CN113776540A - Control method for vehicle-mounted tethered unmanned aerial vehicle to track moving vehicle in real time based on visual navigation positioning - Google Patents
Control method for vehicle-mounted tethered unmanned aerial vehicle to track moving vehicle in real time based on visual navigation positioning Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The invention provides a control method for tracking a mobile vehicle in real time by a vehicle-mounted tethered unmanned aerial vehicle based on visual navigation positioning, which comprises the following steps: performing visual ranging on the tracked vehicle according to the ranging sensor, and feeding back visual ranging information to the cloud; estimating the pose of the tracked vehicle according to the visual ranging information stored in the cloud, and determining the pose of the tracked vehicle; detecting an obstacle according to the pose of the tracked vehicle, and planning a local path according to the obstacle detection result; and determining a tracking waypoint in the local path, and guiding the flight state of the unmanned aerial vehicle by using the waypoint. The invention is used for automatically positioning the tracked object and further realizing displacement along with the movement of the tracked object after positioning.
Description
Technical Field
The invention relates to the technical field of real-time tracking of unmanned aerial vehicles, in particular to a control method for tracking a moving vehicle by a vehicle-mounted mooring unmanned aerial vehicle in real time based on visual navigation positioning.
Background
At present, unmanned aerial vehicles are more and more widely applied, and the existing unmanned aerial vehicles are operated manually and remotely, so that the unmanned aerial vehicles fly, further acquire information in the flying process and finally transmit the acquired information back to a terminal;
however, when a plurality of unmanned aerial vehicles work simultaneously, a terminal is difficult to consider the simultaneous control of the plurality of unmanned aerial vehicles, so that an unmanned aerial vehicle control method which can automatically position a tracked object and further can realize displacement along with the movement of the tracked object after positioning is lacked.
Disclosure of Invention
The invention provides a control method for tracking a moving vehicle in real time by a vehicle-mounted tethered unmanned aerial vehicle based on visual navigation positioning, which is used for automatically positioning a tracked object and further realizing displacement along with the movement of the tracked object after positioning.
The invention provides a control method for tracking a mobile vehicle in real time by a vehicle-mounted tethered unmanned aerial vehicle based on visual navigation positioning, which comprises the following steps:
performing visual ranging on the tracked vehicle according to the ranging sensor, and feeding back visual ranging information to the cloud;
estimating the pose of the tracked vehicle according to the visual ranging information stored in the cloud, and determining the pose of the tracked vehicle;
detecting an obstacle according to the pose of the tracked vehicle, and planning a local path according to the obstacle detection result;
a tracking waypoint is determined in the local path, with which to guide the flight of the drone.
Preferably, the visually ranging the tracked vehicle according to the ranging sensor, and feeding back the visually ranging information to the cloud end comprises:
acquiring image information of a plurality of cameras of the unmanned aerial vehicle, extracting internal parameters of the image information and external parameters of the cameras,
carrying out reverse distortion on the image information of the plurality of cameras to obtain initial calibration image information;
extracting the characteristics of the plurality of pieces of initial calibration image information, and matching the extracted same characteristics to obtain secondary correction image information;
projecting the plurality of secondary correction image information to the same horizontal plane of the plurality of corrected images to be corrected, and performing tertiary correction on the plurality of secondary correction image information through homography matrix deformation;
and (4) performing distance measurement and calculation by utilizing the three-time corrected image information to obtain visual ranging information.
Preferably, the internal parameters of the drone camera include: focal length and pixel information;
the external parameters of the unmanned aerial vehicle camera are the camera position and the camera rotation direction in the world coordinate system.
Preferably, the information of the three times of corrected images includes a first image group and a second image group;
the distance measurement and calculation by utilizing the three times of corrected image information to obtain the visual ranging information comprises the following steps:
the current time in the first image group and the second image grouptAnd the last momentt-1Respectively extracting corresponding images in the images to obtain four groups of images;
acquiring feature matching information in the feature corresponding relation of the four groups of image groups;
according to the feature matching information, constructing reconstruction positions in the reconstruction scene features of the first image group and the second image group;
and (3) performing coordinate transformation by using the formula (1) according to the reconstruction position:
where n is the sum of the points present in the reconstruction location;
is the last momentt-1Time pointqA location in the reconstruction location;
as the current timetTime pointqA location in the reconstruction location;Xin coordinate transformation for reconstructing positionThe coordinates after the rotational movement are obtained,sthe coordinates after the translation action in the coordinate transformation of the reconstruction position;
if a coordinate system is defined at the center of any one of the image groups and the image groups are corrected, the reconstructed location coordinates of the feature matching information are obtained as shown in equation (2)
Wherein (A), (B), (C), (D), (C), (B), (C)d 1 ，d 2 ) Respectively the feature plane coordinates of one of the image groups,fis the focal length of the camera and is,Jis a baseline for a plurality of cameras,cfor the feature disparity on each group of images,Zto reconstruct the position coordinates.
Preferably, estimating the pose of the tracked vehicle according to the visual ranging information stored in the cloud, and determining the pose of the tracked vehicle further includes:
setting a known starting point for the reconstructed coordinates, and accumulating the transformation of the frame according to the starting point; if the pose of the first frame is (0, 0, 0) of the world coordinate system, the tracked vehicle is at the current momenttThe pose of (a) is formula (3):
wherein the content of the first and second substances,O t-1 record for 3 x 3 matrix at last momentt-1Tracked vehicle direction of;q t-1 record the last moment for the 3 x 1 vectort-1Tracked vehicle pose coordinates;O t for 3 x 3 matrix intTracked vehicle direction at time;q t for 3 x 1 vector intThe tracked vehicle pose coordinates at that moment;X tis composed oftRotation parameters in the coordinate transformation of the reconstruction position at the moment;S t is composed oftTranslation parameters in the coordinate transformation of the reconstruction location in time instants.
Preferably, the obstacle detection is performed according to the pose of the tracked vehicle, and a local path is planned according to the obstacle detection result; further comprising:
carrying out three-dimensional matching on the pose of the tracked vehicle and the pose of the unmanned aerial vehicle to obtain a real-time running path;
detecting obstacles according to the real-time running path of the tracked vehicle;
and if no obstacle exists, planning a plurality of local paths existing in the flight path of the unmanned aerial vehicle.
Preferably, if there is an obstacle, the temporary waypoints are matchedmAnd calculating a temporary waypointmAnd the current timetDistance of the unmanned aerial vehicle position;
gridding the distance to obtain a plurality of sub-grid units;
defining an area outside the plurality of sub-grid cells as unobstructed;
and acquiring an obstacle-free boundary, and moving the unmanned aerial vehicle to an obstacle-free area.
Preferably, the determining a tracking waypoint in the local path, the guiding the flight of the unmanned aerial vehicle by using the tracking waypoint, includes:
segmenting the local path, extracting features of sub-local paths in each segment, and defining a plurality of feature information as waypoints;
connecting a plurality of waypoints in a time sequence to obtain waypoint lines;
and taking the waypoint line as a guide line of the flight state of the unmanned aerial vehicle.
In the invention, the distance of the tracked vehicle is monitored by the unmanned aerial vehicle by using visual ranging, the pose of the tracked vehicle is further estimated by using visual ranging information, and then the pose of the unmanned aerial vehicle is determined and estimated, so that the unmanned aerial vehicle can move adaptively along with the movement of the tracked vehicle; simultaneously, at the tracking in-process to the vehicle that is tracked, can also realize the detection to the barrier for unmanned aerial vehicle can avoid the barrier at the in-process of pursuing the target, has improved unmanned aerial vehicle security and stability at the execution flight task in-process. The purpose that a plurality of unmanned aerial vehicles can respectively carry out work simultaneously is realized, the tracked object can be automatically positioned, and further displacement along with the movement of the tracked object can be realized after positioning.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description.
The technical solution of the present invention is further described in detail by the following examples.
Detailed Description
The following description is presented in conjunction with the preferred embodiments of the present invention, and it is to be understood that the preferred embodiments described herein are presented only for the purpose of illustrating and explaining the present invention, and are not intended to limit the present invention.
The embodiment of the invention provides a control method for a vehicle-mounted tethered unmanned aerial vehicle to track a moving vehicle in real time based on visual navigation positioning, which comprises the following steps:
performing visual ranging on the tracked vehicle according to the ranging sensor, and feeding back visual ranging information to the cloud;
estimating the pose of the tracked vehicle according to the visual ranging information stored in the cloud, and determining the pose of the tracked vehicle;
detecting an obstacle according to the pose of the tracked vehicle, and planning a local path according to the obstacle detection result;
and determining a tracking navigation point in the local path, and guiding the flight of the unmanned aerial vehicle by using the tracking navigation point.
In the invention, the distance of the tracked vehicle is monitored by the unmanned aerial vehicle by using visual ranging, the pose of the tracked vehicle is further estimated by using visual ranging information, and then the pose of the unmanned aerial vehicle is determined and estimated, so that the unmanned aerial vehicle can move adaptively along with the movement of the tracked vehicle; simultaneously, at the tracking in-process to the vehicle that is tracked, can also realize the detection to the barrier for unmanned aerial vehicle can avoid the barrier at the in-process of pursuing the target, has improved unmanned aerial vehicle security and stability at the execution flight task in-process. The purpose that a plurality of unmanned aerial vehicles can respectively carry out work simultaneously is realized, the tracked object can be automatically positioned, and further displacement along with the movement of the tracked object can be realized after positioning.
In one embodiment, the visually ranging the tracked vehicle according to the ranging sensor and feeding back the visual ranging information to the cloud end comprises:
acquiring image information of a plurality of cameras of the unmanned aerial vehicle, extracting internal parameters of the image information and external parameters of the cameras,
carrying out reverse distortion on the image information of the plurality of cameras to obtain initial calibration image information;
extracting the characteristics of the plurality of pieces of initial calibration image information, and matching the extracted same characteristics to obtain secondary correction image information;
projecting the plurality of secondary correction image information to the same horizontal plane of the plurality of corrected images to be corrected, and performing tertiary correction on the plurality of secondary correction image information through homography matrix deformation;
and (4) performing distance measurement and calculation by utilizing the three-time corrected image information to obtain visual ranging information.
The internal parameters of the unmanned aerial vehicle camera include: focal length and pixel information;
the external parameters of the unmanned aerial vehicle camera are the camera position and the camera rotation direction in the world coordinate system.
The information of the three times of corrected images comprises a first image group and a second image group;
the distance measurement and calculation by utilizing the three times of corrected image information to obtain the visual ranging information comprises the following steps:
the current time in the first image group and the second image grouptAnd the last momentt-1Respectively extracting corresponding images in the images to obtain four groups of images;
acquiring feature matching information in the feature corresponding relation of the four groups of image groups;
according to the feature matching information, constructing reconstruction positions in the reconstruction scene features of the first image group and the second image group;
and (3) performing coordinate transformation by using the formula (1) according to the reconstruction position:
where n is the sum of the points present in the reconstruction location;
is the last momentt-1Time pointqA location in the reconstruction location;
as the current timetTime pointqA location in the reconstruction location;Xto reconstruct the coordinates after the rotation action in the coordinate transformation of the position,sthe coordinates after the translation action in the coordinate transformation of the reconstruction position;
if a coordinate system is defined at the center of any one of the image groups and the image groups are corrected, the reconstructed location coordinates of the feature matching information are obtained as shown in equation (2)
Wherein (A), (B), (C), (D), (C), (B), (C)d 1 ，d 2 ) Respectively the feature plane coordinates of one of the image groups,fis the focal length of the camera and is,Jis a baseline for a plurality of cameras,cfor the feature disparity on each group of images,Zto reconstruct the position coordinates.
Estimating the pose of the tracked vehicle according to the visual ranging information stored in the cloud, and determining the pose of the tracked vehicle further comprises:
setting a known starting point for the reconstructed coordinates, and accumulating the transformation of the frame according to the starting point; if the pose of the first frame is (0, 0, 0) of the world coordinate system, the tracked vehicle is at the current moment
The pose of (a) is formula (3):
wherein the content of the first and second substances,O t-1 record for 3 x 3 matrix at last momentt-1Tracked vehicle direction of;q t-1 record the last moment for the 3 x 1 vectort-1Tracked vehicle pose coordinates;O t for 3 x 3 matrix intTracked vehicle direction at time;q t for 3 x 1 vector intThe tracked vehicle pose coordinates at that moment;X tis composed oftRotation parameters in the coordinate transformation of the reconstruction position at the moment;S t is composed oftTranslation parameters in the coordinate transformation of the reconstruction location in time instants.
In the embodiment, in the wide-angle image information, the image information around the wide-angle image has distortion, and the distorted image information can cause data inaccuracy, so that the wide-angle image information can better accord with real image information by correcting the distortion, and the situation that the unmanned aerial vehicle is positioned to have larger deviation due to image distortion is reduced; further, feature extraction and coordinate transformation are carried out on the corrected image information, so that the extracted feature information can generate the pose coordinates of the tracked vehicle; and matching the pose coordinates of the tracked vehicle with the pose coordinates of the unmanned aerial vehicle to obtain the tracking path of the unmanned aerial vehicle. Therefore, the purpose of automatic tracking of the unmanned aerial vehicle is achieved.
In one embodiment, the obstacle detection is performed according to the pose of the tracked vehicle, and a local path is planned according to the obstacle detection result; further comprising:
carrying out three-dimensional matching on the pose of the tracked vehicle and the pose of the unmanned aerial vehicle to obtain a real-time running path;
detecting obstacles according to the real-time running path of the tracked vehicle;
and if no obstacle exists, planning a plurality of local paths existing in the flight path of the unmanned aerial vehicle.
If the obstacle exists, matching the temporary path pointmAnd calculating a temporary waypointmAnd the current timetDistance of the unmanned aerial vehicle position;
gridding the distance to obtain a plurality of sub-grid units;
defining an area outside the plurality of sub-grid cells as unobstructed;
and acquiring an obstacle-free boundary, and moving the unmanned aerial vehicle to an obstacle-free area.
The determining a tracking waypoint in the local path, using the tracking waypoint to guide the flight of the unmanned aerial vehicle, includes: the method also comprises the following steps:
segmenting the local path, extracting features of sub-local paths in each segment, and defining a plurality of feature information as waypoints;
connecting a plurality of waypoints in a time sequence to obtain waypoint lines;
and taking the waypoint line as a guide line of the flight state of the unmanned aerial vehicle.
In the embodiment, the obstacle is detected in the image information, so that the unmanned aerial vehicle can effectively avoid the obstacle in the process of executing the flight mission, and the condition that the unmanned aerial vehicle damages the obstacle due to touch is reduced; and further, a guiding route of the flight state of the unmanned aerial vehicle is re-planned by using a path avoiding the obstacle, namely, the method is used for adjusting the flight state or the flight attitude of the unmanned aerial vehicle at the next moment when the obstacle is judged to exist in advance, and guiding the unmanned aerial vehicle to avoid the obstacle.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. The utility model provides a control method of vehicle-mounted mooring unmanned aerial vehicle real-time tracking moving vehicle based on vision navigation positioning which characterized in that includes:
performing visual ranging on the tracked vehicle according to the ranging sensor, and feeding back visual ranging information to the cloud;
estimating the pose of the tracked vehicle according to the visual ranging information stored in the cloud, and determining the pose of the tracked vehicle;
detecting an obstacle according to the pose of the tracked vehicle, and planning a local path according to the obstacle detection result;
and determining a tracking navigation point in the local path, and guiding the flight of the unmanned aerial vehicle by using the tracking navigation point.
2. The control method for the vehicle-mounted tethered unmanned aerial vehicle to track the moving vehicle in real time based on visual navigation positioning as claimed in claim 1, wherein the visually ranging the tracked vehicle according to the ranging sensor and feeding back the visual ranging information to the cloud end comprises:
acquiring image information of a plurality of cameras of the unmanned aerial vehicle, extracting internal parameters of the image information and external parameters of the cameras,
carrying out reverse distortion on the image information of the plurality of cameras to obtain initial calibration image information;
extracting the characteristics of the plurality of pieces of initial calibration image information, and matching the extracted same characteristics to obtain secondary correction image information;
projecting the plurality of secondary correction image information to the same horizontal plane of the plurality of corrected images to be corrected, and performing tertiary correction on the plurality of secondary correction image information through homography matrix deformation;
and (4) performing distance measurement and calculation by utilizing the three-time corrected image information to obtain visual ranging information.
3. The control method for the vehicle-mounted tethered unmanned aerial vehicle to track the moving vehicle in real time based on visual navigation positioning as claimed in claim 2,
the internal parameters of the unmanned aerial vehicle camera include: focal length and pixel information;
the external parameters of the unmanned aerial vehicle camera are the camera position and the camera rotation direction in the world coordinate system.
4. The control method for the vehicle-mounted tethered unmanned aerial vehicle to track the moving vehicle in real time based on visual navigation positioning as claimed in claim 2,
the information of the three times of corrected images comprises a first image group and a second image group;
the distance measurement and calculation by utilizing the three times of corrected image information to obtain the visual ranging information comprises the following steps:
the current time in the first image group and the second image grouptAnd the last momentt-1Respectively extracting corresponding images in the images to obtain four groups of images;
acquiring feature matching information in the feature corresponding relation of the four groups of image groups;
according to the feature matching information, constructing reconstruction positions in the reconstruction scene features of the first image group and the second image group;
and (3) performing coordinate transformation by using the formula (1) according to the reconstruction position:
where n is the sum of the points present in the reconstruction location;
is the last momentt-1Time pointqA location in the reconstruction location;
as the current timetTime pointqA location in the reconstruction location;Xto reconstruct the coordinates after the rotation action in the coordinate transformation of the position,sthe coordinates after the translation action in the coordinate transformation of the reconstruction position;
if a coordinate system is defined at the center of any one of the image groups and the image groups are corrected, the reconstructed location coordinates of the feature matching information are obtained as shown in equation (2)
Wherein (A), (B), (C), (D), (C), (B), (C)d 1 ，d 2 ) Respectively the feature plane coordinates of one of the image groups,fis the focal length of the camera and is,Jis a baseline for a plurality of cameras,cfor the feature disparity on each group of images,Zto reconstruct the position coordinates.
5. The control method for the vehicle-mounted tethered unmanned aerial vehicle to track the moving vehicle in real time based on visual navigation positioning as claimed in claim 2,
estimating the pose of the tracked vehicle according to the visual ranging information stored in the cloud, and determining the pose of the tracked vehicle further comprises:
setting a known starting point for the reconstructed coordinates, and accumulating the transformation of the frame according to the starting point; if the pose of the first frame is (0, 0, 0) of the world coordinate system, the pose of the tracked vehicle at the current time t is formula (3):
wherein the content of the first and second substances,O t-1 record for 3 x 3 matrix at last momentt-1Tracked vehicle direction of;q t-1 record the last moment for the 3 x 1 vectort-1Tracked vehicle pose coordinates;O t for 3 x 3 matrix intTracked vehicle direction at time;q t for 3 x 1 vector intThe tracked vehicle pose coordinates at that moment;X tis composed oftRotation parameters in the coordinate transformation of the reconstruction position at the moment;S t is composed oftTranslation parameters in the coordinate transformation of the reconstruction location in time instants.
6. The control method for the vehicle-mounted tethered unmanned aerial vehicle to track the moving vehicle in real time based on visual navigation positioning as claimed in claim 5,
detecting an obstacle according to the pose of the tracked vehicle, and planning a local path according to the obstacle detection result; further comprising:
carrying out three-dimensional matching on the pose of the tracked vehicle and the pose of the unmanned aerial vehicle to obtain a real-time running path;
detecting obstacles according to the real-time running path of the tracked vehicle;
and if no obstacle exists, planning a plurality of local paths existing in the flight path of the unmanned aerial vehicle.
7. The control method for the vehicle-mounted tethered unmanned aerial vehicle to track the moving vehicle in real time based on visual navigation positioning as claimed in claim 6,
if the obstacle exists, matching the temporary path pointmAnd calculating a temporary pathmAnd the current timetDistance of the unmanned aerial vehicle position;
gridding the distance to obtain a plurality of sub-grid units;
defining an area outside the plurality of sub-grid cells as unobstructed;
and acquiring an obstacle-free boundary, and moving the unmanned aerial vehicle to an obstacle-free area.
8. The control method for the vehicle-mounted tethered drone to track the moving vehicle in real time based on visual navigation positioning as claimed in claim 1, wherein said determining a tracking waypoint in the local path with which to guide the flight of the drone comprises:
segmenting the local path, extracting features of sub-local paths in each segment, and defining a plurality of feature information as waypoints;
connecting a plurality of waypoints in a time sequence to obtain waypoint lines;
and taking the waypoint line as a guide line of the flight state of the unmanned aerial vehicle.
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