CN106651949A - Teleoperation method and system for grabbing objects using space mechanical arm based on simulation - Google Patents
Teleoperation method and system for grabbing objects using space mechanical arm based on simulation Download PDFInfo
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- CN106651949A CN106651949A CN201610903204.5A CN201610903204A CN106651949A CN 106651949 A CN106651949 A CN 106651949A CN 201610903204 A CN201610903204 A CN 201610903204A CN 106651949 A CN106651949 A CN 106651949A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
- B25J9/1697—Vision controlled systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
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Abstract
The invention provides a teleoperation system for grabbing objects using space mechanical arm based on simulation, which comprises a data source acquisition module, a middle piece module, a target tracking and positioning module, an operation planning module, and a motion simulation module. Through an insertion piece type structuring strategy, it is possible to realize the real time acquisition of a plurality of different data sources by the system and to realize the inconsistency adjustment between data acquisition and data processing speed. Through the use of a rapid tracking algorithm, the photographing camera is ensured to track the target in real time; and through the pose measurement algorithm, the synchronization of the poses between a real target and a simulated target could be ensured. The invention provides a testing platform for the visual positioning algorithm in the dynamic target grabbing process by a space mechanism arm and can demonstrate the grabbing process through a three-dimensional visualized manner to assist the operation men on the ground to complete the control over the grabbing process.
Description
Technical field
The present invention relates to mechanical arm remote operating field, and in particular to a kind of space manipulator capture target based on emulation is distant
Method of operating and system.
Background technology
Space manipulator is space station construction and safeguards requisite key equipment, in-orbit can complete the group of spacecraft
It is various scientific exploration experiment etc. to be carried out in installation and dismantling point, maintenance and repair, fuel conveying, satellite release and recovery and space station
Task, it is possible to reduce the extravehicular activity of spacefarer, it is to avoid life danger and save cabin expense.China will in 2022 or so,
Construction completes manned space station engineering system, breaks through and grasp terrestrial space manned technology for a long time, carries out terrestrial space section
Skill is tested, and strengthens comprehensive development and utilization space resources ability.With the development of aerospace industry, space manipulator will be played increasingly
Important effect.
It is one of three large models of space manipulator manipulation that operation is shaken on ground, is that space manipulator performs various complex spaces
The important control method that task has to rely on.When space manipulator performs the tasks such as aircraft is arrested, assembly module is changed, machine
The vision system that tool arm is carried shoots the state of the object to be operated.Ground control personnel are according to lower blit as the behaviour in observation space
Make process, yet with the transmission network bandwidth at space device and ground remote operating center is limited and transmitting procedure exist it is certain
Time delay so that operating personnel cannot Real Time Observation to operating process, also cannot accurately predict mechanical arm with the object to be operated
Relative position relation.When mechanical arm and the object to be operated are closer to the distance, then non-foreseeability collision is susceptible to, damages machinery
Arm, aircraft and assembly module.
The content of the invention
The technical problem to be solved is to provide the image that the vision system of utilization space mechanical arm carrying shoots
Measurement mechanical arm tail end predicts the movement locus of mechanical arm relative to by capture target pose, ancillary terrestrial remote operating people
Member completes the emulation mode for manipulating decision-making, with solve remote operating personnel because cannot spatial predictor mechanical arm and target relative status
And it is difficult to the problem of effective decision-making..
The technical scheme that the present invention solves above-mentioned technical problem is as follows:A kind of space manipulator capture target based on emulation
Teleoperation method, it is characterised in that comprise the following steps:
Step 1, data source acquisition module gather the figure of target by polytype plug-in unit from the data source of corresponding types
As data and unification be converted into being sent to middleware module after same format;
Step 2, middleware module receive and store the view data through changing and send to target tracking and positioning mould
Block is processed, and keeps the speed and target tracking of data source acquisition module collection view data to process image with locating module
Difference between the speed of data is maintained in preset range;
Step 3, target tracking and locating module are processed the view data through conversion, obtain the pose of target;
Step 4, operation planning module are according to the pose of target and the mechanical arm tail end pose of acquisition, planning space mechanical arm
The motion in each joint;
Step 5, motion analog module set up space manipulator threedimensional model and target three-dimensional, and according to operation planning
The motion in each joint of mechanical arm of module planning, the real-time pose for changing space manipulator threedimensional model and target three-dimensional
Pose;
Step 6, repetition above step, until completing capture of the mechanical arm to target in motion analog module.
On the basis of above-mentioned technical proposal, the present invention can also do following improvement.
Further, the step 2 specifically includes following steps:
Step 2.1, plug-in management unit are managed and allotment to polytype plug-in unit, receive the image through conversion
Data are simultaneously stored in automatic adaptation cushion area unit;
Step 2.2, automatic adaptation cushion area unit make the acquisition speed of the data source acquisition module and described
Difference between target tracking and the processing speed of locating module is maintained in preset range;
Step 2.3, data output interface unit send the view data in the automatic adaptation cushion area to target following
With locating module.
Further, the step 2.2 specifically includes following steps:
The largest frames difference that setting buffering area is allowed is FBMAX, the upper limit of the largest frames difference that buffering area is allowed is FMAX, abandon frame
Reference numerals are FTf, the frame difference of IMAQ and image procossing is FP-C;
Step 2.2.1, if FP-C> FBMAX, perform FTf=FTf+ 1, then jump to step 2.2.2;
If FP-C<FBMAX/ 2, then jump to step 2.2.3;
If FP-C≥FBMAX/ 2, and FP-C≤FBMAX, then step 2.2.4 is jumped to;
Step 2.2.2, if FTf≥FBMAX/ 2, perform FBMAX=2*FBMAX, jump to step 2.2.6;If FTf<FBMAX/
2, jump directly to step 2.2.6;
Step 2.2.3, if FP-C≤ 1, then make FTf=0, otherwise perform FTf=(FTf+ 1)/2, until 2*FTf≤FP-C, hold
Go and jump to step 2.2.5 after above-mentioned calculating;
Step 2.2.4, if FTf>0, then perform FTf=FTf- 1, until 2*FTf≤FP-C;
Step 2.2.5, if FBMAX>FMAX, then F is madeBMAX=FBMAX/2;
Step 2.2.6, if FTf>0, abandon the 2*F stored in buffering areaTf- 1 frame image data, then by 2*FTfFrame
View data is pushed to target tracking and locating module, i.e. FP-C=FP-C-2*FTf。
Further, the step 3 specifically includes following steps:
Step 3.1, the view data received through conversion are simultaneously pre-processed, and obtain each of target in current picture frame
Bar edge;
Step 3.2, the target area being calculated by edge housing in current image frame, wherein, the target area
Geometric center for target position, the size of the target area for target size;
Step 3.3, the target area in the current image frame is processed by target tracking algorism after obtain down
Target area in one picture frame;
Step 3.4, in the target area in the next image frame pixel application intensity-weighted geometric center sit
Mark computational methods obtain target following position;
Step 3.5, calculate target projection position and by between the target projection position and the target following position
The measurement model that minimizes of offset error obtain the pose of the target in every two field picture.
Further, the step 3.1 specifically includes following steps:
Step 3.1.1, gaussian filtering is carried out to image, select a certain threshold value T1, make gray scale in image be more than T1Pixel take
It is worth for 255, gray scale is less than T1Pixel value be 0, binaryzation is carried out to the image after gaussian filtering, obtain binary image;
Step 3.1.2, to binary image using corrosion expansion algorithm process, eliminate binary image in it is isolated bright
Point so that it is 255 to only have target area gray value in binary image, and other positions gray value is 0;
Step 3.1.3, to corrosion expansion after binary image carry out edge extracting.
Further, the target tracking algorism in the step 3.3 is the tracking that Camshift and Kalman filtering are blended
Algorithm.
Further, the step 3.4 is specifically, set a certain threshold value T0, all gray values in target area are more than etc.
In T0Pixel carry out intensity-weighted average calculating operation according to its position in the image after gaussian filtering process, try to achieve
Intensity-weighted Geometric center coordinates, its computing formula is:
Wherein xcRepresent the x coordinate of intensity-weighted geometric center, ycThe y-coordinate of intensity-weighted geometric center is represented, x is represented
The x coordinate of pixel in image, y represents the y-coordinate of pixel in image, the gray value at I (x, y) denotation coordination (x, y) place, R
Represent target area.
Further, the step 3.5 specifically includes following steps:
The three-dimensional coordinate position of step 3.5.1, estimation target in world coordinate system;
Step 3.5.2, according to the three-dimensional coordinate position, calculate target projection in the picture using perspective projection model
Coordinate, obtains target projection position;
Step 3.5.3, the target projection position and target following position are compared, calculate offset error;
Step 3.5.4, according to the offset error, using position of the least square refinement target in world coordinate system
Put;
Step 3.5.5, it is repeated multiple times until convergence, i.e., offset error be less than previously given threshold value.
Further, the step 4 specifically includes following steps:
Step 4.1, mechanical arm tail end Motion trajectory unit are according to by the calculated mechanical arm end of mechanical arm configuration
The pose of the target that the pose and target tracking at end is obtained with locating module, plans the mobile route of mechanical arm tail end;
The mobile road of the mechanical arm tail end that each joint cooperative motion planning unit of step 4.2, mechanical arm is obtained according to planning
The discrete loci point in footpath, by Arithmetic of inverse kinematics the movement angle in each each joint of the corresponding mechanical arm of discrete loci point is solved
And angular speed.
A kind of space manipulator capture target remote control system based on emulation, including:
Data source acquisition module, for gathering the image of target from the data source of corresponding types by polytype plug-in unit
Data simultaneously are unified to be converted into being sent to middleware module after same format;
Middleware module, for receiving and store through conversion view data and send to target tracking and locating module
Processed, and keep the speed and target tracking of data source acquisition module collection view data to process picture number with locating module
According to speed between difference be maintained in preset range;
Target tracking and locating module, for processing the view data through conversion, obtain the pose of target;
Operation planning module, for according to the pose of target and the mechanical arm tail end pose for obtaining, planning space mechanical arm
The motion in each joint;
Motion analog module, for setting up space manipulator threedimensional model and target three-dimensional, and according to operation planning
The motion in each joint of mechanical arm of module planning, the real-time pose for changing space manipulator threedimensional model and target three-dimensional
Pose.
Further, the middleware module includes that plug-in management unit, automatic adaptation cushion area unit and unitized data are defeated
Outgoing interface unit;
The plug-in management unit, for polytype plug-in unit to be loaded, managed and allocated, receives through conversion
View data and be stored in automatic adaptation cushion area unit;
Automatic adaptation cushion area unit, for making the acquisition speed and the target of the data source acquisition module
Follow the trail of and the difference between the processing speed of locating module is maintained in preset range;
The unitized data output interface unit, for the view data in the automatic adaptation cushion area to be sent to mesh
Mark tracking and locating module;
Further, the target tracking includes image pre-processing unit, object detection unit, target following with locating module
Unit, position clearing unit and pose solving unit;
Described image pretreatment unit, for reception to be through the view data of conversion and is pre-processed, obtains current
Each bar edge of target in picture frame;
The object detection unit, for the target area being calculated by edge housing in current image frame, wherein,
The geometric center of the target area is the position of target, and the size of the target area is the size of target;
The target tracking unit, for being carried out by target tracking algorism to the target area in the current image frame
The target area in next image frame is obtained after process;
The position solving unit, for adding to the pixel application gray scale in the target area in the next image frame
Power Geometric center coordinates computational methods obtain target following position;
The pose solving unit, for by the offset error between target projection position and the target following position
The measurement model of minimum obtains the pose of the target in every two field picture.
Further, the operation planning module includes mechanical arm tail end Motion trajectory unit and each joint association of mechanical arm
With motion planning unit;
The mechanical arm tail end Motion trajectory unit, for according to the pose and target tracking of mechanical arm tail end with it is fixed
The pose of the target that position module is obtained, plans the mobile route of mechanical arm tail end;
The each joint cooperative motion planning unit of the mechanical arm, the mobile road of the mechanical arm tail end for being obtained according to planning
The discrete loci point in footpath, by Arithmetic of inverse kinematics the movement angle in each each joint of the corresponding mechanical arm of discrete loci point is solved
And angular speed.
The invention has the beneficial effects as follows:Compared with existing remote operating analogue system, the remote operating emulation of present invention design
System can obtain the relative change of image trace target and measure and estimate to be arrested mesh according to mechanical arm tail end vision system
Target position and attitude, by analogue system visualization ground handling operator, ancillary terrestrial personnel's decision-making are showed.This with it is existing
Judge mechanical arm and compared by the teleoperation method of capture target relative pose by operating personnel's image browsing, largely
Alleviate the burden that operating personnel are analyzed mode of operation so that operating personnel can be placed on main attention to space manipulator
Operation and control aspect, greatly improve the efficiency of the practice of remote operating..
Description of the drawings
Fig. 1 is that space manipulator capture target remote control system comprising modules and each module data flow to graph of a relation;
Fig. 2 is space manipulator capture target teleoperation method flow chart;
Fig. 3 is the algorithm flow chart that the method that Camshift and Kalman filtering are blended realizes spatial object tracking;
Fig. 4 is the spatial relationship and its motion control step of space manipulator threedimensional model and extraterrestrial target threedimensional model.
Specific embodiment
The principle and feature of the present invention are described below in conjunction with accompanying drawing, example is served only for explaining the present invention, and
It is non-for limiting the scope of the present invention.
As shown in figure 1, the present invention provide it is a kind of based on emulation space manipulator capture target remote control system by
Data source acquisition module, middleware module, target tracking and locating module, operation planning module and motion analog module composition,
Its implementation is as shown in Fig. 2 comprise the following steps:
S1, data source acquisition module gather the picture number of target by polytype plug-in unit from the data source of corresponding types
According to and unification be converted into being sent to middleware module after same format;
S2, middleware module receive and store the view data through changing and send to target tracking and locating module
Row is processed, and keeps the speed and target tracking of data source acquisition module collection view data to process view data with locating module
Speed between difference be maintained in preset range;
S3, target tracking and locating module are processed the view data through conversion, obtain the pose of target;
S4, operation planning module according to the pose and mechanical arm tail end pose of target, each joint of planning space mechanical arm
Motion, carries out the capture of target;
S5, motion analog module set up the threedimensional model of space manipulator and target, and according to operation planning module planning
The each joint of mechanical arm motion, the pose of space manipulator threedimensional model and the pose of target three-dimensional are changed in real time;
Repeat above step, until completing capture of the mechanical arm to target in motion analog module.
The embodiment of the modules of system is illustrated below:
1st, the enforcement explanation of data source acquisition module
As shown in figure 1, data source acquisition module, including the collection of camera review stream, the collection of disk video flowing and network number
Plug-in unit is gathered according to polytype data sources such as stream collections, every class plug-in unit is explained further as follows.
Every class plug-in unit is mainly used in the reading of the data source for completing a certain type, and such as camera review stream collection plug-in unit can only
The image stream data of acquisition camera equipment, disk video flowing collection plug-in unit can only gather the video file stored in disk (such as
Avi format video files), network data flow collection plug-in unit can only read the image data stream that network interface is received.
It is per the function of class plug-in unit:According to the data that the data form made an appointment will be collected in a certain categorical data source
The view data of single frames form is resolved to, is then repacked as consolidation form image data frame, output is stored in middleware mould
In the automatic adaptation cushion area unit of block, for example consolidation form image data frame can select bitmap format.
Every class plug-in unit data unified to middleware module offer and information output form and functional interface so that all to insert
Part can be managed collectively by middleware module.The functional interface of each plug-in unit mainly includes data source capability, data acquisition control, number
According to the interface of the types such as output buffer setting.
2nd, the enforcement explanation of middleware module
Middleware module, is intermediary that data source acquisition module is interacted with target tracking with locating module, including inserter tube
Reason unit, automatic adaptation cushion area unit and data output interface unit.Middleware module utilizes plug-in management unit, completes to not
The management of same type plug-in unit and allotment.Data output interface unit provides unitized data and work(to target tracking and locating module
Energy interface so that target tracking can correctly read the view data in different types of data source with locating module.Middleware module
Automatic adaptation cushion area is provided with, the quantity for calculating storage image data in buffering area can be passed through, parts of images number is abandoned automatically
According to frame so that data acquisition end and tracking are as synchronous as possible with the process end of positioning.Three units are specifically described as follows respectively.
Plug-in management unit can read data Source Description file, and the information loading in data Source Description file and
Plug-in unit is called to realize the reading to Various types of data source.Data Source Description file essential record data source types, data source path, number
According to information such as source output data forms.Wherein data source types load and call the type of plug-in unit, data for assisted Selection
The information such as source path and data source output data form is used to send plug-in unit to, the correct data source that auxiliary plug-in completes read and
Data form is parsed.
Automatic adaptation cushion area unit can be according to acquisition speed and target tracking and the processing speed of locating module
Difference, carries out the discarding of data storage and partial data frame automatically so that target tracking and the currently processed image of locating module
The difference of frame and the latest image frame of data source acquisition module input is in the range of several frames, it is ensured that data source collection terminal and follow the trail of and calmly
Position processes the synchronism at end.It is the quantity by storage image data in calculating buffering area that it implements method, is automatically selected
Image being read frame by frame or the pattern of image being read in frame-skipping, when image is read in frame-skipping, the picture frame to skipping is abandoned.Specifically
Realize that process is as follows:
The largest frames difference that setting buffering area is allowed is FBMAX, the upper limit of the largest frames difference that buffering area is allowed is FMAX, abandon frame
Reference numerals are FTf, the frame difference of IMAQ and image procossing is FP-C;
Step 1, if FP-C> FBMAX, perform FTf=FTf+ 1, then jump to step 2.2.2;
If FP-C<FBMAX/ 2, then jump to step 2.2.3;
If FP-C≥FBMAX/ 2, and FP-C≤FBMAX, then step 2.2.4 is jumped to;
Step 2, if FTf≥FBMAX/ 2, perform FBMAX=2*FBMAX, jump to step 2.2.6;If FTf<FBMAX/ 2, directly
Connect and jump to step 2.2.6;
Step 3, if FP-C≤ 1, then make FTf=0, otherwise perform FTf=(FTf+ 1)/2, until 2*FTf≤FP-C, performed
Step 2.2.5 is jumped to after above-mentioned calculating;
Step 4, if FTf>0, then perform FTf=FTf- 1, until 2*FTf≤FP-C;
Step 5, if FBMAX>FMAX, then F is madeBMAX=FBMAX/2;
Step 6, if FTf>0, abandon the 2*F stored in buffering areaTf- 1 frame image data, then by 2*FTfTwo field picture
Data-pushing is to target tracking and locating module, i.e. FP-C=FP-C-2*FTf。
Data output interface unit is the interface of middleware module and target tracking and locating module, is responsible for from self-adapting slowly
Rush and a two field picture is read in area's unit, be sent to target tracking and locating module, use with locating module process for target tracking.
Data output interface unit and target tracking refer mainly to reading and the transmission interface of image frame data, bag with the interface of locating module
Include the reading and transmission of description and the image frame data of image frame format etc..
3rd, the enforcement explanation of target tracking and locating module
Target tracking and locating module, mainly by the process of sequence image that data source acquisition module is gathered and point
Analysis, completes the real-time tracking and positioning of extraterrestrial target.Mainly include Image semantic classification, the detection of extraterrestrial target and tracking and space
The functions such as the pose resolving of target.
Image semantic classification mainly includes the preprocessing functions such as gaussian filtering, binaryzation, corrosion expansion and edge extracting, in fact
Existing step is to carry out gaussian filtering to image first, selectes a certain threshold value T1, makes pixel value of the gray scale more than T1 in image be
255, pixel value of the gray scale less than T1 is 0, and to the image after gaussian filtering binaryzation is carried out, and obtains binary image;To two
Value image is processed using corrosion expansion algorithm, eliminates the isolated bright spot in binary image so that in binary image only
Target area gray value is 255, and other positions gray value is 0;Edge extracting is carried out to the binary image after corrosion expansion,
Each target location is obtained according to each bar edge calculations.
The detection of extraterrestrial target, feeling the pulse with the finger-tip is marked on the calculating of positions and dimensions in image.Obtain each according to image and in processing
Bar edge, by edge housing target area is can be calculated, to the geometric center extremely target in region position in the picture
Put, the size of target area is target size in the picture.
The tracking of extraterrestrial target, the method realization blended by Camshift and Kalman filtering, as shown in Fig. 2 its
Realize that step is:
Step 1, Kalman Prediction:Predict extraterrestrial target position in the picture using Kalman's method, extraterrestrial target into
The state transformation equation of picture is expressed asWherein XkFor the position of current frame image Spatial Object,Represent pre-
The position of the next two field picture Spatial Object for measuring, F represents state-transition matrix.The covariance of predicated errorBy it
Obtain in the covariance value at k moment, i.e.,Wherein QkWhat the uncertainty to be shifted due to state was produced
The covariance of random error.By the position of extraterrestrial targetAs target's center, the size of target area in current frame image
As target size, the target area S in next two field picture is calculatedk+1;
Step 2, Camshift tracking:Mainly include 3 steps:1) the histogram calculation Kalman using To Template is pre-
The back projection figure of the target area of survey;3) according to the back projection figure of target area, by first moment and zeroth order square computing meter
Calculate the center of gravity (u of target area back projection figurex,uy), i.e.,
Wherein, Ω represents the coordinate set of target area, m10And m01The first moment of target area back projection figure is represented,
m00Represent the zeroth order square of target area back projection figure;If 3) center of gravity (ux,uy) be less than relative to target area off-centring
A certain threshold value, then terminate tracking, and target area R is updated otherwise centered on position of centre of gravityk+1, repeat 1) to 3) step.Final
To accurate target areaWith target location Zk+1。
Step 3, Kalman filtering updates:Target location is obtained using second step, by kalman filter method amendment mesh
The covariance matrix of cursor position and target error.If turnover rate K of Kalman filterkRepresent given target new location information
Relative to the amendment weight of known target positional information, HkRepresent the observing matrix of target, RkTo observe the association that random noise is produced
Variance matrix, then can obtain:
So as to positional information X of target can be obtainedkWith covariance matrix PkPosterior estimate be:
Based on above-mentioned target tracking algorism, you can obtain target area, the central point for being typically based on this target area is obtained
To target following position, but, when illumination flicker in the picture, the target following position for calculating is unstable, by mistake
Difference is larger, therefore, here to the pixel application intensity-weighted Geometric center coordinates computational methods in target area, can be in the hope of
More stably, accurate target following position, it is asked for mode and is described below:
Set a certain threshold value T0, T is more than or equal to all gray values in target area0Pixel according to its Gauss filter
Position in ripple image carries out intensity-weighted average calculating operation, tries to achieve intensity-weighted center, and its computing formula is:
Wherein xcThe x coordinate of intensity-weighted geometric center, ycThe y-coordinate of intensity-weighted geometric center, x represents picture in image
The x coordinate of vegetarian refreshments, y represents the y-coordinate of pixel in image, and the gray value at I (x, y) denotation coordination (x, y) place, R represents target
Region.
The pose of extraterrestrial target is resolved, and is referred to by the offset error between target projection position and target following position most
The measurement model of littleization solves the pose per the corresponding target of two field picture in space.Wherein target projection position refer to target and
Under the conditions of coordinate is known in the alive boundary's coordinate system of camera photocentre, target electroluminescent lamp can be calculated by the method for perspective projection transformation
Projection coordinate in camera image plane.The survey that offset error between target projection position and target following position is minimized
Amount model refers to three-dimensional coordinate position of the rough estimate target in world coordinate system first, then according to the three-dimensional location coordinates
Target projection coordinate in the picture is calculated using perspective projection model, target projection position is obtained, by the target projection position
The target following position obtained with tracking is compared, and calculates offset error, is repaiied using least square method further according to offset error
Position of the positive goal in world coordinate system;It is repeated multiple times to be less than previously given threshold value up to convergence, i.e. offset error.Formula
Change process description as follows:
AssumeRepresent target position in three dimensions and attitude respectively with θ, N for target electroluminescent lamp number,
Represent target projection position, uiTarget following position is represented, then the skew between target projection position and target following position is missed
Difference minimum can be expressed as:
WhereinRepresent that target projection position is the function of target position in three dimensions and attitude, i.e., thoroughly
Depending on projective transformation function, the function is nonlinear function, can be unfolded as follows by Taylor series linearisation:
WhereinRepresentJacobian matrix, i.e.,OrderThen can be solved according to linear least square:
Pass throughUpdate with θ=θ+Δ θ iterationAnd θ, untilLess than specified threshold.
4th, the enforcement explanation of operation planning module
Operation planning module, including space manipulator end movement trajectory planning unit and each joint cooperative motion of mechanical arm
Planning unit, can make according to the motion in the position of extraterrestrial target and each joint of requirement planning space mechanical arm of capture task
Obtain the asymptotic expression capture that mechanical arm completes extraterrestrial target.
Space manipulator end movement trajectory planning unit, is responsible for the target position tried to achieve according to target tracking and locating module
Appearance and the pose by the calculated mechanical arm tail end of mechanical arm configuration, plan mechanical arm tail end capture target mobile route and
Track;The each joint cooperative motion planning unit of space manipulator, is responsible for the end mobile route discrete loci obtained according to planning
Point, by Arithmetic of inverse kinematics the movement angle and angular speed in each each joint of the corresponding mechanical arm of discrete loci point are solved.
It is expressed as follows by the method for mechanical arm configuration calculating machine arm end pose:If the angle Θ of each joint angle of mechanical arm
=[θ0θ1θ2…θn], in mechanical arm armed lever length di, axial line distance ai, joints axes angle αiIt is certain Deng structural parameters, then i-th
Pose transformation relation between individual joint and i+1 joint is expressed as Mi=R (θi)T(ai,di)R(αi), then mechanical arm tail end
Pose can be calculated as:
Wherein, R (θ1,θ2,…,θn)∈R3×3, T (θ1…θn,α1…αn,d1…dn,a1…an)∈R3×1, machine is represented respectively
Tool arm end is to the rotation between pedestal barycenter and translation transformation relation.
Due to the movement locus of space manipulator end, not only have with the cooperative motion relation in each joint of space manipulator
Close, it is also closely related with the attitude of space manipulator base carrier (space station).In actual applications generally by space manipulator
End movement trajectory planning function is reduced to calculating machine arm end to the shortest path of target, i.e. straight line path;And to machine
When each joint angle cooperative motion relation of tool arm is solved, further according to the minimum pact of base carrier (space station) attitude disturbance
Beam, the end orbit of adjustment space mechanical arm.The process that each joint angle cooperative motion relation of space manipulator is planned, i.e.,
The movement angle and angular speed in each each joint of the corresponding space manipulator of discrete loci point are solved by Arithmetic of inverse kinematics
Process, is described as follows:
Assume that Space Manipulator System has the n free degree, the differential kinematics equation in its each joint is:
Wherein, ve,ωe∈R3The respectively linear velocity and angular speed of space manipulator end, v0,ω0∈R3It is respectively empty
Between stand pedestal barycenter at linear velocity and angular speed, Θ ∈ RnFor joint angle (n is mechanical arm number of degrees of freedom), JsIt is and space station
The related Jacobian matrix of base motion, and JmIt is the Jacobian matrix related to manipulator motion.
Space manipulator is in free floating mode, and base position, attitude be uncontrolled, what space station and mechanical arm were constituted
Total system meets linear momentum and the conservation of angular momentum, that is, meet:
Wherein, ωiFor BiAngular speed.Above formula abbreviation can be obtained for matrix form:
ω is solved using above formula0Can obtain:
By (4-4) bring into (4-1) be available from it is as follows by floating space Mechanical transmission test equation:
Wherein, JgFor the generalized Jacobian of space manipulator, it is space station pedestal attitude Ψ0, joint of mechanical arm angle
Θ, each joint and space station quality miWith inertia IiFunction, JgvAnd JgvIt is respectively the generalized Jacobian square of speed and acceleration
Battle array.
Spatial attitude angle is generally described using Eulerian angles E (α, beta, gamma), Descartes's attitude angular velocity and Euler angle rate it
Between relation be:
If matrix JEFor nonsingular matrix, space station attitude angle change and machinery can be obtained according to formula (4-4) and (4-6)
Relation between shoulder joint angle:
Minimum path planning is affected to pass through following optimization problem space station attitude:
Wherein, Ψl=[αl,βl,γl]T, Ψu=[αu,βu,γu]T, Ψ=[α, beta, gamma]TRepresent mechanical arm from initial shape
Attitude angle of the state to space station under any state of dbjective state, it is necessary to be limited in the range of the attitude of space station normal work.
Formula (4-7) is carried out into discretization according to the method for equal interval sampling, then the optimization problem of discretization is solved, you can asked
Obtain the movement angle Θ in each joint of each moment corresponding space manipulatorjAnd angular speed
5th, the enforcement explanation of motion analog module
Motion analog module, refers to that the virtual emulation based on space manipulator and extraterrestrial target digital three-dimemsional model is soft
Part, including space manipulator threedimensional model and its operation behavior, the threedimensional model of extraterrestrial target and its relative to mechanical arm tail end
Or the movement relation of vision camera.
The profile of space manipulator threedimensional model and extraterrestrial target threedimensional model in virtual emulation software, with space mechanism
Arm entity is completely or approximately consistent with the profile of extraterrestrial target entity, and the size of two class threedimensional models is adopted and two class entities 1:1
Proportionate relationship setting.To space manipulator threedimensional model and the spatial relationship and its motion control step of extraterrestrial target threedimensional model
It is rapid as shown in Figure 3.
The operation behavior of space manipulator threedimensional model refers mainly to each joint motions of space manipulator and base carrier is (empty
Between stand) with the cooperative motion of space manipulator, its implementation includes two steps:
The first step, each joint motions of space manipulator, according to each pass that space manipulator operation planning module planning is obtained
Section angular movement angle and angular speed sequence are set;
The cooperative motion of second step, base carrier (space station) and space manipulator, according to base carrier and space mechanism
The immovable characteristic of arm assembly position of centre of gravity calculating the corresponding variation relation of base carrier position and attitude, according to the change
Each step of change relation setting space manipulator moves corresponding base carrier pose.
Extraterrestrial target threedimensional model relative to the motion of mechanical arm tail end or vision camera, refer to extraterrestrial target relative to
The change of the position orientation relation of mechanical arm tail end or vision camera, needs to consider extraterrestrial target relative to space station (base carrier)
Motion and space manipulator itself motion.Space station (space station and space manipulator composite entity) is with extraterrestrial target in sky
Between middle flight, space station is progressively near extraterrestrial target, it is assumed that the flying speed of space station be more than extraterrestrial target flying speed, exist
Speed difference △ v so that extraterrestrial target occurs the change of △ vt relative to the position of space manipulator end and vision camera;Simultaneously
Because each joint motions of space manipulator cause space station, space manipulator end and vision camera position and attitude to become
Change, cause extraterrestrial target to change relative to the pose of space manipulator end and vision camera.To two kinds of positions and attitude
Change be overlapped, be calculated extraterrestrial target relative to space manipulator end and vision camera absolute pose change close
System, the change of the pose of extraterrestrial target threedimensional model is controlled according to absolute pose variation relation.
The foregoing is only presently preferred embodiments of the present invention, not to limit the present invention, all spirit in the present invention and
Within principle, any modification, equivalent substitution and improvements made etc. should be included within the scope of the present invention.
Claims (13)
1. it is a kind of based on the space manipulator capture target teleoperation method for emulating, it is characterised in that to comprise the following steps:
Step 1, data source acquisition module gather the picture number of target by polytype plug-in unit from the data source of corresponding types
According to and unification be converted into being sent to middleware module after same format;
Step 2, middleware module receive and store the view data through changing and send to target tracking and locating module
Row is processed, and keeps the speed and target tracking of data source acquisition module collection view data to process view data with locating module
Speed between difference be maintained in preset range;
Step 3, target tracking and locating module are processed the view data through conversion, obtain the pose of target;
Step 4, operation planning module are respectively closed according to the pose of target and the mechanical arm tail end pose of acquisition, planning space mechanical arm
The motion of section;
Step 5, motion analog module set up space manipulator threedimensional model and target three-dimensional, and according to operation planning module
The motion in each joint of mechanical arm of planning, changes in real time the pose of space manipulator threedimensional model and the position of target three-dimensional
Appearance;
Step 6, repetition above step, until completing capture of the mechanical arm to target in motion analog module.
2. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 1, it is characterised in that
The step 2 specifically includes following steps:
Step 2.1, plug-in management unit are managed and allotment to polytype plug-in unit, receive the view data through conversion
And be stored in automatic adaptation cushion area unit;
Step 2.2, automatic adaptation cushion area unit make the acquisition speed and the target of the data source acquisition module
Follow the trail of and the difference between the processing speed of locating module is maintained in preset range;
Step 2.3, data output interface unit by the view data in the automatic adaptation cushion area send to target following with it is fixed
Position module.
3. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 2, it is characterised in that
The step 2.2 specifically includes following steps:
The largest frames difference that setting buffering area is allowed is FBMAX, the upper limit of the largest frames difference that buffering area is allowed is FMAX, abandon frame flag
Number is FTf, the frame difference of IMAQ and image procossing is FP-C;
Step 2.2.1, if FP-C> FBMAX, perform FTf=FTf+ 1, then jump to step 2.2.2;
If FP-C<FBMAX/ 2, then jump to step 2.2.3;
If FP-C≥FBMAX/ 2, and FP-C≤FBMAX, then step 2.2.4 is jumped to;
Step 2.2.2, if FTf≥FBMAX/ 2, perform FBMAX=2*FBMAX, jump to step 2.2.6;If FTf<FBMAX/ 2, directly
Connect and jump to step 2.2.6;
Step 2.2.3, if FP-C≤ 1, then make FTf=0, otherwise perform FTf=(FTf+ 1)/2, until 2*FTf≤FP-C, performed
Step 2.2.5 is jumped to after above-mentioned calculating;
Step 2.2.4, if FTf>0, then perform FTf=FTf- 1, until 2*FTf≤FP-C;
Step 2.2.5, if FBMAX>FMAX, then F is madeBMAX=FBMAX/2;
Step 2.2.6, if FTf>0, abandon the 2*F stored in buffering areaTf- 1 frame image data, then by 2*FTfTwo field picture
Data-pushing is to target tracking and locating module, i.e. FP-C=FP-C-2*FTf。
4. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 1, it is characterised in that
The step 3 specifically includes following steps:
Step 3.1, reception are passed through the view data of conversion and are pre-processed, and obtain each bar side of target in current picture frame
Edge;
Step 3.2, the target area being calculated by edge housing in current image frame, wherein, the target area it is several
What center is the position of target, and the size of the target area is the size of target;
Step 3.3, the target area in the current image frame is processed by target tracking algorism after obtain next figure
As the target area in frame;
Step 3.4, to the pixel application intensity-weighted Geometric center coordinates meter in the target area in the next image frame
Calculation method obtains target following position;
Step 3.5, calculate target projection position and by inclined between the target projection position and the target following position
The measurement model that shift error is minimized obtains the pose of the target in every two field picture.
5. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 4, it is characterised in that
The step 3.1 specifically includes following steps:
Step 3.1.1, gaussian filtering is carried out to image, select a certain threshold value T1, make gray scale in image be more than T1Pixel value be
255, gray scale is less than T1Pixel value be 0, binaryzation is carried out to the image after gaussian filtering, obtain binary image;
Step 3.1.2, to binary image using corrosion expansion algorithm process, eliminate binary image in isolated bright spot, make
It is 255 to obtain and only have in binary image target area gray value, and other positions gray value is 0;
Step 3.1.3, to corrosion expansion after binary image carry out edge extracting.
6. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 5, it is characterised in that
Target tracking algorism in the step 3.3 is the track algorithm that Camshift and Kalman filtering are blended.
7. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 4, it is characterised in that
The step 3.4 is specifically, set a certain threshold value T0, T is more than or equal to all gray values in target area0Pixel according to
Its position in the image after gaussian filtering process carries out intensity-weighted average calculating operation, tries to achieve intensity-weighted geometric center
Coordinate, its computing formula is:
Wherein xcRepresent the x coordinate of intensity-weighted geometric center, ycThe y-coordinate of intensity-weighted geometric center is represented, x represents image
The x coordinate of middle pixel, y represents the y-coordinate of pixel in image, and the gray value at I (x, y) denotation coordination (x, y) place, R is represented
Target area.
8. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 4, it is characterised in that
The step 3.5 specifically includes following steps:
The three-dimensional coordinate position of step 3.5.1, estimation target in world coordinate system;
Step 3.5.2, according to the three-dimensional coordinate position, calculate target projection in the picture using perspective projection model and sit
Mark, obtains target projection position;
Step 3.5.3, the target projection position and target following position are compared, calculate offset error;
Step 3.5.4, according to the offset error, using position of the least square refinement target in world coordinate system;
Step 3.5.5, it is repeated multiple times until convergence, i.e., offset error be less than previously given threshold value.
9. a kind of based on the space manipulator capture target teleoperation method for emulating according to claim 1, it is characterised in that
The step 4 specifically includes following steps:
Step 4.1, mechanical arm tail end Motion trajectory unit are according to by the calculated mechanical arm tail end of mechanical arm configuration
The pose of the target that pose and target tracking are obtained with locating module, plans the mobile route of mechanical arm tail end;
The mobile route of the mechanical arm tail end that each joint cooperative motion planning unit of step 4.2, mechanical arm is obtained according to planning
Discrete loci point, by Arithmetic of inverse kinematics movement angle and the angle in each each joint of the corresponding mechanical arm of discrete loci point are solved
Speed.
10. it is a kind of based on the space manipulator capture target remote control system for emulating, it is characterised in that to include:
Data source acquisition module, for gathering the view data of target from the data source of corresponding types by polytype plug-in unit
And unification is converted into being sent to middleware module after same format;
Middleware module, for receiving and the view data and sending to target tracking that stores through changing is carried out with locating module
Process, and keep the speed and target tracking of data source acquisition module collection view data to process view data with locating module
Difference between speed is maintained in preset range;
Target tracking and locating module, for processing the view data through conversion, obtain the pose of target;
Operation planning module, for according to the pose of target and the mechanical arm tail end pose for obtaining, planning space mechanical arm respectively to be closed
The motion of section;
Motion analog module, for setting up space manipulator threedimensional model and target three-dimensional, and according to operation planning module
The motion in each joint of mechanical arm of planning, changes in real time the pose of space manipulator threedimensional model and the position of target three-dimensional
Appearance.
11. is a kind of based on the space manipulator capture target remote control system for emulating according to claim 10, and its feature exists
In the middleware module includes plug-in management unit, automatic adaptation cushion area unit and unitized data output interface unit;
The plug-in management unit, for polytype plug-in unit to be loaded, managed and allocated, receives the figure through conversion
As data and it is stored in automatic adaptation cushion area unit;
Automatic adaptation cushion area unit, for making the acquisition speed and the target tracking of the data source acquisition module
The difference and processing speed of locating module between is maintained in preset range;
The unitized data output interface unit, for by the view data in the automatic adaptation cushion area send to target with
Track and locating module;
12. is a kind of based on the space manipulator capture target remote control system for emulating according to claim 10, and its feature exists
In the target tracking includes image pre-processing unit, object detection unit, target tracking unit, position knot with locating module
Calculate unit and pose solving unit;
Described image pretreatment unit, for reception to be through the view data of conversion and is pre-processed, obtains current image
Each bar edge of target in frame;
The object detection unit, for the target area being calculated by edge housing in current image frame, wherein, it is described
The geometric center of target area is the position of target, and the size of the target area is the size of target;
The target tracking unit, for being processed by target tracking algorism the target area in the current image frame
The target area in next image frame is obtained afterwards;
The position solving unit, for several to the pixel application intensity-weighted in the target area in the next image frame
What centre coordinate computational methods obtains target following position;
The pose solving unit, for minimum by the offset error between target projection position and the target following position
The measurement model of change obtains the pose of the target in every two field picture.
13. is a kind of based on the space manipulator capture target remote control system for emulating according to claim 10, and its feature exists
In the operation planning module includes that mechanical arm tail end Motion trajectory unit and each joint cooperative motion planning of mechanical arm are single
Unit;
The mechanical arm tail end Motion trajectory unit, for according to the pose and target tracking of mechanical arm tail end and positioning mould
The pose of the target that block is obtained, plans the mobile route of mechanical arm tail end;
The each joint cooperative motion planning unit of the mechanical arm, for the mobile route of mechanical arm tail end that obtained according to planning
Discrete loci point, by Arithmetic of inverse kinematics movement angle and the angle in each each joint of the corresponding mechanical arm of discrete loci point are solved
Speed.
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101726296A (en) * | 2009-12-22 | 2010-06-09 | 哈尔滨工业大学 | Vision measurement, path planning and GNC integrated simulation system for space robot |
CN101733746A (en) * | 2009-12-22 | 2010-06-16 | 哈尔滨工业大学 | Autonomously identifying and capturing method of non-cooperative target of space robot |
CN103926845A (en) * | 2014-04-17 | 2014-07-16 | 哈尔滨工业大学 | Ground-based simulation system for space robot visual servo to capture moving target and simulation method |
CN105635648A (en) * | 2014-10-28 | 2016-06-01 | 江苏绿扬电子仪器集团有限公司 | Video real-time edge detection system |
CN106003104A (en) * | 2015-07-03 | 2016-10-12 | 中国运载火箭技术研究院 | Mechanical arm planning method suitable for visual information guiding under multi-constrained condition |
-
2016
- 2016-10-17 CN CN201610903204.5A patent/CN106651949B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101726296A (en) * | 2009-12-22 | 2010-06-09 | 哈尔滨工业大学 | Vision measurement, path planning and GNC integrated simulation system for space robot |
CN101733746A (en) * | 2009-12-22 | 2010-06-16 | 哈尔滨工业大学 | Autonomously identifying and capturing method of non-cooperative target of space robot |
CN103926845A (en) * | 2014-04-17 | 2014-07-16 | 哈尔滨工业大学 | Ground-based simulation system for space robot visual servo to capture moving target and simulation method |
CN105635648A (en) * | 2014-10-28 | 2016-06-01 | 江苏绿扬电子仪器集团有限公司 | Video real-time edge detection system |
CN106003104A (en) * | 2015-07-03 | 2016-10-12 | 中国运载火箭技术研究院 | Mechanical arm planning method suitable for visual information guiding under multi-constrained condition |
Non-Patent Citations (1)
Title |
---|
孙凯等: "《多目标跟踪的改进Camshift/卡尔曼滤波组合算法》", 《信息与控制》 * |
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