CN116755458A - Unmanned aerial vehicle system of autonomous path planning and obstacle avoidance system - Google Patents
Unmanned aerial vehicle system of autonomous path planning and obstacle avoidance system Download PDFInfo
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Abstract
The invention relates to the technical field of unmanned aerial vehicles, and discloses an unmanned aerial vehicle system of an autonomous path planning and obstacle avoidance system, which comprises: the sensor module is connected with the unmanned aerial vehicle through a signal and the Internet of things and is used for sensing obstacles and topographic information of surrounding environments; the map construction module is used for processing and analyzing the data acquired by the sensor module, and the system can generate a map to describe the surrounding environment of the unmanned aerial vehicle; the path planning module is used for determining an optimal path which the unmanned aerial vehicle should take based on the generated map and the target position, so that collision is avoided; the control and monitoring module is used for carrying out flight control on the unmanned aerial vehicle according to the planned path after the path planning is completed, and carrying out real-time tracking and monitoring; the positioning module can be used for carrying out real-time positioning monitoring on the position of the unmanned aerial vehicle; and the early warning module is used for protecting the unmanned aerial vehicle from interference and key components of attack.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle system of an autonomous path planning and obstacle avoidance system.
Background
The unmanned aerial vehicle system is an autonomous flight aviation system, realizes unmanned aerial vehicle control, navigation and task execution by utilizing advanced technologies and components, and refers to an automatic pilot of the unmanned aerial vehicle through a flight control and management subsystem, and is responsible for receiving ground or satellite instructions, controlling parameters such as flight attitude, altitude, speed and the like of the unmanned aerial vehicle, and executing a preset flight plan. The unmanned aerial vehicle system can be used for exploring and detecting areas which cannot be or are inconvenient to visit.
However, in some areas, the unmanned aerial vehicle may be blocked, for example, in some areas, electromagnetic interference sources such as radar, communication equipment and the like may exist; some areas are complicated, more barriers exist, and normal flight of the unmanned aerial vehicle is affected.
The interference source may interfere with the communication, navigation and sensor systems of the unmanned aerial vehicle, affect the control and data collection capacity of the unmanned aerial vehicle, and may cause inaccuracy in positioning of the unmanned aerial vehicle, thereby affecting the effects of navigation and flight monitoring; the obstacle is divided into a static obstacle and a dynamic obstacle, different influences can be caused to the unmanned aerial vehicle aiming at different obstacles, the unmanned aerial vehicle can collide when serious, and the unmanned aerial vehicle is damaged.
Therefore, the inventor proposes an unmanned aerial vehicle system which can protect unmanned aerial vehicles and can avoid obstacles and has autonomous path planning and obstacle avoidance capability.
Disclosure of Invention
The invention provides an unmanned aerial vehicle system of an autonomous path planning and obstacle avoidance system, which is used for solving the technical problems in the background technology.
The invention provides the following technical scheme: unmanned aerial vehicle system of autonomous path planning and obstacle avoidance system, unmanned aerial vehicle system includes:
the sensor module is connected with the unmanned aerial vehicle through a signal and the Internet of things and is used for sensing obstacles and topographic information of surrounding environments;
the map construction module is used for processing and analyzing the data acquired by the sensor module, and the system can generate a map to describe the surrounding environment of the unmanned aerial vehicle;
the path planning module is used for determining an optimal path which the unmanned aerial vehicle should take based on the generated map and the target position, so that collision is avoided;
the control and monitoring module is used for carrying out flight control on the unmanned aerial vehicle according to the planned path after the path planning is completed, and carrying out real-time tracking and monitoring;
the positioning module can be used for carrying out real-time positioning monitoring on the position of the unmanned aerial vehicle;
and the early warning module is used for protecting the unmanned aerial vehicle from interference and key components of attack.
Preferably, the sensor module may sense static and dynamic obstacles;
the static obstacle is perceived through a camera, a laser radar and an ultrasonic sensor;
cameras are one of the most common perception sensors, they help unmanned aerial vehicles acquire visual information of the environment, can provide image and video data, and can be used for map construction, target detection, gesture control and navigation tasks;
the laser radar uses laser beams to measure the distance and the position of surrounding objects, generates accurate point cloud data, can provide high-precision three-dimensional environment perception, and helps an unmanned plane to detect obstacles, establish a map and conduct distance measurement and obstacle avoidance decision;
the ultrasonic sensor is used for measuring the distance of an object by sending and receiving ultrasonic signals, detecting and avoiding obstacles at a close distance and avoiding collision with static obstacles.
Preferably, the dynamic obstacle is sensed by a variety of sensors, including:
infrared sensors, which can detect thermal radiation from surrounding objects for detecting humans, animals, and other heat sources, are useful for target detection and obstacle avoidance in low light conditions or in dense vegetation areas;
radar sensors, which use electromagnetic waves to detect the position and movement of objects, can provide a detection capability over longer distances, and are very effective for target detection and obstacle avoidance in complex weather conditions or in environments where visible light is limited;
the weather sensor is used for measuring weather conditions of the environment, is very important for flight safety and path planning, and avoids influencing the stability and performance of the unmanned aerial vehicle;
microphones and sound sensors that may be used for sound localization and tracking, which may be used to detect sound sources at a remote location, thereby helping the drone to avoid potential collisions;
the gesture sensor is used for measuring the gesture and the direction of the unmanned aerial vehicle, and is important for flight stability, navigation and gesture control.
Preferably, the map construction module may be divided into a two-dimensional map and a three-dimensional map;
the two-dimensional map adopts a two-dimensional grid map, in the two-dimensional grid map, the environment is divided into discrete grids, each grid can represent an air space, an obstacle and other environment characteristics, and a sensor module of the unmanned aerial vehicle can identify the obstacle and update the corresponding grid of the map for path planning, obstacle avoidance and navigation;
the three-dimensional map adopts a three-dimensional point cloud map, in which the environment is represented as a set of discrete point cloud data, each point cloud comprises three-dimensional coordinates and other attribute information, the sensor module captures the point cloud data of the surrounding environment and processes and fuses the data, so that an accurate three-dimensional map can be generated, and the three-dimensional map comprises geometric and semantic information of obstacles, terrains and target objects, and is very useful for navigation, obstacle avoidance and target recognition of an unmanned aerial vehicle.
Preferably, the path planning module further comprises a path planning algorithm, wherein the path planning module determines an optimal path to be taken by the unmanned aerial vehicle through the path planning algorithm based on the generated map and the target position.
Preferably, the path planning algorithm further comprises:
dijkstra algorithm, which is a breadth-first search algorithm for finding the shortest path from the origin to all other nodes;
the algorithm A is a heuristic search algorithm, and combines the shortest path search of the Dijkstra algorithm and the estimated value of a heuristic function;
genetic algorithm, which is an optimization algorithm based on biological evolution theory.
Preferably, the control and monitoring module further comprises:
the flight control module receives the path planning result and converts the path planning result into a control command of the unmanned aerial vehicle so as to realize flying along the planned path, wherein the flight control module is responsible for controlling the gesture, the speed and the position parameters of the unmanned aerial vehicle so as to ensure that the unmanned aerial vehicle flies according to the planned path;
the flight monitoring module can monitor the current flight state of the unmanned aerial vehicle in real time so as to ensure the safety of the unmanned aerial vehicle in the flight process.
Preferably, the positioning module adopts a Global Positioning System (GPS), an Inertial Navigation System (INS) and a visual positioning technology, tracks the position information of the unmanned aerial vehicle in real time, and is connected with the flight monitoring module in real time.
Preferably, the early warning module comprises interference detection and anti-interference measures;
the interference detection can monitor and analyze the electromagnetic environment around the unmanned aerial vehicle so as to detect whether an interference signal exists;
the anti-interference measure can resist interference signals when the unmanned aerial vehicle receives the interference signals, for example, for radio interference, frequency hopping, power control, adaptive modulation and other technologies can be used for maintaining the stability of communication.
The invention has the following beneficial effects:
a sensor module: environmental awareness and obstacle detection are provided to avoid collisions and to achieve safe flight.
And a map construction module: and (3) establishing a map, and providing accurate environment information for path planning, obstacle avoidance and target identification.
And a path planning module: based on the generated map and the target position, an optimal path of the unmanned aerial vehicle is determined, collision is avoided, and safe navigation is realized.
Control and monitoring module: the flight control and monitoring are realized, and the flight safety and stability are ensured.
And a positioning module: and the position of the unmanned aerial vehicle is positioned and monitored in real time, and navigation and flight monitoring are supported.
And the early warning module is used for: monitoring and countering the interference signals, and protecting the unmanned aerial vehicle from interference and attack.
The effects cooperate together, reliable environment sensing, navigation and safety protection capability are provided for the unmanned aerial vehicle system, and the performance and application range of the unmanned aerial vehicle are improved.
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FIG. 1 is a schematic diagram of a system according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Examples
Referring to fig. 1, an unmanned aerial vehicle system of an autonomous path planning and obstacle avoidance system, the unmanned aerial vehicle system comprising:
the sensor module is connected with the unmanned aerial vehicle through signals and the Internet of things and is used for sensing obstacles and terrain information of surrounding environments, wherein the sensor module can sense static obstacles and dynamic obstacles; the static obstacle is perceived through camera, laser radar and ultrasonic sensor, and the dynamic obstacle is perceived through infrared sensor, radar sensor, meteorological sensor, microphone and sound sensor and attitude sensor, wherein through the sensor module of being connected with unmanned aerial vehicle signal and thing networking, static obstacle and the dynamic obstacle in the real-time perception surrounding environment can provide critical environmental information to help unmanned aerial vehicle avoid the obstacle, optimize the flight route, improve flight security and autonomous performance.
Cameras are one of the most common perception sensors, which help unmanned aerial vehicles acquire visual information of the environment, can provide image and video data, and can be used for map construction, target detection, gesture control and navigation tasks, which are very important for autonomous navigation and target positioning of unmanned aerial vehicles in unknown environments.
The laser radar uses laser beams to measure the distance and the position of surrounding objects, generates accurate point cloud data, can provide high-precision three-dimensional environment perception, and helps an unmanned plane to detect obstacles, establish a map and conduct distance measurement and obstacle avoidance decision; the ultrasonic sensor measures the distance of an object by sending and receiving ultrasonic signals, is used for detecting and avoiding obstacles at a close distance, and avoids collision with static obstacles; the laser radar and the ultrasonic sensor are used as perception sensors of the unmanned aerial vehicle, play an important role in environmental perception, obstacle detection, obstacle avoidance decision and the like, and by providing high-precision three-dimensional environmental information and distance measurement, the perception capability of the unmanned aerial vehicle is expanded, and the flight safety and autonomy are improved.
Infrared sensors, which can detect thermal radiation from surrounding objects for detecting humans, animals, and other heat sources, are useful for target detection and obstacle avoidance in low light conditions or in dense vegetation areas; the radar sensor is used for detecting the position and the movement of an object, can provide a detection capability of a longer distance, is very effective for target detection and obstacle avoidance under a complex weather condition or in a visible light limited environment, can provide speed and movement information of a target, is very useful for track planning, target tracking and collaborative flight of an unmanned aerial vehicle, and can make more accurate decisions such as avoidance, tracking or avoidance by acquiring the speed and the movement track of the target object in real time; the infrared sensor and the radar sensor are used as the expansion function of the perception sensor, can provide wider application and benefit, have advantages under low illumination, dense vegetation, complex weather and other environmental conditions, and provide more comprehensive support for target detection, obstacle avoidance decision and task execution of the unmanned aerial vehicle.
The weather sensor is used for measuring weather conditions of the environment, is very important for flight safety and path planning, and avoids influencing the stability and performance of the unmanned aerial vehicle; microphones and sound sensors that may be used for sound localization and tracking, which may be used to detect sound sources at a remote location, thereby helping the drone to avoid potential collisions; the gesture sensor is used for measuring the gesture and direction of the unmanned aerial vehicle and is important for flight stability, navigation and gesture control; meteorological sensors, microphones, and sound sensors, as well as attitude sensors, are extensions to sensor modules that provide additional functionality and information to help the unmanned aerial vehicle perceive the surrounding environment, avoid potential collision risks, and achieve stability and accuracy of flight, and the integrated application of these sensors can improve the unmanned aerial vehicle's flight safety, autonomy, and mission performance.
The system comprises a map construction module, a sensor module and a navigation module, wherein the map construction module is used for processing and analyzing data acquired by the sensor module, the system can generate a map to describe the environment around the unmanned aerial vehicle, the map construction module can be divided into a two-dimensional map and a three-dimensional map, the two-dimensional map adopts a two-dimensional grid map, the environment is divided into discrete grids in the two-dimensional grid map, each grid can represent an air space, an obstacle and other environmental characteristics, and the sensor module of the unmanned aerial vehicle can identify the obstacle and update the corresponding grid of the map for path planning, obstacle avoidance and navigation; the three-dimensional map adopts a three-dimensional point cloud map, in which the environment is represented as a set of discrete point cloud data, each point cloud comprises three-dimensional coordinates and other attribute information, the sensor module captures the point cloud data of the surrounding environment and processes and fuses the data, so that an accurate three-dimensional map can be generated, and the three-dimensional map comprises geometric and semantic information of obstacles, terrains and target objects, and is very useful for navigation, obstacle avoidance and target recognition of an unmanned aerial vehicle.
The map construction module is used for converting the data acquired by the sensor module into a visual map to help the unmanned aerial vehicle understand and recognize the environment, and the maps can be used for tasks such as path planning, obstacle avoidance decision, navigation and target recognition, and provide more comprehensive and accurate environment perception and decision support, so that the autonomy, safety and execution capacity of the unmanned aerial vehicle are enhanced.
And the path planning module is used for determining an optimal path which the unmanned aerial vehicle should take based on the generated map and the target position, avoiding collision, and the output of the path planning module is a discrete path which is usually composed of a series of coordinate points or path nodes. The unmanned plane can navigate and fly according to the path, guide flying along the path, avoid the barrier and finally reach the target position; the path planning module further comprises a path planning algorithm, wherein the path planning algorithm considers factors such as the length, time, flight safety, efficiency and the like of the path based on the generated map and the target position, so as to generate a path meeting the requirements, and the path planning algorithm is used for determining the optimal path to be taken by the unmanned aerial vehicle.
The path planning algorithm further includes:
dijkstra algorithm, which is a breadth-first search algorithm for finding the shortest path from the origin to all other nodes;
algorithm code of Dijkstra algorithm:
the a (a-star algorism) Algorithm, which is a heuristic search Algorithm combining the shortest path search of Dijkstra Algorithm and the estimated value of heuristic function, is used to find the shortest path from the starting point to the target node, and guides the search process by estimating the remaining cost from the starting point to the target node.
Algorithm code of algorithm a:
genetic algorithm, which is an optimization algorithm based on biological evolution theory, searching the solution space of the problem by simulating natural selection, crossover, mutation and other operations;
algorithm code of genetic algorithm:
the control and monitoring module is used for carrying out flight control on the unmanned aerial vehicle according to a planned path after the path planning is completed, carrying out real-time tracking and monitoring, and converting a path planning result into an actual flight control command of the unmanned aerial vehicle and monitoring the flight state of the unmanned aerial vehicle in real time to ensure the safety; the control and monitoring module further comprises: the flight control module receives the path planning result and converts the path planning result into a control command of the unmanned aerial vehicle so as to realize flying along the planned path, wherein the flight control module is responsible for controlling the gesture, speed and position parameters of the unmanned aerial vehicle so as to ensure that the unmanned aerial vehicle flies according to the planned path, and particularly, the flight control module can adjust the pitch angle, the roll angle and the yaw angle of the unmanned aerial vehicle and control the thrust and the course of the unmanned aerial vehicle so as to realize accurate flight path tracking; the flight monitoring module can monitor the current flight state of the unmanned aerial vehicle in real time so as to ensure the safety of the unmanned aerial vehicle in the flight process, and if the unmanned aerial vehicle deviates from a planned path or approaches a dangerous area, the flight monitoring module can trigger a corresponding alarm or an automatic control mechanism so as to avoid potential flight accidents or collisions.
The control and monitoring module is usually in close fit with the flight controller (Flight Controller) and the sensor module, the flight controller is responsible for receiving flight control commands and adjusting the power system and control surface of the unmanned aerial vehicle, the flight behavior of the unmanned aerial vehicle is actually controlled, the sensor module provides real-time environment sensing and unmanned aerial vehicle state information, necessary data support is provided for the control and monitoring module, the accuracy, instantaneity and reliability of flight control are required to be considered in the design of the whole control and monitoring module, and meanwhile, the accurate monitoring and safety protection of the flight state of the unmanned aerial vehicle are guaranteed, so that the unmanned aerial vehicle can fly according to a planned path and timely adjustment and decision are made in the flight process so as to cope with possible flight obstacle and risk.
The positioning module can perform real-time positioning monitoring on the position of the unmanned aerial vehicle, adopts a Global Positioning System (GPS) (the GPS is a widely used positioning technology and provides higher positioning precision and global coverage), an Inertial Navigation System (INS) (the inertial navigation system uses an Inertial Measurement Unit (IMU) to measure the acceleration and the angular velocity of the unmanned aerial vehicle and calculates the position and the attitude information of the unmanned aerial vehicle through integration) and a visual positioning technology, tracks the position information of the unmanned aerial vehicle in real time and is connected with the flight monitoring module in real time.
The positioning module plays a vital role in the unmanned aerial vehicle system, and the positioning information of the unmanned aerial vehicle is tracked and monitored in real time by using technologies such as GPS, INS and visual positioning, and is connected with the flight monitoring module in real time, so that accurate positioning and flight state monitoring are realized, and the unmanned aerial vehicle flight control precision and safety are improved.
And the early warning module is used for protecting the unmanned aerial vehicle from being interfered and attacked by key components and comprises interference detection and anti-interference measures. The interference detection can monitor and analyze the electromagnetic environment around the unmanned aerial vehicle to detect whether an interference signal exists, whether interference exists can be judged by receiving and analyzing radio frequency spectrum, detecting intensity and frequency change of the radio signal and the like, and once the interference signal is detected, the early warning module triggers corresponding reaction measures;
when the unmanned aerial vehicle receives an interference signal, the anti-interference measures can resist the interference signal, for example, for radio interference, the stability of communication can be kept by using frequency hopping, power control, adaptive modulation and other technologies, and for different types of interference, different anti-interference technologies are adopted, for example:
for radio interference: techniques such as frequency hopping, frequency scanning, adaptive modulation, etc. may be employed to select and use interference-free frequency communications, or signal filtering, suppression, and interference cancellation techniques may be employed to reduce the impact of interfering signals on the communication system.
For other types of interfering signals (e.g., electromagnetic interference, optical interference, etc.): shielding measures, filters, interferer positioning, and interferer interference techniques may be employed to mitigate or eliminate the effects of the interfering signals.
The goal of the anti-jamming measure is to maintain the stability and communication quality of the drone when subjected to the jamming signal to ensure that the drone can safely perform tasks.
In summary, the early warning module is a key component in the unmanned aerial vehicle system, and through interference detection and anti-interference measures, the early warning module can monitor and respond to interference signals, and protect the unmanned aerial vehicle from interference and attack, so that flight safety of the unmanned aerial vehicle and smooth execution of tasks are guaranteed.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that it will be apparent to those skilled in the art that several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the scope of the invention.
Claims (9)
1. Unmanned aerial vehicle system of autonomous path planning and obstacle avoidance system, its characterized in that, unmanned aerial vehicle system includes:
the sensor module is connected with the unmanned aerial vehicle through a signal and the Internet of things and is used for sensing obstacles and topographic information of surrounding environments;
the map construction module is used for processing and analyzing the data acquired by the sensor module, and the system can generate a map to describe the surrounding environment of the unmanned aerial vehicle;
the path planning module is used for determining an optimal path which the unmanned aerial vehicle should take based on the generated map and the target position, so that collision is avoided;
the control and monitoring module is used for carrying out flight control on the unmanned aerial vehicle according to the planned path after the path planning is completed, and carrying out real-time tracking and monitoring;
the positioning module can be used for carrying out real-time positioning monitoring on the position of the unmanned aerial vehicle;
and the early warning module is used for protecting the unmanned aerial vehicle from interference and key components of attack.
2. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 1, wherein: the sensor module can sense static obstacles and dynamic obstacles;
the static obstacle is perceived through a camera, a laser radar and an ultrasonic sensor;
cameras are one of the most common perception sensors, they help unmanned aerial vehicles acquire visual information of the environment, can provide image and video data, and can be used for map construction, target detection, gesture control and navigation tasks;
the laser radar uses laser beams to measure the distance and the position of surrounding objects, generates accurate point cloud data, can provide high-precision three-dimensional environment perception, and helps an unmanned plane to detect obstacles, establish a map and conduct distance measurement and obstacle avoidance decision;
the ultrasonic sensor is used for measuring the distance of an object by sending and receiving ultrasonic signals, detecting and avoiding obstacles at a close distance and avoiding collision with static obstacles.
3. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 2, wherein: dynamic obstacles are sensed by a variety of sensors, including:
infrared sensors, which can detect thermal radiation from surrounding objects for detecting humans, animals, and other heat sources, are useful for target detection and obstacle avoidance in low light conditions or in dense vegetation areas;
radar sensors, which use electromagnetic waves to detect the position and movement of objects, can provide a detection capability over longer distances, and are very effective for target detection and obstacle avoidance in complex weather conditions or in environments where visible light is limited;
the weather sensor is used for measuring weather conditions of the environment, is very important for flight safety and path planning, and avoids influencing the stability and performance of the unmanned aerial vehicle;
microphones and sound sensors that may be used for sound localization and tracking, which may be used to detect sound sources at a remote location, thereby helping the drone to avoid potential collisions;
the gesture sensor is used for measuring the gesture and the direction of the unmanned aerial vehicle, and is important for flight stability, navigation and gesture control.
4. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 1, wherein: the map construction module can be divided into a two-dimensional map and a three-dimensional map;
the two-dimensional map adopts a two-dimensional grid map, in the two-dimensional grid map, the environment is divided into discrete grids, each grid can represent an air space, an obstacle and other environment characteristics, and a sensor module of the unmanned aerial vehicle can identify the obstacle and update the corresponding grid of the map for path planning, obstacle avoidance and navigation;
the three-dimensional map adopts a three-dimensional point cloud map, in which the environment is represented as a set of discrete point cloud data, each point cloud comprises three-dimensional coordinates and other attribute information, the sensor module captures the point cloud data of the surrounding environment and processes and fuses the data, so that an accurate three-dimensional map can be generated, and the three-dimensional map comprises geometric and semantic information of obstacles, terrains and target objects, and is very useful for navigation, obstacle avoidance and target recognition of an unmanned aerial vehicle.
5. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 1, wherein: the path planning module further comprises a path planning algorithm, wherein the path planning module determines an optimal path which the unmanned aerial vehicle should take through the path planning algorithm based on the generated map and the target position.
6. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 5, wherein: the path planning algorithm further comprises:
dijkstra algorithm, which is a breadth-first search algorithm for finding the shortest path from the origin to all other nodes;
the algorithm A is a heuristic search algorithm, and combines the shortest path search of the Dijkstra algorithm and the estimated value of a heuristic function;
genetic algorithm, which is an optimization algorithm based on biological evolution theory.
7. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 1, wherein: the control and monitoring module further comprises:
the flight control module receives the path planning result and converts the path planning result into a control command of the unmanned aerial vehicle so as to realize flying along the planned path, wherein the flight control module is responsible for controlling the gesture, the speed and the position parameters of the unmanned aerial vehicle so as to ensure that the unmanned aerial vehicle flies according to the planned path;
the flight monitoring module can monitor the current flight state of the unmanned aerial vehicle in real time so as to ensure the safety of the unmanned aerial vehicle in the flight process.
8. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 7, wherein: the positioning module adopts a Global Positioning System (GPS), an Inertial Navigation System (INS) and a visual positioning technology to track the position information of the unmanned aerial vehicle in real time and is connected with the flight monitoring module in real time.
9. The unmanned aerial vehicle system of the autonomous path planning and obstacle avoidance system of claim 1, wherein: the early warning module comprises interference detection and anti-interference measures;
the interference detection can monitor and analyze the electromagnetic environment around the unmanned aerial vehicle so as to detect whether an interference signal exists;
the anti-interference measure can resist interference signals when the unmanned aerial vehicle receives the interference signals, for example, for radio interference, frequency hopping, power control, adaptive modulation and other technologies can be used for maintaining the stability of communication.
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