CN109917413B - Accurate navigation positioning method of intelligent transfer bed - Google Patents
Accurate navigation positioning method of intelligent transfer bed Download PDFInfo
- Publication number
- CN109917413B CN109917413B CN201910050929.8A CN201910050929A CN109917413B CN 109917413 B CN109917413 B CN 109917413B CN 201910050929 A CN201910050929 A CN 201910050929A CN 109917413 B CN109917413 B CN 109917413B
- Authority
- CN
- China
- Prior art keywords
- reflector
- transfer bed
- navigation
- intelligent transfer
- laser
- 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.)
- Active
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61G—TRANSPORT, PERSONAL CONVEYANCES, OR ACCOMMODATION SPECIALLY ADAPTED FOR PATIENTS OR DISABLED PERSONS; OPERATING TABLES OR CHAIRS; CHAIRS FOR DENTISTRY; FUNERAL DEVICES
- A61G7/00—Beds specially adapted for nursing; Devices for lifting patients or disabled persons
- A61G7/08—Apparatus for transporting beds
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61N—ELECTROTHERAPY; MAGNETOTHERAPY; RADIATION THERAPY; ULTRASOUND THERAPY
- A61N5/00—Radiation therapy
- A61N5/10—X-ray therapy; Gamma-ray therapy; Particle-irradiation therapy
-
- 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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/42—Simultaneous measurement of distance and other co-ordinates
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Electromagnetism (AREA)
- Veterinary Medicine (AREA)
- Public Health (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Animal Behavior & Ethology (AREA)
- Computer Networks & Wireless Communication (AREA)
- Radiology & Medical Imaging (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Pathology (AREA)
- General Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Nursing (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses an accurate navigation positioning method of an intelligent transfer bed, which comprises the following steps: in the automatic transfer process of the intelligent transfer bed, when the intelligent transfer bed is far from a target position L1, the controller adopts a laser navigation method for navigation and positioning, and when the intelligent transfer bed is far from the target position L2, the controller adopts a binocular vision ranging positioning method for navigation and positioning, wherein L2 is more than L1. The invention adopts a novel laser navigation method when the distance from the target position is far, and reduces the minimum requirement of three reflectors into two by extracting and utilizing the complex field information in the laser ranging information, thereby effectively solving the technical bottleneck of the minimum quantity of reflectors and greatly improving the applicability of the laser navigation technology; and when the distance to the target position is close, a binocular vision distance measurement positioning method is adopted.
Description
Technical Field
The invention belongs to the field of medical equipment of intelligent transfer beds, and particularly relates to an accurate navigation and positioning method of an intelligent transfer bed.
Background
Radiotherapy intelligent transfer bed: it is an auxiliary intelligent transfer bed matched with an accelerator treatment bed, as shown in figure 1, the working process is as follows: when the accelerator treats the patient, the transfer bed A is stopped outside the accelerator machine room, the patient needing to be treated next time is laid on the transfer bed, the patient is fixed on the bed surface by the mold, and the treatment of the patient is waited to be finished at present. Meanwhile, a transfer bed B is kept beside the treatment bed, when the treatment of a patient is finished, the transfer bed B is close to the treatment bed, is accurately positioned and is in butt joint with the treatment bed, after the accurate butt joint is finished, the bed surface of the treatment bed and the patient are transferred to the transfer bed B together and fixed, at the moment, the transfer bed A which is already waiting outside the machine room automatically navigates to the side of the treatment bed according to a planned path, and meanwhile, the treatment bed B automatically navigates to a fixed position outside the machine room according to the planned path, stops and safely holds the patient down. After the treatment bed A reaches the accurate designated position of the treatment bed, the patient is transferred to the treatment bed through the transfer guide rail, when the transfer position is accurate, the bed surface is firmly fixed on the accelerator treatment bed, and then the treatment bed A returns to the safe position of the accelerator machine room.
The laser sensor-based positioning and navigation technology is a key technology in the fields of AGV, intelligent robot and the like, and compared with the traditional rail navigation mode, the technology has the advantages of high positioning accuracy, flexibility, changeability and the like, and is suitable for complex and high-dynamic industrial scenes. However, the control accuracy of the transfer bed based on laser navigation is still relatively low compared with the docking accuracy of an accelerator bed, which is usually greater than 5mm, and the accuracy requirement of the transfer bed of an accelerator machine room is within 1mm, so the current AGV control method cannot meet the requirement.
Disclosure of Invention
In order to solve the technical problem, the invention provides an accurate navigation and positioning method of an intelligent transfer bed.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a precise navigation positioning method of an intelligent transfer bed comprises the following steps:
in the automatic transfer process of the intelligent transfer bed, when the intelligent transfer bed is far from a target position L1, the controller adopts a laser navigation method for navigation and positioning, and when the intelligent transfer bed is far from the target position L2, the controller adopts a binocular vision ranging positioning method for navigation and positioning, wherein L2 is more than L1.
The invention provides a novel laser navigation and binocular vision accurate positioning method. When the distance from the target position is far, a novel laser navigation method is adopted, the minimum requirement of three reflectors is reduced to two by extracting and utilizing the complex field information in the laser ranging information, the technical bottleneck of the minimum quantity of reflectors is effectively solved, and the applicability of the laser navigation technology is greatly improved; and when the distance to the target position is close, a binocular vision distance measurement positioning method is adopted.
On the basis of the technical scheme, the following improvements can be made:
preferably, the relationship between the speed v (unit cm/s) of the intelligent transfer bed from the start of operation to the stop of operation and the operation time t (unit s) of the intelligent transfer bed satisfies a piecewise function of the following formula:
v＝-a*t2+b*t，0＜t≤T1；
v＝K*cdt，K＞0，lnc＜0，d＞1，T1＜t≤T2。
preferably, the intelligent transfer bed reaches the distance from the intelligent transfer bed to the target position L1 at time T1.
Preferably, when the intelligent transfer bed is far from the target position L0 and the L0 is between L1 and L2, the controller adopts a laser navigation method and/or a binocular vision distance measurement positioning method for navigation positioning.
Preferably, L1 is greater than 30cm, and L2 is less than or equal to 30 cm.
As a preferred scheme, the laser navigation method specifically comprises the following steps:
(1.1) arranging a reflector in an accelerator room, presetting world coordinates of the reflector, and generating a reflector coordinate list;
(1.2) laser sensors arranged on the mobile platform emit laser to the periphery in a radial shape and receive reflected laser;
(1.3) screening the effective light beams from the reflector: judging whether the laser irradiation object is a reflector or a common environment object by detecting the intensity I of the reflected laser and comparing the intensity I with a preset intensity threshold value sigma;
(1.4) determining the number of the reflectors irradiated at the current moment and relative coordinates of the reflectors relative to the laser sensor:
judging whether the same reflector is used according to the continuity of the angles of the reflected light beams;
or judging whether the same reflector is used according to the continuity of the angle and the distance of the reflected light beam;
obtaining the relative coordinate of the reflector relative to the laser sensor according to the reflected light beams belonging to the same reflector, and storing the relative coordinate into a reflector list;
(1.5) initializing a reflector list to obtain world coordinates of at least two reflectors: determining world coordinates of at least two reflectors in a reflector list corresponding to the initial position; or the laser sensor acquires the returned angles and distances of at least three reflectors at the initial position, calculates the distance between every two reflectors, and matches the reflector distance information generated according to the reflector coordinate list to obtain world coordinates of at least two reflectors;
(1.6) calculating a list of expected reflectors in a dynamic process;
(1.7) matching of reflector lists in a dynamic process: calculating the distance difference and the angle difference corresponding to the same reflector in the current-time reflector list and the expected reflector list, and when the distance difference and the angle difference both meet a preset threshold value, successfully matching;
(1.8) calculating the pose of the laser sensor based on the data of the double reflectors: selecting two reflectors in the successfully matched reflector by using complex frequency domain information of the data measured by the laser sensor: the ith and kth, and calculate:
zk＝Xk+i*Yk；
zl＝Xl+i*Yl；
wherein, subscripts l and k represent the l-th and k-th reflectors, respectively;
alpha and rho respectively represent the angle and the distance of the reflector under the polar coordinate system of the laser sensor relative to the laser sensor;
x and Y are the components of the reflector on X and Y axes respectively;
z is a plurality of coordinates of the reflector under a world coordinate system;
zk，lcalculating world coordinates of the laser sensor according to the l and k reflectors;
θkthe angle of the laser sensor under the world coordinate system is calculated according to the data of the kth reflector.
Preferably, in step (1.6), based on the prediction of the position and angle of the laser sensor at the current time from the previous time, the relative distances and angles between the laser sensor and all the reflectors are estimated, and stored in the expected reflector list, or the position and angle of the laser sensor at the previous time are directly used as the prediction of the current time, or a filtering algorithm is used for the prediction.
Preferably, after the step (1.8), the method further comprises a step of multi-block optimization: if the laser sensor detects three or more reflector data, data fusion can be carried out according to the positions and postures calculated by any two groups of data in the multiple groups of data, and the final positions and angles of the mobile platform and the laser sensor under the world coordinate system are obtained.
As a preferred scheme, the binocular vision ranging positioning method comprises the following steps:
(2.1) calibrating a camera to obtain internal parameters of the camera and a relative position between the two cameras;
(2.2) binocular correction; according to the internal parameters of the cameras and the relative position relationship between the two cameras obtained in the step (2.1), respectively carrying out distortion elimination and line alignment on the left view and the right view, so that the imaging origin coordinates of the left view and the right view are consistent, the optical axes of the two heads are parallel, the left imaging plane and the right imaging plane are coplanar, and the epipolar lines are aligned in a line manner;
(2.3) carrying out binocular matching, matching corresponding image points of the same scene on left and right views to obtain parallax data;
(2.4) calculating depth information, and calculating the depth information according to the parallax data obtained in the step (2.3) and the principle;
and (2.5) obtaining the distance between the intelligent transfer bed and the target position according to the depth information, feeding back to the controller, and adjusting the running speed and the stop position of the intelligent transfer bed by the controller according to the distance.
Drawings
Fig. 1 is a transfer schematic diagram of the intelligent transfer bed.
FIG. 2 is a graph of a piecewise function of a velocity v (in cm/s) and a time t (in s) from start of operation to stop of operation of an intelligent transfer bed provided by an embodiment of the present invention.
Fig. 3 is a schematic view of a binocular ranging apparatus.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
In order to achieve the purpose of the invention, in some embodiments of the method for accurately navigating and positioning the intelligent transfer bed,
a precise navigation positioning method of an intelligent transfer bed comprises the following steps:
in the automatic transfer process of the intelligent transfer bed, when the intelligent transfer bed is far from a target position L1, the controller adopts a laser navigation method for navigation and positioning, and when the intelligent transfer bed is far from the target position L2, the controller adopts a binocular vision ranging positioning method for navigation and positioning, wherein L2 is more than L1.
The invention provides a novel laser navigation and binocular vision accurate positioning method. When the distance from the target position is far, a novel laser navigation method is adopted, the minimum requirement of three reflectors is reduced to two by extracting and utilizing the complex field information in the laser ranging information, the technical bottleneck of the minimum quantity of reflectors is effectively solved, and the applicability of the laser navigation technology is greatly improved; and when the distance to the target position is close, a binocular vision distance measurement positioning method is adopted.
Further, in other embodiments, L1 is greater than 30cm, and L2 is less than or equal to 30 cm.
Further, in other embodiments, L1-50 cm and L2-20 cm.
Further, in other embodiments, L1-40 cm and L2-25 cm.
Wherein, L1 and L2 can also be other values.
In order to further optimize the implementation effect of the invention, in other embodiments, the rest of the characteristic techniques are the same, except that the relationship between the speed v (in cm/s) of the intelligent transfer bed from the start to the stop of the operation and the operation time t (in s) of the intelligent transfer bed satisfies the piecewise function of the following formula:
v＝-a*t2+b*t，0＜t≤T1；
v＝K*cdt，K＞0，lnc＜0，d＞1，T1＜t≤T2。
the intelligent transfer bed starts to run at a rapidly rising speed (the acceleration is increased continuously), and after the intelligent transfer bed rises to a speed peak value, the speed of the intelligent transfer bed is in a slowly descending state (the acceleration is reduced continuously) along a Gompertz (growth) curve. The operation speed of the intelligent transfer bed is controlled by adopting the piecewise function, so that the quick starting speed of the mobile device can be effectively ensured, but the mobile device is slowly stopped when approaching the accurate navigation stage, and the accuracy of navigation and positioning can be effectively improved. The piecewise function curve is shown in figure 2. Among them, T1 may be 5s, and T2 may be 15 s.
Further, the smart transfer bed reaches the distance from the smart transfer bed to the target position L1 at time T1.
In order to further optimize the implementation effect of the invention, in other embodiments, the rest characteristic technologies are the same, except that when the intelligent transfer bed is far from the target position L0, and the L0 is between L1 and L2, the controller adopts a laser navigation method for navigation positioning.
In order to further optimize the implementation effect of the invention, in other embodiments, the rest characteristic technologies are the same, except that when the intelligent transfer bed is far from the target position L0, and L0 is between L1 and L2, the controller adopts a binocular vision ranging positioning method for navigation positioning.
In order to further optimize the implementation effect of the invention, in other embodiments, the rest features are the same, except that when the intelligent transfer bed is far from the target position L0, and L0 is between L1 and L2, the controller performs navigation positioning by using two methods, namely a laser navigation method and a binocular vision ranging positioning method, and specifically includes the following steps:
the controller simultaneously collects the processing data obtained by the two methods, analyzes and compares the processing data, analyzes the difference value with the data obtained by the laser navigation method in the previous period, and judges whether the difference value exceeds a threshold value,
if not, the data obtained by the two methods are randomly selected in the next time period for navigation and positioning,
if the difference obtained by one method exceeds the threshold value, the data obtained by the other method is selected for positioning and navigation in the next time period,
and if the values exceed the threshold value, alarming.
For the sake of more clear expression of the above, it is assumed that L1 is 50cm, L2 is 20cm, and L3 is 30 cm.
When the smart transfer bed is at a distance L0(20cm) from the target position, assume at tn+1In the time interval, the controller simultaneously collects the processing data obtained by the two methods, and the processing data is analyzed, compared and analyzed with the previous time interval (assumed as t)nTime interval) data obtained by the laser navigation method are differentiated, whether the two differences exceed a threshold value or not is judged, the data obtained by the two methods are randomly selected for navigation positioning if the two differences do not exceed the threshold value, and the data obtained by the laser navigation method is continuously selected;
tn+2in the time interval, the controller simultaneously collects the processing data obtained by the two methods, analyzes and compares the processing data, and analyzes the processing data with the processing data in the previous time interval (t)n+1Time interval) of data obtained by the laser navigation method, and whether the two difference values exceed the threshold value or not is judged, if the difference value of the data obtained by the laser navigation method exceeds the threshold value, the next time interval is selected (t)n+3Time period) in another method (i.e.: binocular vision ranging positioning method), and the binocular vision ranging positioning method;
tn+3in the time interval, the controller simultaneously collects the processing data obtained by the two methods, analyzes and compares the processing data, and analyzes the processing data with the processing data in the previous time interval (t)n+2Time interval) of the data obtained by the binocular vision ranging positioning method, and whether the two difference values exceed the threshold value or not, if the difference value of the data obtained by the binocular vision ranging positioning method exceeds the threshold value, the next time interval is selected (t)n+4Time period) in another method (i.e.: laser navigation method) for positioning and navigation;
and the intelligent transfer trolley is far from the target distance L2.
In order to further optimize the implementation effect of the present invention, in other embodiments, the remaining features are the same, except that the laser navigation method specifically includes the following steps:
(1.1) arranging a reflector in an accelerator room, presetting world coordinates of the reflector, and generating a reflector coordinate list;
(1.2) laser sensors arranged on the mobile platform emit laser to the periphery in a radial shape and receive reflected laser;
(1.3) screening the effective light beams from the reflector: judging whether the laser irradiation object is a reflector or a common environment object by detecting the intensity I of the reflected laser and comparing the intensity I with a preset intensity threshold value sigma;
(1.4) determining the number of the reflectors irradiated at the current moment and relative coordinates of the reflectors relative to the laser sensor:
judging whether the same reflector is used according to the continuity of the angles of the reflected light beams;
or judging whether the same reflector is used according to the continuity of the angle and the distance of the reflected light beam;
obtaining the relative coordinate of the reflector relative to the laser sensor according to the reflected light beams belonging to the same reflector, and storing the relative coordinate into a reflector list;
(1.5) initializing a reflector list to obtain world coordinates of at least two reflectors: determining world coordinates of at least two reflectors in a reflector list corresponding to the initial position; or the laser sensor acquires the returned angles and distances of at least three reflectors at the initial position, calculates the distance between every two reflectors, and matches the reflector distance information generated according to the reflector coordinate list to obtain world coordinates of at least two reflectors;
(1.6) calculating a list of expected reflectors in a dynamic process;
(1.7) matching of reflector lists in a dynamic process: calculating the distance difference and the angle difference corresponding to the same reflector in the current-time reflector list and the expected reflector list, and when the distance difference and the angle difference both meet a preset threshold value, successfully matching;
(1.8) calculating the pose of the laser sensor based on the data of the double reflectors: selecting two reflectors in the successfully matched reflector by using complex frequency domain information of the data measured by the laser sensor: the ith and kth, and calculate:
zk＝Xk+i*Yk；
zl＝Xl+i*Yl；
wherein, subscripts l and k represent the l-th and k-th reflectors, respectively;
alpha and rho respectively represent the angle and the distance of the reflector under the polar coordinate system of the laser sensor relative to the laser sensor;
x and Y are the components of the reflector on X and Y axes respectively;
z is a plurality of coordinates of the reflector under a world coordinate system;
zk，lcalculating world coordinates of the laser sensor according to the l and k reflectors;
θkthe angle of the laser sensor under the world coordinate system is calculated according to the data of the kth reflector.
Further, in step (1.6), according to the prediction of the position and angle of the laser sensor at the current moment from the previous moment, the relative distance and angle between the laser sensor and all the reflectors are estimated, and the estimated distance and angle are stored in an expected reflector list, or the position and angle of the laser sensor at the previous moment are directly used as the prediction of the current moment, or a filtering algorithm is used for prediction.
Further, after the step (1.8), a step of multi-block optimization is also included: if the laser sensor detects three or more reflector data, data fusion can be carried out according to the positions and postures calculated by any two groups of data in the multiple groups of data, and the final positions and angles of the mobile platform and the laser sensor under the world coordinate system are obtained.
In order to further optimize the implementation effect of the invention, in other embodiments, the rest of the feature technologies are the same, except that the binocular vision ranging positioning method comprises the following steps:
(2.1) calibrating a camera to obtain internal parameters of the camera and a relative position between the two cameras;
(2.2) binocular correction; according to the internal parameters of the cameras and the relative position relationship between the two cameras obtained in the step (2.1), respectively carrying out distortion elimination and line alignment on the left view and the right view, so that the imaging origin coordinates of the left view and the right view are consistent, the optical axes of the two heads are parallel, the left imaging plane and the right imaging plane are coplanar, and the epipolar lines are aligned in a line manner;
(2.3) carrying out binocular matching, matching corresponding image points of the same scene on left and right views to obtain parallax data;
(2.4) calculating depth information, and calculating the depth information according to the parallax data obtained in the step (2.3) and the principle;
and (2.5) obtaining the distance between the intelligent transfer bed and the target position according to the depth information, feeding back to the controller, and adjusting the running speed and the stop position of the intelligent transfer bed by the controller according to the distance.
As shown in fig. 3, the binocular range finding mainly uses the difference directly existing in the lateral coordinates of the imaging of the target point on the left and right views (parallax d ═ x)l-xr) There is an inverse proportional relationship with the distance Z of the target point to the imaging plane: z ═ fT/d, derived specifically as follows:
let the coordinates of the target point in the left view be (c)x，cy) The coordinate in the right view is (c)x’，cy') the parallax formed in the left and right views is d, and Z is the depth information that we want to find.
In the above formula, the focal length f and the camera center distance T can be obtained by calibration, and therefore, the depth information Z can be obtained as long as the value of the parallax d is obtained.
With respect to the preferred embodiments of the present invention, it should be noted that, for those skilled in the art, various changes and modifications can be made without departing from the inventive concept of the present invention, and these changes and modifications are within the scope of the present invention.
Claims (9)
1. The accurate navigation positioning method of the intelligent transfer bed is characterized by comprising the following steps:
in the automatic transfer process of the intelligent transfer bed, when the intelligent transfer bed is far from a target position L1, the controller adopts a laser navigation method for navigation and positioning, and when the intelligent transfer bed is far from the target position L2, the controller adopts a binocular vision ranging positioning method for navigation and positioning, wherein L2 is more than L1;
when the intelligent transfer bed is far from the target position L0 and L0 is between L1 and L2, the controller performs navigation positioning by adopting two methods, namely a laser navigation method and a binocular vision ranging positioning method, and the method specifically comprises the following steps:
the controller simultaneously collects the processing data obtained by the two methods, analyzes and compares the processing data, analyzes the difference value with the data obtained by the laser navigation method in the previous period, and judges whether the difference value exceeds a threshold value,
if not, the data obtained by any of the two methods is randomly selected for navigation and positioning in the next time period,
if the difference obtained by one method exceeds the threshold value, the data obtained by the other method is selected for positioning and navigation in the next time period,
and if the values exceed the threshold value, alarming.
2. The method as claimed in claim 1, wherein the relationship between the velocity v of the intelligent transfer bed from the start to the stop of the intelligent transfer bed, where v is in cm/s, and the operation time t of the intelligent transfer bed, where t is in s, satisfies the piecewise function of the following formula:
v＝-a*t2+b*t，0＜t≤T1；
v＝K*cdt，K＞0，lnc＜0，d＞1，T1＜t≤T2；
wherein: a. b, K, c and d are formula parameters, and T1 and T2 are running time.
3. The method as claimed in claim 2, wherein the intelligent transfer bed reaches the distance from the target position L1 at T1.
4. The precise navigational positioning method of the intelligent transfer bed of claim 1, wherein the controller employs a laser navigational method and/or a binocular vision ranging positioning method for navigational positioning when the intelligent transfer bed is at a distance L0 from the target position L0 between L1 and L2.
5. The precise navigation and positioning method for the intelligent transfer bed according to any one of claims 1 to 4, wherein L1 is greater than 30cm, and L2 is less than or equal to 30 cm.
6. The precise navigation and positioning method for the intelligent transfer bed according to any one of claims 1 to 4, wherein the laser navigation method specifically comprises the following steps:
(1.1) arranging a reflector in an accelerator room, presetting world coordinates of the reflector, and generating a reflector coordinate list;
(1.2) laser sensors arranged on the mobile platform emit laser to the periphery in a radial shape and receive reflected laser;
(1.3) screening the effective light beams from the reflector: judging whether the laser irradiation object is a reflector or a common environment object by detecting the intensity I of the reflected laser and comparing the intensity I with a preset intensity threshold value sigma;
(1.4) determining the number of the reflectors irradiated at the current moment and relative coordinates of the reflectors relative to the laser sensor:
judging whether the same reflector is used according to the continuity of the angles of the reflected light beams;
or judging whether the same reflector is used according to the continuity of the angle and the distance of the reflected light beam;
obtaining the relative coordinate of the reflector relative to the laser sensor according to the reflected light beams belonging to the same reflector, and storing the relative coordinate into a reflector list;
(1.5) initializing a reflector list to obtain world coordinates of at least two reflectors: determining world coordinates of at least two reflectors in a reflector list corresponding to the initial position; or the laser sensor acquires the returned angles and distances of at least three reflectors at the initial position, calculates the distance between every two reflectors, and matches the reflector distance information generated according to the reflector coordinate list to obtain world coordinates of at least two reflectors;
(1.6) calculating a list of expected reflectors in a dynamic process;
(1.7) matching of reflector lists in a dynamic process: calculating the distance difference and the angle difference corresponding to the same reflector in the current-time reflector list and the expected reflector list, and when the distance difference and the angle difference both meet a preset threshold value, successfully matching;
(1.8) calculating the pose of the laser sensor based on the data of the double reflectors: selecting two reflectors in the successfully matched reflector by using complex frequency domain information of the data measured by the laser sensor: the ith and kth, and calculate:
zk＝Xk+i*Yk；
zl＝Xl+i*Yl；
wherein, subscripts l and k represent the l-th and k-th reflectors, respectively;
alpha and rho respectively represent the angle and the distance of the reflector under the polar coordinate system of the laser sensor relative to the laser sensor;
x and Y are the components of the reflector on X and Y axes respectively;
z is a plurality of coordinates of the reflector under a world coordinate system;
zk，lcalculating world coordinates of the laser sensor according to the l and k reflectors;
θkthe angle of the laser sensor under the world coordinate system is calculated according to the data of the kth reflector.
7. The precise navigation and positioning method for the intelligent transfer bed as claimed in claim 6, wherein in the step (1.6), the relative distances and angles between the laser sensor and all the reflectors are estimated according to the previous prediction of the position and angle of the laser sensor at the current time, and are stored in an expected reflector list, or the position and angle of the laser sensor at the previous time are directly used as the current prediction, or a filtering algorithm is used for prediction.
8. The precise navigational positioning method of the intelligent transfer bed of claim 7, further comprising, after the step (1.8), a step of multi-block optimization: if the laser sensor detects three or more reflector data, data fusion can be carried out according to the positions and postures calculated by any two groups of data in the multiple groups of data, and the final positions and angles of the mobile platform and the laser sensor under the world coordinate system are obtained.
9. The accurate navigation and positioning method of the intelligent transfer bed according to any one of claims 1 to 4, wherein the binocular vision ranging and positioning method comprises the following steps:
(2.1) calibrating a camera to obtain internal parameters of the camera and a relative position between the two cameras;
(2.2) binocular correction; according to the internal parameters of the cameras and the relative position relationship between the two cameras obtained in the step (2.1), respectively carrying out distortion elimination and line alignment on the left view and the right view, so that the imaging origin coordinates of the left view and the right view are consistent, the optical axes of the two heads are parallel, the left imaging plane and the right imaging plane are coplanar, and the epipolar lines are aligned in a line manner;
(2.3) carrying out binocular matching, matching corresponding image points of the same scene on left and right views to obtain parallax data;
(2.4) calculating depth information, and calculating the depth information according to the parallax data obtained in the step (2.3);
and (2.5) obtaining the distance between the intelligent transfer bed and the target position according to the depth information, and feeding back the distance to the controller, wherein the controller adjusts the running speed and the stop position of the intelligent transfer bed according to the distance.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910050929.8A CN109917413B (en) | 2019-01-21 | 2019-01-21 | Accurate navigation positioning method of intelligent transfer bed |
| PCT/CN2019/116427 WO2020151305A1 (en) | 2019-01-21 | 2019-11-07 | Accurate navigation and positioning method for intelligent transfer bed |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910050929.8A CN109917413B (en) | 2019-01-21 | 2019-01-21 | Accurate navigation positioning method of intelligent transfer bed |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109917413A CN109917413A (en) | 2019-06-21 |
| CN109917413B true CN109917413B (en) | 2021-07-06 |
Family
ID=66960436
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910050929.8A Active CN109917413B (en) | 2019-01-21 | 2019-01-21 | Accurate navigation positioning method of intelligent transfer bed |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN109917413B (en) |
| WO (1) | WO2020151305A1 (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109917413B (en) * | 2019-01-21 | 2021-07-06 | 苏州雷泰医疗科技有限公司 | Accurate navigation positioning method of intelligent transfer bed |
| CN114200498A (en) * | 2022-02-16 | 2022-03-18 | 湖南天巡北斗产业安全技术研究院有限公司 | Satellite navigation/optical combined target detection method and system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107144855A (en) * | 2017-07-13 | 2017-09-08 | 浙江科钛机器人股份有限公司 | A kind of laser positioning and air navigation aid based on double reflectors |
| CN107283028A (en) * | 2017-07-19 | 2017-10-24 | 南昌航空大学 | A kind of right angle discharge orifice weld seam recognition tracking welding method |
| CN107807632A (en) * | 2016-09-08 | 2018-03-16 | 福特全球技术公司 | Condition of road surface is perceived from the sensing data of fusion |
| CN108012143A (en) * | 2017-12-04 | 2018-05-08 | 深圳市沃特沃德股份有限公司 | Binocular camera scaling method and device |
| CN108152823A (en) * | 2017-12-14 | 2018-06-12 | 北京信息科技大学 | The unmanned fork truck navigation system and its positioning navigation method of a kind of view-based access control model |
| CN108226931A (en) * | 2017-12-20 | 2018-06-29 | 温州大学激光与光电智能制造研究院 | A kind of vehicle traveling detection system for obstacle and control method |
| CN108629812A (en) * | 2018-04-11 | 2018-10-09 | 深圳市逗映科技有限公司 | A kind of distance measuring method based on binocular camera |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| TWM440110U (en) * | 2012-05-17 | 2012-11-01 | Univ Cheng Shiu | Medical navigation device |
| US9125779B2 (en) * | 2012-09-28 | 2015-09-08 | Elwha Llc | Automated systems, devices, and methods for transporting and supporting patients |
| CN105983183A (en) * | 2015-02-27 | 2016-10-05 | 苏州雷泰医疗科技有限公司 | Radiation therapy device |
| CN108245788B (en) * | 2017-12-27 | 2020-06-02 | 苏州雷泰医疗科技有限公司 | Binocular distance measuring device and method and accelerator radiotherapy system comprising same |
| CN109917413B (en) * | 2019-01-21 | 2021-07-06 | 苏州雷泰医疗科技有限公司 | Accurate navigation positioning method of intelligent transfer bed |
-
2019
- 2019-01-21 CN CN201910050929.8A patent/CN109917413B/en active Active
- 2019-11-07 WO PCT/CN2019/116427 patent/WO2020151305A1/en active Application Filing
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107807632A (en) * | 2016-09-08 | 2018-03-16 | 福特全球技术公司 | Condition of road surface is perceived from the sensing data of fusion |
| CN107144855A (en) * | 2017-07-13 | 2017-09-08 | 浙江科钛机器人股份有限公司 | A kind of laser positioning and air navigation aid based on double reflectors |
| CN107283028A (en) * | 2017-07-19 | 2017-10-24 | 南昌航空大学 | A kind of right angle discharge orifice weld seam recognition tracking welding method |
| CN108012143A (en) * | 2017-12-04 | 2018-05-08 | 深圳市沃特沃德股份有限公司 | Binocular camera scaling method and device |
| CN108152823A (en) * | 2017-12-14 | 2018-06-12 | 北京信息科技大学 | The unmanned fork truck navigation system and its positioning navigation method of a kind of view-based access control model |
| CN108226931A (en) * | 2017-12-20 | 2018-06-29 | 温州大学激光与光电智能制造研究院 | A kind of vehicle traveling detection system for obstacle and control method |
| CN108629812A (en) * | 2018-04-11 | 2018-10-09 | 深圳市逗映科技有限公司 | A kind of distance measuring method based on binocular camera |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109917413A (en) | 2019-06-21 |
| WO2020151305A1 (en) | 2020-07-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107618030B (en) | Robot dynamic tracking grabbing method and system based on vision | |
| KR101394809B1 (en) | A method and systems for obtaining an improved stereo image of an object | |
| CN106272425B (en) | Barrier-avoiding method and robot | |
| US7283661B2 (en) | Image processing apparatus | |
| CN108827154B (en) | Robot non-teaching grabbing method and device and computer readable storage medium | |
| CN109917413B (en) | Accurate navigation positioning method of intelligent transfer bed | |
| CN108214487B (en) | Robot target positioning and grabbing method based on binocular vision and laser radar | |
| CN108942923A (en) | A kind of mechanical arm crawl control method | |
| CN108109174A (en) | A kind of robot monocular bootstrap technique sorted at random for part at random and system | |
| CN111673755A (en) | Picking robot control system and method based on visual servo | |
| CN110976212B (en) | Visual guide method, device and system of gluing robot | |
| JP2017015409A (en) | Road surface detection device, mobile body, road surface detection method, and road surface detection program | |
| CN109444916A (en) | The unmanned travelable area determining device of one kind and method | |
| CN109211260B (en) | Intelligent vehicle driving path planning method and device and intelligent vehicle | |
| JP2019152924A (en) | Self-position identification system, vehicle, and processing device | |
| CN109781010B (en) | Point cloud data calculation method, device and system for large-range data splicing | |
| CN106682584B (en) | Unmanned aerial vehicle obstacle detection method and device | |
| JP2011128020A (en) | Device and method for position estimation of moving body | |
| JPH11211738A (en) | Speed measurement method of traveling body and speed measuring device using the method | |
| CN112170124B (en) | Visual positioning method and device for vehicle body and vehicle frame | |
| WO2022188292A1 (en) | Target detection method and system, and control method, devices and storage medium | |
| TWI608894B (en) | Intelligent anti-collision safety system and tool machine using the same | |
| JPH04155211A (en) | Range-finder | |
| CN112114329A (en) | Unmanned aerial vehicle detection positioning device and method | |
| CN115689199B (en) | Autonomous mobile robot scheduling system for intelligent automobile manufacturing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |