CN114519472B - Emergency management monitoring method based on three-dimensional model - Google Patents
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Abstract
The invention discloses an emergency management monitoring method based on a three-dimensional model, and belongs to the technical field of unmanned aerial vehicle monitoring. It is through surveying the quick positioning danger source of unmanned aerial vehicle and assay out danger area, rescue area and safe region to set up and build the picture and keep away the artifical potential field algorithm behind the barrier module and the supplementary potential field of introduction, generate best three-dimensional emergency rescue route, reduced unmanned aerial vehicle's unnecessary and lost, help improving rescue personnel's search and rescue efficiency simultaneously, thereby can prevent to cause personnel to be meaningless casualties when rescue personnel clear away the danger source.
Description
Technical Field
The invention relates to an emergency management monitoring method based on a three-dimensional model, and belongs to the technical field of unmanned aerial vehicle monitoring.
Background
The pilotless plane is called unmanned plane for short, and is a pilotless plane controlled by radio remote control equipment and a self-contained program control device.
Various danger sources are piled in a chemical plant, the case of explosion of the chemical plant happens frequently, and the situation that the internal situation of the chemical plant cannot be understood usually causes the meaningless casualties of personnel and the heavy loss of trapped personnel and property when rescue workers remove the danger sources. Unmanned aerial vehicle installs equipment such as autopilot, program control device, has replaced personnel to get into the disaster scene, knows the inside condition, provides important information support for seeking help. However, the existing unmanned aerial vehicle is not positioned timely, has low accuracy, is damaged in emergency rescue at a disaster site, and cannot play an important role in the emergency rescue.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides an emergency management monitoring method based on a three-dimensional model, so that a danger source is quickly positioned, a rescue route is generated, and meanwhile, unnecessary breakage of an unmanned aerial vehicle is reduced.
The technical scheme of the invention is as follows:
the invention provides an emergency management monitoring method based on a three-dimensional model, which specifically comprises the following steps:
step S1: preparing an emergency management monitoring system, wherein the emergency management monitoring system comprises a control console and a detection unmanned aerial vehicle, the detection unmanned aerial vehicle is provided with a central control module, a charging module, a navigation map building and obstacle avoiding module, a wireless transmission module, a gas sensor and an infrared camera, and the infrared camera, the gas sensor, the navigation map building and obstacle avoiding module, the wireless transmission module and the charging module are respectively and electrically connected with the central control module;
the navigation map building and obstacle avoiding module detects obstacles appearing on a disaster site, when an infrared camera scans an object obstructing a cruising route, the object is marked as the obstacle, and obstacle avoiding processing is carried out at the first time;
the central control module comprises an analysis unit, a storage unit and a transmission unit, wherein the analysis unit uses the temperature T1 measured by the infrared camera, the concentration w1 measured by the gas sensor, and the temperature threshold T0 and the gas concentration threshold w0 stored by the storage unit as input information of the console, judges whether the site belongs to a dangerous area, a rescue area or a slight dangerous area, and transmits the judgment result to the transmission unit, the transmission unit is connected with the wireless transmission module in a wired manner, and the input video information of the infrared camera and the judgment result output by the central control module are transmitted to the wireless transmission module;
the detection unmanned aerial vehicle is in information communication with the console through the wireless transmission module;
step S2: the control console comprises a three-dimensional live-action modeling software management layer and a three-dimensional live-action modeling software engine layer, a model building task is carried out, the building task comprises aerial triangulation and model three-dimensional reconstruction, the aerial triangulation is in stereo photogrammetry, a group of digital photos shot from different angles to a target chemical plant are input into the three-dimensional live-action modeling software management layer as input data sources, auxiliary data are input simultaneously, the auxiliary data comprise the attribute of a camera, the position of the photo, the angle of a rotating photo, a control point, a dangerous temperature threshold value and a gas concentration threshold value, a small number of field control points in the digital photos are encrypted through the control console indoors, the height and plane positions of the encrypted points are obtained, and the control point 23 is a position required to be reached by traversing the task;
step S3: the three-dimensional live-action modeling software management layer decomposes a construction task into basic operation and submits the basic operation to the three-dimensional live-action modeling software engine layer, the three-dimensional live-action modeling software engine layer processes the basic operation to construct a model, an emergency management monitoring model generated by the three-dimensional live-action modeling software engine layer is fed back to the three-dimensional live-action modeling software management layer, and then the three-dimensional live-action modeling software management layer derives a high-resolution emergency monitoring management model with real texture to complete a visual emergency management monitoring model;
step S4: the detection unmanned aerial vehicle adopts an obstacle avoidance and mapping algorithm to conduct autonomous navigation and obstacle avoidance; the infrared camera and the gas sensor collect information and synchronously transmit the collected information to the analysis unit;
step S5: evaluating the emergency management monitoring model, dividing the emergency management monitoring model into a dangerous area, a rescue area and a slight dangerous area, marking the rescue area and generating a rescue route;
step S6: obtaining an optimal three-dimensional emergency rescue path by introducing an artificial potential field algorithm of the auxiliary potential field of the dangerous area;
step S7: the console demonstrates the source of danger and the optimal rescue route in the building through animation.
Further, in step S4, the obstacle avoidance mapping algorithm is an algorithm that integrates a feature method and a direct method, and three threads are established for real-time tracking of the unmanned aerial vehicle, mapping of the emergency management monitoring system, and closed-loop detection, specifically:
step S41: detecting unmanned aerial vehicle pose initialization: when the unmanned aerial vehicle is detected to be started, taking a first frame image shot by an infrared camera as a key frame, and establishing an initialization map by taking the current three-dimensional coordinate as a base point;
step S42: the detection unmanned aerial vehicle executes real-time tracking and emergency management monitoring system mapping, calculates the corresponding relation between the initial pose shot by the infrared camera and the pixel points by minimizing luminosity errors, optimizes the pose of the infrared camera again by utilizing the reprojection errors of the minimized local map points, and tracks the local map; if the tracking fails, triggering a new tracking period;
the infrared camera shoots a current frame, and if the current frame is different from a previous frame, the current frame is judged as a key frame; if no difference exists, judging the current frame as a non-key frame; in a local mapping thread, ORB characteristics in a current key frame image are extracted and matched, then redundant map points in a current key frame are screened out, new map points are created according to the result of characteristic extraction and matching, and the ORB characteristics are the characteristics based on the combination of characteristic points of an accelerated segmentation test and a binary robust independent basic characteristic descriptor;
and after all key frames are processed, local BA optimization is executed, the poses of the surrounding key frames and the positions of map points are optimized to obtain more accurate positioning and mapping precision, and finally candidate key frames are screened and redundant key frames are removed.
Step S43: detecting an unmanned aerial vehicle to carry out closed-loop detection:
in the closed-loop detection thread, closed-loop detection is executed by retrieving the image recognition database, when a closed loop is detected, the closed-loop period is judged, if the current key frame and the closed-loop key frame do not belong to the same period, the period of the closed-loop key frame and the period of the current key frame are combined into the same period, and finally, global BA optimization is executed by taking all key frame positions and all map point positions in the period as optimization variables, so that an environment map and a camera motion track which are globally consistent are obtained.
Further, well accuse module and navigation are built the picture and are kept away barrier module fixed mounting in the top of surveying unmanned aerial vehicle's frame, the parallel fixed mounting of infrared camera and gas sensor is in the below of surveying unmanned aerial vehicle's frame, the module fixed mounting that charges is in a side of surveying unmanned aerial vehicle's frame.
Furthermore, the charging module comprises a short circuit unit and an overload unit, and the short circuit unit is used for providing short circuit protection for the charging module in the process of charging the detection unmanned aerial vehicle; the overload unit is used for the module of charging to provide overload protection in charging for surveying unmanned aerial vehicle.
Further, still include high temperature resistant protection film, high temperature resistant protection film parcel survey the last well accuse module, the module of charging, the navigation of carrying on of unmanned aerial vehicle and build the picture and keep away barrier module, wireless transmission module, gas sensor, infrared camera, only expose gas sensor's air vent, infrared camera's lens hole and the mouth that charges of the module of charging.
Further, the gas sensor includes a carbon monoxide sensor.
Further, the control points are areas for storing dangerous goods, areas for storing valuable goods, areas for storing important data and areas with a large crowd gathering.
Further, the control point includes a disaster site entrance and a disaster site exit.
Further, the console is a computer or a tablet computer.
Further, in step S6, the artificial potential field algorithm for the auxiliary potential field in the hazardous area refers to a potential field in which three forces exist at the disaster site: detecting a gravitational potential field of the unmanned aerial vehicle pointing to a rescue area, a repulsive potential field of a dangerous area and an auxiliary potential field of the dangerous area, wherein the gravitational potential field is reduced along with the reduction of the distance between the rescue area and the unmanned aerial vehicle; the repulsion force of the dangerous area pointing to the detecting unmanned aerial vehicle is increased along with the reduction of the distance between the detecting unmanned aerial vehicle and the dangerous area; the auxiliary potential field of the danger area is related to the speed of the danger area and the relative angle between the detection unmanned aerial vehicle and the danger area, the attraction potential field of the rescue area, the repulsion potential field of the danger area and the auxiliary potential field of the danger area are combined, the movement of the detection unmanned aerial vehicle is controlled by the superposed resultant force of the three potential fields of the attraction field, the repulsion field and the auxiliary potential field of the danger area, so that the danger area is avoided, and path planning is completed, specifically:
the function of the gravitational potential field of the rescue area is
Wherein, the first and the second end of the pipe are connected with each other,
is gravitational potential energy;
is a gravity gain factor;
detecting the Euclidean distance between the unmanned aerial vehicle and a dangerous area;
the repulsive potential field of the danger zone and the speed of the danger zone
Function of (2)
：
The danger zone repulsive potential field function is:
wherein the content of the first and second substances,
the parameters are adjusted for the danger zone repulsive potential field gain,
is the distance of the robot from the hazardous area,
the influence range of the repulsive potential field of the danger area is defined;
and finally, constructing the auxiliary potential field function of the dangerous area as follows:
wherein, the first and the second end of the pipe are connected with each other,
it is an auxiliary potential field random gain adjustment function;
is gain adjustment coefficient of 0 ≦
1 or less is a random number;
for the potential field to convert the angle matrix,
the rotation angle is related to the relative angle between the unmanned aerial vehicle and the dangerous area and the speed of the dangerous area;
thus detecting the resultant force experienced by the drone
The following:
detecting resultant force borne by the unmanned aerial vehicle
Gravity potential field from rescue area
And repulsive force potential field of dangerous area
And auxiliary potential field of dangerous area
The direction of the negative gradient of the resultant potential field of the composition is calculated.
Advantageous effects
According to the emergency management monitoring method based on the three-dimensional model, disclosed by the invention, the unmanned aerial vehicle is detected to quickly position the hazard source, the danger area, the rescue area and the safe area are analyzed, the navigation map building and obstacle avoiding module is arranged, and the artificial potential field algorithm after the auxiliary potential field is introduced is arranged, so that the optimal three-dimensional emergency rescue path is generated, the unnecessary breakage of the unmanned aerial vehicle is reduced, the search and rescue efficiency of rescuers is improved, and the condition that the rescuers do not have casualties when the hazard source is removed can be prevented.
Drawings
FIG. 1 is a schematic flow chart of an emergency management monitoring method based on a three-dimensional model according to the present invention;
FIG. 2 is a schematic diagram of the operation of the emergency management monitoring system based on the three-dimensional model according to the present invention;
FIG. 3 is a structural diagram of a reconnaissance unmanned aerial vehicle for emergency management monitoring based on a three-dimensional model according to the present invention;
fig. 4 is a structural diagram of an obstacle avoidance and mapping algorithm system for detecting an unmanned aerial vehicle, which integrates a feature method and a direct method;
FIG. 5 is a flow chart of an obstacle avoidance and mapping algorithm for detecting an unmanned aerial vehicle, which combines a feature method and a direct method;
FIG. 6 is a flow chart of an artificial potential field algorithm after introduction of an auxiliary potential field;
wherein, survey unmanned aerial vehicle 10
Central control module 11
Navigation map building and obstacle avoidance module 13
Disaster site portal 22
A disaster site exit 28.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that, in the present application, the embodiments and features of the embodiments may be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
The invention relates to an emergency management monitoring method based on a three-dimensional model, which specifically comprises the following steps as shown in figure 1:
step S1: prepare emergency management monitoring system, as shown in fig. 3, emergency management monitoring system includes the control cabinet and surveys unmanned aerial vehicle 10, surveys unmanned aerial vehicle 10 and is the little miniature unmanned vehicles of many rotor formulas, indicates with four rotor unmanned vehicles in fig. 3.
Survey unmanned aerial vehicle 10 and go up through frame carry-on central control module 11, the module of charging 19 and the navigation is built the picture and is kept away barrier module 13, wireless transmission module 18, gas sensor 15, infrared camera 17. The frame is the metal frame and the support plate of surveying on the unmanned aerial vehicle 10 for fixed small-size equipment or spare part. Central control module 11 and navigation are built the picture and are kept away barrier module 13 fixed mounting and be in the top of surveying the frame of unmanned aerial vehicle 10, infrared camera 17 and gas sensor 15 parallel fixed mounting are in the below of surveying the frame of unmanned aerial vehicle 10, and infrared camera 17 is used for detecting temperature and on-the-spot condition, surveys on-the-spot real-time temperature T1 and video information.
The charging module 19 is fixedly installed on one side of the frame of the unmanned aerial vehicle 10. The gas sensor 15 is generally a carbon monoxide sensor, but it is needless to say that a gas sensor for detecting sulfur, nitrogen, or the like may be used as the actual condition to measure the gas concentration w 1.
The infrared camera 17, the gas sensor 15, the navigation map building obstacle avoidance module 13, the wireless transmission module 18 and the charging module 19 are electrically connected with the central control module 11 respectively. The charging module comprises a short circuit unit and an overload unit, and the short circuit unit is used for providing short circuit protection for the charging module 19 in the process of charging the unmanned aerial vehicle 10; the overload unit is used for the charging module 19 to provide overload protection in charging the detecting drone 10.
Adopt high temperature resistant protection film parcel survey central control module 11, the module of charging 19, the navigation of carrying on unmanned aerial vehicle 10 and build the picture and keep away barrier module 13, wireless transmission module 18, gas sensor 15, infrared camera 17, only expose gas sensor 15's air vent, infrared camera 17's lens hole and the mouth that charges of the module of charging 19, not shown in fig. 3. Generally, the high-temperature resistant protective film adopts alumina fiber which is polycrystal inorganic fiber with the main component of alumina, is white, smooth, soft and elastic, is like absorbent cotton, integrates the characteristics of crystal materials and fiber materials, has the service temperature of 1450-1600 ℃, the melting point of 1840 ℃, better heat-resistant stability, the heat conductivity of 1/6 which is common refractory brick, the volume weight of 1/25 and the energy-saving rate of 15-45 percent. The high-temperature-resistant protective film wraps the central control module 11, the charging module 19, the navigation map building and obstacle avoiding module 13, the wireless transmission module 18, the gas sensor 15 and the infrared camera 17 which are carried on the unmanned detection vehicle 10, and only exposes the vent hole of the gas sensor 15, the lens hole of the infrared camera 17 and the charging port of the charging module 19.
The navigation, map building and obstacle avoidance module 13 detects an obstacle 24 appearing in a disaster site, when the infrared camera 17 scans an object on a route obstructing the cruising, the object is marked as the obstacle 24, and obstacle avoidance processing is performed at the first time, so that the effect of detecting the traversing danger source of the unmanned aerial vehicle 10 can be improved, and the speed of traversing the danger source is improved.
The central control module 11 comprises an analysis unit, a storage unit and a transmission unit, wherein the analysis unit uses the field real-time temperature T1 measured by the infrared camera 17, the concentration w1 measured by the gas sensor 15 and the temperature threshold T and the gas concentration threshold w0 stored in the storage unit as input information of a console to judge whether the field belongs to a dangerous area, a rescue area or a slight dangerous area, and transmits the judgment result to the transmission unit, the transmission unit is in wired connection with the wireless transmission module 18, inputs the video information of the infrared camera 17 and the judgment result output by the central control module 11, and transmits the video information and the judgment result to the wireless transmission module 18;
the detection unmanned aerial vehicle 10 is in information communication with the console through the wireless transmission module 18;
step S2: the control console is an intelligent electronic product such as a computer or a tablet personal computer and the like, smart 3d software is installed on the control console, the software comprises a three-dimensional live-action modeling software management layer and a three-dimensional live-action modeling software engine layer, a model building task is carried out, the building task comprises aerial triangulation and model three-dimensional reconstruction, the aerial triangulation is in stereo photogrammetry, a group of digital photos taken from different angles of a target chemical plant are input into the three-dimensional live-action modeling software management layer as input data sources, and auxiliary data are input simultaneously, the auxiliary data comprise the attribute of a camera, the position of the photo, the angle of a rotating photo, a control point 23, a dangerous temperature threshold value and a gas concentration threshold value, a small number of field control points in the digital photos are encrypted through the control console indoors, and the measurement method of the elevation and the plane position of an encryption point is obtained, the control point 23 is a position to which the traversal task needs to reach, such as an area for storing dangerous goods, an area for storing valuable goods, an area for storing important data, an area with a large crowd gathering, and the like. Control point 23 also includes disaster site entry 22 and disaster site exit 28, as shown in fig. 2.
Step S3: the three-dimensional live-action modeling software management layer decomposes a construction task into basic operation and submits the basic operation to a three-dimensional live-action modeling software engine layer, the three-dimensional live-action modeling software engine layer processes the basic operation to construct a model, an emergency management monitoring model generated by the three-dimensional live-action modeling software engine layer is fed back to the three-dimensional live-action modeling software management layer, and then the three-dimensional live-action modeling software management layer derives a high-resolution emergency monitoring management model with real texture to complete a visual emergency management monitoring model;
step S4: the unmanned detection vehicle 10 performs autonomous navigation and obstacle avoidance by adopting an obstacle avoidance and mapping algorithm; the infrared camera 17 and the gas sensor 15 collect information and synchronously transmit the collected information to the analysis unit; the flying height of the detection unmanned aerial vehicle 10 is set to be 2-3m, the safe flying temperature is 400 ℃, when the temperature of the dangerous source is higher than 400 ℃, the detection unmanned aerial vehicle 10 transfers the flying to the next dangerous source, so that the detection unmanned aerial vehicle 10 can be protected, and on the other hand, because the dangerous source is not necessary for rescue, the time can be saved for protecting the next dangerous source, and the protection efficiency is improved. The obstacle avoidance mapping algorithm is an algorithm integrating a feature method and a direct method, three threads are established, and the three threads are respectively used for detecting real-time tracking of the unmanned aerial vehicle 10, mapping of an emergency management monitoring system and closed-loop detection, and as shown in fig. 5, the method specifically comprises the following steps:
step S41: and (3) detecting initialization of the pose of the unmanned aerial vehicle 10: when the unmanned aerial vehicle 10 is detected to be started, taking a first frame image shot by the infrared camera 17 as a key frame, and taking the current three-dimensional coordinate as a base point to create an initialization map;
step S42: the detection unmanned aerial vehicle 10 executes real-time tracking and emergency management monitoring system mapping, the detection unmanned aerial vehicle 10 calculates the corresponding relation between the initial pose shot by the infrared camera 17 and the pixel points by minimizing photometric errors, and then optimizes the pose of the infrared camera 17 again by utilizing the reprojection errors of the minimized local map points to track the local map; if the tracking fails, triggering a new tracking period;
as shown in fig. 4, a current frame is shot by an infrared camera 17, and if the current frame is different from a previous frame, the current frame is determined as a key frame; if no difference exists, judging the current frame as a non-key frame; in a local mapping thread, ORB features in a current key frame image are extracted and matched, then redundant map points in a current key frame are screened out, new map points are created according to the results of feature extraction and matching, and the ORB features are features based on combination of feature points of an accelerated segmentation test and a binary robust independent basic feature descriptor.
And after all key frames are processed, local BA optimization is executed, the poses of the surrounding key frames and the positions of map points are optimized to obtain more accurate positioning and mapping precision, and finally candidate key frames are screened and redundant key frames are removed.
Step S43: detecting the unmanned aerial vehicle 10 for closed loop detection:
in the closed-loop detection thread, closed-loop detection is executed by retrieving an image recognition database, when a closed loop is detected, the closed-loop period is judged, if the current key frame and the closed-loop key frame do not belong to the same period, the period of the closed-loop key frame and the period of the current key frame are combined into the same period, and finally, global BA optimization is executed by taking the positions of all key frame positions and all map points in the period as optimization variables, so that a globally consistent environment map and camera motion track are obtained.
Step S5: and evaluating the emergency management monitoring model, dividing the emergency management monitoring model into a dangerous area, a rescue area and a slight dangerous area, marking the rescue area and generating a rescue route.
Step S6: and generating an optimal three-dimensional emergency rescue path by introducing an artificial potential field algorithm of the auxiliary potential field of the dangerous area.
The artificial potential field algorithm of the auxiliary potential field in the dangerous area refers to a potential field with three forces existing in a disaster field: detecting an attractive force potential field of the unmanned aerial vehicle 10 pointing to a rescue area, a repulsive force potential field of a dangerous area and a dangerous area auxiliary potential field, wherein the attractive force potential field is reduced along with the reduction of the distance between the rescue area and the unmanned aerial vehicle 10; the repulsive force of the dangerous area directed to the detecting unmanned aerial vehicle 10 increases with the decrease of the distance between the detecting unmanned aerial vehicle 10 and the dangerous area; the auxiliary potential field of the dangerous area is related to the speed of the dangerous area and the relative angle between the unmanned aerial vehicle 10 and the dangerous area, the attraction potential field of the rescue area, the repulsion potential field of the dangerous area and the auxiliary potential field of the dangerous area are combined, the movement of the unmanned aerial vehicle 10 is detected and controlled by the superposed resultant force of the three potential fields of the attraction field, the repulsion field and the auxiliary potential field of the dangerous area, so that the dangerous area is avoided, and path planning is completed, as shown in fig. 6, specifically:
the function of the gravitational potential field of the rescue area is
Wherein, the first and the second end of the pipe are connected with each other,
is gravitational potential energy;
is a gravity gain factor;
detecting the Euclidean distance between the unmanned aerial vehicle and a dangerous area;
the potential field of repulsive force of the dangerous area, the speed of the dangerous area
Function of (2)
：
The danger zone repulsive potential field function is:
wherein the content of the first and second substances,
parameters are adjusted for the repulsive potential field gain of the danger zone,
the distance of the robot from the hazardous area,
the influence range of the repulsive potential field of the danger area is defined;
and finally, constructing the auxiliary potential field function of the dangerous area as follows:
wherein, the first and the second end of the pipe are connected with each other,
it is an auxiliary potential field random gain adjustment function;
is gain adjustment coefficient of 0 ≦
A random number is not less than 1;
is a matrix of potential field-switching angles,
the rotation angle is related to the relative angle between the unmanned aerial vehicle and the dangerous area and the speed of the dangerous area;
thus detecting the resultant force experienced by the drone 10
The following were used:
detecting resultant force applied to the unmanned aerial vehicle 10
Gravity potential field from rescue area
And repulsive force potential field of dangerous area
And auxiliary potential field of dangerous area
The direction of the negative gradient of the resultant potential field of the composition is calculated.
Step S7: and (4) demonstrating danger sources and optimal rescue routes in the building through the control console animation.
The danger source in the building and the generated optimal rescue route are demonstrated to the rescuers through the control console animation formed by other intelligent electronic products such as a computer or a tablet personal computer, the search and rescue efficiency of the rescuers is improved, and therefore the situation that the rescuers do not have casualties when clearing the danger source is avoided.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the embodiments of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (9)
1. An emergency management monitoring method based on a three-dimensional model is characterized in that: the method specifically comprises the following steps:
step S1: preparing an emergency management monitoring system, wherein the emergency management monitoring system comprises a control console and a detection unmanned aerial vehicle (10), a central control module (11), a charging module (19), a navigation map building and obstacle avoiding module (13), a wireless transmission module (18), a gas sensor (15) and an infrared camera (17) are carried on the detection unmanned aerial vehicle (10), and the infrared camera (17), the gas sensor (15), the navigation map building and obstacle avoiding module (13), the wireless transmission module (18) and the charging module (19) are respectively and electrically connected with the central control module (11);
the navigation map building and obstacle avoiding module (13) detects obstacles (24) appearing in a disaster site, when an infrared camera (17) scans an object obstructing a cruising route, the object is marked as the obstacles (24), and obstacle avoiding processing is carried out at the first time;
the central control module (11) comprises an analysis unit, a storage unit and a transmission unit, wherein the analysis unit uses the temperature T1 measured by the infrared camera (17), the concentration w1 measured by the gas sensor (15), the temperature threshold T0 and the gas concentration threshold w0 stored in the storage unit as input information of a console to judge whether the site belongs to a dangerous area, a rescue area or a slight dangerous area, and transmits the judgment result to the transmission unit, the transmission unit is in wired connection with the wireless transmission module (18), inputs video information of the infrared camera (17) and the judgment result output by the central control module (11), and transmits the judgment result to the wireless transmission module (18);
the detection unmanned aerial vehicle (10) is in information communication with the control console through the wireless transmission module (18);
step S2: the console comprises a three-dimensional live-action modeling software management layer and a three-dimensional live-action modeling software engine layer for constructing a model, the construction task comprises aerial triangulation and model three-dimensional reconstruction, the aerial triangulation is in stereo photogrammetry, inputting a group of digital photos of a target chemical plant taken from different angles as input data sources in the three-dimensional live-action modeling software management layer, simultaneously inputting auxiliary data, wherein the auxiliary data comprises the attribute of a camera, the position of a photo, the angle of rotating the photo, a control point (23), a dangerous temperature threshold value and a gas concentration threshold value, and inputting a small number of field control points in the digital photo, encrypting control points indoors through a control console to obtain a measuring method of the elevation and the plane position of the encrypted points, wherein the control points (23) are positions required to be reached by traversing tasks;
step S3: the three-dimensional live-action modeling software management layer decomposes the set-up task into basic operation and submits the basic operation to a three-dimensional live-action modeling software engine layer, the three-dimensional live-action modeling software engine layer processes the basic operation to carry out three-dimensional reconstruction of a model, an emergency management monitoring model generated by the three-dimensional live-action modeling software engine layer is fed back to the three-dimensional live-action modeling software management layer, and then the three-dimensional live-action modeling software management layer derives a high-resolution emergency monitoring management model with real texture to complete a visual emergency management monitoring model;
step S4: the detection unmanned aerial vehicle (10) adopts an obstacle avoidance and mapping algorithm to conduct autonomous navigation and obstacle avoidance; the infrared camera (17) and the gas sensor (15) collect information and synchronously transmit the collected information to the analysis unit;
step S5: evaluating the emergency management monitoring model, dividing the emergency management monitoring model into a dangerous area, a rescue area and a slight dangerous area, marking the rescue area and generating a rescue route;
step S6: obtaining an optimal three-dimensional emergency rescue path by introducing an artificial potential field algorithm of the auxiliary potential field of the dangerous area; the artificial potential field algorithm of the auxiliary potential field in the dangerous area refers to a potential field with three forces existing in a disaster field: the method comprises the following steps that a gravitational potential field of a detection unmanned aerial vehicle (10) pointing to a rescue area, a repulsive potential field of a dangerous area and an auxiliary potential field of the dangerous area are detected, wherein the gravitational potential field is reduced along with the reduction of the distance between the rescue area and the detection unmanned aerial vehicle (10); the repulsive force of the dangerous area pointing to the detecting unmanned aerial vehicle (10) is increased along with the reduction of the distance between the detecting unmanned aerial vehicle (10) and the dangerous area; the speed of the supplementary potential field of danger area and survey unmanned aerial vehicle (10) and danger area are relevant, and the supplementary potential field of regional gravitation of rescue, danger area repulsion potential field and danger area merge, and the motion of surveying unmanned aerial vehicle (10) is controlled by the superimposed resultant force in three potential places of the supplementary potential field of gravitation field, repulsion field and danger area to avoid the danger area, accomplish the route planning, specifically do:
the function of the gravitational potential field of the rescue area is
Wherein, the first and the second end of the pipe are connected with each other,
is gravitational potential energy;
is a gravity gain factor;
detecting the Euclidean distance between the unmanned aerial vehicle and a dangerous area;
the repulsive potential field of the danger zone and the speed of the danger zone
Function of (2)
：
The danger zone repulsive potential field function is:
wherein the content of the first and second substances,
parameters are adjusted for the repulsive potential field gain of the danger zone,
is the distance of the robot from the hazardous area,
the influence range of the repulsive potential field of the danger area is defined;
and finally, constructing the auxiliary potential field function of the dangerous area as follows:
wherein the content of the first and second substances,
it is an auxiliary potential field random gain adjustment function;
is gain adjustment coefficient, 0 ≦
A random number is not less than 1;
is a matrix of potential field-switching angles,
the rotation angle is related to the relative angle between the unmanned aerial vehicle and the dangerous area and the speed of the dangerous area;
thus detecting the resultant force experienced by the drone 10
The following:
detecting resultant force applied to the unmanned aerial vehicle 10
Gravity potential field of rescue area
And repulsive force potential field of dangerous area
And auxiliary potential field of dangerous area
Calculating the direction of the negative gradient of the formed potential field;
step S7: the console demonstrates the source of danger and the optimal rescue route in the building through animation.
2. The three-dimensional model-based emergency management monitoring method according to claim 1, wherein in step S4, the obstacle avoidance and mapping algorithm is a feature method and direct method fused algorithm, and three threads are established for real-time tracking of the detecting unmanned aerial vehicle (10), mapping of the emergency management monitoring system, and closed-loop detection, specifically:
step S41: and (2) detecting the pose initialization of the unmanned aerial vehicle (10): when the unmanned aerial vehicle (10) is detected to be started, a first frame image shot by the infrared camera (17) is used as a key frame, and an initialization map is created by taking the current three-dimensional coordinate as a base point;
step S42: the detection unmanned aerial vehicle (10) executes real-time tracking and emergency management monitoring system mapping, the detection unmanned aerial vehicle (10) calculates the corresponding relation between the initial pose shot by the infrared camera (17) and the pixel points by minimizing luminosity errors, and then optimizes the pose of the infrared camera (17) again by utilizing the reprojection errors of the minimized local map points to track the local map; if the tracking fails, triggering a new tracking period;
the infrared camera (17) shoots a current frame, and if the current frame is different from a previous frame, the current frame is judged as a key frame; if no difference exists, judging the current frame as a non-key frame; in a local mapping thread, extracting and matching ORB features in a current key frame image, screening redundant map points in a current key frame, and creating new map points according to the result of feature extraction and matching, wherein the ORB features are features based on accelerated segmentation test and combined with a binary robust independent basic feature descriptor;
after all key frames are processed, local BA optimization is executed, the poses of the surrounding key frames and the positions of map points are optimized so as to obtain more accurate positioning and mapping accuracy, and finally candidate key frames are screened out and redundant key frames are removed;
step S43: detecting the unmanned aerial vehicle (10) to carry out closed-loop detection:
in the closed-loop detection thread, closed-loop detection is executed by retrieving an image recognition database, when a closed loop is detected, the closed-loop period is judged, if the current key frame and the closed-loop key frame do not belong to the same period, the period of the closed-loop key frame and the period of the current key frame are combined into the same period, and finally, global BA optimization is executed by taking the positions of all key frame positions and all map points in the period as optimization variables, so that a globally consistent environment map and camera motion track are obtained.
3. The three-dimensional model-based emergency management monitoring method according to claim 1, wherein the central control module (11) and the navigation map building and obstacle avoidance module (13) are fixedly installed above the frame of the detecting unmanned aerial vehicle (10), the infrared camera (17) and the gas sensor (15) are fixedly installed below the frame of the detecting unmanned aerial vehicle (10) in parallel, and the charging module (19) is fixedly installed on one side of the frame of the detecting unmanned aerial vehicle (10).
4. The three-dimensional model-based emergency management monitoring method according to claim 1, wherein the charging module comprises a short circuit unit and an overload unit, and the short circuit unit is used for providing short circuit protection for the charging module (19) in charging the detection unmanned aerial vehicle (10); the overload unit is used for the charging module (19) to provide overload protection in charging for the detection unmanned aerial vehicle (10).
5. The three-dimensional model-based emergency management and monitoring method according to claim 1, further comprising a high temperature resistant protective film, wherein the high temperature resistant protective film wraps the central control module (11), the charging module (19), the navigation map building and obstacle avoiding module (13), the wireless transmission module (18), the gas sensor (15) and the infrared camera (17) which are carried on the detection unmanned aerial vehicle (10), and only exposes the vent hole of the gas sensor (15), the lens hole of the infrared camera (17) and the charging port of the charging module (19).
6. The three-dimensional model-based emergency management monitoring method according to claim 1, wherein the gas sensor (15) comprises a carbon monoxide sensor.
7. The three-dimensional model-based emergency management monitoring method according to claim 1, wherein the control points (23) are areas for storing dangerous goods, areas for storing valuable goods, areas for storing important data, and areas where a large crowd is gathered.
8. The three-dimensional model-based emergency management monitoring method according to claim 1, wherein the control point (23) comprises a disaster site entrance (22) and a disaster site exit (28).
9. The three-dimensional model-based emergency management monitoring method according to claim 1, wherein the console is a computer or a tablet computer.
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