CN111708375A - Unmanned aerial vehicle obstacle avoidance system based on laser radar and octagonal air wall algorithm - Google Patents
Unmanned aerial vehicle obstacle avoidance system based on laser radar and octagonal air wall algorithm Download PDFInfo
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Abstract
The invention relates to an unmanned aerial vehicle obstacle avoidance system based on a laser radar and an octagonal air wall algorithm, which comprises a power execution module, a microprocessor module, a sensor module, an attitude angle controller, a laser radar module and the octagonal air wall obstacle avoidance algorithm which are connected through electric signals, wherein the power execution module, the microprocessor module, the sensor module, the attitude angle controller, the laser radar module and the octagonal air wall obstacle avoidance algorithm are connected through electric signals, and: the power execution module provides power for the unmanned aerial vehicle; the microprocessor module receives the data sent by the sensor module and the instruction sent by the remote controller, makes logic judgment on the two kinds of information and controls the unmanned aerial vehicle to fly in a navigation mode; the sensor module is used for resolving the current attitude angle of the unmanned aerial vehicle; the attitude angle controller controls the unmanned aerial vehicle at an actual attitude angle by receiving a remote controller signal; the laser radar module acquires the distance and the relative angle from the obstacle to the unmanned aerial vehicle; the distance data and the angle data collected by the laser radar are processed by the octagonal air wall obstacle avoidance algorithm, accurate obstacle avoidance information is provided, and accurate obstacle avoidance of the unmanned aerial vehicle is achieved. The invention solves the problem that the data acquired by the laser radar has a wild value.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle obstacle avoidance navigation, and particularly belongs to an unmanned aerial vehicle obstacle avoidance system based on a laser radar and an improved octagonal air wall obstacle avoidance algorithm.
Background
The unmanned aerial vehicle of practical at present keeps away barrier scheme and mainly has three kinds: an obstacle avoidance scheme based on an ultrasonic sensor; an obstacle avoidance scheme based on a binocular vision sensor; obstacle avoidance scheme based on laser radar sensors.
(1) Obstacle avoidance scheme based on ultrasonic sensor:
the ultrasonic sensor is the sensor with the most extensive application scenes, such as a reversing radar and the like. The ultrasonic sensor has a certain measurement restriction angle (about 10-70 degrees), and the measurement range is 4-10 m. The ultrasonic sensor is low in price and simple in measurement principle. However, the ultrasonic waves emitted by the ultrasonic sensor are mechanical waves and are easy to attenuate and interfere, so that the measurement accuracy is low; and the data that ultrasonic sensor measured are few, are unfavorable for the unmanned aerial vehicle to keep away the barrier smoothly.
(2) Obstacle avoidance scheme based on binocular vision sensor:
the binocular vision sensor can measure the distance of the obstacle, can obtain rich image information, and can perform three-dimensional modeling on the obstacle. The binocular vision sensor has the advantages of wide measurement range, high precision and the like. Because the binocular vision sensor collects image information, the calculation amount and the data transmission amount of the data processing module are large, and the power consumption is high; the binocular vision sensor is greatly influenced by light and cannot be used in a scene with dark light.
(3) Obstacle avoidance scheme based on laser radar sensor:
the laser radar sensor can not only collect the distance of the obstacle, but also collect the relative angle of the obstacle. The method has the advantages of high precision, 360-degree measurement range, good performance in a low-light environment and the like; the disadvantage is that it is easily disturbed by strong light, but this disadvantage can be compensated by the algorithm.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the utility model provides an unmanned aerial vehicle keeps away barrier system based on laser radar and octagon air wall algorithm to solve present unmanned aerial vehicle and keep away the defect that barrier system precision is low, can not realize that unmanned aerial vehicle accurately keeps away the barrier.
The invention adopts the following technical scheme for solving the technical problems:
the invention provides an unmanned aerial vehicle obstacle avoidance system based on a laser radar and an octagonal air wall algorithm, which specifically comprises the following steps: the system comprises a power execution module, a microprocessor module, a sensor module, an attitude angle controller, a laser radar module and an octagonal air wall obstacle avoidance algorithm which are connected by electric signals, wherein: the power execution module provides power for the unmanned aerial vehicle; the microprocessor module receives the data sent by the sensor module and the instruction sent by the remote controller, makes logic judgment on the two kinds of information and controls the unmanned aerial vehicle to fly in a navigation mode; the sensor module is used for resolving the current attitude angle of the unmanned aerial vehicle; the attitude angle controller controls the unmanned aerial vehicle at an actual attitude angle by receiving a remote controller signal; the laser radar module acquires the distance and the relative angle from the obstacle to the unmanned aerial vehicle; the distance data and the angle data collected by the laser radar are processed by the octagonal air wall obstacle avoidance algorithm, accurate obstacle avoidance information is provided, and accurate obstacle avoidance of the unmanned aerial vehicle is achieved.
The power execution module consists of an electronic speed regulator, a propeller and a direct current brushless motor; the propeller is arranged on the direct current brushless motor, and the motor rotates to drive the propeller to rotate so as to provide lift force for the unmanned aerial vehicle; the electronic speed regulator is arranged between the microprocessor and the DC brushless motor, and because the PWM signal output by the microprocessor module is not large enough to drive the DC brushless motor to rotate, the electronic speed regulator needs to be added for power amplification, so that the microprocessor can output the PWM signal large enough to drive the DC brushless motor.
The microprocessor module adopts a microprocessor chip STM32F427VIT6, and abundant peripheral interfaces of the microprocessor module can communicate with sensors and data storage chips adopting different communication modes.
The sensor module include triaxial accelerometer, triaxial magnetometer and triaxial gyroscope, wherein: the three-axis accelerometer is mounted on the PIXHAWK flight control board and is used for measuring the acceleration of three axes of the unmanned aerial vehicle during flight; the three-axis magnetometer is mounted on the PIXHAWK flight control board and used for measuring the magnetic field intensity of three axes when the unmanned aerial vehicle flies; and the three-axis gyroscope is arranged on the PIXHAWK flight control board and is used for measuring the angular velocity around three axes when the unmanned aerial vehicle flies.
The invention adopts six-axis sensors ICM-20608-G and a magnetometer HMC5983, the six-axis sensors ICM-20608-G integrate two sensors of a three-axis accelerometer and a three-axis gyroscope, and the pitch angle and the roll angle of the unmanned aerial vehicle are calculated through data collected by the three-axis accelerometer; the yaw angle of the unmanned aerial vehicle is solved through data collected by the magnetometer HMC5983, and therefore attitude angle information of the current unmanned aerial vehicle during flying is obtained.
The attitude angle controller adopts a double closed-loop PID controller, the outer ring of the attitude angle controller is designed into an angle ring, the input of the angle ring is the deviation amount of an expected attitude angle and an actual attitude angle, and the output is an expected angular speed; the inner ring is designed into an angular velocity ring, the input of the angular velocity ring is the deviation amount of the expected angular velocity and the actual angular velocity, and the output is expected torque, so that the flying attitude of the unmanned aerial vehicle is controlled.
In the design of the outer ring, the expected attitude angle is the attitude angle input by the remote controller, and the actual attitude angle is the attitude angle calculated by the inertial unit.
In the inner ring design, the expected angular speed is the output of the angle ring, and the actual angular speed is the measured value of the gyroscope.
The laser radar module adopts omnidirectional laser radar SF40, and it gathers the distance and the relative angle of barrier to unmanned aerial vehicle, keeps away the barrier for follow-up unmanned aerial vehicle and provides initial data support.
The octagonal air wall obstacle avoidance algorithm comprises the following steps: collecting and combining raw range measurements by a lidar module, including storing and using the nearest range and angle measurements in 8 sectors; the width of each sector is 45 degrees, the 0 sector points to the front, the 1 sector points to the right, and so on; from these distances and angles, a fence, i.e. a two-dimensional vector array, is established around the drone, with the fence points falling on the straight line between the zones, keeping a certain distance; when no obstacle is detected by all 8 sectors, the available empty sectors will be filled with the distance from the adjacent sectors, forming a "cup" fence to protect the drone from hitting the target.
Compared with the prior art, the invention has the following main beneficial effects:
under the strong light interference, the laser radar sensor can output wrong distance data, and the unmanned aerial vehicle is influenced to accurately avoid the obstacle. Therefore, the invention provides a later algorithm treatment for the defect of the laser radar: and filtering the original data acquired by the laser radar by using a median filter, a low-pass filter and a sliding window average filter in sequence. Experiments prove that after filtering by a median filter, a low-pass filter and a sliding window average filter, outlier points in the distance data are filtered, so that the distance data are more accurate. Make unmanned aerial vehicle can be more accurate keep away the barrier.
Drawings
Fig. 1 is an overall scheme of an unmanned aerial vehicle obstacle avoidance system.
Fig. 2 is a physical diagram of an SF40 omnidirectional lidar.
Fig. 3 is an octagonal air wall obstacle avoidance algorithm.
Fig. 4 shows an obstacle avoidance method for an unmanned aerial vehicle when no obstacle is detected.
Fig. 5 shows data collected by the optimized front octagonal air wall obstacle avoidance algorithm. Wherein: fig. 5-1 to 5-8 are schematic diagrams of waveforms of specific data collected by the optimized front octagonal air wall obstacle avoidance algorithm.
Fig. 6 shows the raw data filtering process.
Fig. 7 is data collected by the optimized octagonal air wall obstacle avoidance algorithm. Wherein: fig. 7-1 to 7-8 are schematic diagrams of waveforms of specific data acquired by the optimized octagonal air wall obstacle avoidance algorithm.
Fig. 8 is a flow chart of obstacle avoidance procedure design.
Fig. 9 is a diagram showing changes in the distance of the obstacle to the unmanned aerial vehicle, the input value of the pitch channel of the remote controller, and the actual pitch angle. Wherein: fig. 9-1 is the distance of the obstacle facing the direction of the drone, fig. 9-2 is the input value of the pitch channel of the remote controller, and fig. 9-3 is the variation graph of the actual pitch angle.
In fig. 2: 1. a laser module; 2. a brushless motor module.
Detailed Description
The invention provides an unmanned aerial vehicle obstacle avoidance system based on a laser radar and an improved octagonal air wall algorithm, wherein an SF40 omnidirectional laser radar sensor is selected by the system to obtain distance and angle information of obstacles in the current flight environment, then the octagonal air wall obstacle avoidance algorithm is adopted to carry out real-time obstacle avoidance, and finally the system is combined with a four-rotor unmanned aerial vehicle flight control system to finish autonomous obstacle avoidance flight of a four-rotor aircraft. In order to overcome the defect that the laser radar is easily affected by interference of strong light, interference points generated under the strong light are filtered by sequentially adding a median filter, a low-pass filter and a sliding window average filter, so that the unmanned aerial vehicle can accurately avoid obstacles under the strong light.
The invention is further illustrated, but not limited, by the following examples and the accompanying drawings.
The unmanned aerial vehicle obstacle avoidance system based on the laser radar and the improved octagonal air wall obstacle avoidance algorithm is improved on the basis of PIXHAWK open source flight control, is suitable for autonomous obstacle avoidance in the actual flight process of the unmanned aerial vehicle, and is particularly suitable for a quad-rotor unmanned aerial vehicle to accurately avoid obstacles.
The invention provides an unmanned aerial vehicle obstacle avoidance system based on a laser radar and an improved octagonal air wall obstacle avoidance algorithm, which comprises a power execution module, a microprocessor module, a sensor module, an attitude angle controller, a laser radar module and the octagonal air wall obstacle avoidance algorithm which are connected through electric signals, wherein: the power execution module provides power for the unmanned aerial vehicle; the microprocessor module receives the data sent by the sensor module and the instruction sent by the remote controller, makes logic judgment on the two kinds of information and controls the unmanned aerial vehicle to fly in a navigation mode; the sensor module comprises a three-axis accelerometer, a three-axis magnetometer and a three-axis gyroscope and is used for resolving the current attitude angle of the unmanned aerial vehicle; the attitude angle controller controls the unmanned aerial vehicle at an actual attitude angle by receiving a remote controller signal; the laser radar module acquires the distance and the relative angle from the obstacle to the unmanned aerial vehicle; the distance data and the angle data collected by the laser radar are processed by the octagonal air wall obstacle avoidance algorithm, accurate obstacle avoidance information is provided, and accurate obstacle avoidance of the unmanned aerial vehicle is achieved.
The invention has two sub-obstacle avoidance systems, as shown in fig. 1.
The first sub-obstacle avoidance system is a data processing system and consists of a laser radar, a data processing module and a communication port. The main functions are as follows: the method comprises the steps of firstly obtaining the distance and the angle between an unmanned aerial vehicle and a barrier through a laser radar, then processing collected data through a data processing module, and finally sending the processed data to a flight control system through a communication port.
The second sub-obstacle avoidance system is a flight control system and consists of a PIXHAWK flight control board and a remote controller. The main functions are as follows: and reading distance and angle information sent by the data processing system, receiving a control signal sent by the remote controller, judging by combining data and a remote control signal sent by the data processing system, and determining whether the unmanned aerial vehicle executes an obstacle avoidance attitude or flies according to the remote control signal.
The laser radar SF40 used in the present invention is an existing sensor. SF40 is a two-dimensional laser radar with low power consumption and a detection range of 360 degrees, the effective measurement distance of the laser radar is 0-100m, and the measurement angle resolution is less than 1 degree. The generated 2-dimensional point cloud data can be applied to map, coordinate and environment modeling. SF40 uses detection frequencies of 1Hz, 2.25Hz, or 4.5Hz, which correspond to range resolutions of 0.03m, 0.06m, and 0.12 m.
The structure of lidar SF40 is shown in fig. 2. The laser module 1 is arranged, so that the laser radar SF40 can emit and receive laser; be equipped with brushless motor module 2, it drives laser module 1 and rotates, lets laser radar SF40 can gather the distance information in the 360 degrees scopes.
The power execution module consists of an electronic speed regulator, a propeller and a direct current brushless motor. The direct-current brushless motor not only has the advantages of large starting torque, wide speed regulation range and the like of the direct-current brush motor, but also abandons a mechanical reversing structure and uses an electronic converter, so that the rotating speed of the motor can be controlled more accurately. Because the size of the PWM modulation signal output by the microprocessor module is not enough to drive the dc brushless motor to rotate, the electronic speed regulator needs to be added to amplify the power of the internal field effect transistor of PWM and the microprocessor, so that the microprocessor can output the PWM modulation signal large enough to drive the dc brushless motor. Install the screw on DC brushless motor, the motor is rotatory to drive the screw rotatory, provides lift for four rotor unmanned aerial vehicle. The brushless DC Motor is Motor6010-KV270 Motor from Kobe, and the electronic speed regulator is SkyWalker-40A.
The microprocessor chip of the microprocessor module selects STM32F427VIT 6. The STM32F427VIT6 has an ARM Cortex-M4 kernel with the main frequency as high as 168MHz, a floating point arithmetic unit and an executable full Digital Signal Processor (DSP) instruction set, so that the data processing capability of the Processor is greatly improved; the STM32F427VIT6 comprises an on-chip Flash Memory unit of 2MB, a Static Random Access Memory (SRAM) of 256kB, an SRAM of 4kB and a Pseudo Static Random Access Memory (PSRAM), and can store codes and data required by a flight control system; the STM32F427VIT6 has a rich peripheral interface, and can communicate with sensors and data storage chips using different communication methods.
The sensor module selects the six-axis sensor ICM-20608-G and the magnetometer HMC 5983. The six-axis sensor ICM-20608-G integrates two sensors, namely a three-axis accelerometer and a three-axis gyroscope, and the pitch angle and the roll angle of the unmanned aerial vehicle are calculated through data collected by the three-axis accelerometer; the yaw angle of the unmanned aerial vehicle is solved through data collected by the magnetometer HMC5983, and therefore the attitude angle information of the current unmanned aerial vehicle is obtained.
And the attitude angle controller selects a double closed-loop PID controller. The outer ring of the controller is designed as an angle ring, the input of the angle ring is the deviation amount of an expected attitude angle (the attitude angle input by the remote controller) and an actual attitude angle (the attitude angle calculated by the inertial unit), and the output is an expected angular speed; the inner ring of the controller is designed as an angular velocity ring, the input of the angular velocity ring is the deviation amount of the expected angular velocity (the output of the angular ring) and the actual angular velocity (the measured value of the gyroscope), and the output of the angular velocity ring is expected torque, so that the attitude of the quad-rotor unmanned aerial vehicle is controlled. This kind of two closed-loop cascade PID controllers is favorable to improving the stability and the accuracy nature of system, can control the accurate stable flight of four rotor unmanned aerial vehicle. The power execution module, the sensor module, the microprocessor module and the attitude angle controller module form a flight control system of the unmanned aerial vehicle.
The lidar module selects an omnidirectional lidar SF 40. The distance and the relative angle between the obstacle and the unmanned aerial vehicle are collected by the omnidirectional laser radar SF40, and initial data support is provided for the follow-up unmanned aerial vehicle to avoid the obstacle.
The obstacle avoidance algorithm of the octagonal air wall comprises the following steps: the omnidirectional lidar sensor SF40 collects raw range measurements which are combined so that only the nearest ranges and angles within 8 sectors are stored and used. Each sector has a width of 45 degrees, with 0 sector pointing forward, 1 sector pointing to the right, and so on. From these distances and angles, a fence (a two-dimensional vector array) is established around the drone. The barrier points fall on a straight line between the zones, maintaining a certain distance, as shown in fig. 3. When all 8 sectors do not detect an obstacle, the empty sector (if available) will be filled with the distance to the neighboring sector. This advantageously creates a "cup-like" barrier that is more likely to protect the drone from hitting a target, as shown in fig. 4.
Setting obstacle avoidance distance to be 5m, setting omnidirectional laser radar SF40 detection farthest distance to be 20m, and enabling the laser radar to collect data. The laser radar collects 8 sectors, the number of data is used as an abscissa, the distance is used as an ordinate, and a curve is drawn. 5-1 to 5-8 show the distances from obstacles in sectors 0-7 to the drone, respectively, as collected by lidar SF 40. As can be seen from fig. 5, the maximum distance in the data collected by the lidar is 20m, but the minimum distance in the data is somewhat less than 5m, because the wave velocity of the omnidirectional lidar is close to the frequency of sunlight, and is easily interfered by the sunlight, so that wrong data is output. Wrong data can influence unmanned aerial vehicle and keep away barrier flight, consequently will optimize the data that laser radar gathered, and the wrong data of filtering lets unmanned aerial vehicle can be accurate keep away the barrier.
The obstacle avoidance algorithm for the octagonal air wall comprises the following steps: the median filter, the low-pass filter and the sliding window average filter are added in sequence to filter the data of the eight sectors, so that the problem that the data in the eight sectors have wild values is solved.
The invention relates to a specific optimization method for an octagonal air wall obstacle avoidance algorithm, which comprises the following steps: the wave speed of the omnidirectional laser radar is close to the frequency of sunlight, and the omnidirectional laser radar is easily interfered by the sunlight, so that error data is output. Wrong data can influence unmanned aerial vehicle and keep away barrier flight, consequently will optimize the data that laser radar gathered, and the wrong data of filtering lets unmanned aerial vehicle can be accurate keep away the barrier. The invention adopts a median filter, a low-pass filter and a sliding window average filter to process data. The process of filtering the raw data is shown in fig. 6.
The distance data acquired by the optimized octagonal air wall obstacle avoidance algorithm is shown in fig. 7, wherein fig. 7-1 to 7-8 respectively show the distances from obstacles in 0-7 sectors acquired by the optimized laser radar SF40 to the unmanned aerial vehicle. As can be seen from comparison between fig. 5 and fig. 7, after the distance data of 8 sectors are processed by the median filter, the low-pass filter and the sliding window averaging filter, the data with the distance far less than 5m are filtered out, which shows that the optimization algorithm adopted by the invention can effectively remove noise data, thereby outputting accurate distance data and providing data support for the precise obstacle avoidance of the unmanned aerial vehicle.
The software flow design of the unmanned gyroplane obstacle avoidance system is shown in fig. 8. After the unmanned aerial vehicle flight control system is electrified and operated, the distance information from the unmanned aerial vehicle to the obstacle and the input remote control signal are read in a circulating mode. When the distance information is larger than the set safe distance, the input remote control signal is subjected to attitude calculation, and the unmanned aerial vehicle is controlled to normally fly according to the remote control signal. When the distance information is smaller than the set safe distance, carrying out attitude calculation on the input remote control signal: if the remote control signal requires that the unmanned aerial vehicle is far away from the obstacle, the unmanned aerial vehicle flies normally according to the remote control signal; if the remote control signal requires that the unmanned aerial vehicle is close to the barrier, the unmanned aerial vehicle is subjected to attitude calculation according to a preset safety distance, and the unmanned aerial vehicle is controlled to be far away from the barrier. After the unmanned aerial vehicle returns to the safe distance, the unmanned aerial vehicle continues to carry out attitude calculation according to the input signal of the remote controller, and the unmanned aerial vehicle is controlled to fly. This procedure is continuously looping and continuously judging.
As shown in fig. 9, wherein: fig. 9-1 is the distance of the obstacle facing the direction of the drone, fig. 9-2 is the input value of the pitch channel of the remote controller, and fig. 9-3 is the variation graph of the actual pitch angle. From fig. 9-1,9-2 and 9-3, it can be seen that the actual pitch angle varies with the distance of the obstacle in front of the drone and with the input from the remote control. The forward acceleration of unmanned aerial vehicle self is adjusted by the change of pitch angle to make unmanned aerial vehicle governing speed, reach and keep away the barrier effect.
The method analyzes the reason that the distance data acquired by the laser radar has the wild value, namely the wave speed of the laser radar is close to the frequency of sunlight and is easily interfered by the sunlight, so that error data are output; the method for filtering the acquired original distance data is provided, namely a median filter, a low-pass filter and a sliding window average filter are added in sequence to filter the original distance data, so that the problem that the data acquired by the laser radar has a wild value is solved.
Claims (10)
1. The utility model provides an unmanned aerial vehicle keeps away barrier system based on laser radar and octagon air wall algorithm, characterized by includes that the power execution module, microprocessor module, sensor module, attitude angle controller, laser radar module, the octagon air wall that link to each other with the signal of telecommunication keep away the barrier algorithm, wherein: the power execution module provides power for the unmanned aerial vehicle; the microprocessor module receives the data sent by the sensor module and the instruction sent by the remote controller, makes logic judgment on the two kinds of information and controls the unmanned aerial vehicle to fly in a navigation mode; the sensor module is used for resolving the current attitude angle of the unmanned aerial vehicle; the attitude angle controller controls the unmanned aerial vehicle at an actual attitude angle by receiving a remote controller signal; the laser radar module acquires the distance and the relative angle from the obstacle to the unmanned aerial vehicle; the distance data and the angle data collected by the laser radar are processed by the octagonal air wall obstacle avoidance algorithm, accurate obstacle avoidance information is provided, and accurate obstacle avoidance of the unmanned aerial vehicle is achieved.
2. The unmanned aerial vehicle obstacle avoidance system of claim 1, characterized by: the power execution module consists of an electronic speed regulator, a propeller and a direct current brushless motor; the propeller is arranged on the direct current brushless motor, and the motor rotates to drive the propeller to rotate so as to provide lift force for the unmanned aerial vehicle; the electronic speed regulator is arranged between the microprocessor and the DC brushless motor, so that the microprocessor can output a PWM signal with enough magnitude to drive the DC brushless motor.
3. The unmanned aerial vehicle obstacle avoidance system of claim 1, characterized by: the microprocessor module adopts a microprocessor chip STM32F427VIT6, and the abundant peripheral interfaces of the microprocessor module can communicate with sensors and data storage chips adopting different communication modes.
4. The unmanned aerial vehicle obstacle avoidance system of claim 1, wherein the sensor modules comprise a three-axis accelerometer, a three-axis magnetometer, and a three-axis gyroscope, all mounted on the pixawk flight control panel, wherein: the three-axis accelerometer is used for measuring the acceleration of three axes when the unmanned aerial vehicle flies; the three-axis magnetometer is used for measuring the magnetic field intensity of three axes when the unmanned aerial vehicle flies; the three-axis gyroscope is used for measuring the angular velocity around three axes when the unmanned aerial vehicle flies.
5. The unmanned aerial vehicle obstacle avoidance system of claim 4, wherein six-axis sensors ICM-20608-G and a magnetometer HMC5983 are adopted, the six-axis sensors ICM-20608-G integrate two sensors, namely a three-axis accelerometer and a three-axis gyroscope, and the pitch angle and the roll angle of the unmanned aerial vehicle are calculated through data collected by the three-axis accelerometer; the yaw angle of the unmanned aerial vehicle is solved through data collected by the magnetometer HMC5983, and therefore attitude angle information of the current unmanned aerial vehicle during flying is obtained.
6. The unmanned aerial vehicle obstacle avoidance system of claim 1, characterized by: the attitude angle controller adopts a double closed-loop PID controller, the outer ring of the attitude angle controller is designed into an angle ring, the input of the angle ring is the deviation amount of an expected attitude angle and an actual attitude angle, and the output is an expected angular velocity; the inner ring is designed into an angular velocity ring, the input of the angular velocity ring is the deviation amount of the expected angular velocity and the actual angular velocity, and the output is expected torque, so that the flying attitude of the unmanned aerial vehicle is controlled.
7. The unmanned aerial vehicle obstacle avoidance system of claim 6, wherein: in the design of the outer ring, the expected attitude angle is the attitude angle input by the remote controller, and the actual attitude angle is the attitude angle calculated by the inertial unit.
8. The unmanned aerial vehicle obstacle avoidance system of claim 6, wherein: in the inner ring design, the desired angular velocity is the output of the angle ring, and the actual angular velocity is the measurement of the gyroscope.
9. The unmanned aerial vehicle obstacle avoidance system of claim 1, characterized by: the laser radar module adopts omnidirectional laser radar SF40, and it gathers the distance and the relative angle of barrier to unmanned aerial vehicle, keeps away the barrier for follow-up unmanned aerial vehicle and provides initial data support.
10. The unmanned aerial vehicle obstacle avoidance system of claim 1, wherein the octagonal air wall obstacle avoidance algorithm is: collecting and combining raw range measurements by a lidar module, including storing and using the nearest range and angle measurements in 8 sectors; the width of each sector is 45 degrees, the 0 sector points to the front, the 1 sector points to the right, and so on; from these distances and angles, a fence, i.e. a two-dimensional vector array, is established around the drone, with the fence points falling on the straight line between the zones, keeping a certain distance; when no obstacle is detected by all 8 sectors, the available empty sectors will be filled with the distance from the adjacent sectors, forming a "cup" fence to protect the drone from hitting the target.
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| CN113138397B (en) * | 2021-06-01 | 2023-12-26 | 中国计量大学 | Unmanned aerial vehicle keeps away barrier device and unmanned aerial vehicle |
| CN115327534A (en) * | 2022-10-13 | 2022-11-11 | 湖南纳雷科技有限公司 | Unmanned aerial vehicle obstacle avoidance radar system and control method |
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