CN113642687A - Substation inspection indoor position calculation method integrating two-dimensional code identification and inertial system - Google Patents
Substation inspection indoor position calculation method integrating two-dimensional code identification and inertial system Download PDFInfo
- Publication number
- CN113642687A CN113642687A CN202110808338.XA CN202110808338A CN113642687A CN 113642687 A CN113642687 A CN 113642687A CN 202110808338 A CN202110808338 A CN 202110808338A CN 113642687 A CN113642687 A CN 113642687A
- Authority
- CN
- China
- Prior art keywords
- dimensional code
- characteristic
- information
- indoor
- visual field
- 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.)
- Pending
Links
- 238000004364 calculation method Methods 0.000 title claims abstract description 35
- 238000007689 inspection Methods 0.000 title claims abstract description 29
- 230000000007 visual effect Effects 0.000 claims abstract description 48
- 238000000034 method Methods 0.000 claims abstract description 18
- 238000012937 correction Methods 0.000 claims abstract description 5
- 230000007704 transition Effects 0.000 claims abstract description 5
- 230000007613 environmental effect Effects 0.000 claims abstract description 3
- 238000006073 displacement reaction Methods 0.000 claims description 12
- 238000001914 filtration Methods 0.000 claims description 10
- 230000003287 optical effect Effects 0.000 claims description 4
- 230000004927 fusion Effects 0.000 claims description 2
- 230000007246 mechanism Effects 0.000 claims description 2
- 230000003068 static effect Effects 0.000 claims description 2
- 238000013461 design Methods 0.000 abstract description 2
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 12
- 239000011159 matrix material Substances 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 230000009466 transformation Effects 0.000 description 4
- 238000011161 development Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000000295 complement effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008909 emotion recognition Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 239000000725 suspension Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
- G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device
- G06K17/0025—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisious for transferring data to distant stations, e.g. from a sensing device the arrangement consisting of a wireless interrogation device in combination with a device for optically marking the record carrier
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
Abstract
A substation inspection indoor position calculation method integrating two-dimensional code identification and an inertia system belongs to the field of calculation. Setting a characteristic two-dimensional code label on the switch cabinet, and acquiring characteristic two-dimensional code label information in a visual field by using a camera device; the current coordinate position and the current posture of the movable robot are comprehensively acquired by depending on the characteristic two-dimensional code label information in the visual field of the camera device and the inertial data of the inertial system of the movable robot, so that the problem of accurate positioning of the absolute position of the indoor robot of the transformer substation is solved. It is through doing the position correction with the help of setting up the characteristic two-dimensional code label on the cubical switchboard, fuses inertial data, according to the difference of environmental location information, uses multiple locate mode comprehensively, and flexible transition between the different locate modes complements error correction, has extremely strong interference killing feature. The method can be widely applied to the field of design and manufacture of the indoor movable robot of the transformer substation.
Description
Technical Field
The invention belongs to the field of calculation, and particularly relates to an indoor position calculation method for a transformer substation inspection robot.
Background
Along with the development of national economy, the demand to electric power is constantly increasing, and the power supply company is also constantly deepening to the upgrading, the transformation of transformer substation, and its aim at strengthens patrolling and managing the equipment running condition of transformer substation, promotes aspects such as the effect of patrolling and examining.
In recent years, a series of movable robot platforms are developed at home and abroad for inspection and patrol in a transformer substation (indoor for short), and the movable robot platforms have various movement modes, such as wheeled type, crawler type, suspension rail type or rope type. With the development of the movable robot platform, how to accurately determine the indoor position of the robot becomes a key node in the development process of the movable robot platform.
The satellite positioning technology is a technology for accurately positioning an object by using a satellite, and can be used for guiding an airplane, a ship, a vehicle and an individual to safely and accurately reach a destination on time along a selected route, but an indoor positioning technology meeting the navigation positioning requirement is still needed for an indoor system which cannot be reached by a satellite signal or a system with higher positioning accuracy requirement. When the indoor environment can not use satellite positioning, the indoor positioning technology is used as auxiliary positioning of satellite positioning, the problems that satellite signals are weak when reaching the ground, cannot penetrate through buildings and are low in positioning accuracy are solved, and finally the current position of an object is positioned, which is a very important problem in the automatic inspection operation process in a transformer substation room.
The indoor positioning scheme is based on cellular positioning technology of a mobile communication network, and common indoor wireless positioning technologies include Wi-Fi, Bluetooth, infrared rays, ultra wide band, RFID, ZigBee, ultrasonic waves and the like. Due to the limitation of the transmitting power, the indoor wireless positioning technology can only cover an area with a radius of about 90 meters generally, and is easily interfered by other signals, so that the precision of the indoor wireless positioning technology is influenced, and the energy consumption of the positioner is high.
Visual understanding technology is an important component of computer vision, and mainly analyzes and understands the content of videos or images, and aims to acquire information from the videos or images. Face detection, face recognition, emotion recognition, text recognition, object classification detection, behavior recognition, classification and understanding of scenes, and classification, summarization of videos, etc. are typical visual understanding techniques. In addition, the visual understanding can also be used for indoor positioning, the deep understanding of the self environment is realized by learning the arrangement of indoor objects and identifying the characteristics of the objects, the spatial modeling is realized on the surrounding scene, the relative position of the self in the room is further obtained, and the self navigation route is planned according to the spatial modeling.
The technology has a certain technology accumulation at present, but the requirement on the artificial intelligence technology is extremely high, a complex and long-term training process is needed, the stability is poor, and the like, so that a long path is needed in the aspects of environment interpretation, virtual interaction, environment construction and the like to achieve the real usability and product level.
How to aim at present cubical switchboard equipment overall arrangement of transformer substation, with the help of current mature technical means, succinctly, rapidly, accurately realize that movable patrols and examines the indoor location of robot, is a technical problem who urgently waits to solve among the actual work.
Disclosure of Invention
The invention aims to solve the technical problem of providing a substation inspection indoor position calculation method integrating two-dimensional code identification and an inertia system. The method utilizes the existing mature two-dimension code recognition algorithm, calibrates the spatial position of the two-dimension code of the material on the switch cabinet, inputs the spatial position information by taking the spatial position as absolute position information, calculates the position deviation by combining an inertial system, corrects the positioning result in real time, and realizes the extremely stable and accurate position calculation method for the inspection of the indoor switch cabinet of the transformer substation.
The technical scheme of the invention is as follows: the method for calculating the indoor position of the transformer substation inspection tour integrating two-dimensional code identification and the inertial system comprises the steps of arranging a camera device on a movable robot used for the transformer substation indoor inspection tour, wherein the movable robot is provided with the inertial system, and is characterized in that:
1) the method comprises the steps that a characteristic two-dimensional code label is arranged on each switch cabinet in a substation room, the characteristic two-dimensional code label at least comprises position information of the switch cabinet, and the characteristic two-dimensional code label has uniform size information;
2) collecting characteristic two-dimensional code label information in a visual field by using a camera device;
3) if no characteristic two-dimensional code label information exists in the visual field of the camera device, the last positioning information is used as a reference, displacement calculation is realized by means of inertial data, and then absolute position positioning information of the movable robot is obtained and stored;
4) if at least two pieces of feature two-dimensional code label information are input in the visual field of the camera device, realizing the absolute position positioning information of the movable robot by depending on the absolute position positioning information corresponding to the feature two-dimensional codes, and storing the position information;
5) when only one characteristic two-dimensional code label exists in the visual field of the camera device, positioning information is acquired by means of the characteristic two-dimensional code label information, and meanwhile, the vector displacement in the current accurate positioning time period to the last time is calculated by means of inertial data in an auxiliary mode, so that the absolute position positioning information of the movable robot is acquired, and the information is stored;
6) the current coordinate position and the current posture of the movable robot are comprehensively acquired by depending on the characteristic two-dimensional code label information in the visual field of the camera device and the inertial data of the inertial system of the movable robot, so that the problem of accurate positioning of the absolute position of the indoor robot of the transformer substation is solved.
Specifically, the substation inspection indoor position calculation method has the advantages that position correction is carried out through the characteristic two-dimensional code labels arranged on the switch cabinets, inertial data are fused, accurate indoor position calculation is achieved, multiple positioning modes are comprehensively used according to different environmental positioning information, flexible transition and complementary error correction are carried out among the different positioning modes, and the substation inspection indoor position calculation method has strong anti-interference capacity.
Furthermore, the substation inspection indoor position calculation method uses a two-dimension code recognition system, obtains a static image in a shooting mode through a camera device, and uses a Zbar two-dimension code recognition library to complete two-dimension code recognition so as to obtain the coding content and size corresponding to all characteristic two-dimension codes in a visual field and the absolute position in the visual field of a camera.
Specifically, when a plurality of characteristic two-dimensional code labels exist in the visual field of the camera, the position of the movable robot is reversely determined according to the relative position of each two-dimensional code in the visual field and the absolute position information corresponding to each characteristic two-dimensional code label.
Specifically, when only one characteristic two-dimensional code label is in the visual field of the camera, the position of the movable robot is calculated according to absolute position information attached to the characteristic two-dimensional code label and the relative position of the characteristic two-dimensional code label in the visual field, inertial data of an inertial system are used in an auxiliary mode, vector displacement from the last time when the characteristic of the two-dimensional code changes to the current time period is calculated, and accidental errors caused by errors in two-dimensional code identification are avoided.
Specifically, when no characteristic two-dimensional code label exists in the visual field of the camera, the position calculation of the movable robot is realized by completely depending on the inertial data of the inertial system and depending on the Kalman filtering algorithm, so that the relatively accurate indoor position positioning in a certain time is ensured.
Furthermore, the self-inertial system consists of a nine-axis high-precision attitude sensor and an optical incremental encoder, wherein the nine-axis high-precision attitude sensor comprises a three-axis accelerometer, a three-axis magnetometer and a three-axis gyroscope; the self inertial system realizes sensor data fusion filtering through a Kalman filtering algorithm, is provided with an optical encoder connected with a moving mechanism of the mobile robot, and can acquire moving speed real-time data of the mobile robot.
According to the method for calculating the indoor position of the power station inspection tour, the positioning information contained in the two-dimensional code label and the size information of the two-dimensional code label are used for positioning the absolute position of the movable robot in the substation inspection tour.
Compared with the prior art, the invention has the advantages that:
1. according to the technical scheme, a camera is used for collecting a view field picture, then the current most mature two-dimensional code recognition tool Zbar is used as a recognition algorithm core, the current coordinate position and the current posture of a carrier are comprehensively obtained by means of two-dimensional code characteristic information in the view field and inertial data of an inertial system of the carrier, and the problem of accurate positioning of an indoor robot or device can be conveniently and rapidly solved;
2. the two-dimension code recognition is applied to the accurate positioning of the transformer substation indoor robot, the position deviation is calculated by combining the inertial system, the positioning result is corrected in real time, and the accuracy of the position calculation mode of the transformer substation indoor switch cabinet inspection is improved.
Drawings
FIG. 1 is a schematic diagram of an indoor position estimation method according to the present invention;
FIG. 2a is a schematic view of a reverse orientation of a visual field in which a plurality of feature two-dimensional codes appear;
FIG. 2b is a schematic view of only one characteristic two-dimensional code view within the field of view;
FIG. 3 is a schematic diagram of a Kalman filtering based attitude estimation and dead reckoning algorithm signal flow.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
The invention mainly relates to an indoor position calculation method which is suitable for substation indoor inspection and integrates two-dimension code identification and an inertia system, the current coordinate position and the attitude of a carrier can be comprehensively obtained by means of two-dimension code characteristic information in a visual field and inertia data of the inertia system, and the problem of accurate positioning of an indoor robot or device can be solved.
The indoor position calculating method can realize positioning by means of absolute position positioning information corresponding to the characteristic two-dimensional code when the characteristic two-dimensional code information is input in a visual field environment; when no characteristic two-dimensional code information exists in the visual field, the last positioning information is used as a reference to realize displacement calculation by relying on inertial data, and then absolute position positioning information is obtained; when only one characteristic two-dimensional code exists in the visual field, positioning information is acquired by means of the characteristic two-dimensional code information, meanwhile, inertial data are used for calculating vector displacement in the current accurate positioning time period, and accidental positioning errors caused by errors in two-dimensional code identification are avoided; the three positioning strategies are flexibly connected and transited, and the anti-interference capacity is very strong.
In the characteristic two-dimensional code identification process, a visual field picture is collected by a camera, and then all characteristic two-dimensional code data in a visual field, including two-dimensional code coding content, size and relative positions of the characteristic two-dimensional codes in the visual field, are acquired by using a current most mature two-dimensional code identification tool Zbar as an identification algorithm core.
The Kalman filtering-based position calculation method can realize accurate attitude information output and displacement calculation only by means of inertial data (triaxial accelerometer data, triaxial magnetometer data, triaxial gyroscope data and encoder speed data), and can realize more accurate indoor position calculation within a certain time by matching with absolute positioning information at the previous moment as a reference.
The Kalman filtering algorithm applied to the indoor positioning calculation process is realized as follows:
1) the system state equation:
the state quantities of the integrated navigation Kalman filter are selected as follows:
wherein, delta phie、δφn、δφuRespectively representing three attitude errors; delta ve、δvnRespectively representing the speed errors in the X direction and the Y direction; delta X and delta Y respectively represent an indoor X coordinate error and an indoor Y coordinate error; epsilonbx、εby、εbzRespectively representing constant drift of the three-axis gyroscope;
representing the zero offset error (X and Y directions) of the two-axis accelerometer, respectively.
The indoor integrated navigation kalman filter state transition equation can be expressed as:
f (t) is of the form:
wherein, F1(t) is an inertial navigation system error matrix, wherein the non-zero elements are as follows:
TABLE 4.7F1Each non-zero element of (t)
F2(t) is a transformation matrix between basic navigation parameters and inertial instrument errors, and the expression of the transformation matrix is as follows:
wherein the content of the first and second substances,
is a carrier seatA transformation matrix of the object system to the navigation coordinate system,
is composed of
Column 1, 2 elements.
The system noise transfer matrix g (t) is shown below:
the system noise matrix W (t) is shown below:
W(t)＝[wgx wgx wgx wgx wgx 0 0 0 0 0 0 0]T
2) the system measurement equation:
the measurement variables of the integrated navigation Kalman filter are selected as follows:
wherein v isie-vge、vin-vgn、Li-Lg、λi-λgRespectively representing the difference between the X-direction velocity, the Y-direction velocity, and X, Y calculated by inertial navigation and the corresponding data provided by the visual two-dimensional code recognition.
The state transition matrix h (t) is represented as follows:
H(t)＝[04×3 Ia×4 04×5]
in summary, the measurement equation of the indoor integrated navigation kalman filter system can be expressed as:
e (t) the speed and position errors provided for the GPS, which in turn are: x-direction speed error, Y-direction speed error, X-coordinate error and Y-coordinate error.
Fig. 1 is a framework of an indoor position calculation method combining two-dimensional code recognition and an inertial system, and when feature two-dimensional code information is input in a visual field environment, positioning is achieved by means of absolute position positioning information corresponding to the feature two-dimensional code; when no characteristic two-dimensional code information exists in the visual field, the last positioning information is used as a reference to realize displacement calculation by relying on inertial data, and then absolute position positioning information is obtained; when only one characteristic two-dimensional code exists in the visual field, positioning information is acquired by means of the characteristic two-dimensional code information, meanwhile, inertial data are used for calculating vector displacement in the current accurate positioning time period, and accidental positioning errors caused by errors in two-dimensional code identification are avoided; the three positioning strategies are flexibly connected and transited, and the anti-interference capacity is very strong.
Fig. 2 is a schematic view of visual reverse positioning of a characteristic two-dimensional code in a field of view, in which the distance between the characteristic two-dimensional code and an observer (i.e., the aforementioned image capturing device or camera) and the relative position offset are represented as differences in size and size of the characteristic two-dimensional code in the field of view on an image, so that by obtaining size information and position information of the characteristic two-dimensional code, a spatial relationship between the observer and a target two-dimensional code can be reversely calculated, and by combining absolute position information corresponding to the characteristic two-dimensional code, absolute position information of the observer can be reversely calculated.
Fig. 2a is a scene where a plurality of characteristic two-dimensional codes appear in a visual field, taking two characteristic two-dimensional codes appearing in the visual field as an example, positioning information of the two characteristic two-dimensional codes is used as input, and position information corresponding to a center of a visual field picture can be calculated through an interpolation method; in fig. 2b, the scene is a scene with only one characteristic two-dimensional code in the visual field, and the offset distance between the center of the two-dimensional code and the center of the visual field can be determined by the scaling relationship between the size of the two-dimensional code and the range of the visual field.
Taking fig. 2b as an example, if the coordinates of the feature two-dimensional code in the field of view are (X3, Y3) and the absolute position information of the feature two-dimensional code is (X, Y), the coordinate position corresponding to the center of the observer field of view is (X-X3, Y-Y3).
Fig. 3 is a signal flow diagram of an attitude estimation and position estimation algorithm based on kalman filtering, as shown in the figure, inertial data required for attitude estimation includes triaxial acceleration, triaxial angular velocity, and triaxial magnetometer data, the velocity data is acquired by an incremental encoder coaxial with a motion platform motor, and by combining the velocity data obtained by an inertial system and an accurate value of last positioning information, vector displacement of the mobile robot within a certain time period can be estimated, so that absolute position information of the mobile robot after the time period is obtained.
The technical proposal of the invention is that a corresponding two-dimensional code is arranged on each switch cabinet, the two-dimensional code comprises a plane space position of the corresponding switch cabinet, by calibrating the spatial position of the two-dimensional code arranged on the switch cabinet, taking the spatial position as absolute position information input, collecting visual field pictures by a camera arranged on the movable robot, then using a two-dimensional code recognition tool Zbar as a recognition algorithm core to acquire all characteristic two-dimensional code data of the visible switch cabinet in a visual field, calculating the position deviation by combining the inertial data of an inertial system of the robot, correcting the positioning result in real time to comprehensively acquire the current coordinate position and posture of a carrier (namely the movable robot), the problem of accurate positioning of an indoor robot or device can be solved, and the robot position calculation which is extremely stable and accurate and is used for inspection of the indoor switch cabinet of the transformer substation is realized.
The invention can be widely applied to the field of design and manufacture of the indoor movable robot of the transformer substation.
Claims (8)
1. The utility model provides a transformer substation patrols and examines indoor position calculation method of calculating with inertia system fuses two-dimensional code discernment, includes to set up camera device on the movable robot that is used for the indoor patrol and examine of transformer substation, movable robot in be provided with self inertia system, characterized by:
1) the method comprises the steps that a characteristic two-dimensional code label is arranged on each switch cabinet in a substation room, the characteristic two-dimensional code label at least comprises position information of the switch cabinet, and the characteristic two-dimensional code label has uniform size information;
2) collecting characteristic two-dimensional code label information in a visual field by using a camera device;
3) if no characteristic two-dimensional code label information exists in the visual field of the camera device, the last positioning information is used as a reference, displacement calculation is realized by means of inertial data, and then absolute position positioning information of the movable robot is obtained and stored;
4) if at least two pieces of feature two-dimensional code label information are input in the visual field of the camera device, realizing the absolute position positioning information of the movable robot by depending on the absolute position positioning information corresponding to the feature two-dimensional codes, and storing the position information;
5) when only one characteristic two-dimensional code label exists in the visual field of the camera device, positioning information is acquired by means of the characteristic two-dimensional code label information, and meanwhile, the vector displacement in the current accurate positioning time period to the last time is calculated by means of inertial data in an auxiliary mode, so that the absolute position positioning information of the movable robot is acquired, and the information is stored;
6) the current coordinate position and the current posture of the movable robot are comprehensively acquired by depending on the characteristic two-dimensional code label information in the visual field of the camera device and the inertial data of the inertial system of the movable robot, so that the problem of accurate positioning of the absolute position of the indoor robot of the transformer substation is solved.
2. The substation inspection indoor position calculation method combining the two-dimensional code identification and the inertial system according to claim 1, is characterized in that the substation inspection indoor position calculation method combines inertial data by performing position correction with the help of characteristic two-dimensional code tags arranged on switch cabinets to realize accurate indoor position calculation, comprehensively uses a plurality of positioning modes according to different environmental positioning information, flexibly transitions between the different positioning modes, complements and corrects errors, and has extremely strong anti-interference capability.
3. The substation inspection indoor position calculating method fusing two-dimensional code identification and an inertia system according to claim 1, wherein the substation inspection indoor position calculating method uses a two-dimensional code identification system to acquire a static image in a shooting mode through a camera device, and uses a Zbar two-dimensional code identification library to complete two-dimensional code identification so as to acquire coding contents, sizes and absolute positions in a camera view field corresponding to all characteristic two-dimensional codes in the view field.
4. The transformer substation inspection indoor position calculating method fusing the two-dimensional code identification and the inertia system according to claim 1, wherein when a plurality of characteristic two-dimensional code labels exist in a visual field of a camera, the position of the movable robot is reversely determined according to the relative position of each two-dimensional code in the visual field and absolute position information corresponding to each characteristic two-dimensional code label.
5. The substation inspection indoor position calculation method fusing two-dimensional code identification and inertia system according to claim 1, wherein when only one characteristic two-dimensional code label exists in the visual field of the camera, the position of the mobile robot is calculated according to absolute position information attached to the characteristic two-dimensional code label and the relative position of the characteristic two-dimensional code label in the visual field, and the inertial data of the inertia system is used in an auxiliary manner to calculate vector displacement from the characteristic change of the last two-dimensional code to the current time period, so as to avoid accidental errors caused by errors in two-dimensional code identification.
6. The substation inspection tour indoor position calculation method fusing two-dimensional code identification and the inertial system according to claim 1, is characterized in that when a camera does not have a characteristic two-dimensional code label in a visual field, the position calculation of the movable robot is realized by completely depending on inertial data of the inertial system and depending on a Kalman filtering algorithm, so as to ensure relatively accurate indoor position positioning within a certain time.
7. The substation inspection tour indoor position calculation method integrating two-dimensional code recognition and inertial system according to claim 1 is characterized in that the self inertial system is composed of a nine-axis high-precision attitude sensor and an optical incremental encoder, wherein the nine-axis high-precision attitude sensor comprises a three-axis accelerometer, a three-axis magnetometer and a three-axis gyroscope;
the self inertial system realizes sensor data fusion filtering through a Kalman filtering algorithm, is provided with an optical encoder connected with a moving mechanism of the mobile robot, and can acquire moving speed real-time data of the mobile robot.
8. The substation inspection indoor position calculation method fusing two-dimensional code identification and an inertial system according to claim 1, wherein the substation inspection indoor position calculation method uses positioning information contained in a two-dimensional code tag and size information of the two-dimensional code tag itself for absolute position positioning of a substation inspection indoor movable robot.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110808338.XA CN113642687A (en) | 2021-07-16 | 2021-07-16 | Substation inspection indoor position calculation method integrating two-dimensional code identification and inertial system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110808338.XA CN113642687A (en) | 2021-07-16 | 2021-07-16 | Substation inspection indoor position calculation method integrating two-dimensional code identification and inertial system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113642687A true CN113642687A (en) | 2021-11-12 |
Family
ID=78417606
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110808338.XA Pending CN113642687A (en) | 2021-07-16 | 2021-07-16 | Substation inspection indoor position calculation method integrating two-dimensional code identification and inertial system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113642687A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114167867A (en) * | 2021-12-02 | 2022-03-11 | 南方电网电力科技股份有限公司 | Positioning and control method of inspection robot and related device |
| CN116824481A (en) * | 2023-05-18 | 2023-09-29 | 国网信息通信产业集团有限公司北京分公司 | Substation inspection method and system based on image recognition |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108489486A (en) * | 2015-06-01 | 2018-09-04 | 北京极智嘉科技有限公司 | Quick Response Code and be used for robotic vision-inertia combined navigation system and method |
| CN108592906A (en) * | 2018-03-30 | 2018-09-28 | 合肥工业大学 | AGV complex navigation methods based on Quick Response Code and inertial sensor |
| CN110673612A (en) * | 2019-10-21 | 2020-01-10 | 重庆邮电大学 | Two-dimensional code guide control method for autonomous mobile robot |
| CN111113415A (en) * | 2019-12-19 | 2020-05-08 | 上海点甜农业专业合作社 | Robot positioning method based on two-dimensional code road sign, camera and gyroscope |
| CN111964680A (en) * | 2020-07-29 | 2020-11-20 | 中国安全生产科学研究院 | Real-time positioning method of inspection robot |
| CN112097768A (en) * | 2020-11-17 | 2020-12-18 | 深圳市优必选科技股份有限公司 | Robot posture determining method and device, robot and storage medium |
-
2021
- 2021-07-16 CN CN202110808338.XA patent/CN113642687A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108489486A (en) * | 2015-06-01 | 2018-09-04 | 北京极智嘉科技有限公司 | Quick Response Code and be used for robotic vision-inertia combined navigation system and method |
| CN108592906A (en) * | 2018-03-30 | 2018-09-28 | 合肥工业大学 | AGV complex navigation methods based on Quick Response Code and inertial sensor |
| CN110673612A (en) * | 2019-10-21 | 2020-01-10 | 重庆邮电大学 | Two-dimensional code guide control method for autonomous mobile robot |
| CN111113415A (en) * | 2019-12-19 | 2020-05-08 | 上海点甜农业专业合作社 | Robot positioning method based on two-dimensional code road sign, camera and gyroscope |
| CN111964680A (en) * | 2020-07-29 | 2020-11-20 | 中国安全生产科学研究院 | Real-time positioning method of inspection robot |
| CN112097768A (en) * | 2020-11-17 | 2020-12-18 | 深圳市优必选科技股份有限公司 | Robot posture determining method and device, robot and storage medium |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114167867A (en) * | 2021-12-02 | 2022-03-11 | 南方电网电力科技股份有限公司 | Positioning and control method of inspection robot and related device |
| CN116824481A (en) * | 2023-05-18 | 2023-09-29 | 国网信息通信产业集团有限公司北京分公司 | Substation inspection method and system based on image recognition |
| CN116824481B (en) * | 2023-05-18 | 2024-04-09 | 国网信息通信产业集团有限公司北京分公司 | Substation inspection method and system based on image recognition |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110446159B (en) | System and method for accurate positioning and autonomous navigation of indoor unmanned aerial vehicle | |
| Gao et al. | Review of wheeled mobile robots’ navigation problems and application prospects in agriculture | |
| Weiss | Vision based navigation for micro helicopters | |
| Davison | Mobile robot navigation using active vision | |
| Frassl et al. | Magnetic maps of indoor environments for precise localization of legged and non-legged locomotion | |
| CN110243358A (en) | The unmanned vehicle indoor and outdoor localization method and system of multi-source fusion | |
| CN111968262A (en) | Semantic intelligent substation inspection operation robot navigation system and method | |
| CN110166571A (en) | A kind of automatic follower method and device based on mobile robot | |
| CN111413970A (en) | Ultra-wideband and vision integrated indoor robot positioning and autonomous navigation method | |
| CN113642687A (en) | Substation inspection indoor position calculation method integrating two-dimensional code identification and inertial system | |
| Di et al. | Progress and applications of visual SLAM | |
| CN102156476A (en) | Intelligent space and nurse robot multi-sensor system and information fusion method of intelligent space and nurse robot multi-sensor system | |
| Khattak et al. | Marker based thermal-inertial localization for aerial robots in obscurant filled environments | |
| CN109648558A (en) | Robot non-plane motion localization method and its motion locating system | |
| Papoutsidakis et al. | Design of an autonomous robotic vehicle for area mapping and remote monitoring | |
| Ding et al. | Development of a high precision UWB/vision-based AGV and control system | |
| CN114323033A (en) | Positioning method and device based on lane lines and feature points and automatic driving vehicle | |
| Doitsidis et al. | 3d surveillance coverage using maps extracted by a monocular slam algorithm | |
| Ziebinski et al. | Challenges associated with sensors and data fusion for AGV-driven smart manufacturing | |
| Mráz et al. | Using fiducial markers to improve localization of a drone | |
| Schell et al. | Autonomous landing of airplanes by dynamic machine vision | |
| Popa et al. | EKF-based adaptive sampling with mobile robotic sensor nodes | |
| Rioux et al. | Cooperative vision-based object transportation by two humanoid robots in a cluttered environment | |
| Qin et al. | Multi-modal sensor fusion method based on Kalman filter | |
| Wang et al. | UAV navigation in large-scale GPS-denied bridge environments using fiducial marker-corrected stereo visual-inertial localisation |
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 |