CN-122018541-A - Intelligent obstacle avoidance method and system for four-rotor unmanned aerial vehicle based on guide vane

CN122018541ACN 122018541 ACN122018541 ACN 122018541ACN-122018541-A

Abstract

The invention provides a four-rotor unmanned aerial vehicle intelligent obstacle avoidance method and system based on guide vanes, wherein the method comprises the following steps of S1, initializing an obstacle avoidance system before the unmanned aerial vehicle works, S2, executing a passive obstacle avoidance mode by default when the unmanned aerial vehicle works, monitoring an environment light intensity level R 2 and a flight area risk level R 3 , judging whether to switch to an active obstacle avoidance mode, S3, calculating the shortest regression path of the unmanned aerial vehicle according to an original route and the current position after the obstacle avoidance is completed, gradually recovering the original flight speed, and resetting the system state after the original route.

Inventors

YANG XIANGDONG
LI YOUHONG
ZHANG BIN
CHEN WEIQUAN
ZHANG DONGPENG
SUN PENG

Assignees

广州华立学院

Dates

Publication Date: 20260512
Application Date: 20260128

Claims (10)

1. The utility model provides a four rotor unmanned aerial vehicle intelligence keep away barrier method based on guide vane, is provided with the guide vane on the unmanned aerial vehicle rotor, is provided with the guiding gutter in the guide vane, and the guiding gutter links to each other with initiative air current emission module, is provided with pressure sensor and angular displacement sensor on the guide vane, includes the following step: S1, initializing an unmanned aerial vehicle, wherein the initializing operation comprises calibration of a reference value and presetting of an angle change threshold value and a pressure change threshold value under a passive obstacle avoidance mode, and an original route and an original flying speed are determined; S2, a passive obstacle avoidance mode is initially executed when the unmanned aerial vehicle works, in the passive obstacle avoidance mode, the pressure value of air flow in a guide groove in the guide plate is detected through a guide plate pressure sensor, the angle value of the air flow influenced by the air flow of the guide plate is determined through an angle displacement sensor, the air flow pressure change value and the air flow angle change value are respectively determined according to the air flow pressure value and the air flow angle value, whether the air flow is disturbed by the rotor wing is determined by comparing the air flow pressure change value with a preset pressure change threshold value and the air flow angle change value with a preset angle change threshold value, if not, the passive risk level is determined according to the peak value of the air flow pressure change value, the peak value of the air flow angle change value and the change speed, different obstacle avoidance actions are determined according to the passive risk level, the environment light intensity level and the risk level of a flying area are monitored, and whether the active obstacle avoidance mode is switched is judged; And S3, after obstacle avoidance is completed, the unmanned aerial vehicle calculates the shortest regression path according to the original route and the current position, and gradually recovers the original flying speed.
2. The intelligent obstacle avoidance method of the four-rotor unmanned aerial vehicle based on the guide vane is characterized in that in the step S2, an airflow pressure change value and an airflow angle change value are respectively determined according to an airflow pressure value and an airflow angle value, wherein the step S2 comprises the steps of filtering the airflow angle value by wavelet transformation filtering, removing an interference frequency part generated by rotor vibration, and extracting a guide vane deflection angle change delta theta caused by airflow disturbance; The air flow pressure value adopts Kalman filtering to remove environmental noise, and the air flow pressure variation delta P is extracted.
3. The intelligent obstacle avoidance method of a four-rotor unmanned aerial vehicle based on a guide vane according to claim 1, wherein in step S2, the passive risk level is determined according to the peak value of the airflow pressure change value, the peak value of the airflow angle change value and the change speed, and determining different obstacle avoidance actions according to the passive risk level comprises determining the passive risk level R 1 according to R 1 =(ΔP/P 0 )×0.7+(Δθ/(θ 0 +0.1) x 0.3, If R 1 is smaller than a preset first passive sensing risk level value, determining that the risk is low, determining that the risk is a long-distance obstacle or a small-size obstacle, only sending disturbance early warning information to a flight control unit, maintaining the original flight attitude and speed by the flight control unit, and continuously monitoring the disturbance change trend by a data processing unit; If a first passive sensing risk level value < R 1 < a second passive sensing risk level value is preset, determining that the risk is middle, determining the direction of the obstacle according to delta theta and delta P distribution of more than two groups of guide plates, enabling the unmanned aerial vehicle to fly and deflect by a preset angle, and keeping the original flying speed; If a second passive sensing risk level value < R 1 is preset, determining that the risk is high, judging that the risk is a close-range obstacle, controlling the unmanned aerial vehicle to hover in a preset time, translating a preset distance to the direction with the minimum disturbance, continuously monitoring air flow disturbance in the translation process, returning to an original route if the disturbance disappears, triggering mode switching if the disturbance continues, and starting an active obstacle avoidance mode.
4. The intelligent obstacle avoidance method of the four-rotor unmanned aerial vehicle based on the guide vane, which is characterized in that in the step S2, judging whether to switch to an active obstacle avoidance mode comprises the steps of immediately sending a mode switching instruction and switching to the active obstacle avoidance mode if the passive obstacle avoidance risk level R 1 is not less than a first preset threshold value or the environment light intensity level R 2 is not less than a second preset threshold value or the flying area risk level R 3 is not less than a third preset threshold value; If the passive obstacle avoidance risk level R 1 is less than the first preset threshold value, the environment light intensity level R 2 is more than the second preset threshold value, and the flight area risk level R 3 is less than the third preset threshold value, the passive obstacle avoidance mode is maintained.
5. The intelligent obstacle avoidance method of the four-rotor unmanned aerial vehicle based on the guide vane is characterized in that step S2 further comprises the steps of transmitting stable air flow through an active air flow transmitting module in sequence, collecting reflected air flow signals through a pressure sensor and an angular displacement sensor, calculating air flow propagation speed through an air flow speed correction algorithm, calculating obstacle distance by combining time difference transmitted to receiving, calculating azimuth angle and pitch angle through a weighted triangular positioning method, identifying obstacle types according to reflected air flow signal characteristics, executing a grading obstacle avoidance response according to obstacle information, and continuously monitoring environmental parameters after the active obstacle avoidance is completed to judge whether to switch back to a passive obstacle avoidance mode.
6. The four-rotor unmanned aerial vehicle intelligent obstacle avoidance method based on the guide vane is characterized in that the environment light intensity level R 2 is equal to actual light intensity/maximum light intensity, the flight area risk level R 3 is equal to 1, the distance from a high-risk area is equal to the safety distance, and the linear distance between the unmanned aerial vehicle body and the boundary of the nearest high-risk area is calculated in real time through a GPS positioning system.
7. The intelligent obstacle avoidance method of a four-rotor unmanned aerial vehicle based on a guide vane according to claim 5, wherein calculating the obstacle distance in the active avoidance mode in combination with the time difference from the emission to the reception comprises determining the capture reception time t 2 when the pressure sensor detects the sudden change of the airflow pressure signal, calculating the time difference Δt=t 2 -t 1 ;t 1 as the start time of the pressure sensor to detect the airflow pressure value, The method for identifying the type of the obstacle according to the characteristics of the reflected airflow signals in the active avoidance mode comprises the steps of carrying out characteristic analysis on the captured reflected airflow signals, extracting three core characteristic parameters of rising edge slope, peak duration and signal attenuation rate, and determining the type of the obstacle according to the core characteristic parameters; The method for calculating the obstacle distance by combining the time difference transmitted to the receiver in the active avoidance mode comprises the steps of calculating the obstacle distance according to the air flow speed v and the time difference delta t determined by an air flow speed correction algorithm, calculating the obstacle distance through a formula D= (v multiplied by delta t)/2, if more than two groups of guide plates detect the same obstacle, calculating to obtain an average value of the obstacle distance by taking more than two groups of guide plates as a final obstacle distance, calculating the azimuth angle alpha and the pitch angle beta of the obstacle by taking the signal peak value of each guide plate pressure sensor as a weight factor by adopting a weighted triangle positioning method, and comparing the obstacle distance with a preset distance to determine the active obstacle avoidance response grade.
8. The intelligent obstacle avoidance method of a four-rotor unmanned aerial vehicle based on a guide vane of claim 5, wherein the airflow speed correction algorithm corrects the airflow propagation speed based on temperature and relative humidity according to the following formula: v is the corrected air flow rate, T is the collected ambient temperature, and RH is the collected relative humidity.
9. The intelligent obstacle avoidance system of the four-rotor unmanned aerial vehicle based on the guide vane is used for realizing the intelligent obstacle avoidance method of the four-rotor unmanned aerial vehicle based on the guide vane, and comprises an unmanned aerial vehicle body, wherein the unmanned aerial vehicle body comprises a rotor protection cover, and is characterized by further comprising a guide vane sensing module, an active airflow emission module, a data processing module and a flight control module, the guide vane sensing module comprises a guide vane, a guide vane system, a pressure sensor and an angular displacement sensor, the guide vane is arranged in the guide vane, the guide vane is connected with the rotor protection cover, the guide vane system comprises a main guide vane extending along the length direction of the guide vane body and guide vanes positioned at two sides of the main guide vane, an inlet of the main guide vane is communicated with the active airflow emission module, the outlet end of the guide vane is provided with the pressure sensor, and the joint of the guide vane and the rotor protection cover is provided with the angular displacement sensor; The data processing module comprises unmanned aerial vehicle initialization operation, detecting an airflow pressure value in an airflow guide groove in the airflow guide plate through an airflow guide plate pressure sensor in a passive obstacle avoidance mode, determining an airflow angle value of the airflow guide plate influenced by airflow through an angular displacement sensor, respectively determining an airflow pressure change value and an airflow angle change value according to the airflow pressure value and the airflow angle value, comparing the airflow pressure change value with a preset pressure change threshold value and the airflow angle change value with a preset angle change threshold value, and determining whether the airflow is disturbance of a rotor wing, if not, determining a passive sensing risk level according to a peak value of the airflow pressure change value, a peak value of the airflow angle change value and a change speed; the flight control module is in signal connection with the data processing module and is used for determining different obstacle avoidance actions according to passive sensing risk levels, executing grading obstacle avoidance response according to obstacle information and realizing fault tolerance control.
10. The intelligent obstacle avoidance system of the four-rotor unmanned aerial vehicle based on the guide vane is characterized by further comprising a temperature and humidity sensor and a vibration sensor, wherein the temperature and humidity sensor is arranged on a preset groove on the surface of the guide vane body, sealant is arranged around the preset groove, and the vibration sensor is arranged at the joint of the guide vane and a rotor protection cover through a fixing piece.

Description

Intelligent obstacle avoidance method and system for four-rotor unmanned aerial vehicle based on guide vane Technical Field The invention relates to the technical field of unmanned aerial vehicle navigation, in particular to a four-rotor unmanned aerial vehicle intelligent obstacle avoidance method and system based on guide vanes. Background With the rapid development of unmanned aerial vehicles and automatic control technologies, four-rotor unmanned aerial vehicles have been widely applied to a plurality of fields due to the flexible and stable characteristics of the four-rotor unmanned aerial vehicles, in the application of the unmanned aerial vehicles, the flight of the unmanned aerial vehicles is limited by navigation technologies, and the unmanned aerial vehicles can generate various barriers in the navigation process, so that unmanned aerial vehicles with obstacle avoidance capability still have a plurality of defects at present, single-kind perception schemes generally have the problem of insufficient environmental adaptability, such as performance reduction of a vision system under low illumination, smoke dust or in the face of transparent objects, and laser radar has limitations in terms of cost, volume and reliability under severe weather, while ultrasonic and millimeter wave schemes are respectively limited by detection precision, anti-interference capability and installation compatibility. In addition, although the airflow sensing method can overcome part of environmental constraints, the existing design is not perfect in the aspects of accurate distance measurement and classification capability of obstacles and pneumatic integration with a fuselage. In the prior art, for example, chinese patent application number CN202511881645.5, publication day 2026.01.13, a system and a method for autonomous obstacle avoidance and path planning of an unmanned aerial vehicle with multi-sensor fusion are disclosed, which include obtaining a dynamic obstacle and a linear obstacle in a scanning area corresponding to a current time, normalizing the characteristics of the dynamic obstacle and the linear obstacle, correcting the normalized characteristics to obtain an obstacle score, obtaining a current obstacle avoidance priority according to the obstacle score, and updating a current path according to the obstacle avoidance priority to obtain a first path. In the above documents, the unmanned aerial vehicle obtains different paths by judging the priority of the current obstacle avoidance and according to the characteristics of the dynamic obstacle and the linear obstacle, so that the unmanned aerial vehicle can realize self-help obstacle avoidance, the obstacle avoidance mode is realized by distinguishing the obstacle to select a flight path, the obstacle distinguishing mode is realized by a visual sensor and the like, the visual sensor cannot realize more accurate determination of the distance of the obstacle in the environment with dark light, the influence of illumination and visibility is received, the shape of the obstacle is required to be determined by the visual sensor, the processing time of the visual sensor is long, the obstacle cannot be timely and accurately determined, and meanwhile, the passive air flow sensing mode is also influenced by the condition of turbulent interference of the air flow of the rotor wing of the unmanned aerial vehicle, so that the obstacle determining mode is inaccurate. Disclosure of Invention The invention provides a four-rotor unmanned aerial vehicle intelligent obstacle avoidance method and system based on guide vanes, which can be suitable for most application scenes, can effectively solve the problem of perception failure of the existing obstacle avoidance technology under extreme conditions such as low illumination, smoke, strong wind, narrow space and the like, and has good obstacle avoidance navigation effect. In order to achieve the above purpose, the invention also provides a four-rotor unmanned aerial vehicle intelligent obstacle avoidance method based on a guide vane, wherein the unmanned aerial vehicle comprises a guide vane arranged on a rotary wing, a guide groove arranged in the guide vane is connected with an active airflow emission module, and a pressure sensor and an angular displacement sensor are arranged on the guide vane, and the method comprises the following steps: S1, initializing an unmanned aerial vehicle, wherein the initializing operation comprises calibration of a reference value and presetting of an angle change threshold value and a pressure change threshold value under a passive obstacle avoidance mode, and an original route and an original flying speed are determined; S2, a passive obstacle avoidance mode is initially executed when the unmanned aerial vehicle works, in the passive obstacle avoidance mode, the pressure value of air flow in a guide groove in the guide plate is detected through a guide plate pressure sensor, the angle value of