Unmanned aerial vehicle-robot cooperative search and rescue method and system for police service site

Abstract

The invention provides an unmanned aerial vehicle-robot cooperative search and rescue method for a police service site, and relates to the technical field of indoor navigation positioning, a three-dimensional grid map is constructed by obtaining building structure data of an indoor search and rescue area, and high-precision three-dimensional positioning is realized based on an air-ground double-layer beacon network. Beacon density and frequency are dynamically adjusted by combining Doppler frequency shift characteristics of acoustic beacons and thermal radiation intensity changes of infrared beacons, search and rescue path planning of cooperation of the unmanned aerial vehicle and the robot is synchronously optimized, and the problems of low target positioning precision and unstable dynamic tracking in a complex indoor environment can be effectively solved. The efficiency and reliability of cooperative operation of the unmanned aerial vehicle and the robot in a police service site and disaster rescue can be improved to a certain extent, so that the success rate and the overall execution effect of a search and rescue task in a complex scene are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of indoor navigation and positioning technology, and more specifically, to a drone-robot collaborative search and rescue method and system at a police scene. Background Art

[0002] In recent years, with the rapid development of drone, robotic, and sensor technologies, drones and ground robots have been widely used for autonomous navigation, target identification, and search and rescue missions in complex environments. The advantages of drone-robot collaboration have become increasingly prominent, particularly in high-risk scenarios such as police operations and disaster relief. Drones, with their flexibility and rapid deployment capabilities, can quickly acquire global information about a target area from high altitudes, simultaneously deploying beacons or sensors to establish temporary communication or positioning networks. Ground robots, with their strong adaptability, can perform sophisticated tasks such as target positioning and material transportation in complex terrain. However, in practical applications, police operations and search and rescue scenes often feature dynamic and complex environments, such as dense obstacles, severe signal interference, and random movement of targets. This places high demands on the stability, accuracy, and real-time performance of drone-robot collaboration.

[0003] In existing technologies, collaborative search and rescue between drones and ground robots primarily relies on a single type of positioning or monitoring method, such as GPS-based positioning, two-dimensional plane maps constructed using lidar, or target tracking using a visual system. However, these methods have significant shortcomings in complex indoor environments or areas with limited signals. For example, GPS signals are difficult to effectively cover in indoor environments, resulting in a significant decrease in positioning accuracy; lidar is prone to occlusion problems in areas with high obstacle density, making it impossible to fully construct a spatial model; and visual tracking technology is easily interfered with by light changes or occlusions, resulting in poor robustness in target recognition and tracking. In addition, existing technologies lack efficient multi-dimensional information fusion methods when drones and robots work together, making it impossible to perceive the target's three-dimensional dynamic information in real time. It is also difficult to dynamically adjust the search and rescue strategy based on the target's motion state, resulting in low search and rescue efficiency. Summary of the Invention

[0004] To address the above-mentioned technical problems, the present invention provides a drone-robot collaborative search and rescue method for police scenes. This method can, to a certain extent, address the low accuracy and time-consuming nature of traditional single-device search and rescue positioning in complex indoor environments, due to limited GPS signals and the uncertainty of hidden personnel locations.

[0005] According to one aspect of the present invention, a drone-robot collaborative search and rescue method at a police scene is provided, comprising:

[0006] Acquiring building structure data of an indoor search and rescue area, constructing a three-dimensional grid map based on the building structure data, and dividing the three-dimensional grid map into a plurality of search and rescue units;

[0007] A double-layer beacon positioning mechanism is adopted, in which a drone is used to drop an acoustic beacon at each search and rescue unit. After receiving the acoustic beacon, the robot deploys an infrared beacon array on the ground to form an air-ground double-layer beacon network.

[0008] Based on the air-ground double-layer beacon network, the three-dimensional coordinate data of the suspicious target is calculated by utilizing the Doppler frequency shift of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon;

[0009] When the suspicious target moves, the coverage density of the infrared beacon array is adjusted according to the change trend of the three-dimensional coordinate data, and the emission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are synchronously adjusted.

[0010] Furthermore, the basis for dividing each search and rescue unit includes the density of obstructions within the search and rescue unit, the proportion of the passable area of ​​the search and rescue unit, the distribution of doors and windows within the search and rescue unit, and the spatial connectivity of the search and rescue unit.

[0011] Furthermore, the dual-layer beacon positioning mechanism includes an airborne acoustic beacon layer and a ground-based infrared beacon layer;

[0012] wherein the drone is controlled to release the acoustic beacon above each search and rescue unit according to a preset release strategy;

[0013] Calculating the spatial position coordinates of each of the acoustic beacons based on the intensity and arrival time difference of the received acoustic wave signals;

[0014] Through the coordinated deployment of the spatial position coordinates of the acoustic beacon and the infrared beacon array, an air-ground double-layer beacon network is formed in the search and rescue area.

[0015] Furthermore, the spatial position coordinates of each of the acoustic beacons are calculated through three acoustic receivers distributed in an equilateral triangle. Based on the arrival time difference and intensity attenuation characteristics of the acoustic signal, a hyperbola positioning algorithm is used to calculate the horizontal two-dimensional coordinates of the acoustic beacon, and its vertical height is calculated in combination with the intensity attenuation relationship to finally determine the spatial position coordinates of the acoustic beacon.

[0016] Furthermore, calculating the three-dimensional coordinate data of the suspicious target includes the following steps:

[0017] Based on the air-ground double-layer beacon network, motion parameters are calculated using acoustic beacons;

[0018] When there is relative motion between the target and the beacon, the received sound wave signal produces a frequency shift, and the frequency shift value is calculated;

[0019] Based on the frequency shift value, the speed and movement direction of the target are calculated;

[0020] When the target moves vertically, the altitude change rate is calculated and the altitude change rate is integrated over time to obtain the real-time altitude of the target;

[0021] Calculate plane position using infrared beacons;

[0022] The three-dimensional coordinates of the target are obtained based on the height data calculated by the acoustic beacon and the plane coordinates calculated by the infrared beacon.

[0023] Furthermore, the calculation of the plane coordinates is shown in the following formula:

[0024]

[0025]

[0026] in,( , ) is the position coordinate of the i-th infrared beacon, is the strength correction factor, is the intensity change between adjacent moments, The number of valid infrared beacons participating in the target positioning calculation;

[0027] in, is the position weight of the target, as shown below:

[0028]

[0029] in, is the time correlation coefficient, is the time decay factor, is the sampling time interval, is the thermal radiation intensity, is the radiation intensity at the standard distance.

[0030] Furthermore, obtaining the three-dimensional coordinates of the target also includes a credibility evaluation factor. When the credibility evaluation factor K is greater than a preset threshold and the coordinate deviation calculated three times in succession is within an allowable range, the three-dimensional coordinates are output as a valid positioning result.

[0031] Furthermore, the coverage density of the infrared beacon array is adjusted to dynamically adjust the range, shape and spacing of the beacon encryption area according to the instantaneous speed and movement direction of the target, and the beacon layout is optimized in combination with acceleration, deceleration, turning, occlusion and multi-target motion characteristics. At the same time, the regional beacon spacing is gradually restored to the standard value after the target leaves.

[0032] Furthermore, the synchronous adjustment of the sampling frequency includes:

[0033] When the target speed is detected to be within a first preset range, the emission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are maintained within the corresponding basic frequency range;

[0034] When it is detected that the target speed is within a second preset range, the transmission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are increased, and the transmission pulse width is shortened to improve the time resolution;

[0035] When the target speed exceeds a third preset range, the emission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are further increased while keeping the time intervals between adjacent samplings constant.

[0036] According to another aspect of the present invention, a drone-robot collaborative search and rescue system for police scenes is provided, comprising:

[0037] Data collection module, used to obtain building structure data of indoor search and rescue areas;

[0038] a search and rescue unit division module, which constructs a three-dimensional grid map based on the data collected by the data collection module and divides the three-dimensional grid map into a plurality of search and rescue units;

[0039] A beacon positioning network construction module is used to deploy acoustic beacons at each of the search and rescue units via a drone. After receiving the acoustic beacons, the robot deploys an infrared beacon array on the ground to form an air-ground double-layer beacon network.

[0040] A coordinate calculation module is used to calculate the three-dimensional coordinate data of the suspicious target based on the air-ground double-layer beacon network using the Doppler frequency shift of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon;

[0041] A frequency adjustment module is used to adjust the coverage density of the infrared beacon array according to the change trend of the three-dimensional coordinate data when the suspicious target moves, and to synchronize the emission frequency of the acoustic beacon with the sampling frequency of the infrared beacon array.

[0042] Compared with the existing technology, the drone-robot collaborative search and rescue method at the police scene provided by the present invention constructs a three-dimensional grid map by acquiring the building structure data of the indoor search and rescue area, and realizes high-precision three-dimensional positioning based on the air-ground double-layer beacon network. The beacon density and frequency are dynamically adjusted by combining the Doppler frequency shift characteristics of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon, and the search and rescue path planning of the drone and robot collaboration is synchronously optimized. It can effectively solve the problems of low target positioning accuracy and unstable dynamic tracking in complex indoor environments, and can improve the efficiency and reliability of the collaborative operation of drones and robots in police scenes and disaster rescue to a certain extent, thereby significantly improving the success rate and overall execution effect of search and rescue missions in complex scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0044] Figure 1 Flowchart of a drone-robot collaborative search and rescue method at a police scene according to an embodiment of the present invention.

[0045] Figure 2 4 is a system block diagram of a drone-robot collaborative search and rescue system at a police scene according to an embodiment of the present invention. DETAILED DESCRIPTION

[0046] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0047] Figure 1 FIG is a flow chart of a drone-robot collaborative search and rescue method at a police scene according to an embodiment of the present invention. Figure 1 As shown, the drone-robot collaborative search and rescue method at the police scene includes:

[0048] S1: Acquire building structure data of an indoor search and rescue area, construct a three-dimensional grid map based on the building structure data, and divide the three-dimensional grid map into a plurality of search and rescue units, wherein the size of each search and rescue unit is determined according to the room structure and the distribution of obstructions;

[0049] Acquire building structure data of the indoor search and rescue area, the building structure data including the wall layout data, floor height data, door and window position data, pipeline distribution data and fixed facility distribution data of the building, wherein the wall layout data obtains the spatial coordinates and geometric dimensions of the wall through a laser rangefinder, the floor height data measures the vertical distance between floors through an ultrasonic sensor, the door and window position data collects the opening position and size of doors and windows through a visual sensor, the pipeline distribution data uses a thermal imager to obtain the direction of pipelines inside the building, and the fixed facility distribution data is based on the pre-calibrated location information of indoor furniture and large equipment; based on the building structure data, an octree space partitioning algorithm is used to construct a three-dimensional grid map, the minimum grid unit of the three-dimensional grid map is set to 0.5 meters × 0.5 meters × 0.5 meters, and the spatial area is divided into grids with different resolutions through recursive subdivision. structure, wherein the grid division in the obstacle-dense area is finer, and the grid division in the open area is coarser; the three-dimensional grid map is divided into multiple search and rescue units, and the division basis of each search and rescue unit includes the density of obstructions in the search and rescue unit, the proportion of the passable area of ​​the search and rescue unit, the distribution of doors and windows in the search and rescue unit, and the spatial connectivity of the search and rescue unit, wherein the density of obstructions is obtained by calculating the proportion of obstacles in a unit volume, the proportion of the passable area is calculated based on the area of ​​the unobstructed area on the ground, the distribution of doors and windows takes into account the number and distribution of entrances and exits, and the spatial connectivity characterizes the difficulty of passage between adjacent search and rescue units. When the density of obstructions is greater than 80%, the search and rescue unit is marked as a high-difficulty area, when the proportion of the passable area is less than 30%, the search and rescue unit is marked as a restricted area, and when the number of doors and windows is less than 2, the search and rescue unit is marked as a closed area.

[0050] S2: Using a double-layer beacon positioning mechanism, the drone drops acoustic beacons at each search and rescue unit. After receiving the acoustic beacons, the robot deploys an infrared beacon array on the ground, forming an air-ground double-layer beacon network.

[0051] A double-layer beacon positioning mechanism is adopted, which includes an aerial acoustic beacon layer and a ground infrared beacon layer; wherein, the UAV is controlled to release the acoustic beacon above each search and rescue unit according to a preset release strategy, and the release strategy determines the release density based on the search and rescue difficulty coefficient of each search and rescue unit, specifically, one acoustic beacon is released every 5 square meters in high-difficulty areas, one acoustic beacon is released every 8 square meters in restricted areas, and one acoustic beacon is released every 12 square meters in ordinary areas. The acoustic beacon uses a working frequency of 40kHz to emit directional sound waves, and each acoustic beacon has a unique pulse code for identity identification; the robot receives the acoustic signal emitted by the acoustic beacon through the acoustic receiver it carries, and calculates the spatial position coordinates of each acoustic beacon based on the intensity and arrival time difference of the received acoustic signal. When the intensity of the received acoustic signal is greater than a preset threshold, The robot deploys the infrared beacon array on the ground at the corresponding position. The infrared beacon array adopts a 7×7 matrix layout, and the spacing between adjacent infrared beacons is 0.8 meters. Each infrared beacon emits near-infrared light with a wavelength of 850nm, and the emission power can be dynamically adjusted between 0.5W and 2W. Through the coordinated deployment of the acoustic beacons and the infrared beacon array, an air-ground double-layer beacon network is formed in the search and rescue area, wherein the acoustic beacons constitute the air positioning layer for providing large-scale coarse positioning information, and the infrared beacon array constitutes the ground positioning layer for providing precise local positioning information. The two positioning layers are spatially aligned through the position information of the robot. All beacons in the air-ground double-layer beacon network are powered by lithium batteries with a battery capacity of 2000mAh, which can work continuously for 8 hours, and each beacon is equipped with a wireless communication module for reporting the working status and remaining power to the control center in real time.

[0052] More specifically, the spatial position coordinates of each of the sonic beacons are calculated based on the intensity and arrival time difference of the received sonic signal, wherein the robot is equipped with three sonic receivers distributed in an equilateral triangle, and the spacing between the three sonic receivers is 0.5 meters; when the sonic beacon transmits a sonic signal, the time difference of the sonic signal arriving at the three sonic receivers in sequence is calculated, and the distance difference of the sonic beacon relative to each receiver is calculated based on the time difference and the propagation speed of the sound wave in the air; the distance difference data is solved by a hyperbola positioning algorithm to obtain the two-dimensional coordinates of the sonic beacon in the horizontal plane, wherein when all three sonic receivers receive valid signals, three pairs of distance difference data are used to calculate the distance difference between the two sonic receivers. The plane position of the acoustic beacon is determined by solving a set of hyperbolic equations; at the same time, the vertical height of the acoustic beacon is calculated using the intensity attenuation characteristics of the acoustic signal during propagation, and the vertical height is determined based on the ratio of the initial emission intensity and the reception intensity of the acoustic signal through the exponential decay relationship between the acoustic intensity and the propagation distance; when the time difference data and the intensity attenuation data obtained by the three acoustic receivers are valid, the plane position coordinates and the vertical height are combined to obtain the spatial position coordinates of the acoustic beacon, wherein when the acoustic signal intensity is lower than a preset threshold or the time difference between any two acoustic receivers exceeds an allowable range, the current position calculation result is determined to be invalid and a re-acquisition procedure is started.

[0053] S3: Based on the air-ground double-layer beacon network, the three-dimensional coordinate data of the suspicious target is calculated using the Doppler frequency shift of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon, wherein the acoustic beacon is used to determine the target height and the infrared beacon array is used to determine the target plane position;

[0054] Based on the air-ground double-layer beacon network, the three-dimensional coordinate data of the suspicious target is calculated using the Doppler frequency shift of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon; the acoustic beacon transmits a detection signal at a frequency of twenty times per second, and the beam width of the transmitted signal is sixty degrees. When there is relative motion between the suspicious target and the acoustic beacon, the frequency of the received acoustic signal is offset relative to the transmitting frequency, wherein the frequency change caused by the 40 kilohertz reference frequency after propagation through the atmosphere needs to be temperature compensated and humidity corrected; the acoustic beacon adopts a unique dual-pulse encoding method when transmitting the detection signal, and improves the anti-interference ability of target detection by alternately transmitting high-frequency narrow pulses and low-frequency width pulses, wherein the high-frequency pulse is used to accurately measure the frequency shift, and the low-frequency pulse is used to ensure the signal penetration ability; when the suspicious target moves, due to the Doppler effect of the sound wave, the frequency of the received signal is offset relative to the transmitting frequency, and the frequency shift value changes with the change of the target movement speed and direction, and is calculated by the formula:

[0055]

[0056] in, is the transmitting frequency, is the target relative motion speed, is the angle between the direction of motion and the direction of sound wave propagation, is the speed of sound, is the temperature correction coefficient, is the ambient temperature.

[0057] There is a nonlinear relationship between the frequency shift value and the actual motion parameters of the target. The influence of ambient temperature on the speed of sound needs to be considered. The temperature correction coefficient α increases with the increase of ambient temperature and shows a good linear characteristic within the temperature range of -20 to 40 degrees Celsius. When the suspicious target moves vertically, the target's altitude change rate is calculated based on the frequency shift value:

[0058]

[0059] in, is the horizontal distance between the target and the acoustic beacon, is the effective detection radius of the acoustic beacon; the calculation of the altitude change rate needs to consider the horizontal distance between the target and the beacon. When the horizontal distance is close to the effective detection radius of the acoustic beacon, the measurement accuracy will be significantly reduced, so a distance correction term is introduced; the real-time altitude of the target is obtained by integrating the altitude change rate over time:

[0060]

[0061] in, is the initial height, is the height attenuation coefficient, which is used to correct the integration error.

[0062] The height calculation result includes an exponential decay term of the initial height, which is used to eliminate the cumulative error in the integration process, where the decay coefficient Dynamically adjust according to the actual measurement environment;

[0063] At the same time, the infrared beacon array detects the target's thermal radiation. Each infrared beacon uses a near-infrared light source with a wavelength of 850 nanometers and an adjustable transmission power between 0.5 watts and 2 watts. The receiver uses a highly sensitive photodiode array capable of detecting weak changes in thermal radiation. When the suspicious target enters the infrared beacon's detection range, the intensity of the reflected thermal radiation meets the following requirements:

[0064]

[0065] in, is the thermal radiation intensity, is the radiation intensity at the standard distance, is the attenuation coefficient, is the directivity coefficient, is the angle of incidence, For distance.

[0066] Based on the thermal radiation intensity, the position weight w of the target is calculated:

[0067]

[0068] in, is the time correlation coefficient, is the time decay factor, is the sampling time interval; using the position weight, calculate the plane coordinates (x, y) of the target:

[0069]

[0070]

[0071] in,( , ) is the position coordinate of the i-th infrared beacon, is the strength correction factor, is the intensity change between adjacent moments, is the number of valid infrared beacons involved in the target positioning calculation; finally, the three-dimensional coordinates P(x, y, h) of the suspicious target are obtained, and the comprehensive credibility evaluation factor is introduced :

[0072]

[0073] in, is the maximum position weight, is the average position weight, is the frequency shift impact factor, is the strength influence factor; when the credibility evaluation factor K is greater than the preset threshold and the coordinate deviation calculated three times in a row is within the allowable range, the three-dimensional coordinates are output as the valid positioning result.

[0074] It's worth noting that while the above description outlines the general process for calculating the three-dimensional coordinates of suspicious targets, the specific implementation details may vary. Taking a shopping mall fire scenario as an example, the application process for calculating the three-dimensional coordinates of suspicious targets is illustrated: When firefighters need to search for trapped personnel in dense smoke, they first deploy a search and rescue system in the clothing area on the third floor of the mall. Drones deploy acoustic beacons every six meters in the top floor, forming the first layer of the detection network. After receiving the acoustic beacon signals, ground robots deploy a seven-by-seven array of infrared beacons at intervals of 0.8 meters in the aisles, forming the second layer of the detection network.

[0075] When a trapped person moves within the fitting room area, the system begins calculating their location. Assuming the person moves from the fitting room toward the emergency exit at a speed of approximately 0.5 meters per second, the frequency of the echo signal received by the overhead acoustic beacon will change. For example, at a transmission frequency of 40 kHz, as the trapped person moves away from the acoustic beacon, the received signal frequency decreases by approximately 0.6 Hz. This frequency shift allows the person's speed and direction of movement to be calculated. Furthermore, because the trapped person's body temperature is higher than the ambient temperature, the infrared beacon array detects noticeable variations in thermal radiation intensity within the fitting room area. For example, the infrared beacon closest to the target detects a thermal radiation intensity 30 percent higher than the standard value, while the thermal radiation intensity detected by adjacent infrared beacons exhibits a gradient attenuation.

[0076] The system processes this data comprehensively: The frequency shift of the acoustic beacon determines that the trapped person is approximately 1.6 meters tall and moving southeast at a speed of 0.5 meters per second. The distribution of thermal radiation intensity detected by the infrared beacon array determines that the trapped person is located near the fourth infrared beacon in the third row, approximately two meters to the right of the fitting room exit. When the trapped person stops to rest, the frequency shift rapidly decreases to near zero, while the thermal radiation intensity remains stable. Based on this, the system determines that the target is stationary. If the thick smoke weakens the detection signal of some infrared beacons at this time, the system automatically increases the transmit power of surrounding infrared beacons to ensure continued acquisition of valid location information.

[0077] This location information is transmitted to the rescue command center in real time, helping firefighters accurately determine the location and movement trajectory of trapped people. For example, if the system shows that the coordinates of a trapped person are within the same fitting room three times in a row, and the reliability assessment factor is higher than 0.85, firefighters can determine that there is a high probability of a trapped person at that location and initiate a rescue operation in a timely manner.

[0078] S4: When the suspicious target moves, the coverage density of the infrared beacon array is adjusted according to the change trend of the three-dimensional coordinate data, and the emission frequency of the acoustic beacon is synchronously adjusted with the sampling frequency of the infrared beacon array to ensure dynamic tracking accuracy.

[0079] The coverage density of the infrared beacon array is adjusted according to the change trend of the three-dimensional coordinate data, when it is detected that the target starts to move.

[0080] First, the position difference of the target at two adjacent sampling moments is calculated to obtain the instantaneous movement speed and movement direction of the target; if the movement speed of the target is greater than 0.2 meters per second and less than 0.5 meters per second, a circular encryption area with a radius of 1.5 meters is constructed around the current position of the target, and the infrared beacon spacing in the area is gradually adjusted from the original 0.8 meters to 0.6 meters; when the target movement speed is greater than 0.5 meters per second and less than one meter per second, the radius of the circular encryption area is expanded to two meters, and the beacon spacing is further reduced to 0.4 meters. At the same time, a fan-shaped prediction area is constructed in front of the target movement direction. The fan-shaped area has an angle of sixty degrees and a depth of twice the current speed. If the target movement speed exceeds one meter per second, the circular encryption area is transformed into an elliptical area. The long axis direction of the ellipse is consistent with the target movement direction, the long axis length is three times the speed, and the short axis length is 1.5 times the speed. The beacon spacing in the area is reduced to 0.3 meters; when the target turns, a circular encryption area with a radius of three meters is constructed with the turning point as the center, and the beacon spacing in the area is adjusted to 0.3 meters. Beacons are deployed at equal intervals in the predicted new direction of motion. If the target's motion accelerates or decelerates, the range of the elliptical encryption area is dynamically adjusted according to the magnitude of the acceleration. During acceleration, the elliptical area extends in the direction of motion, and during deceleration, the elliptical area shrinks in the direction of motion. When the target enters an obstructed area or an area with weakened signal strength, the spacing of the beacons in the area is automatically reduced to 0.2 meters to improve positioning accuracy. If the target is detected to stay at a certain location for more than two seconds, the spacing of the beacons within a one-meter radius around the location is temporarily adjusted to 0.2 meters, while the standard spacing of the outer beacons is maintained. When the target completely leaves a certain encryption area, the spacing of the beacons in the area will gradually return to the standard spacing of 0.8 meters within ten seconds. The recovery process adopts a linear change method to avoid sudden changes in beacon coverage. If the system detects multiple targets at the same time, it prioritizes the beacon encryption effect in the area where the high-speed moving target is located, and maintains basic encryption coverage for the low-speed moving target. When the beacon density in a certain area has reached the maximum value of 0.2 meters, the positioning effect is further enhanced by increasing the beacon transmission power.

[0081] Furthermore, the emission frequency of the acoustic beacon is synchronously adjusted with the sampling frequency of the infrared beacon array, wherein when the target speed is detected to be lower than 0.2 meters per second, the acoustic beacon maintains a basic emission frequency of 20 times per second, and the infrared beacon array adopts a basic sampling frequency of 4 times per second; when the target speed reaches 0.2 meters to 0.5 meters per second, the emission frequency of the acoustic beacon is increased to 25 times per second, and the sampling frequency of the infrared beacon array is correspondingly increased to 6 times per second, and the emission pulse width is shortened from the original 2 milliseconds to 1.5 milliseconds; if the target speed continues to rise to 0.5 meters to 1 meter ... acoustic beacon maintains a basic emission frequency of 20 times per second, and the infrared beacon array adopts a basic sampling frequency of 4 times per second; when the target speed reaches 0.2 meters to 0.5 meters per second, the acoustic beacon maintains a basic emission frequency of 20 times per second, and the infrared beacon array adopts a basic sampling frequency of 4 times per second The emission frequency of the acoustic beacon is further increased to 30 times per second, and the sampling frequency of the infrared beacon array is synchronously increased to 8 times per second. At this time, the emission pulse width is reduced to one millisecond to improve the time resolution; when the target speed exceeds one meter per second, the acoustic beacon adopts the highest emission frequency of 40 times per second, and the sampling frequency of the infrared beacon array is correspondingly adjusted to 10 times per second, and the time interval between two adjacent samples remains constant; if the target is detected to be accelerating, the acoustic beacon superimposes a frequency compensation amount proportional to the acceleration on the base emission frequency. When the acceleration reaches one meter per square second, the emission frequency is increased by an additional five times per second. When the target enters the blocked area or the area with poor signal quality, the acoustic beacon and the infrared beacon array enter the high-frequency working mode at the same time, and the transmission frequency and sampling frequency are increased to 120% of the maximum value, and the duration does not exceed five seconds; if the target stays at a certain position for more than three seconds, the working frequency of the acoustic beacon and the infrared beacon array is synchronously reduced to 80% of the basic frequency to save energy; when multiple targets appear in the detection area at the same time, the nearest acoustic beacon is selected for frequency adjustment based on the proximity principle, and the difference in transmission frequency of adjacent acoustic beacons is maintained at more than five times per second to avoid signal interference; if the target is detected When the beacon makes reciprocating motion, the operating frequencies of the acoustic beacon and the infrared beacon array automatically adjust as the direction of motion changes. The highest frequency is used for sampling at the moment the direction of motion changes, and then the frequency is gradually adjusted to the appropriate frequency according to the new motion characteristics. When the system power is less than 20%, the acoustic beacon and the infrared beacon array enter energy-saving mode, reducing each frequency level by 20%, but keeping the relative relationship between frequencies unchanged. If the target leaves the detection area, the operating frequencies of the acoustic beacon and the infrared beacon array smoothly transition back to the base frequency within ten seconds, and the transition process adopts an exponential decay method to ensure system stability.

[0082] In summary, a drone-robot collaborative search and rescue method at a police scene based on an embodiment of the present invention is illustrated. A three-dimensional grid map is constructed by acquiring the building structure data of the indoor search and rescue area, and high-precision three-dimensional positioning is achieved based on an air-ground double-layer beacon network. The beacon density and frequency are dynamically adjusted in combination with the Doppler frequency shift characteristics of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon, and the search and rescue path planning of the drone and robot collaboration is simultaneously optimized. This can effectively solve the problems of low target positioning accuracy and unstable dynamic tracking in complex indoor environments, and can to a certain extent improve the efficiency and reliability of the collaborative operation of drones and robots at police scenes and disaster rescue, thereby significantly improving the success rate and overall execution effect of search and rescue missions in complex scenarios.

[0083] Here, those skilled in the art will appreciate that the specific operations of each step in the above-mentioned UAV-robot collaborative search and rescue method at the police scene have been referenced above. Figure 1 and Figure 2 The description of the drone-robot collaborative search and rescue method at the police scene has been introduced in detail, and therefore, its repeated description will be omitted.

Claims

1. A drone-robot collaborative search and rescue method at a police scene, characterized in that: include: Acquiring building structure data of an indoor search and rescue area, constructing a three-dimensional grid map based on the building structure data, and dividing the three-dimensional grid map into a plurality of search and rescue units; A double-layer beacon positioning mechanism is adopted, in which a drone is used to drop an acoustic beacon at each search and rescue unit. After receiving the acoustic beacon, the robot deploys an infrared beacon array on the ground to form an air-ground double-layer beacon network. Based on the air-ground double-layer beacon network, the three-dimensional coordinate data of the suspicious target is calculated by utilizing the Doppler frequency shift of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon; When the suspicious target moves, the coverage density of the infrared beacon array is adjusted according to the change trend of the three-dimensional coordinate data, and the emission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are synchronously adjusted.

2. The drone-robot collaborative search and rescue method at a police scene according to claim 1, characterized in that: The basis for dividing each search and rescue unit includes the density of obstructions within the search and rescue unit, the proportion of the passable area of ​​the search and rescue unit, the distribution of doors and windows within the search and rescue unit, and the spatial connectivity of the search and rescue unit.

3. The drone-robot collaborative search and rescue method at a police scene according to claim 1, characterized in that: The dual-layer beacon positioning mechanism includes an airborne acoustic beacon layer and a ground-based infrared beacon layer; wherein the drone is controlled to release the acoustic beacon above each of the search and rescue units according to a preset release strategy; Calculating the spatial position coordinates of each of the acoustic beacons based on the intensity and arrival time difference of the received acoustic wave signals; Through the coordinated deployment of the spatial position coordinates of the acoustic beacon and the infrared beacon array, an air-ground double-layer beacon network is formed in the search and rescue area.

4. The drone-robot collaborative search and rescue method at a police scene according to claim 3, characterized in that: The spatial position coordinates of each acoustic beacon are calculated by three acoustic receivers distributed in an equilateral triangle. Based on the arrival time difference and intensity attenuation characteristics of the acoustic signal, a hyperbola positioning algorithm is used to calculate the horizontal two-dimensional coordinates of the acoustic beacon, and its vertical height is calculated in combination with the intensity attenuation relationship to finally determine the spatial position coordinates of the acoustic beacon.

5. The drone-robot collaborative search and rescue method at a police scene according to claim 1, characterized in that: Calculating the three-dimensional coordinate data of the suspicious target includes the following steps: Based on the air-ground double-layer beacon network, motion parameters are calculated using acoustic beacons; When there is relative motion between the target and the beacon, the received sound wave signal produces a frequency shift, and the frequency shift value is calculated; Based on the frequency shift value, the speed and movement direction of the target are calculated; When the target moves vertically, the altitude change rate is calculated and the altitude change rate is integrated over time to obtain the real-time altitude of the target; Calculate plane position using infrared beacons; The three-dimensional coordinates of the target are obtained based on the height data calculated by the acoustic beacon and the plane coordinates calculated by the infrared beacon.

6. The drone-robot collaborative search and rescue method at a police scene according to claim 5, characterized in that: The calculation of the plane coordinates is shown below: in,( , ) is the position coordinate of the i-th infrared beacon, is the strength correction factor, is the intensity change between adjacent moments, The number of valid infrared beacons participating in the target positioning calculation; in, is the position weight of the target, as shown below: in, is the time correlation coefficient, is the time decay factor, is the sampling time interval, is the thermal radiation intensity, is the radiation intensity at the standard distance.

7. The drone-robot collaborative search and rescue method at a police scene according to claim 5, characterized in that: Obtaining the three-dimensional coordinates of the target also includes a credibility evaluation factor. When the credibility evaluation factor K is greater than a preset threshold and the coordinate deviation calculated three times in succession is within an allowable range, the three-dimensional coordinates are output as a valid positioning result.

8. The drone-robot collaborative search and rescue method at a police scene according to claim 1, characterized in that: Adjust the coverage density of the infrared beacon array to dynamically adjust the range, shape and spacing of the beacon encryption area according to the instantaneous speed and movement direction of the target, and optimize the beacon layout in combination with acceleration, deceleration, turning, occlusion and multi-target motion characteristics. At the same time, gradually restore the regional beacon spacing to the standard value after the target leaves.

9. The drone-robot collaborative search and rescue method at a police scene according to claim 1, characterized in that: The synchronous adjustment of the sampling frequency includes: When the target speed is detected to be within a first preset range, the emission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are maintained within the corresponding basic frequency range; When it is detected that the target speed is within a second preset range, the transmission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are increased, and the transmission pulse width is shortened to improve the time resolution; When the target speed exceeds a third preset range, the emission frequency of the acoustic beacon and the sampling frequency of the infrared beacon array are further increased while keeping the time intervals between adjacent samplings constant.

10. A drone-robot collaborative search and rescue system for police scenes, based on the drone-robot collaborative search and rescue method for police scenes according to any one of claims 1 to 9, characterized in that: include: Data collection module, used to obtain building structure data of indoor search and rescue areas; a search and rescue unit division module, which constructs a three-dimensional grid map based on the data collected by the data collection module and divides the three-dimensional grid map into a plurality of search and rescue units; A beacon positioning network construction module is used to deploy acoustic beacons at each of the search and rescue units via a drone. After receiving the acoustic beacons, the robot deploys an infrared beacon array on the ground to form an air-ground double-layer beacon network. A coordinate calculation module is used to calculate the three-dimensional coordinate data of the suspicious target based on the air-ground double-layer beacon network using the Doppler frequency shift of the acoustic beacon and the change in the thermal radiation intensity of the infrared beacon; A frequency adjustment module is used to adjust the coverage density of the infrared beacon array according to the change trend of the three-dimensional coordinate data when the suspicious target moves, and to synchronize the emission frequency of the acoustic beacon with the sampling frequency of the infrared beacon array.

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