CN104503449A - Positioning method based on environment line features - Google Patents
Positioning method based on environment line features Download PDFInfo
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- CN104503449A CN104503449A CN201410677187.9A CN201410677187A CN104503449A CN 104503449 A CN104503449 A CN 104503449A CN 201410677187 A CN201410677187 A CN 201410677187A CN 104503449 A CN104503449 A CN 104503449A
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Abstract
The invention discloses a positioning method based on environment line features. The method comprises the following steps: 1) a global coordinate system is set; 2) an environment feature map is built; 3) a robot starts to continuously scan environment information from a starting point; 4) filter processing is carried out on scanning data points; 5) the data points after scanning are divided into different types; 6) IEP algorithm is adopted to carry out line feature recognition on each type; 7) a line is drawn from the data point collection of the line features, and feature parameters are calculated; 8) the line features are converted under the global coordinate system from under a laser coordinate system, and laser scanning data are used for correcting dead-reackoning errors of inertial navigation; 9) the obtained line features are added to the environment feature map; 10) the above steps are repeated, and the environment feature map is obtained; and 11) the robot starts to move from the starting point, and the environment features scanned continuously and the built environment feature map are matched for realizing self positioning.
Description
Technical field
The invention belongs to localization for Mobile Robot technical field, particularly a kind of localization method based on environment linear feature.
Background technology
In the application of mobile robot, navigator fix is the key function of robot system.Navigation refers to that mobile robot obtains environmental information and self position and posture by sensor, to realize in the environment of barrier autokinetic movement to destination.The key of navigation and prerequisite are location, and location refers to determines robot self position in the environment and attitude in real time.
At present comparatively common robot localization technology mainly according to the environmental information of priori, in conjunction with the information determination robot position and posture that current robot positional information and sensor obtain.Location technology is mainly divided into absolute fix and relative positioning; What absolute fix was conventional has satellite GPS location, navigation road sign, map match etc., and relative positioning determines current position and posture by calculating relative to the pose change of initial pose, common are odometer, inertial navigation system.GPS positioning error is comparatively large, and easily by electromagnetic interference (EMI); Navigation rout marking allocation needs to set up navigation road sign and changes existing environment, wastes time and energy; And existing map-matching algorithm needs manual creation environmental map or the autonomous not high closed loop etc. that cannot be formed of the accuracy of map created; And odometer, inertial navigation system etc. are long-time or under large scale cumulative errors comparatively large, positioning precision is poor.The various problems that existing navigation locating method exists, cannot accurately, effortlessly for robot provides posture information.
Summary of the invention
The object of the invention is to solve the problem, providing a kind of and can complete robot autonomous establishment map and location without the need to changing environment, and the localization method based on environment linear feature that precision is higher.
For this reason, technical scheme of the present invention is: a kind of localization method based on environment linear feature, the robot at least with kinetic control system, inertial navigation system, scanning laser sensor uses; It is characterized in that: it comprises the following steps:
1) first under new circumstances not known, arranging starting point pose Z0, and arrange global coordinate system as benchmark, is namely coordinate origin with start position, is oriented y-axis forward, by right-hand rule determination x-axis forward with starting point motion;
2) control moves with autonomous creation environment characteristics map in the environment;
3) robot moves from the off, and the continuous scanning circumstance information of the contained laser sensor of robot obtains taking laser sensor as angle, the distance polar coordinates point data of initial point; Robot often motion certain distance will process a laser scanning data;
The boat position information that inertial navigation system continuous output device people is current, this boat position information is utilized constantly to calculate the distance delta_d of current point and last scan-data process position, laser scanning data process below then carrying out when this distance is more than or equal to the threshold value delta_dthreshod of setting, and by clear for delta_d 0, restart to calculate delta_d from current point;
4) filtering process is carried out to mixed and disorderly irregular laser scanning data point, remove and effectively calculating the useless point outside distance range;
5) by the continuation property clustering processing that filtered data point distributes according to it, different classifications is divided into; Calculate adjacent two laser scanning point distance nd_laser, if this distance is less than or equal to setting threshold value thr_cate, be judged to be same classification, same classification represents the continuous surface of this point set from barrier; Suitable threshold value thr_cate is set simultaneously, classification less for data point is rejected to accelerate data processing speed;
6) adopt IEP algorithm to carry out linear feature identification to each classification, find out the data point set forming linear feature in each category; Rational threshold value thr_cate is set, straight line point set less for data point is rejected;
7) utilize criterion of least squares to simulate straight line from the data point set of linear feature, and calculate its characteristic parameter;
Centered by robot, coordinate system overlaps with the coordinate system centered by laser sensor, described parameter is under laser sensor coordinate system, straight line is to the vertical line of initial point distance d, straight line and true origin and polar axis shaft angle theta, rectilinear end point coordinate p1 (x, y), p2 (x, y) and linearly dependent coefficient r; Wherein d, theta straight-line equation parameter, utilizes line segment end points p1, and p2 calculates line segment length and matching line segments; Utilize linear coefficient r as its linear feature similarity degree of differentiation, preferentially utilize the high linear feature of linear coefficient to position calculating;
8) by the linear feature obtained in above-mentioned steps from laser coordinate system downconverts to global coordinate system, and utilize laser scanning data to correct the boat position error of inertial navigation;
The characteristic parameter extracted with twice laser scanning data of same straight line is for benchmark, Extrapolation coordinate system transformation relation, under laser scanner coordinate system, the change of characteristic straight line pose is robot pose variable quantity under global coordinate system between twice laser scanning, corrects the position and posture of inertial navigation output with this;
9) above-mentioned steps being corrected the linear feature obtained adds in environmental characteristic map, and described environmental characteristic map is the database of recording feature straight line parameter, and every bar is recorded as a characteristic straight line, the attribute of record is respectively the characteristic parameter d of straight line, theta, p1, p2;
10) make robot move in whole environment and repeat above-mentioned steps, to obtain the characteristics map of whole environment;
11) robot moves from the off, is undertaken mating realizing self-align by the environmental characteristic constantly scanned and the environmental characteristic map created;
Robot moves from the off, inertial navigation exports the coarse value of current pose, the continuous Current Scan current environment of laser, obtain characteristic straight line according to above-mentioned characteristic extraction procedure at a certain distance and transform to global coordinate system, search corresponding linear feature creating in map, differentiate in map, whether existing straight line is corresponding with current signature straight line.
The present invention is based on the output pose of inertial navigation, utilize the linear feature in laser scanning acquisition physical environment, inertial navigation error is corrected by lap in the twice sweep of front and back, create high-precision environmental characteristic map, then utilize the map of this establishment to mate with real-time scan data and position.The present invention can complete robot autonomous establishment map and location without the need to changing environment, and precision is higher.
Accompanying drawing explanation
Be described in further details below in conjunction with accompanying drawing and embodiments of the present invention.
Fig. 1 workflow diagram of the present invention.
Fig. 2 extraction of straight line process flow diagram of the present invention.
Fig. 3 map building process flow diagram of the present invention.
Fig. 4 error correction process flow diagram of the present invention.
Fig. 5 map match process flow diagram of the present invention.
Embodiment
See accompanying drawing.The present embodiment comprises the following steps:
1) first under new circumstances not known, arranging starting point pose Z0, and arrange global coordinate system as benchmark, is namely coordinate origin with start position, is oriented y-axis forward, by right-hand rule determination x-axis forward with starting point motion;
2) control moves with autonomous creation environment characteristics map in the environment;
3) map building module and map match locating module is mainly comprised as shown in Figure 1; Be illustrated in figure 3 the autonomous constructive process of map based on environmental characteristic:
Robot moves from the off, and the continuous scanning circumstance information of the contained laser sensor of robot obtains taking laser sensor as angle, the distance polar coordinates point data of initial point; Robot often motion certain distance will process a laser scanning data;
The boat position information that inertial navigation system continuous output device people is current, this boat position information is utilized constantly to calculate the distance delta_d of current point and last scan-data process position, laser scanning data process below then carrying out when this distance is more than or equal to the threshold value delta_dthreshod of setting, and by clear for delta_d 0, restart to calculate delta_d from current point;
4) from laser scanning data, extract linear feature process as shown in Figure 2: filtering process is carried out to mixed and disorderly irregular laser scanning data point, remove and effectively calculating the useless point outside distance range;
5) by the continuation property clustering processing that filtered data point distributes according to it, different classifications is divided into; Method is for calculating adjacent two laser scanning point distance nd_laser, if this distance is less than or equal to setting threshold value thr_cate, be judged to be same classification, same classification represents the continuous surface of this point set from barrier; Suitable threshold value thr_cate is set simultaneously, classification less for data point is rejected to accelerate data processing speed;
6) adopt IEP algorithm to carry out linear feature identification to each classification, find out the data point set forming linear feature in each category; Rational threshold value thr_cate is set, straight line point set less for data point is rejected;
7) utilize criterion of least squares to simulate straight line from the data point set of linear feature, and calculate its characteristic parameter;
Suppose that coordinate system overlaps with the coordinate system centered by laser sensor centered by robot, described parameter is under laser sensor coordinate system, straight line is to the vertical line of initial point distance d, straight line and true origin and polar axis shaft angle theta, rectilinear end point coordinate p1 (x, y), p2 (x, y) and linearly dependent coefficient r; Wherein d, theta straight-line equation parameter, utilizes line segment end points p1, and p2 calculates line segment length and matching line segments; Utilize linear coefficient r as its linear feature similarity degree of differentiation, preferentially utilize the high linear feature of linear coefficient to position calculating;
8) by the linear feature obtained in above-mentioned steps from laser coordinate system downconverts to global coordinate system, and utilize laser scanning data to correct the boat position error of inertial navigation;
Be illustrated in figure 4 error recovery procedure, wherein L1 represents the characteristic straight line of extraction parameter under laser sensor coordinate system, and L1 ... } representation feature straight line collection, L1 ', ... represent by straight line collection L1 ... } and transform to global coordinate system under, (L1 ' ', L2 ' '), ... represent by L1 ... } to L2 ... } and line correspondence to mapping ensemblen;
Under characteristic straight line conversion global coordinate system identical in twice laser scanning, its characteristic parameter can there are differences, main cause is that the current pose that inertial navigation causes exists error, namely there is error in coordinate conversion relation, thus causes same straight line in environment to have different parameters under world coordinates; Thus the characteristic parameter extracted with twice laser scanning data of same straight line is for benchmark, Extrapolation coordinate system transformation relation, under laser scanner coordinate system, the change of characteristic straight line pose is robot pose variable quantity under global coordinate system between twice laser scanning, corrects the position and posture of inertial navigation output with this; Nearest neighbor method is wherein adopted to differentiate in twice different scanning data whether be same straight line.Concrete grammar is, supposes a certain straight line parameter that L1 (r1, theta1) extracts for T1 moment laser scanning data, and this moment robot pose coordinate is Z1 (X1, Y1, THETA1); L2 (r2, theta2) be a certain straight line parameter of T2 moment laser scanning data extraction, this moment robot pose is Z2 (X2, Y2, THETA2), under twice, front and back straight line parameter being transformed to global coordinate system, determine that whether two straight lines are from same object according to discrimination standard; The discrimination standard adopted is, two air line distance difference absolute values are less than setting threshold value lthr_d, and two straight line differential seat angle absolute values are less than setting threshold value lthr_theta, and two line correspondences end-point distances are less than setting threshold value lthr_pd; Suppose L1, L2 is judged to be same straight line, then to T2 moment robot pose variable quantity deltaZ when being easy to calculate T1, utilize this pose to correct pose Z2=Z1+deltaZ;
9) above-mentioned steps being corrected the linear feature obtained adds in environmental characteristic map, and described environmental characteristic map is the database of recording feature straight line parameter, and every bar is recorded as a characteristic straight line, the attribute of record is respectively the characteristic parameter d of straight line, theta, p1, p2;
10) make robot move in whole environment and repeat above-mentioned steps, to obtain the characteristics map of whole environment;
11) robot moves from the off, is undertaken mating realizing self-align by the environmental characteristic constantly scanned and the environmental characteristic map created;
Be illustrated in figure 5 map match position fixing process, wherein ML1 is by being recorded a certain characteristic straight line in map, and ML1 ... } be the straight line collection of map record; Robot moves from the off, inertial navigation exports the coarse value of current pose, the continuous Current Scan current environment of laser, obtain characteristic straight line according to above-mentioned characteristic extraction procedure at a certain distance and transform to global coordinate system, search corresponding linear feature creating in map, differentiate it is that in map, whether existing straight line is corresponding with current signature straight line with above-mentioned criterion.If characteristic of correspondence straight line record can be found in map to be assumed to be ML1, then record based on ML1 by this and calculate current pose Z with Current Scan data L1.If characteristic of correspondence straight line record cannot be found in map, suppose L2 ', then judge that Current Scan data are as a new feature, this new feature ML2 ' is added in map to upgrade current map.
Claims (1)
1., based on a localization method for environment linear feature, the robot at least with kinetic control system, inertial navigation system, scanning laser sensor uses; It is characterized in that: it comprises the following steps:
1) first under new circumstances not known, arranging starting point pose Z0, and arrange global coordinate system as benchmark, is namely coordinate origin with start position, is oriented y-axis forward, by right-hand rule determination x-axis forward with starting point motion;
2) control moves with autonomous creation environment characteristics map in the environment;
3) robot moves from the off, and the continuous scanning circumstance information of the contained laser sensor of robot obtains taking laser sensor as angle, the distance polar coordinates point data of initial point; Robot often motion certain distance will process a laser scanning data;
The boat position information that inertial navigation system continuous output device people is current, this boat position information is utilized constantly to calculate the distance delta_d of current point and last scan-data process position, laser scanning data process below then carrying out when this distance is more than or equal to the threshold value delta_dthreshod of setting, and by clear for delta_d 0, restart to calculate delta_d from current point;
4) filtering process is carried out to mixed and disorderly irregular laser scanning data point, remove and effectively calculating the useless point outside distance range;
5) by the continuation property clustering processing that filtered data point distributes according to it, different classifications is divided into; Calculate adjacent two laser scanning point distance nd_laser, if this distance is less than or equal to setting threshold value thr_cate, be judged to be same classification, same classification represents the continuous surface of this point set from barrier; Suitable threshold value thr_cate is set simultaneously, classification less for data point is rejected to accelerate data processing speed;
6) adopt IEP algorithm to carry out linear feature identification to each classification, find out the data point set forming linear feature in each category; Rational threshold value thr_cate is set, straight line point set less for data point is rejected;
7) utilize criterion of least squares to simulate straight line from the data point set of linear feature, and calculate its characteristic parameter;
Centered by robot, coordinate system overlaps with the coordinate system centered by laser sensor, described parameter is under laser sensor coordinate system, straight line is to the vertical line of initial point distance d, straight line and true origin and polar axis shaft angle theta, rectilinear end point coordinate p1 (x, y), p2 (x, y) and linearly dependent coefficient r; Wherein d, theta straight-line equation parameter, utilizes line segment end points p1, and p2 calculates line segment length and matching line segments; Utilize linear coefficient r as its linear feature similarity degree of differentiation, preferentially utilize the high linear feature of linear coefficient to position calculating;
8) by the linear feature obtained in above-mentioned steps from laser coordinate system downconverts to global coordinate system, and utilize laser scanning data to correct the boat position error of inertial navigation;
The characteristic parameter extracted with twice laser scanning data of same straight line is for benchmark, Extrapolation coordinate system transformation relation, under laser scanner coordinate system, the change of characteristic straight line pose is robot pose variable quantity under global coordinate system between twice laser scanning, corrects the position and posture of inertial navigation output with this;
9) above-mentioned steps being corrected the linear feature obtained adds in environmental characteristic map, and described environmental characteristic map is the database of recording feature straight line parameter, and every bar is recorded as a characteristic straight line, the attribute of record is respectively the characteristic parameter d of straight line, theta, p1, p2;
10) make robot move in whole environment and repeat above-mentioned steps, to obtain the characteristics map of whole environment;
11) robot moves from the off, is undertaken mating realizing self-align by the environmental characteristic constantly scanned and the environmental characteristic map created;
Robot moves from the off, inertial navigation exports the coarse value of current pose, the continuous Current Scan current environment of laser, obtain characteristic straight line according to above-mentioned characteristic extraction procedure at a certain distance and transform to global coordinate system, search corresponding linear feature creating in map, differentiate in map, whether existing straight line is corresponding with current signature straight line.
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