CN116824414A - Method for rapidly deploying RTK (real time kinematic) by unmanned aerial vehicle - Google Patents
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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 application relates to a method for rapidly deploying RTK (real time kinematic) of an unmanned aerial vehicle, which relates to the field of satellite positioning technology, and comprises the steps of defining a coverage area and determining the peripheral outline of the area; establishing detection points and determining detection paths on the peripheral outline of the area, and determining the movement paths of the unmanned aerial vehicle; controlling the unmanned aerial vehicle to move along the moving path and acquiring a lower shooting image in real time; feature recognition is carried out in the lower shooting image so as to judge whether tree features exist or not; defining a tree point when the tree feature exists and defining a free point when the tree feature does not exist; determining the path tree duty ratio and the corresponding attenuation distance according to the tree points and the free points; determining an actual coverage distance according to the attenuation distance calculation; and determining the actual coverage distance with the smallest value according to the ordering rule, and defining an influence area by taking the reference point as a midpoint and the actual coverage distance as a radius. The application has the effect of reducing the occurrence of situations that the deployment of the RTK reference station is inaccurate to influence the subsequent mountain mapping operation.
Description
Technical Field
The application relates to the field of satellite positioning technology, in particular to a method for rapidly deploying an RTK (real time kinematic) by an unmanned aerial vehicle.
Background
The RTK carrier phase difference technology is a difference method for processing the observed quantity of the carrier phases of two measuring stations in real time, and the carrier phases acquired by a reference station are sent to a user receiver to calculate the difference and calculate the coordinates.
In the related art, mapping of mountain bodies in mountain areas is often realized by using unmanned aerial vehicles and RTK technology, reference stations are arranged in the mountain bodies, signal transceivers of mobile stations are installed on the unmanned aerial vehicles, and when the unmanned aerial vehicles move in a range covered by the reference stations, position coordinates of the unmanned aerial vehicles can be solved through carrier transmission of satellites, the reference stations and the mobile stations, so that actual positions of the unmanned aerial vehicles in the mountain bodies are determined, and mapping operation of the mountain bodies is facilitated.
Aiming at the related technology, the inventor considers that because a forest zone exists in a mountain, signals are possibly blocked by dense trees in the transmission process of a carrier wave, so that the coverage range of each reference station may deviate from a calibration value, and if a worker deploys the RTK reference station by the calibration value, the situation that the position coordinates of the unmanned aerial vehicle are inaccurately determined during the subsequent unmanned aerial vehicle mapping operation can occur, and the mapping result is influenced.
Disclosure of Invention
In order to reduce the occurrence of situations that RTK reference station deployment is inaccurate to influence subsequent mountain mapping operation, the application provides a method for rapidly deploying RTKs by an unmanned aerial vehicle.
The application provides a method for rapidly deploying RTK (real time kinematic) by an unmanned aerial vehicle, which adopts the following technical scheme:
a method of fast deployment of an RTK by an unmanned aerial vehicle, comprising:
defining a coverage area by taking a preset datum point as a center and a preset calibration distance as a radius, and determining an area peripheral contour according to the coverage area;
establishing a preset fixed number of detection points on the peripheral outline of the area, determining a detection path according to the detection points and the reference points, and determining a movement path of the unmanned aerial vehicle according to the adjacent conditions of the detection points;
controlling the unmanned aerial vehicle to move along a moving path at a preset fixed height, and acquiring a lower shooting image in real time when the unmanned aerial vehicle is positioned on any detection path;
performing feature recognition in the lower shot image to judge whether preset tree features exist or not;
defining the position of the unmanned aerial vehicle as a tree point when the tree feature exists in the lower shot image, and defining the position of the unmanned aerial vehicle as a free point when the tree feature does not exist in the lower shot image;
Counting according to tree points to determine the number of trees, counting according to the free points to determine the free number, and calculating according to the number of trees and the free number to determine the path tree duty ratio;
determining the attenuation distance corresponding to the ratio of the path tree according to a preset attenuation matching relation;
calculating a difference value according to the calibration distance and the attenuation distance to determine an actual coverage distance;
and determining the actual coverage distance with the minimum numerical value according to a preset ordering rule, and defining an influence area by taking the reference point as a midpoint and the actual coverage distance as a radius.
Through adopting above-mentioned technical scheme, when needing to establish RTK reference station in the mountain area, the position of the reference station of needs establishment is in order to control unmanned aerial vehicle and carry out the flight to can confirm the trees condition in the reference point calibration distance, in order to learn the distance condition that can cover when establishing the reference station in reference point department, thereby demarcate comparatively accurate influence area, so that follow-up unmanned aerial vehicle can accurately fix a position in the influence area when the operation, reduce the condition emergence that influences mountain mapping operation because of the location inaccuracy.
Optionally, the method further includes a reference point determining step, which includes:
Acquiring a contour topographic map and a jungle density map;
determining the mountain altitude of each point of the mountain according to the contour map;
determining density coefficients within a calibration distance at each point of a mountain according to a jungle density map, determining the density coefficient with the largest numerical value according to a sequencing rule, and defining the density coefficient as an obstruction coefficient;
calculating according to the mountain altitude, the obstruction coefficient, the preset first altitude weight and the preset first density weight to determine the satisfaction coefficient;
determining a satisfaction coefficient with the largest numerical value according to the ordering rule, and defining mountain point positions corresponding to the satisfaction coefficient as sketching points;
determining the point separation distance according to the planned point and each point on the mountain area outline;
judging whether the point separation distance is smaller than the calibration distance or not;
if the situation that the point separation distance is smaller than the calibration distance does not exist, determining the planned point as a datum point;
if the point separation distance is smaller than the calibration distance, the satisfaction coefficient with the largest value is redetermined in the remaining satisfaction coefficients, and the planned point is updated until the datum point is determined.
By adopting the technical scheme, the position of the datum point can be determined in the mountain area, so that the datum station can be established on the point with higher altitude and fewer surrounding trees.
Optionally, the method further comprises a step of establishing a detection point, which comprises the following steps:
connecting points on the peripheral outline of the region with the reference points to determine detection line segments;
defining the mountain altitude through which the detection line segments pass in the contour topographic map as detection altitude;
determining the detection height with the maximum value and the minimum value in a single detection line segment according to the sequencing rule, and performing difference calculation according to the detection height to determine the altitude difference height;
calculating according to the altitude difference height, the obstruction coefficient, a preset second altitude weight and a preset second density weight to determine an influence coefficient;
and determining an influence coefficient with the maximum value according to the ordering rule, determining the point position on the peripheral outline of the area corresponding to the influence coefficient as a detection point, and equally dividing the rest detection points on the peripheral outline of the area according to the detection point.
Through adopting above-mentioned technical scheme, can confirm the big, big point position of trees influence as the check point to the altitude difference is great to unmanned aerial vehicle normally carries out the operation.
Optionally, the step of controlling the unmanned aerial vehicle to move along the moving path at a preset fixed height includes:
acquiring a front obstacle distance and a lower obstacle distance;
judging whether the front obstacle distance is smaller than a preset safety distance;
if the front obstacle distance is smaller than the safety distance, controlling the unmanned aerial vehicle to move upwards along the height direction until the front obstacle distance is not smaller than the safety distance;
if the front obstacle distance is not smaller than the safety distance, judging whether the movement instruction before the unmanned aerial vehicle is movement in the height direction;
if the movement instruction before the unmanned aerial vehicle is movement in the height direction, controlling the unmanned aerial vehicle to continue to move along a movement path;
if the previous movement instruction of the unmanned aerial vehicle is not movement in the height direction, judging whether the lower barrier distance is greater than the fixed distance;
if the lower barrier distance is greater than the fixed distance, the unmanned aerial vehicle is controlled to move downwards along the height direction until the lower barrier distance is not greater than the fixed distance;
and if the lower barrier distance is not greater than the fixed distance, controlling the unmanned aerial vehicle to continue to move along the moving path.
Through adopting above-mentioned technical scheme for unmanned aerial vehicle can be comparatively stable remove, reduces the possibility that the crash appears in unmanned aerial vehicle.
Optionally, after the unmanned aerial vehicle completes moving on the detection path, the method for rapidly deploying the RTK by the unmanned aerial vehicle further includes:
acquiring the height movement distance of the unmanned aerial vehicle in the height direction;
determining a transmission influence distance corresponding to the height movement distance according to a preset blocking matching relation;
and carrying out summation calculation according to the transmission influence distance and the attenuation distance to update the attenuation distance, and determining the actual coverage distance according to the updated attenuation distance.
By adopting the technical scheme, the attenuation distance can be updated according to the change of the altitude of the point position, so that the accuracy of determining the actual coverage distance is further improved.
Optionally, after the unmanned aerial vehicle passes through all the detection points, the method for rapidly deploying the RTK by the unmanned aerial vehicle further includes:
defining the ratio of the tree on the detected path as the first density, and defining the density coefficient determined in the direction of the detected path compared with the reference point as the second density;
performing difference calculation according to the first density and the second density to determine a difference density;
judging whether all the difference densities are smaller than a preset allowable density;
if all the difference densities are smaller than the allowable density, maintaining the currently determined influence area;
If the difference density of any one of the detection paths is not smaller than the allowable density, defining the detection point on the detection path as an abnormal point;
defining a first detection point which is not an abnormal point as a starting point according to the moving path;
determining an adjusting radian corresponding to the difference density according to a preset adjusting matching relation;
controlling the abnormal points and the detection points after the abnormal points to move to the direction of the starting point to adjust radian so as to form new detection points, and determining coverage radian after all abnormal points are moved;
calculating according to the coverage radians and the fixed quantity to determine a mean radian;
calculating according to the coverage radian and a preset whole circle radian to determine an available radian, and determining the generation quantity according to the available radian and the average radian;
generating new detection points on the peripheral outline of the area according to the generated number and the available radian, controlling the unmanned aerial vehicle to perform flight operation again by the new detection points, and updating the affected area.
Through adopting above-mentioned technical scheme, when detecting that trees condition changes greatly, steerable unmanned aerial vehicle carries out the secondary flight to correct the flight path according to trees condition, thereby can carry out comparatively accurate determination to the trees condition in the demarcation distance, in order to confirm comparatively accurate influence area.
Optionally, in the process of the unmanned aerial vehicle flying again, the method for rapidly deploying the RTK by the unmanned aerial vehicle further includes:
defining the attenuation distance determined by the previous detection path as an initial distance and the attenuation distance determined by the current detection path as a termination distance;
performing difference calculation according to the initial distance and the termination distance to determine an attenuation deviation distance;
judging whether the attenuation deviation distance is larger than a preset abrupt change distance or not;
if the attenuation deviation distance is not greater than the abrupt change distance, the unmanned aerial vehicle is controlled to continue to move along the moving path;
if the attenuation deviation distance is larger than the abrupt change distance, performing difference calculation according to the attenuation deviation distance and the abrupt change distance to determine an adjustment distance;
determining a correction radian corresponding to the adjustment distance according to a preset correction matching relation;
and moving the rest original detection points on the peripheral outline of the area according to the corrected radian, and generating new detection points according to the preset interval radian.
Through adopting above-mentioned technical scheme, at unmanned aerial vehicle secondary flight's in-process, can carry out continuous correction to unmanned aerial vehicle route according to trees actual conditions to make unmanned aerial vehicle's detection effect preferred.
Optionally, the method further includes a step of determining a spacing radian, the step including:
Defining a detection point passed by the unmanned aerial vehicle as a finishing point, and defining a detection point not passed by the unmanned aerial vehicle as a point to be detected;
counting and summing according to the finishing points and the points to be detected to determine the total detection quantity;
determining a detected radian according to the finishing point, and determining a fixed radian according to the detected radian, the adjusting radian and a preset unit radian;
calculating according to the whole circle radian and the fixed radian to determine a variable radian;
calculating according to the fixed radian and the total detection quantity to determine a fixed average radian;
calculating and rounding according to the variable radian and the fixed average radian to determine the number of arc segments;
and calculating according to the variable radian and the number of the arc segments to determine the interval radian.
By adopting the technical scheme, more accurate interval radian can be determined according to the detection point conditions, so that detection points with proper intervals can be conveniently generated.
In summary, the present application includes at least one of the following beneficial technical effects:
1. before the deployment of the reference station, the unmanned aerial vehicle can be controlled to work so as to determine the surrounding tree conditions, so that the shielding condition of the tree to the signal can be known, and a more accurate influence area can be defined for the unmanned aerial vehicle for subsequent mapping, so that the mapping effect is better;
2. In the defining process of the influence area, secondary operation can be performed according to the change condition of the tree so as to improve the accuracy of defining the influence area;
3. in the process of unmanned aerial vehicle secondary operation, can be according to the trees condition to the constant correction of check point to make unmanned aerial vehicle detection effect preferred.
Drawings
Fig. 1 is a flow chart of a method of a drone to rapidly deploy an RTK.
Fig. 2 is a schematic diagram of a path of travel of the drone.
Fig. 3 is a flowchart of a reference point determination method.
Fig. 4 is a flowchart of a detection point establishment method.
Fig. 5 is a flow chart of a method of drone movement control.
Fig. 6 is a flowchart of a decay distance update method.
Fig. 7 is a flowchart of a method of controlling a secondary operation of the unmanned aerial vehicle.
Fig. 8 is a flowchart of the secondary operation detection point determination method.
Fig. 9 is a flow chart of a method of determining radians of intervals.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings 1 to 9 and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
Embodiments of the application are described in further detail below with reference to the drawings.
The embodiment of the application discloses a method for rapidly deploying an RTK (real time kinematic) by an unmanned aerial vehicle, which is characterized in that when a reference station is required to be established in a mountain area to assist in subsequent unmanned aerial vehicle mapping operation, deployment points of the reference station are determined according to the topography condition of the mountain area, and the unmanned aerial vehicle is used for detecting the range within the calibration distance of the reference station to determine the tree shielding condition, so that the actual coverage area of the reference station can be determined, the subsequent unmanned aerial vehicle can not move to a position which cannot be accurately positioned during the mapping operation, and the mountain mapping operation of the subsequent unmanned aerial vehicle is facilitated.
Referring to fig. 1, a method flow of a method for a drone to rapidly deploy an RTK includes the steps of:
step S100: and defining a coverage area by taking a preset datum point as a center and a preset calibration distance as a radius, and determining the peripheral outline of the area according to the coverage area.
The reference point is a point location of a reference station in an RTK technology to be established in a mountain area, a specific determination method is described below, the calibration distance is a range distance which can be covered by the reference station to be established under the theoretical condition, a coverage area is defined to determine an area range to which signals of the reference station can be transmitted under the condition that no tree is used for shielding, and the peripheral outline of the area is the whole external outline of the coverage area.
Step S101: and establishing a preset fixed number of detection points on the peripheral outline of the area, determining a detection path according to the detection points and the reference points, and determining the movement path of the unmanned aerial vehicle according to the adjacent conditions of the detection points.
The fixed number is the fixed value number set by the staff, the detection points are uniformly distributed on the peripheral outline of the area, one detection point can be positioned in the fixed direction of the datum point so as to facilitate the distribution of other detection points, meanwhile, the first detection point can be determined according to the actual situation of the area, and the specific method is set by the staff according to the actual situation and is not repeated; the detection path is a path formed between the detection point and the reference point, and referring to fig. 2, the movement path is a path that the unmanned aerial vehicle needs to move when it needs to go through all the detection paths.
Step S102: and controlling the unmanned aerial vehicle to move along the moving path at a preset fixed height, and acquiring a lower shooting image in real time when the unmanned aerial vehicle is positioned on any detection path.
The fixed height is the distance height between the unmanned aerial vehicle and the barrier below of the needs that the staff set for, who can all be carried out by the staff according to actual conditions, and the image is shot under the unmanned aerial vehicle to the below, and accessible carries the utensil that has the shooting function on unmanned aerial vehicle and obtains.
Step S103: and carrying out feature recognition in the lower shooting image to judge whether preset tree features exist or not.
The tree characteristics are characteristics which can be identified as trees and are set by staff, and the purpose of judgment is to know whether the area flown by the unmanned aerial vehicle is provided with the trees or not so as to facilitate the subsequent analysis of the signal shielding condition of the trees; the feature recognition method is a conventional technical means for those skilled in the art, and is not described in detail.
Step S104: and defining the position of the unmanned aerial vehicle as a tree point when the tree feature exists in the lower shot image, and defining the position of the unmanned aerial vehicle as a free point when the tree feature does not exist in the lower shot image.
The tree points and the empty points are defined, and the tree condition on the detection path can be analyzed, so that the tree shielding condition can be conveniently determined later.
Step S105: counting according to tree points to determine the number of trees, counting according to the free points to determine the free number, and calculating according to the number of trees and the free number to determine the path tree duty ratio.
The number of the trees is the total number value of the tree points determined on the single detection path, the tree points can be obtained by counting one by one, and the number of the empty points is the total number value of the empty points determined on the single detection path, and the tree points can be obtained by counting the empty points one by one; the ratio of the tree points of the path to the tree points of the detection path is the ratio of the tree points to all points.
Step S106: and determining the attenuation distance corresponding to the path tree ratio according to a preset attenuation matching relation.
Different path tree ratios indicate that the number of the trees in the calibration distance is inconsistent, when the number of the trees is large, the shielding condition of the signals is strong, the transmission distance attenuation condition of the signals is large, the attenuation distance is the distance which can attenuate the transmission of the signals under the path tree ratio, different path tree ratios have different attenuation distances, and the attenuation matching relation between the two is analyzed and determined by staff according to the signal transmission conditions of reference stations and mobile stations in other areas.
Step S107: and carrying out difference calculation according to the calibration distance and the attenuation distance to determine the actual coverage distance.
The actual coverage distance is a distance value which can normally transmit signals sent by the reference station in the direction corresponding to the detection path, and the attenuation distance is subtracted from the calibration distance to determine.
Step S108: and determining the actual coverage distance with the minimum numerical value according to a preset ordering rule, and defining an influence area by taking the reference point as a midpoint and the actual coverage distance as a radius.
The sequencing rule is a method with a numerical value comparison function set by a worker, such as an bubbling method, the actual coverage distance with the smallest numerical value can be determined through the sequencing rule, and an influence area is defined by utilizing the actual coverage distance, so that the area which can be covered by the reference station set by the reference point is determined, the subsequent unmanned aerial vehicle can be accurately positioned in the influence area in the mapping process, and the stability of mapping operation is improved.
Referring to fig. 3, the method further includes a reference point determining step including:
step S200: and obtaining a contour topographic map and a jungle density map.
The contour topographic map is a topographic map obtained by satellites in the mountain area, and the jungle density map is a topographic map in which the tree density condition is recorded.
Step S201: and determining the mountain altitude of each mountain point according to the contour map.
The mountain area outline is the whole outline of the mountain area of the current required construction reference station, the mountain altitude is the altitude of each point, and altitude acquisition can be carried out through a contour topographic map.
Step S202: and determining density coefficients within a calibration distance at each point of the mountain according to the jungle density map, determining the density coefficient with the largest numerical value according to the ordering rule, and defining the density coefficient as an obstruction coefficient.
The density coefficient is a tree density value on a path established by taking any point on a jungle density chart as a starting point and the other end point and the starting point as calibration distances, namely the ratio of the trees on the path, the maximum tree influence condition suffered by the point when a reference station is established can be determined through an ordering rule, and the density coefficient is defined as an obstruction coefficient for identification so as to facilitate subsequent analysis.
Step S203: and calculating according to the mountain altitude, the obstruction coefficient, the preset first altitude weight and the preset first density weight to determine the satisfaction coefficient.
The first height weight is the weight ratio of the altitude condition to the selection condition when determining the reference station, and the first density weight is the weight ratio of the tree density condition to the selection condition when determining the reference station, wherein the reference station needs to receive satellite signals and transmit carriers, so as to establish points with fewer trees at high positions and surrounding positions as far as possible, thereby meeting the coefficient of satisfactionTo meet the requirement of the reference station, the higher the value is, the more the value meets the requirement of the reference station, the calculation formula isWhereinTo satisfy the coefficient of sexual>For the first height weight, +.>For the first density weight->Is mountain altitude, ++>To block coefficients.
Step S204: and determining a satisfaction coefficient with the largest value according to the ordering rule, and defining the mountain point position corresponding to the satisfaction coefficient as a planned point.
The point positions which are most in line with the reference point requirements can be determined through the ordering rule, and the point positions are defined as sketched points at the moment so as to distinguish different point positions, so that the subsequent analysis is facilitated.
Step S205: and determining the point separation distance according to the planned point and each point on the mountain area outline.
The point separation distance is the distance value between the planned point and each point on the mountain area outline.
Step S206: and judging whether the point separation distance is smaller than the calibration distance.
The purpose of the judgment is to know whether the unmanned aerial vehicle flies out of the mountain coverage area when performing the detection operation.
Step S2061: if the point separation distance is smaller than the calibration distance, the proposed point is determined as a datum point.
When the situation that the point separation distance is smaller than the calibration distance does not exist, the fact that the determined planned point meets the mountain standard station construction is indicated, and the planned point is determined to be the standard point.
Step S2062: if the point separation distance is smaller than the calibration distance, the satisfaction coefficient with the largest value is redetermined in the remaining satisfaction coefficients, and the planned point is updated until the datum point is determined.
When the distance between the points is smaller than the calibration distance, the condition that the determined flight path of the unmanned aerial vehicle is invalid when the planned point is used as the datum point is described, namely, the planned point is closer to the edge of the mountain, and even if the datum station is established, the condition that the partial coverage area is invalid is also caused, and the planned point which meets the best requirements is continuously determined in the rest points until the datum point which meets the requirements is determined, so that the effective determination of the datum point is realized.
Referring to fig. 4, the method further includes a step of establishing a detection point, the step including:
step S300: points on the peripheral contour of the region are connected to the reference points to determine the detected line segments.
The detection line segment is formed by connecting a datum point with a point on the peripheral outline of the area.
Step S301: the mountain altitude through which the detection line segment passes is defined as the detection altitude in the contour topographic map.
The height is defined to determine the height that the unmanned aerial vehicle needs to pass when along the direction of the detected road section, so as to facilitate subsequent analysis.
Step S302: and determining the detection height with the largest value and the smallest value in the single detection line segment according to the sequencing rule, and performing difference calculation according to the detection height to determine the altitude difference height.
The detection height with the largest value and the smallest value is determined by using the sorting rule, the altitude condition of the unmanned aerial vehicle can be determined, and the altitude difference value height is the altitude change value which is required to appear when the unmanned aerial vehicle moves along the detection line segment.
Step S303: and calculating according to the altitude difference height, the obstruction coefficient, the preset second altitude weight and the preset second density weight to determine the influence coefficient.
The larger the altitude difference height is, the more complex the terrain of the area is, the more has the detection meaning, the second altitude weight is the influence weight which can be generated by the altitude difference height when the detection point is determined, the second density weight is the influence weight which can be generated by the obstruction coefficient when the detection point is determined, the influence coefficient is the coefficient of the point position which needs to be detected on the external contour of the area, the larger the coefficient value is, the more has the detection meaning, the calculation formula is that. Wherein->To influence the coefficient +.>For the second height weight, +>For the second density weight->Is the altitude difference height.
Step S304: and determining an influence coefficient with the maximum value according to the ordering rule, determining the point position on the peripheral outline of the area corresponding to the influence coefficient as a detection point, and equally dividing the rest detection points on the peripheral outline of the area according to the detection point.
And determining the influence coefficient with the largest numerical value by using the ordering rule to determine the point position which is most required to be detected, and determining the point position as a detection point at the moment so as to determine the rest detection points according to the detection point, thereby enabling the unmanned aerial vehicle to carry out more stable detection.
Referring to fig. 5, the step of controlling the unmanned aerial vehicle to move along the moving path at a predetermined fixed height includes:
Step S400: the forward obstacle distance and the lower obstacle distance are acquired.
The distance between the obstacle and the unmanned aerial vehicle detected in the front of the unmanned aerial vehicle moving direction is the distance value, and the distance between the obstacle and the unmanned aerial vehicle detected under the unmanned aerial vehicle is the distance value, and the accessible installs distance sensor on unmanned aerial vehicle and obtains.
Step S401: and judging whether the front obstacle distance is smaller than a preset safety distance.
The safety distance is a maximum distance value when an obstacle exists in front of the safety distance set by a worker and needs to be avoided, and the purpose of the judgment is to know whether the unmanned aerial vehicle needs to perform an avoidance operation or not.
Step S4011: and if the front obstacle distance is smaller than the safety distance, controlling the unmanned aerial vehicle to move upwards along the height direction until the front obstacle distance is not smaller than the safety distance.
When the front obstacle distance is smaller than the safety distance, the situation that the obstacle exists in front is indicated, at the moment, the unmanned aerial vehicle needs to avoid, and the unmanned aerial vehicle is controlled to move upwards so as to avoid the front obstacle.
Step S4012: if the front obstacle distance is not smaller than the safety distance, judging whether the movement instruction before the unmanned aerial vehicle is movement in the height direction.
When the front obstacle distance is not smaller than the safety distance, the situation that no obstacle exists in front of the unmanned aerial vehicle to influence the movement of the unmanned aerial vehicle is described, and the purpose of judgment is to know whether the unmanned aerial vehicle just performs the front obstacle avoidance action.
Step S40121: and if the movement instruction before the unmanned aerial vehicle is movement in the height direction, controlling the unmanned aerial vehicle to continue to move along the movement path.
When the movement instruction before the unmanned aerial vehicle is movement in the height direction, the unmanned aerial vehicle is stated to avoid the obstacle before, and the unmanned aerial vehicle can continue to move according to the movement path at the moment.
Step S40122: if the movement instruction before the unmanned aerial vehicle is not movement in the height direction, judging whether the lower barrier distance is larger than the fixed distance.
When the movement instruction before the unmanned aerial vehicle is not the movement in the height direction, the unmanned aerial vehicle is described as normally moving before, and the purpose of judgment at this time is to know whether the unmanned aerial vehicle can better identify and analyze the tree condition below.
Step S401221: and if the lower barrier distance is greater than the fixed distance, controlling the unmanned aerial vehicle to move downwards along the height direction until the lower barrier distance is not greater than the fixed distance.
When the obstacle distance below is greater than the fixed distance, the unmanned aerial vehicle can not better analyze the tree condition below at the moment, and the unmanned aerial vehicle is controlled to move downwards at the moment so that the unmanned aerial vehicle can better acquire and analyze the tree image below.
Step S401222: and if the lower barrier distance is not greater than the fixed distance, controlling the unmanned aerial vehicle to continue to move along the moving path.
When the barrier distance below is not greater than the fixed distance, the unmanned aerial vehicle can analyze the tree below better, and the unmanned aerial vehicle can be controlled to move normally at the moment.
Referring to fig. 6, after the unmanned aerial vehicle completes moving on the detection path, the method for rapidly deploying the RTK by the unmanned aerial vehicle further includes:
step S500: and acquiring the height movement distance of the unmanned aerial vehicle in the height direction.
The height moving distance is a distance value of the unmanned aerial vehicle moving in the height direction, namely a distance value between the lowest point and the highest point of the unmanned aerial vehicle in the height direction.
Step S501: and determining the transmission influence distance corresponding to the height movement distance according to the preset blocking matching relation.
Different altitude changes can lead to the transmission of carrier signals to have influence, and transmission influence distances are distance values of carrier influence caused by the altitude changes, different altitude moving distances correspond to different transmission influence distances, and a blocking matching relation between the transmission influence distances and the transmission influence distances is determined by staff through multiple experiments in advance.
Step S502: and carrying out summation calculation according to the transmission influence distance and the attenuation distance to update the attenuation distance, and determining the actual coverage distance according to the updated attenuation distance.
The transmission influence distance plus the attenuation distance are utilized to determine the influence of altitude change and tree conditions on carrier transmission, so that the accurate attenuation distance is determined to determine the actual coverage distance, and the accuracy of the influence area demarcation is improved.
Referring to fig. 7, after the unmanned aerial vehicle passes through all detection points, the method for rapidly deploying the RTK by the unmanned aerial vehicle further includes:
step S600: the ratio of the tree on the detected path is defined as a first density, and the density coefficient determined in the direction of the detected path compared with the reference point is defined as a second density.
The first density and the second density are defined, and the tree density condition actually acquired by the unmanned aerial vehicle on the detection path and the tree density condition acquired by the jungle density chart can be distinguished, so that subsequent analysis is facilitated.
Step S601: and performing difference calculation according to the first density and the second density to determine a difference density.
The difference density is the difference between the first density and the second density, the difference being an absolute value.
Step S602: judging whether all the difference densities are smaller than a preset allowable density.
The maximum allowable difference density when no large change exists between the tree on the detection path and the jungle density map is determined by the allowed density set by the staff, and the purpose of the judgment is to know whether the current forest area in the mountain area has large change compared with the jungle density map.
Step S6021: if all the difference densities are less than the allowable density, the currently determined area of influence is maintained.
When all the difference densities are smaller than the allowable density, the change of the forest area is not obvious, and the method is used according to the determined influence area.
Step S6022: if the difference density of any one of the detection paths is not smaller than the allowable density, the detection point on the detection path is defined as an abnormal point.
When the difference density of any one of the detection points is not smaller than the allowable density, the forest region is indicated to have obvious change on the detection path, and the detection point is defined as an abnormal point for identification so as to facilitate subsequent further analysis.
Step S603: the first detection point which is not an abnormal point is defined as a starting point according to the moving path.
Defining a starting point to distinguish different abnormal points, and facilitating subsequent analysis.
Step S604: and determining the adjusting radian corresponding to the difference density according to a preset adjusting matching relation.
Different difference densities indicate different tree change conditions on the detection path, when the difference density is larger, the tree change at the position is larger, the position needs to be continuously and accurately detected, the adjusting radian is the radian required to be adjusted between an abnormal point and a previous detection point, the further detection of the position area is realized through the adjustment of the radian, different difference densities correspond to different adjusting radians, and the adjusting matching relation between the two is determined by staff in advance according to multiple tests.
Step S605: and controlling the abnormal points and the detection points after the abnormal points to move to the direction of the starting point to adjust the radian so as to form new detection points, and determining the coverage radian after all the abnormal points are moved.
The abnormal point and the subsequent detection points are controlled to move towards the direction of the starting point, so that the situation between the abnormal point and the last detection point can be further detected, and the coverage radian is the radian value of the fixed number of detection points.
Step S606: and calculating according to the coverage radians and the fixed quantity to determine the average radian.
The mean radian is the average radian between the currently determined detection points and the detection points, and is determined by dividing the coverage radian by the fixed number minus one.
Step S607: and calculating according to the coverage radian and a preset whole circle radian to determine an available radian, and determining the generation quantity according to the available radian and the average radian.
The whole circle of radian is the radian when one circle, namely 360 degrees, the available radian is the radian which needs to be detected, the coverage radian is subtracted from the whole circle of radian to determine, the number of the generated new detection points which need to be generated is determined by dividing the available radian by the average radian, the corresponding integer is determined by adopting a rounding method after decimal point to determine the result, and the generated number is determined by subtracting one from the integer.
Step S608: generating new detection points on the peripheral outline of the area according to the generated number and the available radian, controlling the unmanned aerial vehicle to perform flight operation again by the new detection points, and updating the affected area.
And generating detection points with consistent radian intervals for the areas with the available radians according to the generated quantity so as to control the unmanned aerial vehicle to perform flight operation again with the new detection points, thereby determining more accurate forest conditions and improving the accuracy of determining the affected areas.
Referring to fig. 8, in the process of flying the unmanned aerial vehicle again, the method for rapidly deploying the RTK by the unmanned aerial vehicle further includes:
step S700: the attenuation distance determined by the previous detection path is defined as an initial distance, and the attenuation distance determined by the current detection path is defined as a termination distance.
And defining an initial distance and a termination distance to determine the detection condition of the unmanned aerial vehicle, so that subsequent analysis is facilitated.
Step S701: and carrying out difference calculation according to the initial distance and the final distance to determine the attenuation deviation distance.
The attenuation deviation distance is a deviation value of attenuation distances detected by the unmanned aerial vehicle at adjacent detection points, and the deviation value is an absolute value.
Step S702: and judging whether the attenuation deviation distance is larger than a preset abrupt change distance.
The abrupt change distance is the minimum attenuation deviation distance set by the staff and used for judging whether the adjacent detection points have large changes in the environment when the adjacent detection points are determined to have obvious attenuation distance changes.
Step S7021: and if the attenuation deviation distance is not greater than the abrupt change distance, controlling the unmanned aerial vehicle to continue to move along the moving path.
When the attenuation deviation distance is not greater than the abrupt change distance, the change of the current environment is stable, and corresponding detection is carried out according to the moving path.
Step S7022: if the attenuation deviation distance is larger than the abrupt change distance, performing difference calculation according to the attenuation deviation distance and the abrupt change distance to determine the adjustment distance.
When the attenuation deviation distance is larger than the abrupt change distance, the environmental change in the area range is obvious, and the subsequent detection condition needs to be adjusted; the adjustment distance is a distance value that the currently determined attenuation deviation distance exceeds the abrupt change distance, and is determined by subtracting the abrupt change distance from the attenuation deviation distance.
Step S703: and determining the correction radian corresponding to the adjustment distance according to the preset correction matching relation.
The correction radian is the radian required to be adjusted for the subsequent detection point, different adjustment distances indicate that the change condition of the current environment is inconsistent, the correction radian required to be adjusted is different at the moment, and the correction matching relationship between the two is determined by staff in advance according to multiple tests.
Step S704: and moving the rest original detection points on the peripheral outline of the area according to the corrected radian, and generating new detection points according to the preset interval radian.
The rest detection point moving correction radian is controlled to update the position of the rear detection point, so that the unmanned aerial vehicle can detect the area more comprehensively, and meanwhile, a new detection point is generated to detect the area which is formed after the detection point moves and does not have the detection point, and the accuracy of a detection result is improved; the specific determination method is as follows, wherein the interval radian is the generated radian interval value between detection points which are not the original fixed number.
Referring to fig. 9, the determining of the interval radians includes:
step S800: and defining a detection point which is passed by the unmanned aerial vehicle as a finishing point, and defining a detection point which is not passed by the unmanned aerial vehicle as a point to be detected.
And defining the finishing point and the point to be detected so as to distinguish different detection points, thereby facilitating the subsequent analysis.
Step S801: and counting and summing according to the finish point and the point to be detected to determine the total detection quantity.
The total detection number is the number of all detection points when the unmanned aerial vehicle works for the second time.
Step S802: and determining the detected radian according to the finishing point, and determining the fixed radian according to the detected radian, the adjusting radian and the preset unit radian.
The detected radian is the radian of an arc between the first determined finishing point and the last finishing point, the unit radian is the radian between the subsequent detection points and the detection points, the fixed radian is the radian which can be passed by the fixed number of detection points, and the detection finishing radian is added with all the unit radians and then subtracted with the adjustment radian to determine.
Step S803: the calculation is performed based on the full circle arc and the fixed arc to determine the variable arc.
The variable radian is the radian value of the arc needing to be added with a detection point, and the variable radian is obtained by subtracting the fixed radian from the whole circle of radian.
Step S804: a calculation is performed to determine a fixed average arc from the fixed arc and the total number of detections.
The fixed average radian is the average radian value corresponding to the original detection point under the current condition, and the fixed radian is divided by the total detection quantity minus one value to obtain.
Step S805: and calculating and rounding according to the variable radian and the fixed average radian to determine the number of arc segments.
The arc segment number is the average segment number formed by dividing the arc corresponding to the variable radian, dividing the variable radian by the fixed average radian, and rounding to obtain the arc segment number.
Step S806: and calculating according to the variable radian and the number of the arc segments to determine the interval radian.
The variable radian is divided by the number of arc segments to determine the interval radian of each arc, so that a more appropriate detection point can be conveniently generated later for unmanned aerial vehicle operation.
Claims (8)
1. A method for rapid deployment of an RTK by an unmanned aerial vehicle, comprising:
defining a coverage area by taking a preset datum point as a center and a preset calibration distance as a radius, and determining an area peripheral contour according to the coverage area;
establishing a preset fixed number of detection points on the peripheral outline of the area, determining a detection path according to the detection points and the reference points, and determining a movement path of the unmanned aerial vehicle according to the adjacent conditions of the detection points;
controlling the unmanned aerial vehicle to move along a moving path at a preset fixed height, and acquiring a lower shooting image in real time when the unmanned aerial vehicle is positioned on any detection path;
performing feature recognition in the lower shot image to judge whether preset tree features exist or not;
defining the position of the unmanned aerial vehicle as a tree point when the tree feature exists in the lower shot image, and defining the position of the unmanned aerial vehicle as a free point when the tree feature does not exist in the lower shot image;
counting according to tree points to determine the number of trees, counting according to the free points to determine the free number, and calculating according to the number of trees and the free number to determine the path tree duty ratio;
Determining the attenuation distance corresponding to the ratio of the path tree according to a preset attenuation matching relation;
calculating a difference value according to the calibration distance and the attenuation distance to determine an actual coverage distance;
and determining the actual coverage distance with the minimum numerical value according to a preset ordering rule, and defining an influence area by taking the reference point as a midpoint and the actual coverage distance as a radius.
2. The method of rapid RTK deployment by an unmanned aerial vehicle of claim 1, further comprising a reference point determining step comprising:
acquiring a contour topographic map and a jungle density map;
determining the mountain altitude of each point of the mountain according to the contour map;
determining density coefficients within a calibration distance at each point of a mountain according to a jungle density map, determining the density coefficient with the largest numerical value according to a sequencing rule, and defining the density coefficient as an obstruction coefficient;
calculating according to the mountain altitude, the obstruction coefficient, the preset first altitude weight and the preset first density weight to determine the satisfaction coefficient;
determining a satisfaction coefficient with the largest numerical value according to the ordering rule, and defining mountain point positions corresponding to the satisfaction coefficient as sketching points;
Determining the point separation distance according to the planned point and each point on the mountain area outline;
judging whether the point separation distance is smaller than the calibration distance or not;
if the situation that the point separation distance is smaller than the calibration distance does not exist, determining the planned point as a datum point;
if the point separation distance is smaller than the calibration distance, the satisfaction coefficient with the largest value is redetermined in the remaining satisfaction coefficients, and the planned point is updated until the datum point is determined.
3. The method for rapid RTK deployment by an unmanned aerial vehicle of claim 2, further comprising a step of establishing a detection point, the step comprising:
connecting points on the peripheral outline of the region with the reference points to determine detection line segments;
defining the mountain altitude through which the detection line segments pass in the contour topographic map as detection altitude;
determining the detection height with the maximum value and the minimum value in a single detection line segment according to the sequencing rule, and performing difference calculation according to the detection height to determine the altitude difference height;
calculating according to the altitude difference height, the obstruction coefficient, a preset second altitude weight and a preset second density weight to determine an influence coefficient;
And determining an influence coefficient with the maximum value according to the ordering rule, determining the point position on the peripheral outline of the area corresponding to the influence coefficient as a detection point, and equally dividing the rest detection points on the peripheral outline of the area according to the detection point.
4. The method of claim 1, wherein the step of controlling the drone to move along the path of movement at a predetermined fixed height comprises:
acquiring a front obstacle distance and a lower obstacle distance;
judging whether the front obstacle distance is smaller than a preset safety distance;
if the front obstacle distance is smaller than the safety distance, controlling the unmanned aerial vehicle to move upwards along the height direction until the front obstacle distance is not smaller than the safety distance;
if the front obstacle distance is not smaller than the safety distance, judging whether the movement instruction before the unmanned aerial vehicle is movement in the height direction;
if the movement instruction before the unmanned aerial vehicle is movement in the height direction, controlling the unmanned aerial vehicle to continue to move along a movement path;
if the previous movement instruction of the unmanned aerial vehicle is not movement in the height direction, judging whether the lower barrier distance is greater than the fixed distance;
if the lower barrier distance is greater than the fixed distance, the unmanned aerial vehicle is controlled to move downwards along the height direction until the lower barrier distance is not greater than the fixed distance;
And if the lower barrier distance is not greater than the fixed distance, controlling the unmanned aerial vehicle to continue to move along the moving path.
5. The method for quickly deploying an RTK by a drone according to claim 4, wherein the method for quickly deploying the RTK by the drone after the movement of the drone on the detection path is completed further comprises:
acquiring the height movement distance of the unmanned aerial vehicle in the height direction;
determining a transmission influence distance corresponding to the height movement distance according to a preset blocking matching relation;
and carrying out summation calculation according to the transmission influence distance and the attenuation distance to update the attenuation distance, and determining the actual coverage distance according to the updated attenuation distance.
6. The method for rapid RTK deployment by a drone of claim 2, wherein after the drone passes through all detection points, the method for rapid RTK deployment by a drone further comprises:
defining the ratio of the tree on the detected path as the first density, and defining the density coefficient determined in the direction of the detected path compared with the reference point as the second density;
performing difference calculation according to the first density and the second density to determine a difference density;
judging whether all the difference densities are smaller than a preset allowable density;
If all the difference densities are smaller than the allowable density, maintaining the currently determined influence area;
if the difference density of any one of the detection paths is not smaller than the allowable density, defining the detection point on the detection path as an abnormal point;
defining a first detection point which is not an abnormal point as a starting point according to the moving path;
determining an adjusting radian corresponding to the difference density according to a preset adjusting matching relation;
controlling the abnormal points and the detection points after the abnormal points to move to the direction of the starting point to adjust radian so as to form new detection points, and determining coverage radian after all abnormal points are moved;
calculating according to the coverage radians and the fixed quantity to determine a mean radian;
calculating according to the coverage radian and a preset whole circle radian to determine an available radian, and determining the generation quantity according to the available radian and the average radian;
generating new detection points on the peripheral outline of the area according to the generated number and the available radian, controlling the unmanned aerial vehicle to perform flight operation again by the new detection points, and updating the affected area.
7. The method for rapid RTK deployment by a drone of claim 6, wherein during the drone re-flights, the method for rapid RTK deployment by a drone further comprises:
Defining the attenuation distance determined by the previous detection path as an initial distance and the attenuation distance determined by the current detection path as a termination distance;
performing difference calculation according to the initial distance and the termination distance to determine an attenuation deviation distance;
judging whether the attenuation deviation distance is larger than a preset abrupt change distance or not;
if the attenuation deviation distance is not greater than the abrupt change distance, the unmanned aerial vehicle is controlled to continue to move along the moving path;
if the attenuation deviation distance is larger than the abrupt change distance, performing difference calculation according to the attenuation deviation distance and the abrupt change distance to determine an adjustment distance;
determining a correction radian corresponding to the adjustment distance according to a preset correction matching relation;
and moving the rest original detection points on the peripheral outline of the area according to the corrected radian, and generating new detection points according to the preset interval radian.
8. The method of unmanned aerial vehicle rapid deployment of RTKs of claim 7, further comprising a step of determining a spacing arc, the step comprising:
defining a detection point passed by the unmanned aerial vehicle as a finishing point, and defining a detection point not passed by the unmanned aerial vehicle as a point to be detected;
counting and summing according to the finishing points and the points to be detected to determine the total detection quantity;
Determining a detected radian according to the finishing point, and determining a fixed radian according to the detected radian, the adjusting radian and a preset unit radian;
calculating according to the whole circle radian and the fixed radian to determine a variable radian;
calculating according to the fixed radian and the total detection quantity to determine a fixed average radian;
calculating and rounding according to the variable radian and the fixed average radian to determine the number of arc segments;
and calculating according to the variable radian and the number of the arc segments to determine the interval radian.
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