Obstacle avoidance method and system during unmanned aerial vehicle inspection

Abstract

The invention relates to the technical field of obstacle avoidance for unmanned aerial vehicles, and specifically discloses an obstacle avoidance method and system in a process of unmanned aerial vehicle inspection, comprising the following steps: obtaining flight data at a current time s, comparing a flight obstacle distance value at the current time s with a flight target safety value; obtaining a flight target point safety signal; mapping and constructing a target passage coordinate system based on base state safety information, and constructing a safety base state surface domain; obtaining a minimum value of a vertex obstacle distance in a vertex direction of a target safety surface domain range and a minimum value of a midpoint obstacle distance in a midpoint direction of a target safety surface domain range; comparing them with a vertex obstacle safety value and a midpoint obstacle safety value respectively; obtaining a flight path safety signal, and when there is an obstacle in the flight path, the obstacle can be quickly judged on the flight path, so as to achieve early prediction of obstacles on the unmanned aerial vehicle inspection flight path, and avoid collisions between the unmanned aerial vehicles and the unmanned aerial vehicles during flight.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle obstacle avoidance, and in particular to an obstacle avoidance method and system during an unmanned aerial vehicle inspection process. Background Art

[0002] With the development of drone technology, drones are widely used in power line inspections. The main inspection contents of drones include: whether the insulator string has cracks, aging and glaze defects, whether the tower is deformed, rusted and missing, whether there are birds nesting on the tower, etc.

[0003] Drones are combined with AI vision technology to capture a large number of images during drone inspections for technicians to review. When drones perform inspection tasks along the planned routes, they may encounter unexpected threats that were not known in advance, such as static obstacles, including unknown rocks, bird nests, etc.; or dynamic obstacles, such as flying birds, balloons, kites, etc.

[0004] Therefore, during the inspection process, the UAV needs to detect the location of obstacles in real time and predict the obstacles on the flight planning route to ensure safety during the flight. Based on this, we propose an obstacle avoidance method for UAV inspection. Summary of the invention

[0005] The purpose of the present invention is to provide an obstacle avoidance method and system during drone inspection to solve the above-mentioned problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A method and system for avoiding obstacles during drone inspection, comprising the following steps:

[0008] Build a three-dimensional model of the inspection environment based on multi-sensor data, obtain drone point coordinate data, mark the drone point coordinates as (XW, YW, ZW), and update the drone point coordinate data and the three-dimensional status of the inspection environment in real time;

[0009] Take unit time t as the unit to obtain the flight data at the current time s, including the flight speed value FV s and flight space coordinates (XW s , YW s , ZW s ); obtain the flight target data at the next flight time s+1, including the flight target coordinates (XW s+1 , YW s+1 , ZW s+1 );

[0010] The flight status data of the drone at the current time s is obtained by calculation, that is, the flight vector Get the flight obstacle distance value ZA at the current time s s ;

[0011] The flight obstacle distance value ZA at the current time s s and flight target safety value MF s Make comparisons; obtain safety signals of flight target points;

[0012] Based on the safety signal of the flight target point, the base state safety information of the UAV is obtained, wherein the base state safety information refers to the minimum safety area range value that the UAV can safely pass through during flight; the base state safety information includes: the longitudinal safety base state range value SAJ and the lateral safety base state range value HAJ; based on the base state safety information, the target passage coordinate system is mapped and constructed to construct the safety base state surface area;

[0013] Obtain the minimum vertex obstacle distance Dj in the vertex direction of the target safety surface area range and the minimum midpoint obstacle distance Zj in the midpoint direction of the target safety surface area range;

[0014] The minimum vertex obstacle distance Dj is compared with the vertex obstacle safety value DSA; at the same time, the minimum midpoint obstacle distance Zj is compared with the midpoint obstacle safety value ZSA; and a flight path safety signal is obtained.

[0015] As a further solution of the present invention: the flight obstacle distance value ZA at the current time s is s and flight target safety value MF s Make comparisons;

[0016] If the flight obstacle distance value ZA at the current time s s Greater than the flight target safety value MF s , generate a flight target point safety signal;

[0017] If the flight obstacle distance value ZA at the current time s s Less than or equal to the flight target safety value MF s , generate target point obstacle signal.

[0018] As a further solution of the present invention: the target passing coordinate system is constructed as follows:

[0019] The flight target coordinates at the current flight time s are taken as the coordinate origin, and the flight vector The direction is the vertical coordinate Z axis; further, the plane perpendicular to the vertical coordinate Y axis where the origin of the flight target coordinate is located is the coordinate plane formed by the X axis and the Y axis.

[0020] As a further solution of the present invention: the vertex obstacle distance values ​​in the vertex direction of the target safety surface range are measured in sequence by an infrared range finder, and are marked as DJJ A 、DJJ B 、DJJ C 、DJJ D ;

[0021] Among them, the minimum vertex obstacle distance Dj = min{DJJ A , DJJ B , DJJ C , DJJ D}.

[0022] As a further solution of the present invention: the midpoint obstacle distance values ​​in the midpoint direction of the target safety surface range are measured in sequence by an infrared rangefinder, and are marked as ZJJ respectively. a 、ZJJ b 、ZJJ c 、ZJJ d ;

[0023] Among them, the minimum value of the midpoint obstacle distance Zj=min{ZJJ a , ZJJ b , ZJJ c , ZJJ d}.

[0024] As a further solution of the present invention: the minimum vertex obstacle distance Dj is compared with the vertex obstacle safety value DSA; at the same time, the minimum midpoint obstacle distance Zj is compared with the midpoint obstacle safety value ZSA:

[0025] If the minimum vertex obstacle distance Dj is greater than the vertex obstacle safety value DSA, and the minimum midpoint obstacle distance Zj is greater than the midpoint obstacle safety value ZSA, a flight path safety signal is generated;

[0026] Otherwise, a flight path obstruction signal is generated.

[0027] As a further solution of the present invention: the calculation method of the midpoint obstacle safety value ZSA and the vertex obstacle safety value DSA is:

[0028] Compare the longitudinal safety base state range value SAJ and the lateral safety base state range value HAJ, and select the extreme value AJ of the safety base state range value.

[0029] As a further solution of the present invention: an obstacle avoidance system during an unmanned aerial vehicle inspection process, comprising:

[0030] Data acquisition module: Build a three-dimensional model of the inspection environment based on multi-sensor data, obtain drone point coordinate data, mark the drone point coordinates as (XW, YW, ZW), and update the drone point coordinate data and the three-dimensional status of the inspection environment in real time;

[0031] Take unit time t as the unit to obtain the flight data at the current time s, including the flight speed value FV s and flight space coordinates (XW s , YW s , ZW s ); obtain the flight target data at the next flight time s+1, including the flight target coordinates (XW s+1 , YW s+1 , ZW s+1 );

[0032] Data calculation module: obtains the flight status data of the drone at the current time s by calculation, that is, the flight vector Get the flight obstacle distance value ZA at the current time s s ;

[0033] The flight obstacle distance value ZA at the current time s s and flight target safety value MF s Make comparisons; obtain safety signals of flight target points;

[0034] Model construction module: Based on the safety signal of the flight target point, the base state safety information of the UAV is obtained, where the base state safety information refers to the minimum safety area range value that the UAV can safely pass through during flight; the base state safety information includes: longitudinal safety base state range value SAJ and lateral safety base state range value HAJ; based on the base state safety information, the target passage coordinate system is mapped and constructed to construct the safety base state domain;

[0035] State calculation module: obtain the minimum value Dj of the vertex obstacle distance in the vertex direction of the target safety surface area range and the minimum value Zj of the midpoint obstacle distance in the midpoint direction of the target safety surface area range;

[0036] Signal generation module: compare the minimum vertex obstacle distance Dj with the vertex obstacle safety value DSA; at the same time, compare the minimum midpoint obstacle distance Zj with the midpoint obstacle safety value ZSA; obtain the flight path safety signal.

[0037] Beneficial effects of the present invention:

[0038] In the present invention, by constructing a three-dimensional model of the inspection environment and the coordinate data of the drone, the current flight status data of the drone is judged, and it is judged whether there are obstacles at the target point of the drone at the next inspection moment. During the inspection process, it is possible to wait or re-plan the flight path based on the inspection obstacles. At the same time, during the drone inspection flight, the obstacles within the maximum range of the flight path at the next inspection flight moment are judged. When there are obstacles in the flight path, the flight path can be quickly judged for obstacles, and the flight attitude or flight inspection path can be adjusted in time based on the flight path obstacle signal to avoid unexpected situations such as drone collisions. This can achieve early prediction of obstacles in the drone inspection flight path to avoid collisions between drones during flight. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention will be further described below in conjunction with the accompanying drawings.

[0040] Figure 1 It is a schematic flow chart of the method of the present invention;

[0041] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0042] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] See also Figure 1 As shown, the present invention is a method for avoiding obstacles during an unmanned aerial vehicle inspection process, comprising the following steps:

[0044] Step 1: Build a three-dimensional model of the inspection environment based on multi-sensor data, obtain the drone point coordinate data, mark the drone point coordinates as (XW, YW, ZW), and update the drone point coordinate data and the three-dimensional status of the inspection environment in real time;

[0045] Take unit time t as the unit to obtain the flight data at the current time s, including the flight speed value FV s and flight space coordinates (XW s , YW s , ZW s );

[0046] Get the flight target data at the next flight time s+1, including the flight target coordinates (XW s+1 , YW s+1 , ZWs+1 );

[0047] Step 2: Pass Calculate the flight status data of the drone at the current time s, that is, the flight vector

[0048] Based on flight vector And the flight speed value FV s ,pass Calculate the flight target safety value MF s ; Where a is the flight target distance coefficient, and b is the flight safety factor;

[0049] The flight target safety value refers to the flight target point at the next flight unit time t and the current flight speed of the drone during the flight process. If an obstacle appears, the required avoidance distance is calculated. When the drone is in the current flight state, it can effectively ensure the safety and stability of the drone's flight state;

[0050] Based on the flight status data of the drone at the current time s, adjust the infrared rangefinder's ranging direction to the same direction as the flight direction, i.e., the flight vector, to measure obstacles; obtain the flight obstacle distance value ZA at the current time s s ;

[0051] Then, the flight obstacle distance value ZA at the current time s is s and flight target safety value MF s Make comparisons;

[0052] If the flight obstacle distance value ZA at the current time s s Greater than the flight target safety value MF s , generating a flight target point safety signal; at this time, it means that there is no direct obstacle at the flight target point of the UAV within the next flight time t;

[0053] If the flight obstacle distance value ZA at the current time s s Less than or equal to the flight target safety value MF s , generating a target point obstacle signal; that is, indicating that an obstacle appears in the flight path within the next flight time t. The obstacle may be a mobile obstacle or a fixed obstacle. At this time, it is necessary to control the drone to adjust the flight path or keep the drone in a hovering state;

[0054] For example, in some embodiments, when the obstacle does not exist in the constructed three-dimensional model of the inspection environment, it means that the obstacle may be a mobile obstacle. At this time, the drone can be kept in a hovering state; further, when the drone is in a hovering state for more than a preset hovering time value, at this time, the flight path of the drone can be adjusted so that the drone flies along a new flight inspection path;

[0055] Step 3: Based on the safety signal of the flight target point, the base state safety information of the UAV is obtained, wherein the base state safety information refers to the minimum safety area range value that the UAV can safely pass through during flight; for example, when the UAV passes through a hole, the minimum cross-sectional area value of the hole; the base state safety information includes: the longitudinal safety base state range value SAJ and the lateral safety base state range value HAJ;

[0056] Based on the base state safety information, the target passage coordinate system is mapped and constructed to construct the safety base state domain;

[0057] Specifically, the target transit coordinate system is constructed as follows:

[0058] The flight target coordinates at the current flight time s are taken as the coordinate origin, and the flight vector The direction of is the vertical coordinate Z axis; further, the plane perpendicular to the vertical coordinate Y axis where the origin of the flight target coordinate is located is the coordinate plane formed by the X axis and the Y axis;

[0059] The method of constructing the safety base state domain is:

[0060] Update the flight target coordinates to Based on the longitudinal safety base state range value SAJ and the lateral safety base state range value HAJ;

[0061] Construct the coordinate set {A, B, C, D} of the vertices of the target safety surface range and the coordinate set {a, b, c, d} of the midpoint of the target safety surface range at the next flight time s+1;

[0062] Among them, the coordinates of the four points A, B, C, and D in the coordinate set of the vertices of the target safety surface range are

[0063] The coordinates of the four points a, b, c, and d in the coordinate set of the midpoint of the target safety surface area are

[0064] Step 4: First, use the infrared rangefinder to measure the vertex obstacle distance values ​​in the vertex direction of the target safety surface range in sequence, and mark them as DJJ A 、DJJ B 、DJJ C 、DJJD ;

[0065] Get the minimum value of the vertex obstacle distance value set in the vertex direction of the target safety surface range, recorded as the minimum vertex obstacle distance value Dj; where Dj = min{Dj A , DJJ B , DJJ C , DJJ D};

[0066] Then, the infrared rangefinder is used to measure the midpoint obstacle distance values ​​in the midpoint direction of the target safety surface range in turn, and they are marked as ZJJ respectively. a 、ZJJ b 、ZJJ c 、ZJJ d ;

[0067] Get the minimum value of the midpoint obstacle distance value set in the midpoint direction of the target safety surface range, recorded as the minimum midpoint obstacle distance value Zj; where Zj = min{ZJJ a , ZJJ b , ZJJ c , ZJJ d};

[0068] Step 5: Compare the minimum vertex obstacle distance Dj with the vertex obstacle safety value DSA; at the same time, compare the minimum midpoint obstacle distance Zj with the midpoint obstacle safety value ZSA;

[0069] If the minimum vertex obstacle distance Dj is greater than the vertex obstacle safety value DSA, and the minimum midpoint obstacle distance Zj is greater than the midpoint obstacle safety value ZSA, a flight path safety signal is generated; at this time, the drone can continue to perform flight inspections according to the flight path;

[0070] Otherwise, a flight path obstacle signal is generated, which indicates that there is an obstacle on the flight path of the drone when it is flying to the flight target coordinate point at the next flight time; the flight path of the drone needs to be adjusted so that the drone can fly along a new flight inspection path;

[0071] The calculation method of the midpoint obstacle safety value ZSA and the vertex obstacle safety value DSA is:

[0072] Compare the longitudinal safety base state range value SAJ and the lateral safety base state range value HAJ, and select the extreme value AJ of the safety base state range value, where AJ = max{SAJ, HAJ};

[0073] pass Calculate and obtain the midpoint obstacle safety value ZSA;

[0074] Then through Calculate and obtain the vertex barrier safety value DSA.

[0075] By constructing a three-dimensional model of the inspection environment and the coordinate data of the UAV, the current flight status data of the UAV is judged, and it is determined whether there are obstacles at the target point of the UAV at the next inspection time. During the inspection process, it is possible to wait or re-plan the flight path based on the inspection obstacles. At the same time, during the inspection flight of the UAV, the obstacles within the maximum range of the flight path at the next inspection flight time are judged. When there are obstacles in the flight path, the obstacle can be quickly judged on the flight path, and the flight attitude or flight inspection path can be adjusted in time based on the flight path obstacle signal to avoid unexpected situations such as UAV collisions. This can achieve early prediction of obstacles in the UAV inspection flight path to avoid collisions of UAVs during flight.

[0076] Embodiment 2

[0077] Reference Figure 2 As shown, an obstacle avoidance system for a drone inspection process includes:

[0078] Data acquisition module: Build a three-dimensional model of the inspection environment based on multi-sensor data, obtain drone point coordinate data, mark the drone point coordinates as (XW, YW, ZW), and update the drone point coordinate data and the three-dimensional status of the inspection environment in real time;

[0079] Take unit time t as the unit to obtain the flight data at the current time s, including the flight speed value FV s and flight space coordinates (XW s , YW s , ZW s ); obtain the flight target data at the next flight time s+1, including the flight target coordinates (XW s+1 , YW s+1 , ZW s+1 );

[0080] Data calculation module: through Calculate the flight status data of the drone at the current time s, that is, the flight vector Get the flight obstacle distance value ZA at the current time s s ;

[0081] The flight obstacle distance value ZA at the current time s s and flight target safety value MF s Make comparisons; obtain safety signals of flight target points;

[0082] Model construction module: Based on the safety signal of the flight target point, the base state safety information of the UAV is obtained, where the base state safety information refers to the minimum safety area range value that the UAV can safely pass through during flight; the base state safety information includes: longitudinal safety base state range value SAJ and lateral safety base state range value HAJ; based on the base state safety information, the target passage coordinate system is mapped and constructed to construct the safety base state domain;

[0083] State calculation module: obtain the minimum value Dj of the vertex obstacle distance in the vertex direction of the target safety surface area range and the minimum value Zj of the midpoint obstacle distance in the midpoint direction of the target safety surface area range;

[0084] Signal generation module: compare the minimum vertex obstacle distance Dj with the vertex obstacle safety value DSA; at the same time, compare the minimum midpoint obstacle distance Zj with the midpoint obstacle safety value ZSA; obtain the flight path safety signal.

[0085] It can quickly judge obstacles on the flight path and adjust the flight attitude or flight inspection path in time based on the flight path obstacle signal to avoid unexpected situations such as drone collisions. It can predict obstacles on the drone inspection flight path in advance to avoid collisions between drones during flight.

[0086] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. An obstacle avoidance method during drone inspection, characterized in that: The following steps are involved: Build a three-dimensional model of the inspection environment based on multi-sensor data, obtain drone point coordinate data, mark the drone point coordinates as (XW, YW, ZW), and update the drone point coordinate data and the three-dimensional status of the inspection environment in real time; Take unit time t as the unit to obtain the flight data at the current time s, including the flight speed value FV s and flight space coordinates (XW s , YW s , ZW s ); Get the flight target data at the next flight time s+1, including the flight target coordinates (XW s+1 , YW s+1 , ZW s+1 ); The flight status data of the drone at the current time s is obtained by calculation, that is, the flight vector ; Get the flight obstacle distance value ZA at the current time s s ; The flight obstacle distance value ZA at the current time s s and flight target safety value MF s Make comparisons; obtain safety signals of flight target points; Based on the safety signal of the flight target point, the base state safety information of the UAV is obtained, wherein the base state safety information refers to the minimum safety area range value that the UAV can safely pass through during flight; the base state safety information includes: the longitudinal safety base state range value SAJ and the lateral safety base state range value HAJ; based on the base state safety information, the target passage coordinate system is mapped and constructed to construct the safety base state surface area; Obtain the minimum value Dj of the vertex obstacle distance in the vertex direction of the target safety surface area range and the minimum value Zj of the midpoint obstacle distance in the midpoint direction of the target safety surface area range; Compare the minimum vertex obstacle distance Dj with the vertex obstacle safety value DSA; at the same time, compare the minimum midpoint obstacle distance Zj with the midpoint obstacle safety value ZSA; if the minimum vertex obstacle distance Dj is greater than the vertex obstacle safety value DSA, and the minimum midpoint obstacle distance Zj is greater than the midpoint obstacle safety value ZSA, a flight path safety signal is obtained.

2. The obstacle avoidance method during drone inspection according to claim 1 is characterized in that: The flight obstacle distance value ZA at the current time s s and flight target safety value MF s Make comparisons; If the flight obstacle distance value ZA at the current time s s Greater than the flight target safety value MF s , generate a flight target point safety signal; If the flight obstacle distance value ZA at the current time s s Less than or equal to the flight target safety value MF s , generate target point obstacle signal.

3. The obstacle avoidance method during drone inspection according to claim 1 is characterized in that: The target transit coordinate system is constructed as follows: The flight target coordinates at the current time s are taken as the coordinate origin, and the flight vector The direction is the vertical coordinate Z axis; the plane perpendicular to the vertical coordinate Z axis where the coordinate origin is located is the coordinate plane formed by the X-axis and the Y-axis.

4. The obstacle avoidance method during drone inspection according to claim 1 is characterized in that: The vertex obstacle distance values ​​in the vertex direction of the target safety surface range are measured in sequence by an infrared rangefinder and marked as DJJ A 、DJJ B 、DJJ C 、DJJ D ; Among them, the minimum vertex obstacle distance .

5. The obstacle avoidance method during drone inspection according to claim 1, characterized in that: The midpoint obstacle distance values ​​in the midpoint direction of the target safety surface range are measured in sequence by an infrared rangefinder and marked as ZJJ a 、ZJJ b 、ZJJ c 、ZJJ d ; Among them, the minimum value of the midpoint obstacle distance .

6. The obstacle avoidance method during drone inspection according to claim 1, characterized in that: The calculation method of the midpoint obstacle safety value ZSA and the vertex obstacle safety value DSA is: Compare the longitudinal safety base state range value SAJ and the lateral safety base state range value HAJ, and select the extreme value AJ of the safety base state range value.

7. An obstacle avoidance system during drone inspection, characterized in that: The system is used to execute the obstacle avoidance method as described in any one of claims 1 to 6, comprising: Data acquisition module: Build a three-dimensional model of the inspection environment based on multi-sensor data, obtain drone point coordinate data, mark the drone point coordinates as (XW, YW, ZW), and update the drone point coordinate data and the three-dimensional status of the inspection environment in real time; Take unit time t as the unit to obtain the flight data at the current time s, including the flight speed value FV s and flight space coordinates (XW s , YW s , ZW s ); Get the flight target data at the next flight time s+1, including the flight target coordinates (XW s+1 , YW s+1 , ZW s+1 ); Data calculation module: obtains the flight status data of the drone at the current time s by calculation, that is, the flight vector ; Get the flight obstacle distance value ZA at the current time s s ; The flight obstacle distance value ZA at the current time s s and flight target safety value MF s Make comparisons; obtain safety signals of flight target points; Model construction module: Based on the safety signal of the flight target point, the base state safety information of the UAV is obtained, where the base state safety information refers to the minimum safety area range value that the UAV can safely pass through during flight; the base state safety information includes: longitudinal safety base state range value SAJ and lateral safety base state range value HAJ; based on the base state safety information, the target passage coordinate system is mapped and constructed to construct the safety base state domain; State calculation module: obtain the minimum value Dj of the vertex obstacle distance in the vertex direction of the target safety surface area range and the minimum value Zj of the midpoint obstacle distance in the midpoint direction of the target safety surface area range; Signal generation module: compare the minimum vertex obstacle distance Dj with the vertex obstacle safety value DSA; at the same time, compare the minimum midpoint obstacle distance Zj with the midpoint obstacle safety value ZSA; if the minimum vertex obstacle distance Dj is greater than the vertex obstacle safety value DSA, and the minimum midpoint obstacle distance Zj is greater than the midpoint obstacle safety value ZSA, a flight path safety signal is obtained.

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