CN107515384A - The positioning of Indoor Robot based on UWB and multisensor and environmental modeling method - Google Patents
The positioning of Indoor Robot based on UWB and multisensor and environmental modeling method Download PDFInfo
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- CN107515384A CN107515384A CN201710801558.3A CN201710801558A CN107515384A CN 107515384 A CN107515384 A CN 107515384A CN 201710801558 A CN201710801558 A CN 201710801558A CN 107515384 A CN107515384 A CN 107515384A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0257—Hybrid positioning
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
Abstract
The invention discloses a kind of positioning of the Indoor Robot based on UWB and multisensor and environmental modeling method, in robot moving process, UWB labels send the pulse data bag being made up of ultra-wideband pulse and give UWB receivers, the time difference that UWB receivers reach pulse data bag by interchanger each receiver is sent to central processing unit, and central processing unit determines the position of UWB labels according to three side weighted mass center algorithmic preliminaries；Electronic compass gathers the current course angle information of robot, the ultrasonic signal that ultrasonic sensor collection currently returns, central processing unit gathers signal according to ultrasonic sensor and Kalman filtering algorithm obtains the positional information of barrier, and environmental map is updated；The positional information of the positions of the UWB labels that central processing unit primarily determines that according to double-deck Kalman filtering algorithm fusion, current course angle information and barrier, obtains robot currently accurate posture information.The present invention improves the precision, real-time and stability of positioning.
Description
Technical field
The present invention relates to robot localization technical field, is specifically related to a kind of indoor set based on UWB and multisensor
The positioning of device people and environmental modeling method.
Background technology
In open outdoor environment, it can obtain more accurately positioning by GPS positioning system, but environment indoors
In, gps signal decay is serious, and indoor environment is complicated, a variety of interference, noise be present, can not be accurately positioned.It is common at present
Indoor positioning technologies solution mainly have ultrasonic wave location technology, Bluetooth technology, infrared technology, REID,
Super-broadband tech, WLAN, light track and localization technology etc..Super-broadband tech UWB has low in energy consumption, anti-multipath effect
It is good, safe, system complexity is low, has the advantages that good temporal resolution, positioning precision can reach Centimeter Level, be adapted to
In the needs of following wireless location technology, it is accurately positioned and tracks available for static or mobile object.
《Indoor mobile robot ultrasonic sensor net localization method is studied》Ambient condition information is perceived using single-sensor,
Location information is optimized, but larger angle error be present, and is easily influenceed under half structure complex environment by non line of sight etc., its
Alignment system stability is inadequate.《Application study of the multi-sensor fusion technology in localization for Mobile Robot》A variety of biographies are merged
Sensor information, location information is merged using expanded Kalman filtration algorithm, but because robot motion's nonlinearity is higher, obtained
Positioning result larger error be present, and there is the problem of computationally intensive, real-time property is not high enough, system in Multi-sensor Fusion
Anti-interference and stability also have much room for improvement.
The content of the invention
It is an object of the invention to provide a kind of positioning of Indoor Robot based on UWB and multisensor and environmental modeling
Method, data computation complexity is on the one hand reduced, improve positioning real-time, another aspect UWB positioning is auxiliary with multisensor
Help positioning to be complementary to one another, improve the stability of positioning.
Solve the object of the invention technical solution be：The positioning of Indoor Robot based on UWB and multisensor with
Environmental modeling method, comprises the following steps：
Step 1, system is built, the system includes interchanger, UWB receivers, UWB labels, electronic compass, several ultrasounds
Wave sensor and central processing unit, wherein UWB receivers are laid on the ceiling, UWB labels, electronic compass and supersonic sensing
Device is fixed on robot platform, and interchanger connects UWB receivers and central processing unit by shielding netting wire；
Step 2, extraction environment fixed character, initialization context map；
In step 3, robot moving process, UWB labels send the pulse data bag being made up of ultra-wideband pulse and connect to UWB
Receipts machine, the time difference that UWB receivers reach pulse data bag by interchanger each receiver are sent to central processing unit, in
Central processor determines the position of UWB labels according to three side weighted mass center algorithmic preliminaries；
The current course angle information of step 4, electronic compass collection robot, ultrasonic sensor collection currently return super
Acoustic signals, central processing unit gathers signal according to ultrasonic sensor and Kalman filtering algorithm obtains the position letter of barrier
Breath, and environmental map is updated；
The position for the UWB labels that step 5, central processing unit primarily determine that according to double-deck Kalman filtering algorithm fusion, when
The positional information of preceding course angle information and barrier, robot currently accurate posture information is obtained, return again to step 3 and continue machine
The positioning of people and environmental modeling.
The step of this method also includes map being uploaded to high in the clouds.
Step 1 every 30-100 rice set a UWB receiver, each UWB receivers joined end to end by daisy chain or
The mode of star-like connection is connected with interchanger.
The environment fixed character that step 2 is extracted includes wall, desk, UWB base stations.
Three side weighted mass center algorithms of step 3 are specially：First from all UWB receivers for receiving pulse data bag
Optional three form one group, using each UWB receiver coordinates as the center of circle, are drawn by radius of the distance of UWB receivers to UWB labels
Circle；Then the triangle formed according to intersection point, seeks its center-of-mass coordinate (xk,yk), k=1,2 ... l, l are that the barycenter that combination obtains is total
Number；Then according to the bigger principle of the bigger position error of distance, be assigned to weights to the center-of-mass coordinate of each combination, wherein weights by
UWB labels determine to the reciprocal of corresponding centroid distance；Finally the barycenter of each combination is weighted to obtain final UWB tag locations
As a result, specific formula for calculation is as follows：
In formula, (xi,yi) it is center-of-mass coordinate, LiFor the distance with UWB labels to corresponding barycenter.
The double-deck Kalman filtering algorithm of step 5 is made up of two parts：Bottom Kalman filtering and top layer Kalman filtering, its
Middle bottom uses EKF model, to primarily determine that the positions of UWB labels as basic status, with current course angle
Information obtains Posterior estimator to prior estimate amendment, believed with extracting the relative position needed for the actual time of arrival as observation
Breath；Top layer uses Kalman filter model, and basic shape is used as using the robot displacement variable quantity in each ultrasonic wave observation cycle
The input of state renewal, the changing coordinates being calculated by ATOA methods are used as observation renewal, currently accurate to obtain robot
Posture information.
Compared with prior art, its remarkable advantage is the present invention：1) present invention uses UWB location technologies, is not easy by interior
The influence of the environmental factors such as light, non-line-of-sight propagation and multipath effect, anti-interference, stability are strong, and positioning precision is higher, positioning
Precision can reach Centimeter Level；2) present invention fusion multisensor auxiliary positioning, improves positioning precision, realizes under robot
The prediction of one pose；3) present invention uses three side weighted mass center location algorithms, reduces calculation error, improves positioning precision；
4) present invention fixes UWB receivers using absolute coordinate system, avoids the accumulated error that relative coordinate system positioning belt comes；5) this hair
It is bright to be believed using double-deck Kalman filtering algorithm process UWB label rough locations information, current course angle information and Obstacle Position
Breath, algorithm is filtered compared with individual layer Kalman filtering algorithm and spreading kalman, improves the precision of result；6) it is of the invention by robot position
Appearance and real-time map information deposit high in the clouds, improve resource utilization, while can also realize the multimachine interconnection of robot, resource
Shared and remote control.
Brief description of the drawings
Fig. 1 is flow chart of the method for the present invention.
Fig. 2 is the procedure chart of the double-deck Kalman filtering algorithm of the present invention.
Fig. 3 is the connected mode figure of central processing unit of the present invention, interchanger and UWB receivers.
Fig. 4 is UWB of the present invention and base station with the end to end connected mode figure of daisy chain.
Fig. 5 is for UWB of the present invention with base station with the star-like connected mode figure being connected.
Embodiment
Below in conjunction with the accompanying drawings and specific embodiment, the present invention program is expanded on further.
Embodiment 1：
In the embodiment of the present invention, first configure switch network parameter, according to every 30-100 rice or so principle in day
On card arrange UWB receivers, by each UWB receivers daisy chain join end to end or star-like connection by way of use gauze screen
Line is connected with interchanger, and localization region signal all standing on the one hand can be achieved, and on the other hand can reduce the deployment number of UWB receivers
Amount.The change of indoor environment will certainly influence signal attenuation degree, therefore UWB receivers place spacing and need to be had according to actual conditions
Adjusted.When careat is smaller, UWB receivers are each other away from being arranged on 30 meters or so, and the distance is unsuitable too small, otherwise easily
Interfere, influence positioning precision；When careat is larger, then receiver spacing can be amplified, it is left that maximum can reach 100
It is right.
Then, ultrasonic sensor, electronic compass, UWB positioning labels are fixed in robot, wherein supersonic sensing
Device is uniformly fixed on around robot platform at away from ground 20cm, and is tilted down with horizontal plane with 5 ° of angles.When robot is put down
Platform is smaller, then by least four ultrasonic sensor so that not less than e, (e design parameter will be according to the inspection of corresponding ultrasonic sensor
Curve is surveyed to determine) spacing be uniformly placed on robot platform, then can be by some sensors and when robot platform is larger
With 10cm between left and right away from placement.
Exchange data transmission port, ultrasonic sensor and electronic compass are connected with central processing unit again, UWB labels
Establish and connect with UWB receivers.
As shown in figure, it is after the completion of hardware connection, indoor environment is scaled on map, and extraction environment is fixed
Feature, such as wall, desk, UWB receivers, and it is uploaded to high in the clouds.This example uses Grid Method to be created with ARCGIS softwares
Initial map (receiver, reference label position will be labeled on map with point), specially represents clear, black with white
Represent that the mode of barrier marks out indoor object, and UWB receiver locations are outpoured with a case marker.When grid division is too small
When, processing data amount is excessive, and division is excessive and can influence positioning and path planning precision, therefore considers to determine grid size
In 1cm or so.
Then, in robot moving process, UWB labels send the pulse data bag being made up of ultra-wideband pulse repeatedly,
UWB receivers receive these pulse data bags and are uploaded to interchanger, and interchanger is powered by shielding netting wire to receiver, simultaneously
To receiver tranmitting data register source and serial communication data, and pulse data bag is reached to time difference (the i.e. TDOA of each receiver
Detection method) etc. data message central processing unit is uploaded to by the communication serial ports of interchanger, central processing unit adds according to three sides
Power centroid algorithm primarily determines that the position of positioning label, specifically, three side weighted mass center location algorithms, be it is determined that after distance,
Optional three form one group from all receivers for receiving pulse signal, using each receiver coordinate as the center of circle, measure
Receiver draws circle to positioning terminal distance for radius, the triangle then formed according to intersection point, seeks its barycenter.Then, according to away from
The principle bigger from bigger position error, weights are assigned to the center-of-mass coordinate of each combination, the weights are by UWB labels to corresponding matter
Heart distance (Lk) determination reciprocal.Finally, the result that each combination obtains is weighted to obtain final UWB tag location results
(x, y), specific formula for calculation are as follows：Wherein (xi,yi) sat for barycenter
Mark, liFor the distance with UWB labels to corresponding barycenter.
The current course angle information of robot is can obtain by electronic compass, by the return signal of ultrasonic sensor collection
Central processing unit is reached, central processing unit can obtain the positional information of barrier through Kalman filtering algorithm, and according to the position
Information real-time update high in the clouds cartographic information, i.e., the ultrasonic echo received using ultrasonic receiver, according to transmitting and receive
Between time difference can calculate ultrasonic sensor to the distance of barrier, with reference to the distance measurement result and robot posture information
Obstacle Position can be indicated on map, if the barrier overlaps with the sign in initial map, map is constant, it is on the contrary then
The obstacle information is added on map, i.e., is showed with black, to realize positioning and environmental modeling simultaneously.
Finally, the positional information of the UWB labels primarily determined that using double-deck Kalman filtering algorithm DLKF processing, current boat
To angle and as the obstacle position information obtained by ultrasonic sensor, to obtain robot currently accurate posture information.It is wherein double
Layer Kalman filtering algorithm includes bottom Kalman filtering and top layer Kalman filtering.Bottom uses EKF mould
Type, using UWB location informations as basic status, the current course angle information obtained using electronic compass is estimated as observation to priori
Meter amendment obtains Posterior estimator, and bottom is used as the relative position information needed for extraction actual time of arrival (ATOA)；Top layer uses
Kalman filter model, the displacement variable of each ultrasonic wave observation cycle inner machine people is defeated as basic status using in bottom
Enter, updated using current time by the changing coordinates that ATOA methods are calculated as observation, so as to obtain accurate UWB labels
Posture information.
Claims (6)
1. the positioning of the Indoor Robot based on UWB and multisensor and environmental modeling method, it is characterised in that including following step
Suddenly：
Step 1, system is built, the system includes interchanger, UWB receivers, UWB labels, electronic compass, several ultrasonic waves and passed
Sensor and central processing unit, wherein UWB receivers are laid on the ceiling, and UWB labels, electronic compass and ultrasonic sensor are consolidated
It is scheduled on robot platform, interchanger connects UWB receivers and central processing unit by shielding netting wire；
Step 2, extraction environment fixed character, initialization context map；
In step 3, robot moving process, UWB labels are sent to be received by the pulse data bag that ultra-wideband pulse forms to UWB
Machine, the time difference that UWB receivers reach pulse data bag by interchanger each receiver are sent to central processing unit, center
Processor determines the position of UWB labels according to three side weighted mass center algorithmic preliminaries；
The current course angle information of step 4, electronic compass collection robot, the ultrasonic wave that ultrasonic sensor collection currently returns
Signal, central processing unit gathers signal according to ultrasonic sensor and Kalman filtering algorithm obtains the positional information of barrier,
And environmental map is updated；
The position for the UWB labels that step 5, central processing unit primarily determine that according to double-deck Kalman filtering algorithm fusion, current boat
To the positional information of angle information and barrier, robot currently accurate posture information is obtained, step 3 is returned again to and continues robot
Positioning and environmental modeling.
2. the positioning of the Indoor Robot according to claim 1 based on UWB and multisensor and environmental modeling method, its
It is characterised by, this method is also including the step of map is uploaded into high in the clouds.
3. the positioning of the Indoor Robot according to claim 1 based on UWB and multisensor and environmental modeling method, its
Be characterised by, step 1 every 30-100 rice set a UWB receiver, each UWB receivers joined end to end by daisy chain or
The mode of star-like connection is connected with interchanger.
4. the positioning of the Indoor Robot according to claim 1 based on UWB and multisensor and environmental modeling method, its
It is characterised by, the environment fixed character that step 2 is extracted includes wall, desk, UWB base stations.
5. the positioning of the Indoor Robot according to claim 1 based on UWB and multisensor and environmental modeling method, its
It is characterised by, three side weighted mass center algorithms of step 3 are specially：First from all UWB receivers for receiving pulse data bag
In it is optional three form one group, using each UWB receiver coordinates as the center of circle, using the distance of UWB receivers to UWB labels as radius
Draw circle；Then the triangle formed according to intersection point, seeks its center-of-mass coordinate (xk,yk), k=1,2 ... l, l are the barycenter that combination obtains
Sum；Then according to the bigger principle of the bigger position error of distance, weights, wherein weights are assigned to the center-of-mass coordinate of each combination
Determined by UWB labels to the reciprocal of corresponding centroid distance；Finally the barycenter of each combination is weighted to obtain final UWB labels and determined
Position result, specific formula for calculation are as follows：
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In formula, (xi,yi) it is center-of-mass coordinate, LiFor the distance with UWB labels to corresponding barycenter.
6. the positioning of the Indoor Robot according to claim 1 based on UWB and multisensor and environmental modeling method, its
It is characterised by：The double-deck Kalman filtering algorithm of step 5 is made up of two parts：Bottom Kalman filtering and top layer Kalman filtering,
Wherein bottom uses EKF model, to primarily determine that the positions of UWB labels as basic status, with current course
Angle information obtains Posterior estimator, to extract the relative position needed for the actual time of arrival as observation to prior estimate amendment
Information；Top layer uses Kalman filter model, using the robot displacement variable quantity in each ultrasonic wave observation cycle as substantially
The input of state renewal, the changing coordinates being calculated by ATOA methods are used as observation renewal, currently smart to obtain robot
True posture information.
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| CN108152792A (en) * | 2017-12-29 | 2018-06-12 | 同方威视技术股份有限公司 | Method, mobile equipment and the alignment system of the mobile equipment of positioning |
| CN108572647A (en) * | 2018-07-24 | 2018-09-25 | 南京阿凡达机器人科技有限公司 | A kind of smart home management method and management platform based on mobile robot |
| CN108680176A (en) * | 2018-05-16 | 2018-10-19 | 电子科技大学 | A kind of generation method of blind man navigation avoidance map |
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| CN108827316A (en) * | 2018-08-20 | 2018-11-16 | 南京理工大学 | Mobile robot visual orientation method based on improved Apriltag label |
| CN109116851A (en) * | 2018-09-05 | 2019-01-01 | 南京理工大学 | A kind of crusing robot inbound/outbound process algorithm based on Map Switch |
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| CN108680176A (en) * | 2018-05-16 | 2018-10-19 | 电子科技大学 | A kind of generation method of blind man navigation avoidance map |
| CN108572647A (en) * | 2018-07-24 | 2018-09-25 | 南京阿凡达机器人科技有限公司 | A kind of smart home management method and management platform based on mobile robot |
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| CN109283490A (en) * | 2018-11-14 | 2019-01-29 | 东南大学 | The UWB localization method of Taylor series expansion based on mixing least square method |
| CN109491395A (en) * | 2018-12-24 | 2019-03-19 | 山东农业大学 | Greenhouse AUTONOMOUS TASK Navigation Control Unit, method and controller |
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| CN110244715A (en) * | 2019-05-23 | 2019-09-17 | 西安理工大学 | A kind of multiple mobile robot's high-precision cooperative tracking method based on super-broadband tech |
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| CN113132894A (en) * | 2019-12-31 | 2021-07-16 | 华为技术有限公司 | Positioning method and device, WLAN (Wireless local area network) equipment, computing equipment and storage medium |
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| CN113137967A (en) * | 2021-05-19 | 2021-07-20 | 深圳市优必选科技股份有限公司 | Robot positioning method and device, robot and readable storage medium |
| WO2022242075A1 (en) * | 2021-05-19 | 2022-11-24 | 深圳市优必选科技股份有限公司 | Robot positioning method and apparatus, robot and readable storage medium |
| CN113137967B (en) * | 2021-05-19 | 2023-05-26 | 深圳市优必选科技股份有限公司 | Robot positioning method, device, robot and readable storage medium |
| CN113352300A (en) * | 2021-06-28 | 2021-09-07 | 广东工业大学 | Spraying robot demonstrator and method |
| CN117368844A (en) * | 2023-09-28 | 2024-01-09 | 河北振创电子科技有限公司 | Wall climbing robot positioning method and device, electronic equipment and storage medium |
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