CN109917413B - An accurate navigation and positioning method of an intelligent transfer bed - Google Patents

An accurate navigation and positioning method of an intelligent transfer bed Download PDF

Info

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
navigation
transfer bed
intelligent transfer
reflectors
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
Application number
CN201910050929.8A
Other languages
Chinese (zh)
Other versions
CN109917413A (en
Inventor
易军
姚毅
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Leitai Tengfei Medical Technology Co ltd
Original Assignee
Suzhou Linatech Medical Science And Technology Co ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Suzhou Linatech Medical Science And Technology Co ltd filed Critical Suzhou Linatech Medical Science And Technology Co ltd
Priority to CN201910050929.8A priority Critical patent/CN109917413B/en
Publication of CN109917413A publication Critical patent/CN109917413A/en
Priority to PCT/CN2019/116427 priority patent/WO2020151305A1/en
Application granted granted Critical
Publication of CN109917413B publication Critical patent/CN109917413B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

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)
  • General Health & Medical Sciences (AREA)
  • Veterinary Medicine (AREA)
  • Electromagnetism (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Animal Behavior & Ethology (AREA)
  • Biomedical Technology (AREA)
  • Public Health (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Nursing (AREA)
  • Pathology (AREA)
  • Radiology & Medical Imaging (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

本发明公开一种智能转移床的精确导航定位方法，包括以下内容：智能转移床在自动转移的过程中，当智能转移床距离目标位置L1时，控制器采用激光导航方法进行导航定位，当智能转移床距离目标位置L2时，控制器采用双目视觉测距定位方法进行导航定位，其中L2＜L1。本发明在距离目标位置较远时采用新型的激光导航方法，通过提取和利用激光测距信息中的复数域信息，将三块反光板的最低要求降低为两块，有效解决了反光板最低数量的技术瓶颈，大大提高了激光导航技术的适用性；在距离目标位置较近时，采用双目视觉测距定位方法。

Figure 201910050929

The invention discloses a precise navigation and positioning method of an intelligent transfer bed, which includes the following contents: in the process of automatic transfer of the intelligent transfer bed, when the intelligent transfer bed is far away from the target position L1, the controller adopts a laser navigation method for navigation and positioning; When the transfer bed is far from the target position L2, the controller adopts the binocular vision ranging and positioning method for navigation and positioning, where L2<L1. The present invention adopts a new type of laser navigation method when the distance from the target position is far away, and by extracting and utilizing the complex domain information in the laser ranging information, the minimum requirement of three reflectors is reduced to two, which effectively solves the problem of the minimum number of reflectors. It greatly improves the applicability of laser navigation technology; when it is close to the target position, the binocular vision ranging positioning method is adopted.

Figure 201910050929

Description

Accurate navigation positioning method of intelligent transfer bed
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:
Figure BDA0001951740600000041
Figure BDA0001951740600000042
zk＝Xk+i*Yk；
zl＝Xl+i*Yl；
Figure BDA0001951740600000043
Figure BDA0001951740600000044
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:
Figure BDA0001951740600000091
Figure BDA0001951740600000092
zk＝Xk+i*Yk；
zl＝Xl+i*Yl；
Figure BDA0001951740600000101
Figure BDA0001951740600000102
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:
Figure BDA0001951740600000111
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)

1.一种智能转移床的精确导航定位方法，其特征在于，包括以下内容：1. a precise navigation and positioning method of an intelligent transfer bed, is characterized in that, comprises the following content: 智能转移床在自动转移的过程中，当智能转移床距离目标位置L1时，控制器采用激光导航方法进行导航定位，当智能转移床距离目标位置L2时，控制器采用双目视觉测距定位方法进行导航定位，其中L2＜L1；In the process of automatic transfer of the intelligent transfer bed, when the intelligent transfer bed is far from the target position L1, the controller adopts the laser navigation method for navigation and positioning. When the intelligent transfer bed is far from the target position L2, the controller adopts the binocular vision ranging and positioning method. Navigation and positioning, where L2<L1; 当所述智能转移床距离目标位置L0时，L0在L1和L2之间时，所述控制器采用激光导航方法和双目视觉测距定位方法两种方法进行导航定位，具体包括以下内容：When the intelligent transfer bed is away from the target position L0, when L0 is between L1 and L2, the controller adopts the laser navigation method and the binocular vision ranging and positioning method for navigation and positioning, which specifically includes the following contents: 所述控制器同时采集两种方法得到的处理数据，对该处理数据进行分析评比，分析与前一时段通过激光导航方法得到的数据的差值，看其差值是否超过阈值，The controller simultaneously collects the processed data obtained by the two methods, analyzes and evaluates the processed data, analyzes the difference with the data obtained by the laser navigation method in the previous period, and sees whether the difference exceeds a threshold value, 若均没有超过，则下一时段随意选择两种方法任一得到的数据进行导航定位，If it does not exceed, the data obtained by either of the two methods will be randomly selected for navigation and positioning in the next period. 若有其中一种方法得到的差值超过阈值，则下一时段选用另一种方法得到的数据进行定位导航，If the difference obtained by one of the methods exceeds the threshold, the data obtained by the other method will be used for positioning and navigation in the next period. 若均超过阈值，则报警。If both exceed the threshold, an alarm will be issued. 2.根据权利要求1所述的智能转移床的精确导航定位方法，其特征在于，所述智能转移床从开始运行到停止运行的速度v，其中v单位为cm/s，与所述智能转移床的运行时间t，其中t单位为s，之间的关系满足下式的分段函数：2. The precise navigation and positioning method of the intelligent transfer bed according to claim 1, characterized in that, the speed v of the intelligent transfer bed from starting to running to stopping operation, wherein v is in cm/s, which is the same as that of the intelligent transfer bed. The running time of the bed, t, where t is in units of s, is related to the piecewise function of: v＝-a*t2+b*t，0＜t≤T1；v=-a*t 2 +b*t, 0<t≤T1; v＝K*cdt，K＞0，lnc＜0，d＞1，T1＜t≤T2；v=K*c dt , K>0, lnc<0, d>1, T1<t≤T2; 其中：a、b、K、c、d均为公式参数，T1和T2为运行时间。Among them: a, b, K, c, d are formula parameters, T1 and T2 are running time. 3.根据权利要求2所述的智能转移床的精确导航定位方法，其特征在于，所述智能转移床在T1时刻到达所述智能转移床距离目标位置L1的距离。3 . The precise navigation and positioning method of the intelligent transfer bed according to claim 2 , wherein the intelligent transfer bed reaches the distance from the intelligent transfer bed to the target position L1 at time T1 . 4 . 4.根据权利要求1所述的智能转移床的精确导航定位方法，其特征在于，当所述智能转移床距离目标位置L0时，L0在L1和L2之间时，所述控制器采用激光导航方法和/或双目视觉测距定位方法进行导航定位。4. The precise navigation and positioning method of the intelligent transfer bed according to claim 1, wherein when the intelligent transfer bed is away from the target position L0, and when L0 is between L1 and L2, the controller adopts laser navigation method and/or binocular vision ranging and positioning method for navigation and positioning. 5.根据权利要求1-4任一项所述的智能转移床的精确导航定位方法，其特征在于，L1＞30cm，L2≤30cm。5 . The precise navigation and positioning method of an intelligent transfer bed according to claim 1 , wherein L1 > 30 cm and L 2 < 30 cm. 6 . 6.根据权利要求1-4任一项所述的智能转移床的精确导航定位方法，其特征在于，所述激光导航方法具体包括以下步骤：6. The precise navigation and positioning method of an intelligent transfer bed according to any one of claims 1-4, wherein the laser navigation method specifically comprises the following steps: (1.1)在加速器机房中布置反光板，预设反光板世界坐标，生成反光板坐标列表；(1.1) Arrange reflectors in the accelerator room, preset the world coordinates of the reflectors, and generate a list of reflector coordinates; (1.2)安装在移动平台上的激光传感器向周围呈辐射状发射激光，并接收反射激光；(1.2) The laser sensor installed on the mobile platform emits laser light radially to the surroundings and receives reflected laser light; (1.3)筛选来源于反光板的有效光束：通过检测反射激光强度I并与预设强度阈值σ相比较，判定激光照射物是反光板还是普通环境物体；(1.3) Screening the effective beam from the reflector: by detecting the reflected laser intensity I and comparing it with the preset intensity threshold σ, it is determined whether the laser irradiated object is a reflector or an ordinary environmental object; (1.4)确定当前时刻照射到的反光板数量及其相对激光传感器的相对坐标：(1.4) Determine the number of reflectors irradiated at the current moment and their relative coordinates relative to the laser sensor: 根据反射光束角度的连续性，判断是否为同一块反光板；According to the continuity of the reflected beam angle, judge whether it is the same reflector; 或者，根据反射光束角度和距离的连续性，判断是否为同一块反光板；Or, according to the continuity of the angle and distance of the reflected beam, determine whether it is the same reflector; 根据属于同一反光板的反射光束得到该反光板相对于激光传感器的相对坐标，并存入反光板列表；The relative coordinates of the reflector relative to the laser sensor are obtained according to the reflected beams belonging to the same reflector, and stored in the reflector list; (1.5)初始化反光板列表，得到至少两个反光板的世界坐标：确定初始位置对应的反光板列表中至少两个反光板的世界坐标；或者，激光传感器在初始位置获取至少三个反光板返回的角度和距离，计算两两反光板之间的距离，与根据反光板坐标列表生成的反光板距离信息相匹配，得到至少两个反光板的世界坐标；(1.5) Initialize the reflector list to obtain the world coordinates of at least two reflectors: determine the world coordinates of at least two reflectors in the reflector list corresponding to the initial position; or, the laser sensor obtains at least three reflectors at the initial position and returns Calculate the distance between the two reflectors, match the reflector distance information generated according to the reflector coordinate list, and obtain the world coordinates of at least two reflectors; (1.6)在动态过程中计算期望反光板列表；(1.6) Calculate the list of expected reflectors in the dynamic process; (1.7)在动态过程中反光板列表的匹配：计算当前时刻反光板列表与期望反光板列表中同一个反光板对应的距离之差和角度之差，当距离之差和角度之差均满足预设阈值时，匹配成功；(1.7) Matching of the reflector list in the dynamic process: Calculate the difference between the distance and angle corresponding to the same reflector in the reflector list at the current moment and the same reflector in the expected reflector list. When the threshold is set, the matching is successful; (1.8)基于双反光板数据的激光传感器位姿计算：利用激光传感器测量数据的复频域信息，在匹配成功的反光板中任选两块：第l个和第k个，并计算：(1.8) Laser sensor pose calculation based on double reflector data: Using the complex frequency domain information of the laser sensor measurement data, choose two of the successfully matched reflectors: the lth and the kth, and calculate:
Figure FDA0003044411450000031
Figure FDA0003044411450000031
Figure FDA0003044411450000032
Figure FDA0003044411450000032
 zk＝Xk+i*Yk；z k =X k +i*Y k ; zl＝Xl+i*Yl；z l =X l +i*Y l ;
Figure FDA0003044411450000033
Figure FDA0003044411450000033
Figure FDA0003044411450000034
Figure FDA0003044411450000034
 其中，下标l和k分别代表第l和第k个反光板；Among them, the subscripts l and k represent the lth and kth reflectors, respectively; α和ρ分别代表在激光传感器相对自身的极坐标系下，反光板的角度和距离；α and ρ represent the angle and distance of the reflector in the polar coordinate system of the laser sensor relative to itself; X和Y分别为反光板在X和Y轴的分量；X and Y are the components of the reflector on the X and Y axes, respectively; z为反光板在世界坐标系下的复数坐标；z is the complex coordinate of the reflector in the world coordinate system; zk，l为根据第l和第k个反光板计算得到的激光传感器世界坐标；z k, l is the world coordinate of the laser sensor calculated according to the lth and kth reflectors; θk是根据第k块反光板的数据计算得到的激光传感器在世界坐标系下的角度。θ k is the angle of the laser sensor in the world coordinate system calculated from the data of the kth reflector. 7.根据权利要求6所述的智能转移床的精确导航定位方法，其特征在于，在所述步骤(1.6)中，根据上一时刻对当前时刻激光传感器位置和角度的预测，估计激光传感器与所有反光板之间的相对距离和角度，并存入期望反光板列表，或者直接采用上一时刻激光传感器的位置和角度作为当前时刻的预测，或者采用滤波算法进行预测。7. The precise navigation and positioning method of the intelligent transfer bed according to claim 6, characterized in that, in the step (1.6), according to the prediction of the position and angle of the laser sensor at the current moment at the previous moment, it is estimated that the laser sensor and the The relative distances and angles between all reflectors are stored in the list of expected reflectors, or the position and angle of the laser sensor at the last moment are directly used as the prediction at the current moment, or the filtering algorithm is used for prediction. 8.根据权利要求7所述的智能转移床的精确导航定位方法，其特征在于，在所述步骤(1.8)之后，还包括多块优化的步骤：如果激光传感器检测到三个及以上的反光板数据，可以根据多组数据中任意两组计算得到的位姿进行数据融合，得到最终的移动平台及激光传感器在世界坐标系下的位置及角度。8. The precise navigation and positioning method of the intelligent transfer bed according to claim 7, characterized in that, after the step (1.8), it further comprises the step of multi-block optimization: if the laser sensor detects three or more reflections The board data can be fused according to the calculated poses of any two groups of multiple sets of data to obtain the final position and angle of the mobile platform and the laser sensor in the world coordinate system. 9.根据权利要求1-4任一项所述的智能转移床的精确导航定位方法，其特征在于，所述双目视觉测距定位方法包括以下步骤：9. The precise navigation and positioning method of an intelligent transfer bed according to any one of claims 1-4, wherein the binocular vision ranging and positioning method comprises the following steps: (2.1)相机标定，得到相机的内部参数和两相机之间的相对位置；(2.1) Camera calibration to obtain the internal parameters of the camera and the relative position between the two cameras; (2.2)双目校正；根据步骤(2.1)得到的相机的内部参数和两相机之间的相对位置关系后，分别对左右视图进行消除畸变和行对准，使得左右视图的成像原点坐标一致、两相头光轴平行、左右成像平面共面、对极线行对齐；(2.2) Binocular correction; according to the internal parameters of the camera obtained in step (2.1) and the relative positional relationship between the two cameras, the left and right views are respectively distorted and aligned, so that the imaging origin coordinates of the left and right views are consistent, The optical axes of the two-phase heads are parallel, the left and right imaging planes are coplanar, and the epipolar lines are aligned; (2.3)双目匹配，把同一场景在左右视图上对应的像点匹配起来，得到视差数据；(2.3) Binocular matching, matching the corresponding image points on the left and right views of the same scene to obtain parallax data; (2.4)计算深度信息，根据步骤(2.3)得到的视差数据，计算出深度信息；(2.4) Calculate the depth information, and calculate the depth information according to the parallax data obtained in step (2.3); (2.5)根据深度信息得到所述智能转移床与目标位置之间的距离，反馈给所述控制器，所述控制器根据该距离调节所述智能转移床的运行速度和停止位置。(2.5) Obtain the distance between the intelligent transfer bed and the target position according to the depth information, and feed it back to the controller, and the controller adjusts the running speed and stop position of the intelligent transfer bed according to the distance.
CN201910050929.8A 2019-01-21 2019-01-21 An accurate navigation and positioning method of an intelligent transfer bed Active CN109917413B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201910050929.8A CN109917413B (en) 2019-01-21 2019-01-21 An accurate navigation and positioning method of an 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 An accurate navigation and positioning method of an 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 An accurate navigation and positioning method of an intelligent transfer bed

Country Status (2)

Country Link
CN (1) CN109917413B (en)
WO (1) WO2020151305A1 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
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 An accurate navigation and positioning method of an 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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TWM440110U (en) * 2012-05-17 2012-11-01 Univ Cheng Shiu Medical navigation device
US8886383B2 (en) * 2012-09-28 2014-11-11 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 A binocular ranging device and method, and an accelerator radiotherapy system including the device
CN109917413B (en) * 2019-01-21 2021-07-06 苏州雷泰医疗科技有限公司 An accurate navigation and positioning method of an intelligent transfer bed

Patent Citations (7)

* Cited by examiner, † Cited by third party
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
KR101394809B1 (en) A method and systems for obtaining an improved stereo image of an object
JP6825569B2 (en) Signal processor, signal processing method, and program
US7966094B2 (en) Workpiece picking apparatus
JP5602392B2 (en) Information processing apparatus, information processing method, and program
CN106272425B (en) Barrier-avoiding method and robot
US20050002555A1 (en) Image processing apparatus
CN108214487B (en) Robot target localization and grasping method based on binocular vision and lidar
CN109781010B (en) Point cloud data calculation method, device and system for large-range data splicing
CN109917413B (en) An accurate navigation and positioning method of an intelligent transfer bed
WO2022188292A1 (en) Target detection method and system, and control method, devices and storage medium
CN120307309B (en) An adaptive force manipulator gripping control method and system based on image recognition
CN109332886A (en) A kind of laser processing method and device with infinite width
CN109211260B (en) Intelligent vehicle driving path planning method and device and intelligent vehicle
CN112750194A (en) Obstacle avoidance method and device for unmanned automobile
CN117245175A (en) Multilayer multichannel weld tracking system and method based on active and passive vision
CN106682584B (en) Unmanned aerial vehicle obstacle detection method and device
JP5370122B2 (en) Moving object position estimation device and moving object position estimation method
CN112170124B (en) Visual positioning method and device for vehicle body and vehicle frame
CN112254647A (en) Object recognition and distance measurement method and device based on camera device
US20230182289A1 (en) Picking device, picking method, and program
JP2020146773A (en) Handling device and robot device
CN114942634B (en) Control method of mobile device, electronic device and storage medium
TWI608894B (en) Intelligent anti-collision safety system and tool machine using the same
Liu et al. Vehicle Distance Estimation Based on Monocular Vision and CNN
CN117325162A (en) Robot and part grabbing method, device, equipment and medium thereof

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
CP03 Change of name, title or address

Address after: 100000, 1st Floor, Building 7, No. 7 Tongji Middle Road, Beijing Economic and Technological Development Zone, Daxing District, Beijing

Patentee after: Beijing Leitai Tengfei Medical Technology Co.,Ltd.

Country or region after: China

Address before: No. 3 Jinsheng Road, Suzhou Industrial Park, Jiangsu Province

Patentee before: SUZHOU LINATECH MEDICAL SCIENCE AND TECHNOLOGY

Country or region before: China

CP03 Change of name, title or address