CN106092086A - A kind of quick, robot indoor orientation method of high robust based on panoramic vision - Google Patents
A kind of quick, robot indoor orientation method of high robust based on panoramic vision Download PDFInfo
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- CN106092086A CN106092086A CN201610407064.2A CN201610407064A CN106092086A CN 106092086 A CN106092086 A CN 106092086A CN 201610407064 A CN201610407064 A CN 201610407064A CN 106092086 A CN106092086 A CN 106092086A
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- 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
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- 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
Abstract
The invention belongs to mobile robot visual field of locating technology, be specifically related to a kind of quick, robot indoor orientation method of high robust based on panoramic vision.The present invention includes: (1) designs road sign based on SURF characteristic point；(2) road sign of design is quickly accurately identified by the SURF Feature Points Matching algorithm using improvement in panoramic picture；(3) robot accurate location at place two-dimensional space is calculated according to the recognition result of three road signs of setting in environment.Present invention achieves the indoor positioning function of mobile robot, the robot localization task being applicable under complex indoor environment, can be widely applied in the navigation of home-services robot, industrial robot, the rapidity of algorithm and robustness can ensure that robot has more accurate stationkeeping ability in motor process.
Description
Technical field
The invention belongs to mobile robot visual field of locating technology, be specifically related to a kind of based on panoramic vision quick,
The robot indoor orientation method of high robust.
Background technology
The self-align problem of mobile robot is always underlying issue and the hot issue in robot research field.Machine regards
Feel contain much information by it, the advantage such as cheap, be widely used in the research of robot localization.
In traditional vision positioning method, localization method based on physical feature typically requires the substantial amounts of feature of extraction,
Algorithm operation quantity more greatly, does not possess real-time, and is vulnerable to light change or environmental change is affected.Based on artificial landmark determine
Method for position the most then has higher motility, just can be targetedly to road sign by the feature of manually-set road sign
It is identified, reduces the design difficulty of recognizer, improve efficiency of algorithm.
In the selection of sensor, omni-directional visual can obtain the comprehensive visual field of 360 degree, with traditional visual imaging
Equipment is compared and can be obtained more environmental information, and the research for this technology the most in recent years has obtained significant progress.So
And the image that panorama camera is collected is the image having distortion, the colouring information of road sign is the most generally utilized to position,
The light of environment is just required higher by this, and requires not exist in environment the interference of same color, and poor robustness is difficult to application
In the environment of more complicated.
The method of present invention design solves indoor positioning rapidity and the robustness problem of mobile robot, establishes whole
Individual indoor locating system, has important reference for robot chamber inner position, may be directly applied to home services machine
The fields such as device people, industrial robot.
Summary of the invention
Object of the present invention is to provide based on panoramic vision quick, the high robust under a kind of complex indoor environment
Robot indoor orientation method.
The object of the present invention is achieved like this:
(1) road sign based on SURF characteristic point is designed；
(1.1) utilize SURF feature point extraction algorithm that circle, triangle, tetragon, pentagonal basis geometry are entered
Row feature point detection, the feature recording each shape is counted；
(1.2) in the environment of these shapes being positioned over difference, utilize panoramic vision to its imaging, every in record image
The characteristic point of geometry and the matching rate of shape exemplary feature point；
(1.3) by being analyzed the data of record, comprehensive Design goes out readily identified road sign shape；
(2) road sign of design is quickly carried out accurately by the SURF Feature Points Matching algorithm using improvement in panoramic picture
Identify；
(2.1) according to refraction-reflection panorama camera image-forming principle, panoramic picture exists one with image center of fiqure as circle
The circle of the heart, the object point being positioned in same level with curved mirror focus will be imaged on this circle, utilizes this circle characteristic by road
Mark is arranged at higher than on the wall of video camera, by pixel within the circle zero setting during feature point detection；
(2.2) a circular detection window is set, is determined by experiment the correct radial of window, reduces feature further
Point detection region, simplifies region of search, shortens operation time；
(2.3) by the extraction to road sign outline, it is determined that the profile of road sign center circle, by calculating the circle of center circle
Being accurately positioned of the existing road sign of excess of the heart；
(2.4) successfully identify the road sign that recognizes after road sign as new template, real-time update template；
(3) robot standard at place two-dimensional space is calculated according to the recognition result of three road signs of setting in environment
Really position；
(3.1) place three road signs being higher than robot in the environment, three road signs are identified, determine that it is at panorama
Coordinate in image, calculates and the angle of panorama center of fiqure；
(3.2) two equation of a circles are determined according to two angle values and known road sign actual coordinate；
(3.3) two equation of a circle simultaneous being tried to achieve two intersection points, one of them is the coordinate of middle road sign, and another is
The two-dimensional coordinate of robot.
The beneficial effects of the present invention is:
Present invention achieves the indoor positioning function of mobile robot, it is adaptable to the robot localization under complex indoor environment
Task, can be widely applied in the navigation of home-services robot, industrial robot, and the rapidity of algorithm and robustness can ensure
Robot has more accurate stationkeeping ability in motor process.
Accompanying drawing explanation
Fig. 1 is the road sign of design in the present invention；
Fig. 2 is the landmark identification algorithm flow chart based on SURF characteristic matching improved in the present invention.
Fig. 3 is the system architecture diagram of the present invention；
Detailed description of the invention
The present invention is described in detail below in conjunction with the accompanying drawings.
The present invention devises a kind of quick, mobile robot indoor orientation method of high robust based on artificial landmark,
Including artificial landmark design, landmark identification algorithm based on panoramic vision and location algorithm.For color road sign by light intensity shadow
Ring big problem and devise the road sign of beneficially Feature point recognition, it is proposed that the artificial landmark recognizer of distinguished point based, profit
By the shape information (characteristic point) of road sign rather than colouring information carries out landmark identification, overcoming colour recognition algorithm is affected by light intensity
Problem；The mistake that the factors such as, pattern distortion big for panoramic picture feature extraction operand, visual angle change and circumstance complication cause
Identification problem, improves on the basis of traditional characteristic point matching algorithm, by reducing detection region, arranging detection window, reality
Time the method such as more new template devise one landmark identification algorithm fast and accurately；By arranging three road signs in indoor, on road
The location algorithm of robot is achieved on the basis of mark recognizer.Present invention achieves the indoor positioning merit of mobile robot
Can, it is adaptable to the robot localization task under complex indoor environment, can be widely applied to home-services robot, industrial robot
Navigation in, the rapidity of algorithm and robustness can ensure that robot has more accurate stationkeeping ability in motor process.
Quick, the robot indoor orientation method of high robust based on panoramic vision, devises the shape of artificial landmark,
The SURF Feature Points Matching algorithm improved is utilized road sign in panoramic picture to be identified, by recognizing the position of three road signs
Carry out the robot absolute fix at two-dimensional space.Wherein:
(1) road sign based on SURF feature point detection algorithm design, the road sign of design has more characteristic point, it is easy to know
Not and be accurately positioned；
(2) traditional SURF Feature Points Matching algorithm is improved, improve rapidity and the standard of identification that algorithm runs
Really property, quickly accurately identifies the road sign of design in panoramic picture；
(3) robot standard at place two-dimensional space is calculated according to the recognition result of three road signs of setting in environment
Really position.
In some embodiments, artificial landmark design particularly as follows:
(1) utilize SURF feature point extraction algorithm that the basis geometry such as circle, triangle, tetragon, pentagon are carried out
Feature point detection, the feature recording each shape is counted；
(2) in the environment of these shapes being positioned over difference, utilize panoramic vision to its imaging, the most several in record image
The characteristic point of what shape and the matching rate of shape exemplary feature point；
(3) by being analyzed the data of record comprehensive Design and go out readily identified road sign shape, this road sign has not
Being prone to characteristic point and the more beneficially identification of characteristic point misidentified, the shape at the road sign center additionally designed is the most right
It is accurately positioned.
In some embodiments, improvement SURF Feature Points Matching algorithm particularly as follows:
(1) according to the image-forming principle of refraction-reflection panorama camera, panoramic picture exists one with image center of fiqure as circle
The circle of the heart, the object point being positioned in same level with curved mirror focus will be imaged on this circle, utilizes this circle characteristic by road
Mark is arranged at higher than on the wall of video camera, by pixel within the circle zero setting during feature point detection, reduces region of search, eliminates
Part interference；
(2) it is provided with a circular detection window, is determined through experimentation the correct radial of window, reduces further
Feature point detection region, simplifies region of search as far as possible, shortens operation time；
(3) by the extraction to road sign outline, it is determined that the profile of road sign center circle, by calculating the center of circle of center circle
Achieve being accurately positioned of road sign.
(4) successfully identify the road sign that recognizes after road sign as new template, real-time update template.
In some embodiments, localization method design particularly as follows:
(1) place three road signs being higher than robot in the environment, utilize the landmark identification method of the present invention to three roads
Mark is identified, and determines its coordinate in panoramic picture, calculates and the angle of panorama center of fiqure；
(2) two equation of a circles are determined according to two angle values and known road sign actual coordinate；
(3) two equation of a circle simultaneous being tried to achieve two intersection points, one of them is the coordinate of middle road sign, and another is machine
The two-dimensional coordinate of device people.
(1) the road sign design of feature based Point matching
First the road sign being provided with some basic configurations is tested, including annulus, triangle, rectangle, pentagon, six limits
Shape and five-pointed star, to select axisymmetric shape be to ask for central point for convenience thus positions, a size of 290mm ×
400mm.These road signs are placed in three different indoor environments, utilize panoramic vision to gather image, detection characteristic point.Will
Road sign is placed in the position remote away from camera 3m, the characteristic point detected and template is mated, according to correct of characteristic point
Join quantitative analysis to go out: the feature correctly matched is counted and is directly proportional to its angle point quantity.Therefore road sign as shown in Figure 1 is devised
Shape.Symmetrical shape ensures that each visual angle all has identical resolution；Road sign exists more angle point and ensures higher
Discrimination；The circle at the center target that is conducive to satisfying the need is accurately positioned.
(2) the landmark identification algorithm based on SURF Feature Points Matching improved
In order to improve the speed of service and the recognition success rate of algorithm, a series of means are utilized to reduce lane marker detection region.Dynamic
State updates road sign masterplate and eliminates the impact that pattern distortion brings, and final design recognizer flow chart sees Fig. 2.
First, according to panorama camera image-forming principle, at curved mirror ideally, in panoramic picture, there is one to scheme
As center of fiqure is the circle in the center of circle, the object point being positioned in same level with curved mirror focus will be imaged on this circle.Indoor set
The space of device people is plane, then the object point that the pixel on this circle is always in same level, higher than this height
The pixel that object is corresponding is positioned at above this circle.In order to avoid blocking of ground object, the placing height of road sign is more than in robot
The setting height(from bottom) of panorama camera.Therefore can utilize the pixel that this characteristic will be located in outside this circle as feature point detection region,
Rest of pixels Ignore All, had the most both improve the speed of service, and had eliminated a part of noise spot, improve matching rate.
Then, the road sign center recognized is arranged a circular detection window as the center of circle, by the region in this circle
As detecting the region of characteristic point next time, further reduce detection region.According to image-forming principle and mobile robot
Actual speed, determines robot displacement in panoramic picture in the road sign unit interval under motion conditions, is set to P picture
Element, if landmark identification algorithm cycle of operation is t, then circle detection windows radius is P*t, and trying to achieve P is 305 pixels, takes t=
1s, does not affect the identification of road sign in time testing the detection window of this radius robot motion, further increase recognition speed,
Eliminate part noise spot.
It follows that it is different to there is, for panoramic picture, the shape that distorts under distortion and different visual angles, the present invention is by the most more
The method of new road sign template, using the road sign at characteristic point place that matches every time as new mould after initializing road sign template
Plate, the method that cooperation is reduced detection region, in the case of execution cycle is short, robot motion's a small distance will update
Template, is ensured the accuracy of template matching.
Finally, after determining the region of road sign, in order to obtain higher positioning precision, it is thus necessary to determine that road sign center institute
Exact position, i.e. in the road sign designed herein circle the center of circle position.First to the region detected from background
Separate, utilize the marginal information of Canny operator extraction road sign.Pixel shared by the profile of road sign center circle seldom and distorts
More serious, so being difficult with the means such as Hough loop truss to detect center circle.The present invention first passes through search area maximum
Profile finds the outward flange of road sign, obtains the center of fiqure that road sign is overall on this basis, and center circle is closest from center of fiqure
One profile, is therefore i.e. the center circle of road sign from one group of pixel sequence closed that center of fiqure distance is minimum, obtains this profile
Center is the position at road sign center.
(3) location algorithm
Seeing Fig. 3, this system is by more than three road signs, equipped with the mobile robot of panoramic camera and data handling system
Composition.Utilize three artificial landmarks set, use triangle polyester fibre algorithm based on panoramic vision to realize robot localization.Three
Angle location algorithm i.e. places the artificial landmark of more than three in experimental enviroment, utilize three road signs in panoramic picture relative to
The angular relationship of robot according to geometrical principle so that it is determined that robot is at the coordinate of two-dimensional space.Its algorithm principle is: if
The coordinate of known two road signs, P1 (x1, y1), P2 (x2, y2) and the angle a from robot to two road sign line1Also may be used
With identify road sign success after directly try to achieve, then can determine a circle according to these three amount, according to same arc to angle of circumference
Equal principle, robot must be on this circle, and condition that this satisfactory foot is following:
1) P1 (x1, y1), P2 (x2, y2) meet the equation of circle；
2) robot is equal to a to the angle of two road signs1。
So any two road sign and their angle then corresponds to the equation of a circle, when the road sign number in image is
N, and during N >=3, N (N-1)/2 equation of a circle can be obtained.Owing to being multiple road signs in terms of same viewpoint, viewpoint one is scheduled on these
On the intersection point of circle, the intersection point solving these equation of a circles is coordinate i.e. the coordinate of video camera photocentre, i.e. machine of this viewpoint
People position.
Claims (1)
1. quick, the robot indoor orientation method of high robust based on panoramic vision, it is characterised in that include as follows
Step:
(1) road sign based on SURF characteristic point is designed；
(1.1) utilize SURF feature point extraction algorithm that circle, triangle, tetragon, pentagonal basis geometry are carried out spy
Levying a detection, the feature recording each shape is counted；
(1.2), in the environment of these shapes being positioned over difference, utilize panoramic vision to its imaging, the every geometry in record image
The characteristic point of shape and the matching rate of shape exemplary feature point；
(1.3) by being analyzed the data of record, comprehensive Design goes out readily identified road sign shape；
(2) road sign of design is quickly accurately known by the SURF Feature Points Matching algorithm using improvement in panoramic picture
Not；
(2.1) according to refraction-reflection panorama camera image-forming principle, panoramic picture exists one with image center of fiqure as the center of circle
Circle, the object point being positioned in same level with curved mirror focus will be imaged on this circle, utilizes this circle characteristic to be set by road sign
It is placed higher than on the wall of video camera, by pixel within the circle zero setting during feature point detection；
(2.2) a circular detection window is set, is determined by experiment the correct radial of window, reduces feature spot check further
Survey region, simplify region of search, shorten operation time；
(2.3) by the extraction to road sign outline, it is determined that the profile of road sign center circle, real by calculating the center of circle of center circle
Being accurately positioned of existing road sign；
(2.4) successfully identify the road sign that recognizes after road sign as new template, real-time update template；
(3) the robot accurate position at place two-dimensional space is calculated according to the recognition result of three road signs of setting in environment
Put；
(3.1) place three road signs being higher than robot in the environment, three road signs are identified, determine that it is at panoramic picture
In coordinate, calculate and the angle of panorama center of fiqure；
(3.2) two equation of a circles are determined according to two angle values and known road sign actual coordinate；
(3.3) two equation of a circle simultaneous being tried to achieve two intersection points, one of them is the coordinate of middle road sign, and another is machine
The two-dimensional coordinate of people.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106709942A (en) * | 2016-12-13 | 2017-05-24 | 广州智能装备研究院有限公司 | Panoramic image mistaken matching elimination method based on characteristic azimuth |
| CN106767833A (en) * | 2017-01-22 | 2017-05-31 | 电子科技大学 | A kind of robot localization method of fusion RGBD depth transducers and encoder |
| CN106908040A (en) * | 2017-03-06 | 2017-06-30 | 哈尔滨工程大学 | A kind of binocular panorama visual robot autonomous localization method based on SURF algorithm |
| CN107145906A (en) * | 2017-05-02 | 2017-09-08 | 哈尔滨工程大学 | A kind of method quickly gone home in mobile robot room based on panoramic vision imaging system |
| CN107478228A (en) * | 2017-07-13 | 2017-12-15 | 杭州品铂科技有限公司 | A kind of indoor orientation method |
| CN108122252A (en) * | 2016-11-26 | 2018-06-05 | 沈阳新松机器人自动化股份有限公司 | A kind of image processing method and relevant device based on panoramic vision robot localization |
| CN108446725A (en) * | 2018-03-12 | 2018-08-24 | 杭州师范大学 | A kind of Image Feature Matching method of feature based triangle |
| CN109099915A (en) * | 2018-06-27 | 2018-12-28 | 未来机器人（深圳）有限公司 | Method for positioning mobile robot, device, computer equipment and storage medium |
| CN109141432A (en) * | 2018-09-19 | 2019-01-04 | 西安科技大学 | A kind of indoor positioning air navigation aid assisted based on image space and panorama |
| CN109974722A (en) * | 2019-04-12 | 2019-07-05 | 珠海市一微半导体有限公司 | A kind of the map rejuvenation control method and map rejuvenation control system of vision robot |
| CN110332938A (en) * | 2019-06-20 | 2019-10-15 | 南京航空航天大学 | A kind of indoor monocular method for self-locating based on mobile phone |
| CN110928311A (en) * | 2019-12-16 | 2020-03-27 | 哈尔滨工业大学 | Indoor mobile robot navigation method based on linear features under panoramic camera |
| CN111966041A (en) * | 2020-08-26 | 2020-11-20 | 珠海格力电器股份有限公司 | Robot control method and device |
| CN113791377A (en) * | 2021-09-09 | 2021-12-14 | 中国科学院微小卫星创新研究院 | Positioning method based on angle measurement |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100329513A1 (en) * | 2006-12-29 | 2010-12-30 | Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. | Apparatus, method and computer program for determining a position on the basis of a camera image from a camera |
| US20110046838A1 (en) * | 2009-08-20 | 2011-02-24 | Hung-Yin Tsai | Automatic search system and method |
| CN102135429A (en) * | 2010-12-29 | 2011-07-27 | 东南大学 | Robot indoor positioning and navigating method based on vision |
| CN103901895A (en) * | 2014-04-18 | 2014-07-02 | 江苏久祥汽车电器集团有限公司 | Target positioning method based on unscented FastSLAM algorithm and matching optimization and robot |
| CN104007760A (en) * | 2014-04-22 | 2014-08-27 | 济南大学 | Self-positioning method in visual navigation of autonomous robot |
-
2016
- 2016-06-12 CN CN201610407064.2A patent/CN106092086B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100329513A1 (en) * | 2006-12-29 | 2010-12-30 | Fraunhofer-Gesellschaft Zur Foerderung Der Angewandten Forschung E.V. | Apparatus, method and computer program for determining a position on the basis of a camera image from a camera |
| US20110046838A1 (en) * | 2009-08-20 | 2011-02-24 | Hung-Yin Tsai | Automatic search system and method |
| CN102135429A (en) * | 2010-12-29 | 2011-07-27 | 东南大学 | Robot indoor positioning and navigating method based on vision |
| CN103901895A (en) * | 2014-04-18 | 2014-07-02 | 江苏久祥汽车电器集团有限公司 | Target positioning method based on unscented FastSLAM algorithm and matching optimization and robot |
| CN104007760A (en) * | 2014-04-22 | 2014-08-27 | 济南大学 | Self-positioning method in visual navigation of autonomous robot |
Non-Patent Citations (2)
| Title |
|---|
| 王开宇等: "基于EKF的全景视觉机器人SLAM算法", 《计算机应用研究》 * |
| 陈明芽等: "单目视觉自然路标辅助的移动机器人定位方法", 《浙江大学学报（工学版）》 * |
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| CN106709942A (en) * | 2016-12-13 | 2017-05-24 | 广州智能装备研究院有限公司 | Panoramic image mistaken matching elimination method based on characteristic azimuth |
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| CN109099915B (en) * | 2018-06-27 | 2020-12-25 | 未来机器人（深圳）有限公司 | Mobile robot positioning method, mobile robot positioning device, computer equipment and storage medium |
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| US11892301B2 (en) | 2019-04-12 | 2024-02-06 | Amicro Semiconductor Co., Ltd. | Map update control method and map update control system for vision robot |
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| CN111966041A (en) * | 2020-08-26 | 2020-11-20 | 珠海格力电器股份有限公司 | Robot control method and device |
| CN113791377A (en) * | 2021-09-09 | 2021-12-14 | 中国科学院微小卫星创新研究院 | Positioning method based on angle measurement |
| CN113791377B (en) * | 2021-09-09 | 2024-04-12 | 中国科学院微小卫星创新研究院 | Positioning method based on angle measurement |
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