CN102096927A - Target tracking method of independent forestry robot - Google Patents
Target tracking method of independent forestry robot Download PDFInfo
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Abstract
The invention discloses a target tracking method of an independent forestry robot, and the method can be applied to target tracking of the independent forestry robot consisting of a computer visual and digital control pan-tilt and a central control computer. in the method, a moving target detection part and a pan-tilt real-time movement control part are utilized, wherein the moving target detection part comprises an image pretreatment module, a movement information acquisition module adopting a multi-frame difference method, a moving target judgment module and a target central coordinate calculation module; the moving target detection part is used for detecting the information of a moving target and recording the bounding rectangle and central coordinate of the target; and the pan-tilt real-time movement control part is used for controlling the center of the target to be positioned at an area adjacent to an image center. By utilizing the method, the independent forestry robot is ensured to control the operation target to be positioned at the image center or the area adjacent to the image central of the vision system of the independent forestry robot all the time in the operation process.
Description
Technical field
The present invention relates to a kind of robot target tracking technique, relate in particular to a kind of autonomous forestry robot target tracking.
Background technology
AUTONOMOUS TASK type forestry robot belongs to a kind of of specialized robot, and its research is noticeable day by day, and this mainly is because this particular environment of forest zone determines.Autonomous forestry robot wishes that in operation process operative goals is positioned at the picture centre position or the near zone of forestry robotic vision system all the time.Because target and forestry robot all may be for motion states, institute is kept in motion with the relative robot of forestry robot manipulating task target, and the shape size of operative goals is all uncertain, in order to guarantee that operative goals is positioned at the picture centre position or the near zone of forestry robotic vision system all the time, need to detect in real time moving target, calculate the centre coordinate of target, and adjust the direction and the angle of The Cloud Terrace according to the difference of target's center's coordinate and picture centre position in real time.
In the prior art, because the target that detects has uncertainty, especially the target when motion is complicated, is not easy to carry out color of image, and during the description of shape, the real-time detection of target in the image/video sequence then has certain difficulty; The rarely seen report of real-time adaptive control algolithm of while The Cloud Terrace.
Summary of the invention
The purpose of this invention is to provide a kind of autonomous forestry robot that can make in operation process, make operative goals be positioned at the picture centre position of forestry robotic vision system or the autonomous forestry robot target tracking of near zone all the time.
The objective of the invention is to be achieved through the following technical solutions:
Autonomous forestry robot target tracking of the present invention, this method is applied to comprise the target following of the autonomous forestry robot of computer vision, digital control The Cloud Terrace and central control computer, comprises moving object detection part and The Cloud Terrace real time kinematics control section;
Described moving object detection partly comprises movable information acquisition module, moving target discrimination module, target's center's coordinate Calculation module of image pretreatment module, Multi Frame Difference point-score;
Described image pre-service is used for multiple image is carried out image filtering, image gray processing and the conversion of image segmentation linear segmented;
The movable information acquisition module of described Multi Frame Difference point-score at first carries out difference in twos to all images, and each difference image is carried out image segmentation, then the difference image after cutting apart is accumulated summation, obtains moving target information;
Described moving target discrimination module judges whether to exist moving target according to preset threshold;
If have moving target, boundary rectangle and target's center's coordinate of then described target's center coordinate Calculation module records target;
Described The Cloud Terrace real time kinematics control section is controlled the near zone that is centered close to picture centre of described target.
As seen from the above technical solution provided by the invention, the autonomous forestry robot target tracking that the embodiment of the invention provides, owing to comprise moving object detection part and The Cloud Terrace real time kinematics control section, moving object detection partly detects moving target information, and the boundary rectangle of record object and target's center's coordinate; The near zone that is centered close to picture centre of The Cloud Terrace real time kinematics control section controlled target.Can make autonomous forestry robot in operation process, make operative goals be positioned at the picture centre position or the near zone of forestry robotic vision system all the time.
Description of drawings
In order to be illustrated more clearly in the technical scheme of the embodiment of the invention, the accompanying drawing of required use is done to introduce simply in will describing embodiment below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite of not paying creative work, can also obtain other accompanying drawings according to these accompanying drawings.
The autonomous forestry robot target tracing task synoptic diagram that Fig. 1 provides for the embodiment of the invention;
Fig. 2 is based on the The Cloud Terrace real-time control system structural representation of computer vision in the embodiment of the invention;
Fig. 3 is that autonomous forestry robot target is followed the tracks of overall flow figure in the embodiment of the invention;
Fig. 4 is the real-time testing process figure of moving target in the embodiment of the invention;
Fig. 5 is a The Cloud Terrace real time kinematics control flow chart in the embodiment of the invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on embodiments of the invention, those of ordinary skills belong to protection scope of the present invention not making the every other embodiment that is obtained under the creative work prerequisite.
Below in conjunction with accompanying drawing the embodiment of the invention is described in further detail.
Autonomous forestry robot target tracking of the present invention, this method are applied to comprise the target following of the autonomous forestry robot of computer vision, digital control The Cloud Terrace and central control computer, and its preferable embodiment is:
Comprise moving object detection part and The Cloud Terrace real time kinematics control section;
Described moving object detection partly comprises movable information acquisition module, moving target discrimination module, target's center's coordinate Calculation module of image pretreatment module, Multi Frame Difference point-score;
Described image pre-service is used for multiple image is carried out image filtering, image gray processing and the conversion of image segmentation linear segmented;
The movable information acquisition module of described Multi Frame Difference point-score at first carries out difference in twos to all images, and each difference image is carried out image segmentation, then the difference image after cutting apart is accumulated summation, obtains moving target information;
Described moving target discrimination module judges whether to exist moving target according to preset threshold;
If have moving target, boundary rectangle and target's center's coordinate of then described target's center coordinate Calculation module records target;
Described The Cloud Terrace real time kinematics control section is controlled the near zone that is centered close to picture centre of described target.
The movable information acquisition module of described Multi Frame Difference point-score obtains moving target information and comprises step:
A, image difference calculate: sequence of video images and sampling rate are provided with, to be applicable to the target of accurate extraction different motion speed;
The Threshold Segmentation of B, difference image: carry out Threshold Segmentation at each difference image, obtain bianry image;
C, all bianry images are sued for peace, the zone of location persistent movement obtains moving object boundary information.
In the described steps A, default setting is: every group of image sequence n=3 width of cloth gray scale picture, sampling rate is 0.2s.Be that every 200ms gathers a frame picture second, obtaining 3 frame pictures continuously altogether is one group, utilizes 3 width of cloth images to carry out calculus of differences in twos, obtains difference image n altogether
Δ f=3* (3-1)/2 width of cloth;
Among the described step B, utilizing the maximum between-cluster variance threshold method to calculate segmentation threshold, specifically is to utilize at random that threshold value is divided into two classes with pixel grey scale, and this two classes gray average distance threshold value farthest is an optimal segmenting threshold;
Among the described step C,, utilize the disposal route of the after expansion of corrosion earlier of mathematical morphology to remove noise and noise spot, obtain the boundary information of moving target for the image after the summation.
Described preset threshold is the area threshold of moving target;
Described target's center coordinate is the first moment of target image and the ratio of zeroth order square.
Described The Cloud Terrace real time kinematics control section is according to the level of described target's center coordinate control figure control The Cloud Terrace, the angular setting tolerance of vertical both direction, and the formation closed-loop control system.
The control algolithm of described The Cloud Terrace real time kinematics control section comprises:
The boundary rectangle cross-directional length that makes target is W, and vertical-direction length is H, and target's center's coordinate is that (x, y), the picture centre coordinate is (x
0, y
0), the set-up procedure of digital control The Cloud Terrace is as follows:
D, calculating target's center and picture centre position difference (Δ x, Δ y), Δ x=x
0-x, Δ y=y
0-y;
E, if
Then target is for picture centre or near zone, and The Cloud Terrace does not need to adjust, and turns to step D; If
The Cloud Terrace need be adjusted, and turns to step F;
F, if | Δ x|＞δ, the The Cloud Terrace horizontal direction is adjusted angle delta θ
x=k
xΔ x, wherein
As Δ θ
x＞0 The Cloud Terrace in the horizontal direction should be along counterclockwise adjusting, as Δ θ
x＜0 The Cloud Terrace in the horizontal direction should be along the clockwise direction adjustment; If | Δ y|＞δ, the The Cloud Terrace vertical direction is adjusted angle delta θ
y=k
yΔ y, wherein
As Δ θ
y＞0 The Cloud Terrace should be adjusted downwards in the horizontal direction, as Δ θ
y＜0 The Cloud Terrace should adjust upward in the horizontal direction; The Cloud Terrace level, vertical both direction adjustment change step D over to after finishing;
In the following formula, δ is a preset threshold.
The present invention is mainly used in autonomous forestry robot and detects target automatically when forest operation, and adjusts the angle of The Cloud Terrace in real time, allows the centre coordinate of operative goals of forestry robot be in picture centre or near zone all the time, belongs to forestry intelligence equipment field.
Autonomous forestry of the present invention robot, the hardware supported based on the The Cloud Terrace real-time control system of computer vision that comprises that video camera, digital control The Cloud Terrace and control computer etc. form comprises three parts such as video camera, digital control The Cloud Terrace and control computer.Camera pedestal is located on the digital control The Cloud Terrace, and video camera is connected by the IEEE1394 interface with supervisory control comuter, reads the image that video camera obtains in real time by supervisory control comuter, and carries out Flame Image Process and analysis according to the related algorithm of the bright proposition of this law.Digital control The Cloud Terrace is connected the row communication of going forward side by side by the RS232 interface with computing machine, computing machine sends the real-time attitude control command of The Cloud Terrace by the RS232 interface to the Numerical Control The Cloud Terrace, and The Cloud Terrace is realized autonomous forestry robot target tracking according to the attitude that control command changes self.The interface that connects between type of hardware and the hardware in this system is not limited thereto.
The present invention has the following advantages:
Autonomous forestry robot target tracking of the present invention does not rely on specific hardware system, be used in The Cloud Terrace real-time control system based on computer vision, as long as this system comprises supervisory control comuter, digital control The Cloud Terrace and video camera, the concrete model of these hardware and interface type are not limited to previously described IEEE1394 interface and RS232 interface, and dissimilar interfaces is the driving method difference;
The target of automatic real-time track automatically detects by moving target and obtains among the present invention, does not need the priori relevant with target, such as the target sizes shape type etc.The autonomous forestry robot that can be applied to the different work type of this invention;
The control in real time of the self-adaptation of The Cloud Terrace is a closed-loop control among the present invention, control algolithm can be according to the size apart from self-adaptation adjustment The Cloud Terrace level, vertical both direction angle accent amount of target location with picture centre, in target location and picture centre position bigger in, The Cloud Terrace orientation angle accent amount is big, in target location and picture centre position less in The Cloud Terrace orientation angle accent amount little.Designed a tolerance surplus δ simultaneously, do not need target's center to overlap fully with picture centre, only need target to get final product at the picture centre near zone, can avoid like this when target during very near picture centre The Cloud Terrace also be in the situation of adjustment state always.
Specific embodiment, extremely shown in Figure 5 as Fig. 1:
The forestry robot target tracing task synoptic diagram that Fig. 1 provides has reflected the concrete and tracing process of target following; Fig. 2 has provided the The Cloud Terrace real-time control system structural drawing based on computer vision, just realizes the hardware system of a kind of autonomous forestry robot target tracking that the present invention proposes; Fig. 3, Fig. 4 and Fig. 5 are a kind of software flow patterns of autonomous forestry robot target tracking.
As shown in Figure 1, it is exactly the angle of controlling the horizontal vertical direction of The Cloud Terrace under autonomous forestry robot ambulation or static situation automatically that autonomous forestry robot target is followed the tracks of, and allows target be positioned at the center or the near zone of image all the time;
As shown in Figure 2, be a kind of The Cloud Terrace real-time control system based on computer vision, wherein video camera, The Cloud Terrace monitoring calculating and the interface between them there are not special requirement;
Again referring to Fig. 1, at the camera acquisition image and after detecting target, calculate difference (the Δ x of target's center's coordinate and picture centre position, Δ y), the The Cloud Terrace real time kinematics control method that supervisory control comuter proposes according to the present invention is adjusted the attitude of The Cloud Terrace, allows target be positioned at the center or the near zone of image all the time.
As shown in Figure 3, be that autonomous forestry robot target is followed the tracks of overall flow figure, video camera, The Cloud Terrace initialization need respectively to utilize that related function carries out initialization to video camera and The Cloud Terrace in the application program interface function storehouse of video camera that video camera and The Cloud Terrace producer provide and The Cloud Terrace, and related function carries out image acquisition in the application program interface function storehouse of video camera then.Images acquired is carried out Treatment Analysis, whether there is target in elder generation's detected image, if there is target, calculate the center of target and judge that whether target is at picture centre and near zone thereof, if target's center is not at picture centre and near zone thereof, adjust the The Cloud Terrace attitude according to target's center's coordinate and the real-time control algolithm of The Cloud Terrace, allow target's center be in picture centre and near zone thereof all the time.
As shown in Figure 4, be the moving object detection program flow diagram, the detailed performing step of algorithm comprises: 1. image difference calculates, and can be provided with sequence of video images and sampling rate, to be applicable to the target of accurate extraction different motion speed.Default setting is: every group of image sequence n=3 width of cloth gray scale picture, sampling rate is 0.2s.Be that every 200ms gathers a frame picture second, obtaining 3 frame pictures continuously altogether is one group.Utilize 3 width of cloth images to carry out calculus of differences in twos, difference image is total to n so
Δ f=3* (3-1)/2.2. the Threshold Segmentation of difference image is carried out Threshold Segmentation at each difference image, obtains bianry image.Utilization is calculated the threshold value that difference image is cut apart based on the maximum between-cluster variance criterion, and its basic thought is to utilize at random that threshold value Z ' is divided into two classes with pixel grey scale, and making this two classes gray average distance Z farthest is optimal segmenting threshold.3. the difference image after all process image threshold processing is sued for peace, the zone of location persistent movement obtains moving object boundary information.For the image after the summation, utilize the disposal route of the after expansion of corrosion earlier of mathematical morphology to remove noise and noise spot, finally can obtain the border of comparatively ideal moving target.
As shown in Figure 5, be The Cloud Terrace real time kinematics control flow chart, provided the detailed process that the The Cloud Terrace attitude is adjusted.The boundary rectangle cross-directional length that makes target is W, and vertical-direction length is H, and target's center's coordinate is that (x, y), the picture centre coordinate is (x
0, y
0).The adjustment algorithm specific implementation step of digital control The Cloud Terrace is as follows: (1) calculates target's center and picture centre position difference (Δ x, Δ y), Δ x=x
0-x, Δ y=y
0-y.(2) if
Then target is for picture centre or near zone, and The Cloud Terrace does not need to adjust, and turns to step (1); If
The Cloud Terrace need be adjusted, and turns to step (3).(3) if | Δ x|＞δ, the The Cloud Terrace horizontal direction is adjusted angle delta θ
x=k
xΔ x, wherein
As Δ θ
x＞0 The Cloud Terrace in the horizontal direction should be along counterclockwise adjusting, as Δ θ
x＜0 The Cloud Terrace in the horizontal direction should be along the clockwise direction adjustment; If | Δ y|＞δ, the The Cloud Terrace vertical direction is adjusted angle delta θ
y=k
yΔ y, its
As Δ θ
y＞0 The Cloud Terrace should be adjusted downwards in the horizontal direction, as Δ θ
y＜0 The Cloud Terrace should adjust upward in the horizontal direction; The Cloud Terrace level, vertical both direction adjustment change step (1) over to after finishing.
The above; only for the preferable embodiment of the present invention, but protection scope of the present invention is not limited thereto, and anyly is familiar with those skilled in the art in the technical scope that the present invention discloses; the variation that can expect easily or replacement all should be encompassed within protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claims.
Claims (6)
1. autonomous forestry robot target tracking, this method is applied to comprise the target following of the autonomous forestry robot of computer vision, digital control The Cloud Terrace and central control computer, it is characterized in that, comprise moving object detection part and The Cloud Terrace real time kinematics control section;
Described moving object detection partly comprises movable information acquisition module, moving target discrimination module, target's center's coordinate Calculation module of image pretreatment module, Multi Frame Difference point-score;
Described image pre-service is used for multiple image is carried out image filtering, image gray processing and the conversion of image segmentation linear segmented;
The movable information acquisition module of described Multi Frame Difference point-score at first carries out difference in twos to all images, and each difference image is carried out image segmentation, then the difference image after cutting apart is accumulated summation, obtains moving target information;
Described moving target discrimination module judges whether to exist moving target according to preset threshold;
If have moving target, boundary rectangle and target's center's coordinate of then described target's center coordinate Calculation module records target;
Described The Cloud Terrace real time kinematics control section is controlled the near zone that is centered close to picture centre of described target.
2. autonomous forestry robot target tracking according to claim 1 is characterized in that, the movable information acquisition module of described Multi Frame Difference point-score obtains moving target information and comprises step:
A, image difference calculate: sequence of video images and sampling rate are provided with, to be applicable to the target of accurate extraction different motion speed;
The Threshold Segmentation of B, difference image: carry out Threshold Segmentation at each difference image, obtain bianry image;
C, all bianry images are sued for peace, the zone of location persistent movement obtains moving object boundary information.
3. autonomous forestry robot target tracking according to claim 2 is characterized in that:
In the described steps A, default setting is: every group of image sequence n=3 width of cloth gray scale picture, sampling rate is 0.2s.Be that every 200ms gathers a frame picture, obtaining 3 frame pictures continuously altogether is one group, utilizes 3 width of cloth images to carry out calculus of differences in twos, obtains difference image n altogether
Δ f=3* (3-1)/2 width of cloth;
Among the described step B, utilizing the maximum between-cluster variance threshold method to calculate segmentation threshold, specifically is to utilize at random that threshold value is divided into two classes with pixel grey scale, and this two classes gray average distance threshold value farthest is an optimal segmenting threshold;
Among the described step C,, utilize the disposal route of the after expansion of corrosion earlier of mathematical morphology to remove noise and noise spot, obtain the boundary information of moving target for the image after the summation.
4. autonomous forestry robot target tracking according to claim 1 is characterized in that described preset threshold is the area threshold of moving target;
Described target's center coordinate is the first moment of target image and the ratio of zeroth order square.
5. according to each described autonomous forestry robot target tracking of claim 1 to 4, it is characterized in that, described The Cloud Terrace real time kinematics control section is according to the level of described target's center coordinate control figure control The Cloud Terrace, the angular setting tolerance of vertical both direction, and the formation closed-loop control system.
6. autonomous forestry robot target tracking according to claim 5 is characterized in that the control algolithm of described The Cloud Terrace real time kinematics control section comprises:
The boundary rectangle cross-directional length that makes target is W, and vertical-direction length is H, and target's center's coordinate is that (x, y), the picture centre coordinate is (x
0, y
0), the set-up procedure of digital control The Cloud Terrace is as follows:
D, calculating target's center and picture centre position difference (Δ x, Δ y), Δ x=x
0-x, Δ y=y
0-y;
E, if
Then target is for picture centre or near zone, and The Cloud Terrace does not need to adjust, and turns to step D; If
The Cloud Terrace need be adjusted, and turns to step F;
F, if | Δ x|＞δ, the The Cloud Terrace horizontal direction is adjusted angle delta θ
x=k
xΔ x, wherein
As Δ θ
x＞0 The Cloud Terrace in the horizontal direction should be along counterclockwise adjusting, as Δ θ
x＜0 The Cloud Terrace in the horizontal direction should be along the clockwise direction adjustment; If | Δ y|＞δ, the The Cloud Terrace vertical direction is adjusted angle delta θ
y=k
yΔ y, wherein
As Δ θ
y＞0 The Cloud Terrace should be adjusted downwards in the horizontal direction, as Δ θ
y＜0 The Cloud Terrace should adjust upward in the horizontal direction; The Cloud Terrace level, vertical both direction adjustment change step D over to after finishing;
In the following formula, δ is a preset threshold.
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