor, explore the running assembly that vehicle main body is provided with driving anti-terrorism SEEK BUS traveling, its appearance is wrapped up by explosion-proof lamp, and processor is connected with running assembly, sensor assembly and all cameras.Because the anti-terrorism SEEK BUS can detect the range information and the image by camera shooting surrounding environment of anti-terrorism SEEK BUS and surrounding objects by sensor assembly, under the control of a processor, according to these range informations and view data, carry out unmanned and anti-terrorism target identification, so that anti-terrorism SEEK BUS can automatically be searched in dangerous environment, lean out the position of anti-terrorism target, anti-terrorism officer is allowed in the place away from hazardous environment, the positional information of anti-terrorism target is received by wearable device, understand site environment as on the spot in person, precisely make the decision of next step action, reduce unnecessary casualties.
Description
Technical field
The present invention relates to anti-terrorism auxiliary equipment technical field, and in particular to a kind of anti-terrorism SEEK BUS, wearable device and void
Intend real detection system.
Background technology
In recent years, anti-terrorism situation is further severe, and terrorist incident happens occasionally, and the life security to the people is caused greatly
Influence.Terrorist and explosive are usually hidden in ND place, and existing anti-terrorism mode generally requires anti-terrorism people
Member goes to search site, but enters unknown hazardous environment rashly, and extremely dangerous for anti-terrorism officer, it is unnecessary to easily cause
Personal injury.
The content of the invention
In view of this, the application provides a kind of anti-terrorism SEEK BUS, wearable device and virtual reality detection system, the anti-terrorism
SEEK BUS can automatically be searched for into hazardous environment, explored and concealed terrorist therein and may explode object location, allow anti-terrorism
Personnel away from hazardous environment place, it is on the spot in person as understand site environment so as to precisely make next step action determine
It is fixed, reduce unnecessary casualties.
According in a first aspect, provide a kind of anti-terrorism SEEK BUS in a kind of embodiment, including：
Vehicle main body is explored, the running assembly of driving anti-terrorism SEEK BUS traveling is provided with, the exploration vehicle main body is by explosion-proof timber
Material parcel, wherein, running assembly at least includes wheel；
Sensor assembly, is arranged in exploration vehicle main body, the sensor assembly at least includes：Radar and supersonic sensing
Device, the range information for detecting anti-terrorism SEEK BUS and surrounding objects；
At least four cameras, are arranged in exploration vehicle main body, the image for shooting surrounding environment；
Processor, is connected with the exploration vehicle main body, sensor assembly and at least four cameras, described for controlling
Running assembly action is so as to drive anti-terrorism SEEK BUS to travel, and the range information for being detected according to the sensor assembly and institute
The view data of at least four cameras shooting is stated, map is positioned and built, is anti-terrorism SEEK BUS planning travel route, control
Anti-terrorism SEEK BUS automatic running；It is additionally operable to from described image data, identifies default anti-terrorism target and its positional information, its
In, anti-terrorism target includes：Explosive and weapon.
According to second aspect, a kind of wearable device is provided in a kind of embodiment, including：
Data reception module, for receive anti-terrorism target information that anti-terrorism SEEK BUS as claimed in claim 1 identifies and
Its positional information；
VR display modules, are connected with the data reception module, for rebuilding the anti-terrorism mesh in reality environment
Information and its positional information are marked, and carries out video playback.
According to the third aspect, a kind of virtual reality detection system is provided in a kind of embodiment, including as described in relation to the first aspect
Anti-terrorism SEEK BUS and the wearable device as described in second aspect.
According to above-described embodiment, because the anti-terrorism SEEK BUS that the application is provided can detect that anti-terrorism is explored by sensor assembly
The range information and the image by camera shooting surrounding environment of car and surrounding objects, and can under the control of a processor, root
According to these range informations and view data, unmanned and anti-terrorism target identification is carried out so that anti-terrorism SEEK BUS can be in terror point
Searched for automatically in the environment that son or explosive are concealed, lean out the position of anti-terrorism target, allow anti-terrorism officer in remote hazardous environment
Place, by wearable device receive anti-terrorism target positional information, it is on the spot in person as understand site environment, precisely make down
The dynamic decision of one walking, reduces unnecessary casualties.
Brief description of the drawings
A kind of anti-terrorism SEEK BUS structural representation that Fig. 1 provides for a kind of embodiment；
Fig. 2 is a kind of a kind of composition frame chart of anti-terrorism SEEK BUS of offer of embodiment；
Fig. 3 is camera, processor and the data outputting module group of a kind of a kind of anti-terrorism SEEK BUS of offer of embodiment
Into block diagram；
A kind of a kind of composition frame chart for wearable device that Fig. 4 provides for embodiment；
A kind of virtual reality detection system that Fig. 5 provides for the application.
Embodiment
The present invention is described in further detail below by embodiment combination accompanying drawing.Wherein different embodiments
Middle similar component employs associated similar element numbers.In the following embodiments, many detailed descriptions be in order to
The application is better understood.However, those skilled in the art can be without lifting an eyebrow recognize, which part feature
It is dispensed, or can be substituted by other elements, material, method in varied situations.In some cases, this Shen
Certain operations that please be related do not show or description that this is the core in order to avoid the application by mistake in the description
Many descriptions are flooded, and to those skilled in the art, be described in detail these associative operations be not it is necessary, they
The general technology knowledge of description and this area in specification can completely understand associative operation.
In addition, feature described in this description, operation or feature can be combined to form respectively in any suitable way
Plant embodiment.Meanwhile, each step or action in method description can also be aobvious and easy according to those skilled in the art institute energy
The mode carry out order exchange or adjustment seen.Therefore, the various orders in specification and drawings are intended merely to clearly describe a certain
Individual embodiment, is not meant to be necessary order, wherein some sequentially must comply with unless otherwise indicated.
Embodiment one：
Fig. 1 and Fig. 2 are refer to, a kind of anti-terrorism SEEK BUS provided for the application, including：Explore vehicle main body 1, sensor die
Block 50, at least four cameras 20 and processor 10.
The running assembly 60 that vehicle main body 1 is provided with driving anti-terrorism SEEK BUS traveling is explored, the appearance of vehicle main body 1 is explored explosion-proof
Material wraps up preventing anti-terrorism SEEK BUS by terrorist's malicious sabotage.Wherein, running assembly 60 at least includes wheel 61, one
A little embodiments, wheel 61 is universal wheel, anti-terrorism SEEK BUS can 360 degree flexibly turn to.
Sensor assembly 50 is arranged in exploration vehicle main body 1, and sensor assembly 50 at least includes：Radar and supersonic sensing
Device, the range information for detecting anti-terrorism SEEK BUS and surrounding objects.Different from this passive avoidance mode of infrared obstacle avoidance, this Shen
Avoiding obstacles by supersonic wave and radar avoidance please be use, avoiding obstacles by supersonic wave can monitor long range ultrasonic sensor in real time, be robot
Search for open path.When with a certain distance from robot also has far from barrier, ultrasonic sensor is just able to detect that relevant information,
And control machine people leaves accordingly；Radar avoidance can consider required precision and speed simultaneously due to the distance measurement technique based on laser
Degree is required, and laser radar is adusk more preferable apart from Detection results, is relatively applied to the environment that anti-terrorism target is concealed, because
Terrorist and explosive are usually concealed in dark environment.
At least four cameras 20 are arranged in exploration vehicle main body 1, the image for shooting surrounding environment.Because terror point
Son is possible to attack unmanned SEEK BUS from different directions, therefore at least four camera 20 is fish-eye camera, is clapped
The sliceable image taken the photograph is 360 degree of images of panorama, and by 360 degree of observations without dead angle, attacking for terrorist can be found in advance
Hit intention.
Processor 10 is arranged in exploration vehicle main body, with running assembly 60, sensor assembly 50 and the phase of all cameras 20
Connection, processor 10 is used to control the action of running assembly 60 so as to drive anti-terrorism SEEK BUS to travel, the action bag of running assembly 60
Include：Steering, retrogressing, speedup or deceleration etc.；Processor 10 and range information for being detected according to sensor assembly 50 and all
The view data that camera 20 is shot, is positioned and is built map, is anti-terrorism SEEK BUS planning travel route, and control anti-terrorism is explored
Car automatic running；Processor 10 is additionally operable to the view data shot according to camera 20, identifies the default anti-terrorism mesh in image
Mark and its positional information, wherein, anti-terrorism target includes：Explosive and weapon.
As can be seen here, because the anti-terrorism SEEK BUS that the application is provided can detect anti-terrorism SEEK BUS and week by sensor assembly
Enclose the range information of object and the image of surrounding environment is shot by camera, and can under the control of a processor, according to these
Range information and view data, carry out unmanned and anti-terrorism target identification so that anti-terrorism SEEK BUS can be in terrorist or quick-fried
Searched for automatically in the environment that fried thing is concealed, lean out the position of anti-terrorism target, allowed anti-terrorism officer in the place away from hazardous environment, lead to
Cross the anti-terrorism target and its positional information identified, it is on the spot in person as understand site environment, precisely make next step action
Decision, reduce unnecessary casualties.
In some embodiments, exploring vehicle main body 1 includes front and rear, and front and rear is respectively arranged with two shootings
Head, wherein, after the view data that an anterior camera and a camera at rear portion are shot is handled through merging algorithm for images,
Sliceable generation one panorama, 360 degree of images, therefore, the view data of at least four cameras 20 shooting of the application is through image
At least two panoramas, 360 degree of images can be produced after splicing.In the specific implementation, two cameras that front and rear is set respectively
Primary optical axis be horizontal direction.
Specifically, with reference to Fig. 2, processor 10 includes：Object-recognition unit 17 and unmanned unit 18.Target identification list
The view data that member 17 is shot according to camera 20, identification anti-terrorism target and its positional information.Unmanned unit 18 includes
SLAM modules, anti-terrorism SEEK BUS and the range information of surrounding objects that unmanned unit 18 can be detected according to sensor assembly 50
The image shot with least four camera 20, is positioned and is built map, and plan travel route, control for anti-terrorism SEEK BUS
Running assembly 60 processed carries out corresponding actions so that anti-terrorism SEEK BUS automatic running.In some embodiments, processor 10 also includes：
Avoidance unit 19, the distance that avoidance unit 19 is used for the anti-terrorism SEEK BUS and surrounding objects detected according to sensor assembly 50 is believed
Breath, sends control signal control running assembly 60 and is acted timely avoidance accordingly.
As shown in Fig. 2 the anti-terrorism SEEK BUS of the application also includes：Data outputting module 40, data outputting module 40 and place
Reason device 10 is connected, the anti-terrorism target and its positional information recognized for being wirelessly transferred.
With reference to Fig. 3, in some embodiments, the anti-terrorism SEEK BUS of the application also includes：D GPS locating module 30, GPS location mould
Block 30 is connected with processor 10, the current geographic position information for obtaining anti-terrorism SEEK BUS in real time；Wherein, processor 10 is gone back
Including：Image processing module 12, deep learning module 13 and depth of field detection module 14.
Image processing module 12 is used to obtain the view data that all cameras 20 are shot, and is entered using merging algorithm for images
Row image mosaic, generates at least two panoramas, 360 degree of images.In one embodiment, image processing module 12 also includes vision
Module, the vision module is used for before the image that 12 pairs of all cameras 20 of image processing module are shot splices, and first carries out
Pretreatment of the anti-distortion with going noise.
Deep learning module 13 is connected with image processing module 12, for using deep learning algorithm recognize this at least two
Anti-terrorism target in individual 360 degree of images of panorama.The concept of deep learning comes from the research of artificial neural network, is to set up, simulates
Human brain carries out the neutral net of analytic learning, explains data by imitating the mechanism of human brain, deep learning is by combining low layer
Feature formation more abstract high-rise expression attribute classification or feature, are represented with the distributed nature for finding view data, so that
Identify and anti-terrorism target is preset in image.
360 degree of images of panorama that foregoing image processing module 12 is generated, the image for being 2D can not therefrom know each identification
The depth of view information of anti-terrorism target out, can not just extrapolate the specific locus of each object.Depth of field detection module 14 with
Image processing module 12 is connected with deep learning module 13, compares at least two panorama, 360 degree of images, is imaged using triangle
Rule, can obtain the depth of view information for the anti-terrorism target that deep learning module 13 is recognized.According to the depth of view information, so that it may calculate anti-
Probably target and the relative position information of anti-terrorism SEEK BUS, are combining the geographical position for the anti-terrorism SEEK BUS that d GPS locating module 30 is obtained
Confidence ceases, and can obtain the accurate geographical location information of anti-terrorism target.For example, the current geographic position of anti-terrorism SEEK BUS is<xa,
ya,za>, and the depth of view information of anti-terrorism target is<xb,yb,zb>, then the accurate geographical position of anti-terrorism target is<xa+xb,ya
+yb,za+zb>。
In one embodiment, processor 10 also includes：Data Integration module 16, Data Integration module 16 and deep learning mould
Block 13, depth of field detection module 14 are connected with d GPS locating module 30, the anti-terrorism target that is recognized according to deep learning module 13,
Depth of field detection module 14 calculates the current geographic position information that obtained depth of view information and d GPS locating module 30 are obtained, generation one
Individual 360 degree of video flowings of panorama, 360 degree of video flowings of the panorama include the beacon information and geographical location information of anti-terrorism target.Specifically
During embodiment, 360 degree of video stream datas of the panorama are wirelessly transferred by data outputting module 40；Processor 10 also includes building map
Module so that the beacon information and its geographical location information of anti-terrorism target are in video with the formal presentation of map.
As can be seen here, the application on 360 degree of videos of panorama by being superimposed current geographic position information, anti-terrorism target designation
Information and depth of view information, can help the hiding position of anti-terrorism officer's precise positioning terrorist or explosive, recognize in advance
Potential danger in anti-terrorism environment, makes more rationally efficient tactical disposition, it is to avoid unnecessary casualties occur, ensure
The personal safety of anti-terrorism soldier.
With reference to Fig. 4, correspondingly, the application also provides a kind of wearable device, including：Data reception module 24 and VR are shown
Module 20, also includes regular display 21 in some embodiments, the following detailed description of.
Data reception module 24 is used to receive anti-terrorism target information and its positional information that above-mentioned anti-terrorism SEEK BUS is identified.
In certain embodiments, reception be above-mentioned data outputting module 40 be wirelessly transferred and come include anti-terrorism target beacon information and
360 degree of video flowings of panorama of geographical location information.
VR display modules 20 are used to rebuild the anti-terrorism target information and its positional information in reality environment, and are regarded
Frequency is played.In certain embodiments, beacon information and the geographical position of anti-terrorism target are included for being rebuild in reality environment
360 degree of video flowings of panorama of information, and carry out video playback.
Common display module 21 is connected with data reception module 24, for playing the panorama 360 by regular display
Video flowing is spent, so that anti-terrorism officer observes the position of anti-terrorism target.
By dressing the wearable device (such as VR glasses), it may be such that anti-terrorism soldier locks terrorist or explosive in advance
Position, obtain accurately battle field information, it is to avoid rashly into hazardous environment, unpredictable dangerous situation occur, cause not
Necessary personal injury.
With reference to Fig. 5, based on above-mentioned anti-terrorism SEEK BUS and wearable device, present invention also provides a kind of detection of virtual reality
System, the virtual reality detection system includes：Above-mentioned anti-terrorism SEEK BUS and wearable device.
In summary, what the virtual reality detection system can be wirelessly transferred by wearable device reception anti-terrorism SEEK BUS is complete
360 degree of video flowings of scape, the environmental aspect that local net cast terrorist or explosive outside away from hazardous environment conceal,
Site environment is understood as on the spot in person, and real-time anti-terrorism war place figure can be set up so that anti-terrorism soldier has to anti-terrorism battlefield
It is apparent from, so as to precisely make the decision of next step action.
Embodiment two：
Based on a kind of anti-terrorism SEEK BUS of embodiment, present invention also provides a kind of anti-terrorism SEEK BUS object localization method,
This method includes：
(1) using the image of at least four camera surrounding environment, sliceable captured image is at least two panoramas
360 degree of images；
(2) anti-distortion is first carried out to the image of camera surrounding environment and goes noise, then carry out image mosaic, after splicing
At least two panoramas, 360 degree of images carry out deep learnings, recognize wherein default anti-terrorism target；
(3) compare at least two panorama, 360 degree of images, rule is imaged using triangle, obtain by deep learning identification
The depth of view information of the anti-terrorism target arrived, so as to obtain the relative position information between anti-terrorism target and anti-terrorism SEEK BUS；
(4) current geographic position information of anti-terrorism SEEK BUS is obtained, it is relative with anti-terrorism SEEK BUS in conjunction with anti-terrorism target
Positional information, obtains the accurate geographical location information of anti-terrorism target；
(5) according to the beacon information and geographical location information of anti-terrorism target, build corresponding map and present, and with video shape
Formula is played in reality environment by wearable device.
It will be understood by those skilled in the art that all or part of function of various methods can pass through in above-mentioned embodiment
The mode of hardware is realized, can also be realized by way of computer program.When all or part of function in above-mentioned embodiment
When being realized by way of computer program, the program can be stored in a computer-readable recording medium, and storage medium can
With including：Read-only storage, random access memory, disk, CD, hard disk etc., perform the program above-mentioned to realize by computer
Function.For example, by program storage in the memory of equipment, when passing through computing device memory Program, you can in realization
State all or part of function.In addition, when in above-mentioned embodiment all or part of function realized by way of computer program
When, the program can also be stored in the storage mediums such as server, another computer, disk, CD, flash disk or mobile hard disk
In, by download or copying and saving into the memory of local device, or version updating is carried out to the system of local device, when logical
When crossing the program in computing device memory, you can realize all or part of function in above-mentioned embodiment.
Use above specific case is illustrated to the present invention, is only intended to help and is understood the present invention, not to limit
The system present invention.For those skilled in the art, according to the thought of the present invention, it can also make some simple
Deduce, deform or replace.
Claims (10)
1. a kind of anti-terrorism SEEK BUS, it is characterised in that including：
Vehicle main body is explored, the running assembly of driving anti-terrorism SEEK BUS traveling is provided with, the exploration vehicle main body is by explosion-proof lamp bag
Wrap up in, wherein, running assembly at least includes wheel；
Sensor assembly, is arranged in exploration vehicle main body, the sensor assembly at least includes：Radar and ultrasonic sensor,
Range information for detecting anti-terrorism SEEK BUS and surrounding objects；
At least four cameras, are arranged in exploration vehicle main body, the image for shooting surrounding environment；
Processor, is arranged at exploring in vehicle main body, is connected with the running assembly, sensor assembly and at least four cameras
Connect, for controlling the running assembly action so as to drive anti-terrorism SEEK BUS to travel, and for being examined according to the sensor assembly
The view data that the range information of survey and at least four camera are shot, is positioned and is built map, be anti-terrorism SEEK BUS
Travel route is planned, anti-terrorism SEEK BUS automatic running is controlled；It is additionally operable to from described image data, identifies default anti-terrorism mesh
Mark and its positional information, wherein, anti-terrorism target includes：Explosive and weapon.
2. anti-terrorism SEEK BUS as claimed in claim 1, it is characterised in that also include：Data outputting module, the data output
Module is connected with processor, the anti-terrorism target and its positional information recognized for being wirelessly transferred.
3. anti-terrorism SEEK BUS as claimed in claim 1, it is characterised in that also include：D GPS locating module, the GPS location mould
Block is connected with processor, the current geographic position information for obtaining anti-terrorism SEEK BUS in real time.
4. anti-terrorism SEEK BUS as claimed in claim 1, it is characterised in that the processor is used to be examined according to sensor assembly 50
The anti-terrorism SEEK BUS and the range information of surrounding objects of survey, send control signal control running assembly 60 and carry out corresponding action and keep away
Barrier.
5. anti-terrorism SEEK BUS as claimed in claim 1, it is characterised in that the exploration vehicle main body includes front and rear, preceding
Portion and rear portion are respectively arranged with two cameras, wherein, the figure that an anterior camera and a camera at rear portion are shot
As the view data warp that data can produce 360 degree of images of a panorama after image mosaic, and at least four camera is shot
At least two panoramas, 360 degree of images can be produced after image mosaic.
6. anti-terrorism SEEK BUS as claimed in claim 5, it is characterised in that the processor also includes：
Image processing module, for obtaining the view data that at least four camera is shot, and carries out image mosaic, generates
At least two 360 degree of panorama images；
Deep learning module, is connected with described image processing module, for recognizing in described at least two panoramas, 360 degree of images
Anti-terrorism target；
Depth of field detection module, is connected with described image processing module and deep learning module, relatively more described at least two panorama
360 degree of images, rule is imaged using triangle, obtains the depth of view information for the anti-terrorism target that deep learning module is recognized.
7. anti-terrorism SEEK BUS as claimed in claim 6, it is characterised in that described image processing module also includes：Vision module,
The vision module is used for before the image that described image processing module is shot at least four camera splices, first
Carry out pretreatment of the anti-distortion with going noise.
8. anti-terrorism SEEK BUS as claimed in claims 6 or 7, it is characterised in that the processor also includes：Data Integration mould
Block, the Data Integration module is connected with the deep learning module, depth of field detection module and d GPS locating module, according to institute
State that the anti-terrorism target, depth of field detection module that deep learning module recognizes calculate the obtained depth of view information and GPS is fixed
The current geographic position information that position module is obtained, generates 360 degree of video flowings of a panorama, described 360 degree of video flowings of panorama
Beacon information and geographical location information including anti-terrorism target.
9. a kind of wearable device, it is characterised in that including：
Data reception module, for receive anti-terrorism target information that anti-terrorism SEEK BUS as claimed in claim 1 identifies and its
Positional information；
VR display modules, are connected with the data reception module, for rebuilding the anti-terrorism target letter in reality environment
Breath and its positional information, and carry out video playback.
10. a kind of virtual reality detection system, it is characterised in that including anti-terrorism SEEK BUS as claimed in claim 1 and as weighed
Profit requires the wearable device described in 9.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108093241A (en) * | 2017-11-03 | 2018-05-29 | 国网河南省电力公司检修公司 | A kind of valve Room intelligent patrol detection sampler based on VR technologies |
| US10390003B1 (en) | 2016-08-29 | 2019-08-20 | Perceptln Shenzhen Limited | Visual-inertial positional awareness for autonomous and non-autonomous device |
| US10437252B1 (en) | 2017-09-08 | 2019-10-08 | Perceptln Shenzhen Limited | High-precision multi-layer visual and semantic map for autonomous driving |
| US10794710B1 (en) | 2017-09-08 | 2020-10-06 | Perceptin Shenzhen Limited | High-precision multi-layer visual and semantic map by autonomous units |
| CN111824371A (en) * | 2020-07-23 | 2020-10-27 | 张月云 | Safety distance identification platform and method applying type analysis |
| US11328158B2 (en) | 2016-08-29 | 2022-05-10 | Trifo, Inc. | Visual-inertial positional awareness for autonomous and non-autonomous tracking |
| US11774983B1 (en) | 2019-01-02 | 2023-10-03 | Trifo, Inc. | Autonomous platform guidance systems with unknown environment mapping |
| US11842500B2 (en) | 2016-08-29 | 2023-12-12 | Trifo, Inc. | Fault-tolerance to provide robust tracking for autonomous and non-autonomous positional awareness |
| US11953910B2 (en) | 2016-08-29 | 2024-04-09 | Trifo, Inc. | Autonomous platform guidance systems with task planning and obstacle avoidance |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN200988219Y (en) * | 2006-12-26 | 2007-12-12 | 上海市延安中学 | Intelligent anti-terrorist explosive defusing robot |
| CN104149782A (en) * | 2014-07-31 | 2014-11-19 | 同济大学 | Automatic driving system of magnetic-navigation based multi-sensor fusion intelligent vehicle |
| CN105005304A (en) * | 2015-03-26 | 2015-10-28 | 嘉兴市德宝威微电子有限公司 | Anti-terrorism robot |
| CN105974920A (en) * | 2016-06-14 | 2016-09-28 | 北京汽车研究总院有限公司 | Unmanned driving system |
| CN106003064A (en) * | 2016-06-17 | 2016-10-12 | 上海工程技术大学 | Complex-environment multi-sensor intelligent detection robot |
| CN106394545A (en) * | 2016-10-09 | 2017-02-15 | 北京汽车集团有限公司 | Driving system, unmanned vehicle and vehicle remote control terminal |
| CN207164772U (en) * | 2017-08-22 | 2018-03-30 | 深圳普思英察科技有限公司 | A kind of anti-terrorism SEEK BUS, wearable device and virtual reality detection system |
-
2017
- 2017-08-22 CN CN201710724530.4A patent/CN107273881A/en not_active Withdrawn
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN200988219Y (en) * | 2006-12-26 | 2007-12-12 | 上海市延安中学 | Intelligent anti-terrorist explosive defusing robot |
| CN104149782A (en) * | 2014-07-31 | 2014-11-19 | 同济大学 | Automatic driving system of magnetic-navigation based multi-sensor fusion intelligent vehicle |
| CN105005304A (en) * | 2015-03-26 | 2015-10-28 | 嘉兴市德宝威微电子有限公司 | Anti-terrorism robot |
| CN105974920A (en) * | 2016-06-14 | 2016-09-28 | 北京汽车研究总院有限公司 | Unmanned driving system |
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