CN105318888A - Unmanned perception based unmanned aerial vehicle route planning method - Google Patents
Unmanned perception based unmanned aerial vehicle route planning method Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
Abstract
The invention discloses an unmanned perception based unmanned aerial vehicle route planning method for rapidly planning the vehicle driving route. According to the invention, based on the unmanned flight perception system, road video images around a target vehicle are photographed by utilizing an unmanned flight to be sent to a ground station; the ground station receives the video images and processes the video images so as to obtain the vehicle and road messages, route planning is carried out according to the vehicle position, and the route is transmitted to the unmanned aerial vehicle; and a computer module of the ground station calculates a flight control signal to control the unmanned aerial vehicle to follow the vehicle to proceed, and corrects the route in real time. According to the invention, based on an unmanned flight platform, the operation state is stable; and the road environment around the vehicle is photographed from a great height, the coverage area is wide, and the observed road traffic information is distinct and clear, so that the road distribution condition and the traffic condition around the target vehicle can be obtained rapidly, the reasonable route planning can be obtained, the route is more precise, and the road condition analysis is more timely and accurate.
Description
Technical field
The present invention relates to image processing field, be specifically related to a kind of automatic driving vehicle Path Planning Technique based on unmanned plane perception, can unmanned vehicle perception vehicle periphery road environment be passed through, and plan this vehicle running path fast.
Background technology
Intelligent vehicle and traffic technique rise, and automatic driving vehicle technology is developed as one of its gordian technique.Automatic driving vehicle driving process needs many parts collaborative work, ensures that the perception of outer vicinity obstacle and travel route anticipation and planning etc. just can make it exercise safely to the monitoring of a large amount of internal datas.
Travel route anticipation and the planning technology part of existing automatic driving vehicle are learnt by road driving, partly depend on GPS navigation.For road driving study, after repeatedly carrying out travel route training, the achievement of automatic driving vehicle machine learning is remarkable, but automatic driving vehicle can only tackle uniline afterwards, is of limited application.GPS navigation technology maturation, is widely used, easy to use, after being combined, can navigate in conjunction with condition of road surface with intelligent transportation system, formulates rational routes.But there is requirement GPS location to signal, and in urban environment, signal is interfered, easily produces the inaccurate situation in location, affect driving safety.Meanwhile, along with various constructing items is implemented, electronic urban map upgrades slowly, causes map and city actual conditions not to meet, and the same safety of automatic driving vehicle that threatens is exercised.In addition, the current range of application of intelligent transportation system is less, and reaction traffic exists delay, time update cannot carry out path, cause vehicle to be stagnated, auxiliary programming limited efficiency.
Summary of the invention
The present invention is directed to the deficiency in existing vehicle path planning technology, provide a kind of automatic driving vehicle paths planning method based on unmanned plane perception.The method carries out the planning of target vehicle driving path according to the road and traffic information obtained by unmanned vehicle High Altitude Platform.
Automatic driving vehicle paths planning method based on unmanned plane perception provided by the invention, based on unmanned vehicle sensory perceptual system.
Described unmanned vehicle sensory perceptual system comprises unmanned vehicle and land station.Described unmanned vehicle is powered by target vehicle by mooring line, unmanned vehicle carries camera head, the first wireless communication module and the first image transmission module; Taken by camera head road pavement, obtain the video image of road; By the first image transmission module by shooting transmission of video images to land station; Flight control signal is received by the first wireless communication module.Described land station is placed on target vehicle, and is powered by target vehicle; The second wireless communication module, the second image transmission module and computer module are equipped with in land station; By the second radio communication mold Bulk transport flight control signal to unmanned vehicle; Receive unmanned vehicle by the second image transmission module and transmit video image; By computer module, the video image received is processed, obtain road information and carry out path planning, and calculate flight controling parameters to unmanned vehicle, carry out information interaction by data line and automatic driving vehicle simultaneously.
Described automatic driving vehicle paths planning method, performing step is as follows:
Step (1) starts unmanned vehicle sensory perceptual system, and unmanned vehicle takes off, and set up with land station after hovering and communicate, the road video image of photographic subjects vehicle periphery, sends to land station;
Step (2) ground station reception video image is gone forward side by side row relax, obtains vehicle and road information, carries out path planning, and route is passed to automatic driving vehicle according to vehicle location.Described vehicle and road information comprise distance between the position relationship of target vehicle and road, vehicle and road area.
Step (3) computer module controls unmanned vehicle and follows vehicle advance, revises path in real time.
Further, the course of work of described step (2) comprising:
During the shooting of step 2.1, unmanned vehicle, the camera lens vertical ground increasing steady cradle head control camera head is taken, and image is downward projection, and passing ratio conversion obtains the actual range between object.
The computer module of step 2.2, land station carries out image procossing to video and graphic, draws road area, and retrieval vehicle, obtains the ratio of the vehicle total area and path area on each bar road, and carry out path planning to target vehicle.
Further, in described step (3), computer module using the picture center of video image as unmanned vehicle present position, the searching target vehicle of special color mark roof in the regional extent of setting, after finding target vehicle position, calculate the actual shifts distance between unmanned vehicle and vehicle and direction.Land station only controls pitching and driftage two parameters of unmanned flight's machine, adopts dual-mode parameter Self-tuning fuzzy PID to calculate flight controling parameters, after obtaining flight controling parameters, sends to unmanned vehicle.In step (3), when after unmanned vehicle lose objects vehicle, provide the guiding to unmanned vehicle by mooring line.
Technical solution of the present invention, has following innovative point and advantage:
(1) the present invention is based on unmanned flight's applicator platform, stable working state, from high-altitude shooting vehicle periphery road environment, wide coverage, viewed Traffic Information clear and definite under this position, by obtaining target vehicle surrounding road distribution situation and traffic fast after image procossing, this information is real-time, accurate, can obtain rational path planning according to these data.Carry out route guidance based on unmanned vehicle aware platform compared to traditional GPS, route is more accurate, and compared to the road traffic condition that intelligent traffic network provides, road condition analyzing is more timely.
(2) unmanned vehicle of the present invention is followed automatic driving vehicle and is moved, can distribute and traffic to the road around centered by vehicle by Real-time Collection, realize the driving path revising automatic driving vehicle in real time, guarantee to obtain best route.Due to the finite rate of unmanned vehicle, simultaneously for security consideration, automatic driving vehicle travel speed needs to control at below 40km/h.
(3) the unmanned vehicle system that the present invention adopts is powered by car-mounted device.Land station directly by charging inlet and information interactive interface integrated, simplify land station composition structure and system building operate, maintain the stable operation of land station simultaneously.The perception of road and traffic information then needs the long-time stagnant sky shooting of unmanned vehicle, because existing unmanned vehicle battery life is limited, adopts mooring line to power and maintains its flight.In addition, mooring line possesses certain guidance capability, and unmanned vehicle and vehicle can be stoped to a certain extent to scatter.
(4), in the present invention, unmanned vehicle is for gathering road information, and data processing work is taken by land station.Reduce unmanned vehicle treatment progress, make unmanned vehicle have more multiple resource and optimize flight control procedure to promote flight precision and flight safety.The computer module computing power of land station is higher, and stability is high, is responsible for receiving image, process image, thus carries out path planning and unmanned aerial vehicle (UAV) control parameter calculates, and completes information interaction.Two parts device is worked in coordination with mutually, can realize the vehicle path planning of unmanned vehicle sensory perceptual system fast, glibly.
Accompanying drawing explanation
Fig. 1 is the unmanned vehicle sensory perceptual system composition schematic diagram that the present invention adopts;
Fig. 2 is the schematic flow sheet of automatic driving vehicle paths planning method of the present invention;
Fig. 3 is road of the present invention and vehicle identification process schematic;
Fig. 4 is the schematic diagram in the embodiment of the present invention, path being carried out to Global motion planning;
Fig. 5 is the schematic diagram in the embodiment of the present invention, vehicle periphery driving path being carried out to sector planning.
In accompanying drawing: the target vehicle 1, needing path planning, 2, land station, 3, mooring line, 4, unmanned vehicle.
Embodiment
Below in conjunction with accompanying drawing, the invention will be further described:
As shown in Figure 1, the unmanned vehicle sensory perceptual system that the present invention adopts, it comprises: the target vehicle 1 needing path planning, land station 2, mooring line 3, and unmanned vehicle 4.Described land station 2 is placed on target vehicle 1, is powered by vehicle 1, and unmanned vehicle 4 is powered by vehicle 1 by mooring line 3.
Embodiment of the present invention unmanned vehicle 4 is four rotor unmanned aircrafts.Unmanned vehicle 4 is equipped with GPS (GPS) module, AHRS (attitude heading reference system) module and flight control assemblies, to ensure the stability and safety flight of unmanned vehicle.Unmanned vehicle 4 carries and increases steady The Cloud Terrace and camera head, to realize the steady shot of unmanned vehicle road pavement, obtain the video image of road and traffic.Unmanned vehicle 4 carries the first wireless communication module and the first image transmission module.Flight control signal is received by the first wireless communication module.By the first image transmission module by shooting transmission of video images to land station 2.
The second wireless communication module, the second image transmission module and computer module are equipped with in land station 2.By the second radio communication mold Bulk transport flight control signal to unmanned vehicle 4.Receive unmanned vehicle 4 by the second image transmission module and transmit video image.By computer module, the video image received is processed, obtain road information and carry out path planning, and carrying out information interaction by data line and automatic driving vehicle 1.Land station 2 can by charging inlet and information interactive interface integrated, to simplify ground station structure, solve powerup issue simultaneously.
As shown in Figure 2, the present invention is based on the workflow diagram of the automatic driving vehicle paths planning method of unmanned plane perception, its step is as follows:
Step (1) the present invention adopts the road video image around unmanned vehicle 4 photographic subjects vehicle 1, and video image is sent to land station 2, to carry out the collection of vehicle quantity information on the distribution of target vehicle 1 surrounding road and road.
When system brings into operation, unmanned vehicle 4 takes off rising 100-200 rice hovering, and sets up with vehicle 1 simultaneously and communicate, the video image of the road and traffic information around beginning photographic subjects vehicle 1, sends to land station 2.
When unmanned vehicle 4 flying height is 120-150 rice, angle lens is 60 °-80 °.When being positioned at this height, the radius of view of unmanned vehicle 4, at 70-125 rice, comprises the object on a large scale of target vehicle 1, can guarantee to obtain abundant road information and carry out path planning.
The camera head monocular camera lens that unmanned vehicle 4 carries needs to demarcate, and to revise the radian produced at its shooting process cathetus, goes back original path and vehicle deformation, reduces interference and the false drop rate of environment sensing.
Step (2) land station 2 receiver, video image is gone forward side by side row relax, and obtain vehicle and road information, carry out path planning according to vehicle location, then route is passed to automatic driving vehicle by data line by land station 2.Vehicle and road information comprise length and the width of road, the distance etc. between target vehicle and other vehicles.
The video that unmanned vehicle 4 carries out taking passes video image back land station 2 by the first image transmission module.The computer module of land station 2 will carry out image procossing immediately, to obtain vehicle, road information, and carry out path planning.The course of work of step (2) is as follows:
When step 2.1, shooting, the camera lens vertical ground increasing steady cradle head control camera head is taken, and image is downward projection, and wherein the range information of object can directly calculate by passing ratio, avoids perspective computing and coordinate transform.
By input target vehicle length a, width b, according to ratio k:
s＝kS
Wherein, A, B are cornerwise 2 points being positioned at target vehicle 1 in image, coordinate is respectively (x
a, y
a), (x
b, y
b); S is the distance of two articles in image, and s is the distance in two articles reality.
The range information in image can be obtained, comprise link length, width etc.
The computer module of step 2.2, land station 2 carries out image procossing to the road video image collected, and obtains vehicle and road information, thus carry out path planning by methods such as image registration, color threshold segmentation, morphological operation and sorter identifications.Detailed process is as follows:
1., by image registration carry out increasing steady, the unique point in tracking image obtains the motion of image background, thus eliminates shake by affine transformation method.
2., as shown in Figure 3, by shooting image from RGB (red, green, blue) color space conversion to HSV (tone, saturation degree, brightness) color space.Then choose the region of intensity value in 0%-5% in image and its brightness adjustment is become 0 (black), the brightness in all the other regions is set to 255 (whites), thus obtains road bianry image.
Carry out morphology opening and closing operation to bianry image, wherein, adopt circle to be structural element, its diameter is 1/2 of vehicle width on road, thus eliminates the cavity that on road, vehicle causes, smooth road border.
Then carry out rim detection, the gray-scale value due to pixel each in bianry image is 0 or 255, and wherein, gray scale sudden change place is then road boundary.But may be irregular curve by the edge obtained after morphological operation, need to draw edge line by Hough transformation, thus obtain the road area of rule, set up two-dimentional road model.
Hough transformation process: for several A on road edge line a
1(x
1, y
1), A
2(x
2, y
2) ..., A
n(x
n, y
n), be similar to and meet straight line: Xcos θ+Ysin θ=r, wherein θ, r are parameters.With an A
1(x
1, y
1) be example, by x
1, y
1as parameter, then, in r-θ parameter plane, curve can be obtained: r=Xcos θ+Ysin θ.Thus, point set A can be converted to the some curves in r-θ plane, these curves cross same point (θ, r).After Hough transformation, the peak point in statistics r-θ plane, obtains this point coordinate, i.e. parameter θ, the r of straight line, thus draws out straight line.
3., subsequently, carrying out vehicle detection by adopting based on Haar feature cascade classifier, obtaining the coordinate of each vehicle center point in image and vehicle length and width and size.When using detection of classifier, find a certain oversize vehicle in figure, the length of setting search window is 1.2 times of this oversize vehicle length, search window wide is 1.2 times of this oversize vehicle width, and keep retrieval window size constancy, other non-vehicle objects detected to get rid of, ensure accuracy of detection.After detection terminates, calculate the ratio of the vehicle total area and path area on each bar road, this ratio is using one of foundation as path planning.
4., finally carry out path planning, it comprises: Global motion planning and sector planning.
During Global motion planning, as shown in Figure 4, computer module, according to the GPS information on unmanned vehicle 4, arranges area-of-interest in current map location, and road model above-mentioned steps obtained in this region carries out template matches, obtain the position of target vehicle in electronic chart.According to vehicle location and final position, in conjunction with C space arithmetic and dijkstra's algorithm, carry out Global motion planning.Utilize C space arithmetic, in electronic chart, impassability regional expansion is become polygon, by starting point, be connected with straight line between terminal with all polygon vertexs, set up routing information topological network.Then adopt dijkstra's algorithm search shortest path, this algorithm travels through all summits successively, and with the weighted value w=k of vehicle fleet size in link length and road
1d+k
2h is the weights on each summit, carries out calculating optimum solution, and wherein d is two summit spacing, and h is road vehicle area ratio, k
1, k
2value is determined by city, place, is the empirical value preset.Global motion planning unmanned vehicle 4 hover set up with the communication of land station 2 after, perform once, judge that the driving trace of vehicle 1 is whether on route, if departed from, plans again subsequently.
During sector planning, the positional distance relation of target vehicle 2 and other vehicles is obtained during computer module image procossing, adopt Artificial Potential Field Method, limited range is sailed on road (avoiding driving in the wrong direction) in present feasible, virtual front is direction, the field of force, other vehicles are repulsion, set up gravitational field function and carry out path finding.Calculate other Velicle motion velocities as necessary by successive frame, and imported function and carry out calculating to carry out path finding.Sector planning provides a kind of driving trace reference, and actual decision-making is comprehensively provided in conjunction with each sensing data by vehicle 1 electronic control unit.
Step (3) computer module control unmanned vehicle 4 is followed target vehicle 1 and is advanced, for revising path in real time.
Step (3) principle of work comprises:
1, computer module obtains the position relationship of unmanned vehicle 4 and target vehicle 1 by image procossing, according to offset distance and direction and PID control principle, calculate the flight controling parameters of unmanned vehicle 4 and be sent to unmanned vehicle 4, control unmanned vehicle 4 and follow vehicle advance, for revising path in real time.
2, in order to simplify control procedure, only pitching and driftage two parameters of the unmanned vehicle 4 in flight course are controlled.Control to adopt dual-mode parameter Self-tuning fuzzy PID to calculate flight controling parameters.
3, wherein, when calculating position relationship, using picture center as unmanned vehicle 4 present position in image processing process, an area-of-interest scope is set at picture immediate vicinity, the searching target vehicle of special color mark roof.Real middle distance is being calculated according to the position relationship of two articles in image.Then the actual shifts distance between unmanned vehicle and vehicle and direction is obtained.
4, when after unmanned vehicle lose objects vehicle, mooring line can provide the guiding to unmanned vehicle to a certain extent.
Claims (7)
1. based on an automatic driving vehicle paths planning method for unmanned plane perception, it is characterized in that, the method is based on a kind of unmanned vehicle sensory perceptual system; Described unmanned vehicle sensory perceptual system comprises unmanned vehicle and land station;
Described unmanned vehicle is powered by target vehicle by mooring line, unmanned vehicle carries and increases steady The Cloud Terrace, camera head, the first wireless communication module and the first image transmission module; Taken by camera head road pavement, obtain the video image of road; By the first image transmission module by shooting transmission of video images to land station; Flight control signal is received by the first wireless communication module;
Described land station is placed on target vehicle, and is powered by target vehicle; The second wireless communication module, the second image transmission module and computer module are equipped with in land station; By the second radio communication mold Bulk transport flight control signal to unmanned vehicle; Receive unmanned vehicle by the second image transmission module and transmit video image; By computer module, the video image received is processed, obtain road information and carry out path planning;
The performing step of described automatic driving vehicle paths planning method is as follows:
Step 1, start unmanned vehicle sensory perceptual system, unmanned vehicle takes off, and set up with land station after hovering and communicate, the road video image of photographic subjects vehicle periphery, sends to land station;
Step 2, ground station reception video image is gone forward side by side row relax, obtains vehicle and road information, carries out path planning, and route is passed to automatic driving vehicle according to vehicle location; Described vehicle and road information comprise distance between the position relationship of target vehicle and road, vehicle and road area;
Step 2.1: during unmanned vehicle capture video image, the camera lens vertical ground increasing steady cradle head control camera head is taken, and the video image obtained is downward projection, and passing ratio conversion obtains the actual range between object;
The computer module of step 2.2, land station carries out image procossing to video and graphic, draws road area, and retrieval vehicle, obtains the ratio of the vehicle total area and path area on each bar road, and carry out path planning to target vehicle;
Step 3, computer module controls unmanned vehicle and follows target vehicle advance, and revises path in real time.
2. the automatic driving vehicle paths planning method based on unmanned plane perception according to claim 1, is characterized in that, in described step 1, unmanned vehicle takes off to vehicle up direction 100-200 rice, land station place and hovers.
3. the automatic driving vehicle paths planning method based on unmanned plane perception according to claim 1, it is characterized in that, in described step 1, the monocular camera lens of the camera head on unmanned vehicle is demarcated, to revise the radian produced at its shooting process cathetus.
4. the automatic driving vehicle paths planning method based on unmanned plane perception according to claim 1, is characterized in that, in described step 2.2, carry out graphics process, comprising:
1., by image registration carry out increasing steady, the unique point in tracking image obtains the motion of image background, eliminates shake by affine transformation method;
2., by the image of shooting from RGB color space conversion to hsv color space, then choose the region of intensity value in 0%-5% in image and its brightness adjustment is become 0, the brightness in all the other regions is set to 255, obtains road bianry image;
Carry out morphology opening and closing operation to bianry image, wherein, adopt circle to be structural element, its diameter is 1/2 of vehicle width on road, eliminates the cavity that on road, vehicle causes, smooth road border;
Then carry out rim detection and Hough transformation, draw edge line, obtain the road area of rule, set up road model;
3., adopt and carry out vehicle detection based on Haar feature cascade classifier, obtain the coordinate of each vehicle center point in image and vehicle length and width and size; When using detection of classifier, find a certain oversize vehicle in figure, the length of setting search window is 1.2 times of this oversize vehicle length, and search window wide be 1.2 times of this oversize vehicle width, and keeps retrieving window size constancy; After vehicle detection terminates, calculate the ratio of the vehicle total area and path area on each bar road;
4., carry out path planning, comprise: Global motion planning and sector planning;
During Global motion planning, according to the GPS information of unmanned vehicle, obtained road model is carried out template matches, obtain the position of target vehicle in electronic chart, according to vehicle location and final position, carry out Global motion planning;
During sector planning, according to the positional distance relation of obtained target vehicle and other vehicles, adopt Artificial Potential Field Method, limited range is sailed on road in present feasible, virtual front is direction, the field of force, and other vehicles are repulsion, sets up gravitational field function and carries out path finding.
5. the automatic driving vehicle paths planning method based on unmanned plane perception according to claim 4, it is characterized in that, described 4. in when carrying out Global motion planning, utilize C space arithmetic, in electronic chart, impassability regional expansion is become polygon, by starting point, is connected with straight line between terminal with all polygon vertexs, sets up routing information topological network; Then adopt dijkstra's algorithm search shortest path, when searching for, the weight w=k on summit is set
1d+k
2h, wherein k
1and k
2for the empirical value preset, d is two summit spacing, and h is road vehicle area ratio.
6. the automatic driving vehicle paths planning method based on unmanned plane perception according to claim 1, it is characterized in that, described 4. in when carrying out sector planning, according to the positional distance relation of target vehicle and other vehicles, adopt Artificial Potential Field Method, limited range is sailed on road in present feasible, and virtual front is direction, the field of force, other vehicles are repulsion, set up gravitational field function and carry out path finding.
7. the automatic driving vehicle paths planning method based on unmanned plane perception according to claim 1, it is characterized in that, in described step 3, computer module using the picture center of video image as unmanned vehicle present position, the searching target vehicle of special color mark roof in the regional extent of setting, after finding target vehicle position, calculate the actual shifts distance between unmanned vehicle and vehicle and direction; Only pitching and driftage two parameters of unmanned flight's machine are controlled, adopt dual-mode parameter Self-tuning fuzzy PID to calculate flight controling parameters, after obtaining flight controling parameters, send to unmanned vehicle;
When after unmanned vehicle lose objects vehicle, provide the guiding to unmanned vehicle by mooring line.
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