An unmanned aerial vehicle obstacle clearing device and method based on ultrasonic detection

Abstract

The application discloses an unmanned aerial vehicle obstacle removing device and method based on ultrasonic detection, and belongs to the technical field of unmanned aerial vehicle obstacle removing. The device comprises an unmanned aerial vehicle (1), an unmanned obstacle removing vehicle (2), an intelligent lock (3) and an article positioner (4). The unmanned aerial vehicle (1) performs identity recognition operation with the unmanned obstacle removing vehicle (2), the intelligent lock (3) and the article positioner (4) through ultrasonic signal emission, so as to realize obstacle recognition and positioning. The unmanned aerial vehicle (1) and the unmanned obstacle removing vehicle (2) are wirelessly connected to communicate, and thus the obstacle removing work of the unmanned obstacle removing vehicle (2) is realized. The application can realize rapid obstacle recognition and removal in a complex mountainous environment, effectively improves the efficiency and safety of mountainous obstacle cleaning operation, and improves the recognition and connection accuracy of the equipment.

Description

Technical Field

[0001] This invention relates to the field of drone obstacle removal technology, and more specifically, to a drone obstacle removal device and method based on ultrasonic detection. Background Technology

[0002] Due to complex terrain and variable weather, mountain roads are prone to being blocked by obstacles such as falling rocks, landslides, and fallen trees, severely impacting traffic safety and rescue efficiency. Especially after heavy rain, earthquakes, and extreme weather, roads are often covered with large amounts of rubble, mud, and fallen trees. Traditional manual clearing methods require personnel to carry machinery into dangerous areas, which is not only inefficient but also poses high personal safety risks. At the same time, mountain roads are usually narrow and winding, with some sections impassable for vehicles, making it difficult to carry out clearing work in a timely manner and easily causing prolonged traffic disruptions. Therefore, how to achieve efficient, safe, and automated road obstacle removal in complex mountain environments has become an urgent problem to be solved in the fields of traffic management and emergency rescue.

[0003] In recent years, with the rapid development of drone technology, artificial intelligence technology, and intelligent sensing technology, drones have been increasingly applied to scenarios such as mountain patrols, disaster monitoring, and road condition detection. Drones have advantages such as high mobility, wide field of view, and flexible deployment, enabling them to quickly reach areas inaccessible to personnel. By carrying cameras and sensors, they can monitor the road environment in real time and identify targets, thereby quickly locating obstacles and obtaining on-site information. Using drones for patrol and inspection of mountain roads can significantly improve road inspection efficiency and reduce the risk of personnel entering dangerous areas. In addition, combining drones with ground clearing equipment can achieve air-ground collaborative operations, with drones responsible for environmental perception and path guidance, while ground clearing equipment is responsible for the actual removal of obstacles, thereby further improving clearing efficiency and automation.

[0004] However, existing drone-assisted obstacle removal technologies still have many shortcomings in practical applications. First, in terms of collaborative operations between drones and obstacle removal vehicles, most systems currently rely on simple communication methods for information transmission, lacking a stable and reliable collaborative mechanism. This results in low collaboration efficiency between drones and obstacle removal vehicles, making it difficult to form a complete air-ground collaborative obstacle removal system. Second, regarding device connectivity, connections between devices are easily affected by factors such as terrain obstruction and connection distance in complex mountainous environments, leading to unstable connections and affecting the overall operation progress. Finally, most existing drone obstacle removal systems are designed for single drone and single obstacle removal vehicle operation modes, lacking support for collaborative operations of multiple drones and multiple obstacle removal vehicles. This can easily lead to matching errors and make it impossible to deploy multiple devices simultaneously for collaborative obstacle removal in large-scale mountainous environments, resulting in overall operational efficiency that is insufficient to meet the obstacle removal needs of large-scale disasters and complex road sections.

[0005] Therefore, how to design a mountain drone obstacle removal device that can achieve stable connection, accurate device identification, and simultaneous support for collaborative operation of multiple drones and multiple obstacle removal vehicles has become an important problem that urgently needs to be solved in the current technology field. Summary of the Invention

[0006] The purpose of this invention is to overcome the above-mentioned problems existing in the prior art and to greatly improve its technical effect on the basis of the original technology. To this end, this invention provides an unmanned aerial vehicle obstacle removal device based on ultrasonic detection, which includes an unmanned aerial vehicle (1), an unmanned obstacle removal vehicle (2), a smart lock (3) and a placement locator (4).

[0007] The drone (1) is a multi-functional intelligent drone (1) used to locate obstacle location information, identify unmanned obstacle clearing vehicle (2), open smart lock (3), guide unmanned obstacle clearing vehicle (2) and identify object locator (4); the unmanned obstacle clearing vehicle (2) has a drone (1) landing platform on its top; the unmanned obstacle clearing vehicle (2) is used to park drone (1), connect drone (1), receive drone (1) navigation route and move obstacle to object locator; the smart lock (3) can intelligently lock and unlock; it is used to close roadblocks by locking to prevent any vehicle from entering the closed section of the mountain road; it is used to open roadblocks by unlocking to allow unmanned obstacle clearing vehicle (2) to enter the closed section of the mountain road; the object locator (4) is used to help drone (1) identify object locator and then guide unmanned obstacle clearing vehicle (2) to move obstacle to object locator; the object locator refers to the area used to place obstacle.

[0008] The unmanned aerial vehicle (1), the unmanned obstacle clearing vehicle (2), the smart lock (3) and the object locator (4) are all equipped with ultrasonic transmitting devices for emitting ultrasonic waves.

[0009] In addition, the multi-functional intelligent drone (1) includes functions such as camera, target recognition, positioning and ultrasonic wave transmission; when the drone (1) is working, it first cruises the mountain roads to determine the obstacle information in the mountain area; the location information of the obstacle includes: the drone (1) flies away from the drone (1) landing platform of the unmanned clearing vehicle (2) to cruise the mountain roads; the drone (1) identifies the obstacle information on the mountain roads through its own deep learning algorithm YOLO, and hovers above the obstacle to mark the location information to complete the positioning of the obstacle target.

[0010] Identifying the unmanned obstacle clearing vehicle (2) includes: after the drone (1) completes the patrol of the mountain road to determine the location information of the obstacle, it flies to the entrance of the mountain to identify the unmanned obstacle clearing vehicle (2); the identification of the unmanned obstacle clearing vehicle (2) is divided into two steps: acquiring the image information of the unmanned obstacle clearing vehicle (2) and establishing a connection with the unmanned obstacle clearing vehicle (2); the acquisition of the image information of the unmanned obstacle clearing vehicle (2) includes: acquiring the image information of the unmanned obstacle clearing vehicle (2) through the camera of the drone (1), and determining that the acquired image information of the unmanned obstacle clearing vehicle (2) is consistent with the corresponding image information stored in the drone (1) through the built-in deep learning algorithm YOLO; the establishment of a connection with the unmanned obstacle clearing vehicle (2) includes: the drone (1) hovers 2 meters directly above the unmanned obstacle clearing vehicle (2), and emits obstacle clearing ultrasonic waves to the unmanned obstacle clearing vehicle (2) through an ultrasonic transmitter. After receiving the obstacle clearing ultrasonic waves, the unmanned obstacle clearing vehicle (2) immediately sends ultrasonic waves of the same frequency and the corresponding Bluetooth connection address to the drone (1); the drone (1) determines whether the ultrasonic waves of the same frequency are emitted by the unmanned obstacle clearing vehicle (2) below. The determination method is: through the formula The threshold range is used to determine whether the ultrasonic waves of the same frequency are emitted by the corresponding unmanned obstacle clearing vehicle (2); where v0 is the speed of ultrasonic wave propagation, t0 is the delay time of the unmanned obstacle clearing vehicle (2) equipment, that is, the reaction time from receiving the ultrasonic wave to emitting the ultrasonic wave; T2 is the actual time required for the UAV (1) to receive the ultrasonic wave of the same frequency from emitting the ultrasonic wave. The value of δ is the theoretical time required for the drone (1) to receive the ultrasonic wave of the same frequency from emitting it. Therefore, δ is the ratio of the absolute value of the difference between the theoretical time and the actual time to the theoretical time. If δ is within the threshold range, a Bluetooth connection with the corresponding unmanned vehicle (2) is established. After the connection is established, the drone (1) and the corresponding unmanned vehicle (2) will refuse to establish connections with other devices. That is, a drone (2) can only connect to one unmanned vehicle (2) at the same time. If δ is outside the threshold range, the Bluetooth connection with the corresponding unmanned vehicle (2) is refused, and a second connection with the unmanned vehicle (2) is attempted. If the connection still cannot be established the second time, the drone moves to another unmanned vehicle (2) and performs the operation of identifying the unmanned vehicle (2). The value of the threshold range is determined according to the accuracy requirements. The smaller the value of the threshold range, the higher the required accuracy. The larger the value of the threshold range, the lower the required accuracy.

[0011] Opening the smart lock (3) includes: after establishing a Bluetooth connection between the drone (1) and the corresponding unmanned obstacle clearing vehicle (2), the drone (1) flies to a position 2 meters directly above the smart lock (3) and hovers and emits a first specific frequency ultrasonic wave to the smart lock (3); after receiving the first specific frequency ultrasonic wave, the smart lock (3) activates the unlocking mechanism to automatically open the obstacle and allow the unmanned obstacle clearing vehicle (2) connected with the corresponding drone (1) to pass; after the unmanned obstacle clearing vehicle (2) passes the obstacle, it activates the locking mechanism to automatically close the obstacle; the first specific frequency ultrasonic wave is different from the obstacle clearing ultrasonic wave, and the first specific frequency ultrasonic wave is a specially set designated frequency used to open the smart lock (3).

[0012] The unmanned obstacle clearing vehicle (2) navigation includes: the drone (1) autonomously plans its path based on the mountain environment map and the location of the obstacle, and plans the flight path to perform the obstacle clearing operation; the drone (1) flies according to the flight path to perform the obstacle clearing operation, and sends its location information to the unmanned obstacle clearing vehicle (2) that it has established a connection with via Bluetooth in real time; the unmanned obstacle clearing vehicle (2) moves along the road according to the location information sent by the drone (1).

[0013] The identification of the object locator (4) includes: when the drone (1) leads the corresponding unmanned obstacle clearing vehicle (2) to the obstacle location information, identifying the object locator (4) placed around it, obtaining the location information of the object locator (4), and guiding the corresponding unmanned obstacle clearing vehicle (2) to move the obstacle to the object locator (4).

[0014] Furthermore, the unmanned obstacle clearing vehicle (2) is a modified obstacle clearing vehicle, with a drone (1) landing platform on the top and an onboard intelligent sensing and control integrated machine installed; the drone (1) landing platform is used to park the drone (1) when it is not in operation, and the onboard intelligent sensing and control integrated machine has an obstacle sensing module, an intelligent algorithm module and an execution control interface; the obstacle sensing module is used to identify the position and size of the obstacle; the intelligent algorithm module includes: obstacle recognition algorithm, size estimation algorithm, path planning algorithm and pusher action control algorithm; the execution control interface is used to control the pusher to push the obstacle to the designated area.

[0015] Furthermore, the smart lock (3) includes an embedded control board for parsing the received ultrasonic signal and determining whether the signal is valid; if the signal is valid, the electronic lock is controlled to unlock; if the signal is invalid, no response is made.

[0016] Furthermore, when identifying the object locator (4), the drone (1) hovers 2 meters directly above the object locator (4) and emits a second specific frequency ultrasonic wave towards the object locator (4). After receiving the second specific frequency ultrasonic wave, the object locator (4) immediately emits an ultrasonic wave of the same frequency as the second specific frequency ultrasonic wave back to the drone (1). After receiving the ultrasonic wave of the same frequency as the second specific frequency ultrasonic wave, the drone (1) extracts the location information of the object locator (4) and sends the location information to the unmanned obstacle clearing vehicle (2), which then moves the obstacle to the location of the object locator (4). The second specific frequency ultrasonic wave is a specially set designated frequency for identifying the object locator (4). The second specific frequency ultrasonic wave is different from both the first specific frequency ultrasonic wave and the obstacle clearing ultrasonic wave. Therefore, the first specific frequency ultrasonic wave and the second specific frequency ultrasonic wave are two different specific value frequencies of ultrasonic waves, while the obstacle clearing ultrasonic wave is an ultrasonic wave with a freely selectable frequency that is different from the first specific frequency ultrasonic wave and the second specific frequency ultrasonic wave.

[0017] In addition, the present invention also provides a method for clearing obstacles by unmanned aerial vehicles (UAVs) based on ultrasonic detection. The method is characterized by being implemented based on the above-mentioned obstacle clearing device for UAVs (1) based on ultrasonic detection. The method includes: S100, after receiving the obstacle clearing task, the UAV (1) leaves the UAV (1) landing platform of the unmanned obstacle clearing vehicle (2) and cruises along the mountain road to obtain obstacle location information; S200, the UAV (1) flies to the entrance of the mountain area and identifies the unmanned obstacle clearing vehicle (2) by acquiring image information of the unmanned obstacle clearing vehicle (2) and establishing a connection with the unmanned obstacle clearing vehicle (2); subsequently, the UAV (1) hovers 2 meters above the smart lock (3) and activates the unlocking mechanism of the smart lock (3) by emitting a first specific frequency ultrasonic wave to the smart lock (3). By unlocking the roadblock, the unmanned obstacle clearing vehicle (2) is allowed to enter the closed section of the mountain road; S300, the drone (1) performs autonomous path planning based on the mountain environment map and the location of the obstacle, and plans the flight path to perform the obstacle clearing operation; the drone (1) flies according to the flight path to perform the obstacle clearing operation, and sends the location information to the unmanned obstacle clearing vehicle (2) that it has established a connection with via Bluetooth in real time, and the unmanned obstacle clearing vehicle (2) moves along the road according to the location information sent by the drone (1); S400, the drone (1) arrives at the location of the obstacle, identifies the location of the object locator (4) by emitting a second specific frequency ultrasonic wave, and sends the location of the object locator (4) to the unmanned obstacle clearing vehicle (2), and the unmanned obstacle clearing vehicle (2) moves the obstacle to the location of the corresponding object locator (4).

[0018] The beneficial effects of this invention are as follows: 1) Improved accuracy of equipment identification and connection: By introducing ultrasonic verification technology, this invention enables accurate identification and verification between multiple UAVs (1) and multiple unmanned obstacle clearing vehicles (2). In complex operating environments, ultrasonic signals have strong anti-interference capabilities, which can effectively avoid incorrect connection problems caused by signal confusion or misidentification, thereby achieving accurate identification and stable connection between multiple UAVs (1) and multiple unmanned obstacle clearing vehicles (2), and improving the reliability and safety of the overall collaborative operation of the system; 2) Improved obstacle clearing efficiency: By using UAVs (1) for path planning and UAVs (1) to guide unmanned obstacle clearing vehicles (2), the unmanned obstacle clearing vehicles (2) can quickly reach the target obstacle clearing area according to the optimal route; Compared with the traditional method of relying on manual scheduling and fixed paths, This solution can significantly reduce path search and decision-making time, improve the rationality of the operation path, and thus complete the obstacle clearing task more quickly and efficiently, thereby improving the overall efficiency and response speed of obstacle clearing work; 3) It can enhance the collaborative operation capability of multiple devices: through the collaborative communication and navigation guidance mechanism between the drone (1) and the unmanned obstacle clearing vehicle (2), multiple devices can form an efficient collaborative operation system, and can still maintain stable collaboration in complex environments or large-scale operation scenarios, thereby improving the overall operation capability of the system; 4) This invention forms a complete mountain drone obstacle clearing device based on ultrasonic technology by using drone (1), unmanned obstacle clearing vehicle (2), smart lock (3) and object locator (4), which can realize the rapid identification and clearing of mountain obstacles in various complex environments, thereby improving the efficiency and safety of mountain obstacle clearing operations. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of an obstacle removal device for unmanned aerial vehicles based on ultrasonic detection according to the present invention.

[0020] Figure 2 This is a flowchart of an obstacle removal method for unmanned aerial vehicles based on ultrasonic detection according to the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be described more clearly and completely below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0022] like Figure 1The diagram shows a schematic of an unmanned aerial vehicle obstacle removal device based on ultrasonic detection according to the present invention; the schematic diagram includes: unmanned aerial vehicle (1), unmanned obstacle removal vehicle (2), smart lock (3) and object locator (4).

[0023] Among them, the drone (1) is a multi-functional intelligent drone (1) used to locate obstacle location information, identify the unmanned obstacle clearing vehicle (2), open the smart lock (3), guide the unmanned obstacle clearing vehicle (2) and identify the placement locator (4); the unmanned obstacle clearing vehicle (2) has a drone (1) landing platform on its top; the unmanned obstacle clearing vehicle (2) is used to park the drone (1), connect to the drone (1), receive the drone (1) navigation route and move obstacles to the placement location point; the smart lock (3) can intelligently lock and unlock; it is used to close by locking. The roadblock prohibits any vehicle from entering the closed section of the mountain road; by unlocking the roadblock, the unmanned clearing vehicle (2) is allowed to enter the closed section of the mountain road; the object locator (4) is used to help the drone (1) identify the object location point, and then guide the unmanned clearing vehicle (2) to move the obstacle to the object location point; the object location point refers to the area used to place the obstacle; in addition, the drone (1), the unmanned clearing vehicle (2), the smart lock (3) and the object locator (4) are all equipped with ultrasonic transmitters to emit ultrasonic waves to verify identity information or issue instructions.

[0024] This embodiment uses a DJI drone equipped with an ultrasonic transmitter to form the multifunctional intelligent drone (1) of this invention. Before working, the drone of this invention is stationed on the drone (1) landing platform of the unmanned obstacle clearing vehicle (2). After receiving the obstacle clearing task, it first conducts a patrol of the mountain road to determine the obstacle information. The specific steps include: the drone (1) flies away from the drone (1) landing platform of the unmanned obstacle clearing vehicle (2) and conducts a patrol of the mountain road; the drone (1) identifies the obstacle information on the mountain road through the deep learning algorithm YOLO, and hovers above the obstacle to mark the position information to complete the target positioning.

[0025] The steps for identifying obstacle information on mountain roads and obtaining obstacle location information using the YOLO deep learning algorithm built into the UAV (1) are as follows: S1, the UAV (1) uses its onboard visible light camera to cruise and photograph the mountain roads, collecting real-time image information of the roads and surrounding areas to provide data input for obstacle identification; S2, the collected images are input into the YOLO target detection model built into the UAV (1), which extracts features and judges targets from the images, identifies obstacles on the road, and outputs obstacle category information, confidence information, and target bounding box location information; S3, based on the target bounding box center coordinates output by the YOLO model, combined with the flight attitude, gimbal attitude, and camera parameters of the UAV (1), the position of the obstacle in the actual space is calculated, thereby determining the relative orientation information of the obstacle; S4, the flight control system of the UAV (1) controls the UAV to move along the front-back, left-right, and height directions according to the relative orientation information of the obstacle. S5. When the deviation between the center of the obstacle's bounding box and the center of the UAV's (1) onboard camera's field of view is less than a preset threshold, the UAV is controlled to hover directly above the obstacle and maintain stable hovering to complete the alignment of the obstacle's top. S6. While hovering, the UAV reads the current position, flight altitude, and time information and records and marks them as the location information of the obstacle, providing a basis for subsequent unmanned obstacle clearing vehicle operations and path planning. S7. After completing the identification and positioning of a single obstacle, the UAV transmits the identification results and location information back to the ground control terminal or task processing module. If there are still other obstacles in the inspection area, the UAV continues to collect images, identify targets, hover and locate and record information along the predetermined route until the obstacle identification and positioning task of the entire inspection area is completed.

[0026] After the drone (1) completes the patrol of the mountain road and determines the location information of the obstacle, it flies to the entrance of the mountain to identify the unmanned obstacle clearing vehicle (2). Identifying the unmanned obstacle clearing vehicle (2) is divided into two steps: obtaining the image information of the unmanned obstacle clearing vehicle (2) and establishing a connection with the unmanned obstacle clearing vehicle (2).

[0027] The acquisition of image information of the unmanned vehicle (2) includes: acquiring image information of the unmanned vehicle (2) through the camera of the drone (1), and determining that the acquired image information of the unmanned vehicle (2) is consistent with the corresponding image information stored in the drone (1) through the built-in deep learning algorithm YOLO; specifically: S10, the drone (1) acquires image information of the unmanned vehicle (2) in real time through its onboard camera; the acquired image information is transmitted to the internal processing unit of the drone (1) and is passed as input data to the built-in deep learning algorithm YOLO for target detection and matching; S11, the YOLO algorithm extracts features from the transmitted image information and performs classification and localization analysis of the image content through a pre-trained model; first, the YOLO algorithm will identify the unmanned vehicle in the image. The relevant feature information of the obstacle clearing vehicle (2), including but not limited to visual features such as the shape, color and size of the object, is compared with the standard image information stored in the UAV (1); S12, the comparison process includes extracting the reference image data stored in the UAV (1) and matching the feature points with the currently acquired image data. If the matching degree exceeds the preset threshold, the YOLO algorithm confirms that the image information of the two is consistent and marks the image as the target image; if the matching degree is lower than the threshold, the YOLO algorithm considers the image information to be inconsistent and performs further processing or re-acquires the image; S13, through this process, the UAV (1) can accurately identify and confirm whether the acquired image information of the unmanned obstacle clearing vehicle (2) is consistent with the stored reference image information, thereby providing effective support for subsequent target positioning and obstacle clearing tasks.

[0028] In addition, the connection process with the unmanned obstacle clearing vehicle (2) is as follows: the drone (1) hovers 2 meters directly above the unmanned obstacle clearing vehicle (2) and emits obstacle clearing ultrasonic waves to the unmanned obstacle clearing vehicle (2) through an ultrasonic transmitter. After receiving the obstacle clearing ultrasonic waves, the unmanned obstacle clearing vehicle (2) immediately sends ultrasonic waves of the same frequency and the corresponding Bluetooth connection address back to the drone (1). It should be noted that the ultrasonic transmitter of the present invention is a dual-purpose device for transmitting and receiving ultrasonic waves. Subsequently, the drone (1) determines whether the ultrasonic waves of the same frequency received are emitted by the unmanned obstacle clearing vehicle (2) below. The determination method is: by formula The threshold range is used to determine whether the ultrasonic waves of the same frequency are emitted by the corresponding unmanned obstacle clearing vehicle (2); where v0 is the speed of ultrasonic wave propagation, t0 is the delay time of the unmanned obstacle clearing vehicle (2) equipment, that is, the reaction time from receiving the ultrasonic wave to emitting the ultrasonic wave; T2 is the actual time required for the UAV (1) to receive the ultrasonic wave of the same frequency from emitting the ultrasonic wave. The value is the theoretical time required for the drone (1) to receive the ultrasonic wave of the same frequency from emitting the ultrasonic wave. Therefore, δ is the ratio of the absolute value of the theoretical time and the actual time difference to the theoretical time. If δ is within the threshold range, a Bluetooth connection with the corresponding unmanned vehicle (2) is established; if δ is outside the threshold range, the Bluetooth connection with the corresponding unmanned vehicle (2) is rejected, and a second attempt is made to establish a connection with the unmanned vehicle (2); if the second attempt still fails to establish a connection, the drone moves to another unmanned vehicle (2) and performs the operation of identifying the unmanned vehicle (2). The threshold range value of the present invention is confirmed according to the accuracy requirements. The smaller the threshold range value, the higher the required accuracy; the larger the threshold range value, the lower the required accuracy. However, the threshold range value cannot be too small or too large. If it is too small, the drone (1) and the corresponding unmanned vehicle (2) will be unable to establish a connection. The unmanned vehicle (2) is difficult to establish a connection; if the connection is too large, the drone (1) and the unmanned vehicle (2) will have incorrect or false connections; therefore, the lower bound of the threshold range is usually set to 0, and the upper bound is a number between 0.01 and 0.05; that is, the threshold range can be set to [0, ω], then the value of ω is a number between 0.01 and 0.1; that is, if δ is in the range of [0, ω], then a Bluetooth connection with the corresponding unmanned vehicle (2) is established; if it is outside the range, then no connection is established; at the same time, in order to further determine the value of the upper bound, it can be done according to the actual situation; in the actual working environment, if the distance between the ultrasonic transmitters worn by two unmanned vehicles (2) A and B when they are closest is 1 meter, then when the drone establishes a connection with the unmanned vehicle corresponding to A, the diagonal distance between the drone and the unmanned vehicle corresponding to B is: If both unmanned obstacle clearing vehicles receive ultrasonic waves emitted by the unmanned obstacle clearing vehicle located at point A, and then emit ultrasonic waves of the same frequency back to the drone, then the time difference between the drone receiving the ultrasonic waves emitted by the unmanned obstacle clearing vehicles located at points A and B is: Substitute into the formula Known The value is the theoretical time required for the UAV (1) to receive the ultrasonic wave of the same frequency from the UAV (1) that is emitted and the UAV (1) receives the ultrasonic wave of the same frequency from the UAV (1). Assuming that the t0 values ​​of the two UAVs are the same in this formula and are 0.005 seconds, the difference between the δ value corresponding to UAV (1) and UAV (1) is: =0.08. Without considering the error, if we choose 0.01≤ω<0.08, then the drone can only connect to the unmanned obstacle clearing vehicle corresponding to A, and cannot connect to the unmanned obstacle clearing vehicle corresponding to B. If we consider the error and assume the influence of the error on the δ value, then we choose 01≤ω<0.07, which can also ensure that the drone can only connect to the unmanned obstacle clearing vehicle corresponding to A. The reason for choosing the value of ω between 0.01 and 0.1 is that in reality, the distance between the ultrasonic transmitters worn by the two unmanned obstacle clearing vehicles (2) when they are closest is often greater than 1 meter. Therefore, it is reasonable to choose the value of ω between 0.01 and 0.1.

[0029] The process of opening the smart lock (3): After the drone (1) completes the connection with the corresponding unmanned obstacle clearing vehicle (2), the drone (1) flies to a position 2 meters above the smart lock (3) and hovers and emits a first specific frequency ultrasonic wave to the smart lock (3); after the smart lock (3) receives the first specific frequency ultrasonic wave, it starts the unlocking mechanism to automatically open the roadblock and allows the unmanned obstacle clearing vehicle (2) connected with the corresponding drone (1) to pass; after the unmanned obstacle clearing vehicle (2) passes the roadblock, it starts the locking mechanism to automatically close the roadblock; among them, the first specific frequency ultrasonic wave is different from the obstacle clearing ultrasonic wave. The first specific frequency ultrasonic wave is a specially set designated frequency ultrasonic wave used to open the smart lock (3), while the obstacle clearing ultrasonic wave is a frequency ultrasonic wave with a randomly selected value that can change.

[0030] The unmanned obstacle clearing vehicle (2) navigation process is as follows: S20, the UAV (1) inputs the map data and obstacle location information into the path planning module on the UAV (1) based on the pre-constructed mountain environment map and the identified road obstacle location data. The path planning module analyzes the obstacle distribution and road topology by combining the A* algorithm and the improved heuristic search algorithm, calculates the optimal flight path from the starting position to the target obstacle, and considers the flight safety distance, obstacle height, slope change and mountain wind factors to generate an autonomous flight path suitable for the complex mountain terrain for obstacle clearing operation; S21, the UAV (1) takes off according to the planned flight path and obtains its own attitude information, GPS positioning information and obstacle dynamic position changes in real time through the onboard sensors during the flight. It also optimizes and adjusts the flight trajectory online by combining the deep reinforcement learning algorithm to ensure that the flight path is suitable for the complex mountain environment. S22. During flight, the UAV (1) sends its current location and the location of the target obstacle to the unmanned obstacle clearing vehicle (2) that it has established a connection with via Bluetooth communication module. The unmanned obstacle clearing vehicle (2) travels along the road according to the received location information and corrects the path through the vehicle navigation system to keep it consistent with the flight trajectory of the UAV (1), thereby realizing the collaborative execution of obstacle clearing tasks by the UAV (1) and the unmanned obstacle clearing vehicle (2). S23. After the UAV (1) completes the clearing of one obstacle, it calls the autonomous path planning module again to generate the next flight path according to the mountain environment map and the location of the remaining obstacles, and repeats the above flight, real-time optimization and location information sending steps until all planned obstacle clearing operations are completed, thereby realizing the automated execution of the entire mountain road obstacle clearing task.

[0031] It should be noted that during the process of the drone (1) leading the unmanned obstacle clearing vehicle (2), the distance between the drone (1) and the corresponding unmanned obstacle clearing vehicle (2) should not be too far to prevent the Bluetooth signal from being unstable or interrupted; therefore, the drone (1) flies directly in front of the corresponding unmanned obstacle clearing vehicle (2), and the distance between the two is always kept within 10 meters.

[0032] The process of identifying the object locator (4) is as follows: when the drone (1) leads the corresponding unmanned obstacle clearing vehicle (2) to the obstacle location information, it identifies the object locator (4) placed around it, obtains the location information of the object locator (4), and guides the corresponding unmanned obstacle clearing vehicle (2) to move the obstacle to the object locator (4); the object locator is a locator placed in an appropriate position around the obstacle location after the obstacle information is identified, without affecting road traffic, and is used to determine the final placement position of the obstacle.

[0033] Furthermore, the unmanned obstacle clearing vehicle (2) is a modified obstacle clearing vehicle with a landing platform for the drone (1) on its top, as shown in the figure. This landing platform is used for parking the drone (1) when it is resting. In addition, the unmanned obstacle clearing vehicle (2) is also equipped with an on-board intelligent sensing and control integrated machine. The on-board intelligent sensing and control integrated machine has an obstacle sensing module, an intelligent algorithm module, and an execution control interface. The obstacle sensing module is used to identify the position and size of obstacles. The intelligent algorithm module includes: obstacle recognition algorithm, size estimation algorithm, path planning algorithm, and pusher action control algorithm. The execution control interface is used to control the pusher to push the obstacle to the designated position.

[0034] The smart lock (3) is equipped with an embedded control board, which is used to analyze the received ultrasonic signal and determine whether the signal is valid. If the signal is valid, the smart lock is controlled to unlock. If the signal is invalid, no response is made. The valid signal is an ultrasonic wave with a first specific frequency received by the smart lock.

[0035] During the process of identifying the object locator (4), the drone (1) hovers 2 meters directly above the object locator (4) and emits a second specific frequency ultrasonic wave towards the object locator (4). After receiving the second specific frequency ultrasonic wave, the object locator (4) immediately emits an ultrasonic wave of the same frequency as the second specific frequency ultrasonic wave back to the drone (1). After receiving the ultrasonic wave of the same frequency as the second specific frequency ultrasonic wave, the drone (1) extracts the location information of the object locator (4) and sends the location information to the unmanned obstacle clearing vehicle (2). The unmanned obstacle clearing vehicle (2) moves the obstacle to the location of the object locator (4). The second specific frequency ultrasonic wave is a specially set designated frequency for identifying the object locator (4). The second specific frequency ultrasonic wave is different from the first specific frequency ultrasonic wave and the obstacle clearing ultrasonic wave. Therefore, the first specific frequency ultrasonic wave and the second specific frequency ultrasonic wave are two different specific value frequencies of ultrasonic waves, while the obstacle clearing ultrasonic wave is an ultrasonic wave with a freely selectable frequency that is different from the first specific frequency ultrasonic wave and the second specific frequency ultrasonic wave.

[0036] like Figure 2This is a flowchart of a drone obstacle removal method based on ultrasonic detection. The flowchart includes: S100, after receiving the obstacle removal task, the drone (1) leaves the drone (1) landing platform of the unmanned obstacle removal vehicle (2) and cruises along the mountain road to obtain obstacle location information; S200, the drone (1) flies to the entrance of the mountain area and identifies the unmanned obstacle removal vehicle (2) by acquiring image information of the unmanned obstacle removal vehicle (2) and establishing a connection with the unmanned obstacle removal vehicle (2); then, the drone (1) hovers 2 meters above the smart lock (3) and activates the unlocking mechanism of the smart lock (3) by emitting a first specific frequency ultrasonic wave to the smart lock (3). The smart lock (3) unlocks the roadblock and allows the unmanned obstacle removal vehicle (2) to enter the closed mountain area. S300, the UAV (1) performs autonomous path planning based on the mountain environment map and the location of the obstacle, and plans the flight path for performing obstacle removal operation; the UAV (1) flies according to the flight path for performing obstacle removal operation, and sends the location information to the unmanned obstacle removal vehicle (2) connected to it in real time via Bluetooth, and the unmanned obstacle removal vehicle (2) moves along the road according to the location information sent by the UAV (1); S400, the UAV (1) arrives at the location of the obstacle, identifies the location of the object locator (4) by emitting a second specific frequency ultrasonic wave, and sends the location of the object locator (4) to the unmanned obstacle removal vehicle (2), and the unmanned obstacle removal vehicle (2) moves the obstacle to the location of the corresponding object locator (4).

[0037] Finally, the function of the method of the present invention is specifically explained through each component of the device of the present invention; the drone (1) is the core of the present invention, and it performs obstacle identification and positioning through its onboard sensors and deep learning algorithms (such as YOLO); the drone is also responsible for guiding the unmanned obstacle clearing vehicle (2), collecting mountain road information in real time, performing path planning, and transmitting obstacle location data to the unmanned obstacle clearing vehicle (2) during flight; the drone (1) and the unmanned obstacle clearing vehicle (2) communicate through an ultrasonic transmitter to ensure data transmission and task coordination; the drone (1) also serves as the switch to start the smart lock (3) and the identification of the object locator (4); the unmanned obstacle clearing vehicle (2) is responsible for receiving the obstacle location data transmitted by the drone (1) and clearing obstacles along the path; the unmanned obstacle clearing vehicle (2) is equipped with a landing platform for the drone (1) on its top, which can be set up for parking and charging the drone (1); the unmanned obstacle clearing vehicle is equipped with an intelligent perception and control system, which can identify obstacles and perform path planning and pushing actions; the smart lock (3) is used to control the closing and unlocking of mountain roads to prevent unauthorized vehicles. The vehicle enters; the drone (1) sends an ultrasonic signal of a first specific frequency to the smart lock through the ultrasonic transmitter to activate the unlocking mechanism, allowing the unmanned obstacle clearing vehicle (2) to enter the closed mountain road. The design of the smart lock ensures safety and controllability; the object locator (4) is a device used to guide the unmanned obstacle clearing vehicle (2) to move the obstacle to the designated location; the drone (1) identifies the object locator through the ultrasonic transmitter and obtains the location information of the object locator, and transmits the location information to the unmanned obstacle clearing vehicle (2) to ensure that the obstacle is moved to a suitable storage area; therefore, the present invention provides an efficient and automated method for clearing obstacles in mountainous areas by using a complete obstacle clearing device composed of drone (1), unmanned obstacle clearing vehicle (2), smart lock (3) and object locator (4); the unique ultrasonic recognition technology of the present invention makes the connection between drone (1) and unmanned obstacle clearing vehicle (2) safer, and through deep learning algorithms, positioning technology, path planning technology and the collaborative operation design of drone (1) and unmanned obstacle clearing vehicle (2), it fully meets the needs of obstacle clearing in mountainous areas and can contribute to the development of obstacle clearing technology in mountainous areas.

Claims

1. A drone obstacle removal device based on ultrasonic detection, characterized in that, The device includes: Drones (1), unmanned obstacle clearing vehicles (2), smart locks (3) and object locators (4); The drone (1) is a multi-functional intelligent drone (1) used to locate obstacle location information, identify unmanned clearing vehicle (2), open smart lock (3), guide unmanned clearing vehicle (2) and identify object locator (4). The unmanned obstacle clearing vehicle (2) has a drone (1) landing platform on its top; the unmanned obstacle clearing vehicle (2) is used to park the drone (1), connect the drone (1), receive the drone (1) navigation route and move obstacles to the placement point; The smart lock (3) is capable of intelligently locking and unlocking; it is used to close roadblocks by locking to prevent any vehicle from entering the closed section of the mountain road; and to open roadblocks by unlocking to allow unmanned clearing vehicles (2) to enter the closed section of the mountain road. The object locator (4) is used to help the drone (1) identify the object locator point, and then guide the unmanned obstacle clearing vehicle (2) to move the obstacle to the object locator point; the object locator point refers to the area used to place the obstacle. The unmanned aerial vehicle (1), the unmanned obstacle clearing vehicle (2), the smart lock (3) and the object locator (4) are all equipped with ultrasonic transmitting devices for emitting ultrasonic waves.

2. The UAV obstacle removal device based on ultrasonic detection according to claim 1, characterized in that, The multi-functional intelligent drone (1) first cruises the mountain roads to determine the information of obstacles in the mountains, including: the drone (1) flies away from the drone (1) landing platform of the unmanned obstacle clearing vehicle (2) to cruise the mountain roads; the drone (1) identifies the information of obstacles on the mountain roads through the deep learning algorithm YOLO on its own, and hovers directly above the obstacles to mark the location information to complete the target positioning.

3. The UAV obstacle removal device based on ultrasonic detection according to claim 1, characterized in that, The identification of the unmanned obstacle clearing vehicle (2) includes: after the drone (1) completes the patrol of the mountain road to determine the location information of the obstacle, it flies to the entrance of the mountain to identify the unmanned obstacle clearing vehicle (2); the identification of the unmanned obstacle clearing vehicle (2) is divided into two steps: acquiring the image information of the unmanned obstacle clearing vehicle (2) and establishing a connection with the unmanned obstacle clearing vehicle (2); the acquisition of the image information of the unmanned obstacle clearing vehicle (2) includes: acquiring the image information of the unmanned obstacle clearing vehicle (2) through the camera of the drone (1), and determining that the acquired image information of the unmanned obstacle clearing vehicle (2) is consistent with the corresponding image information stored in the drone (1) through the built-in deep learning algorithm YOLO; the establishment of a connection with the unmanned obstacle clearing vehicle (2) includes: the drone (1) hovers 2 meters directly above the unmanned obstacle clearing vehicle (2), and emits obstacle clearing ultrasonic waves to the unmanned obstacle clearing vehicle (2) through an ultrasonic transmitter. After receiving the obstacle clearing ultrasonic waves, the unmanned obstacle clearing vehicle (2) immediately sends ultrasonic waves of the same frequency and the corresponding Bluetooth connection address to the drone (1); the drone (1) determines whether the ultrasonic waves of the same frequency are emitted by the unmanned obstacle clearing vehicle (2) below. The determination method is: through the formula The threshold range is used to determine whether the ultrasonic waves of the same frequency are emitted by the corresponding unmanned obstacle clearing vehicle (2); where v0 is the speed of ultrasonic wave propagation, t0 is the delay time of the unmanned obstacle clearing vehicle (2) equipment, that is, the reaction time from receiving the ultrasonic wave to emitting the ultrasonic wave; T2 is the actual time required for the UAV (1) to receive the ultrasonic wave of the same frequency from emitting the ultrasonic wave. The value of δ is the theoretical time required for the drone (1) to receive ultrasonic waves of the same frequency from emitting ultrasonic waves. Therefore, δ is the ratio of the absolute value of the theoretical time and the actual time difference to the theoretical time. If δ is within the threshold range, a Bluetooth connection with the corresponding unmanned vehicle (2) is established. After the connection is established, the drone (1) and the corresponding unmanned vehicle (2) will refuse to establish connections with other devices. That is, a drone (2) can only connect to one unmanned vehicle (2) at the same time. If δ is outside the threshold range, the Bluetooth connection with the corresponding unmanned vehicle (2) is refused, and a second connection with the unmanned vehicle (2) is attempted. If the connection still cannot be established the second time, the drone moves to another unmanned vehicle (2) and performs the operation of identifying the unmanned vehicle (2). The value of the threshold range is determined according to the accuracy requirements. The smaller the value of the threshold range, the higher the required accuracy. The larger the value of the threshold range, the lower the required accuracy. The process of opening the smart lock (3) includes: after establishing a Bluetooth connection between the drone (1) and the corresponding unmanned obstacle clearing vehicle (2), the drone (1) flies to a position 2 meters above the smart lock (3) and hovers there and emits a first specific frequency ultrasonic wave to the smart lock (3); after receiving the first specific frequency ultrasonic wave, the smart lock (3) activates the unlocking mechanism to automatically open the obstacle and allow the unmanned obstacle clearing vehicle (2) connected to the corresponding drone (1) to pass through; after the unmanned obstacle clearing vehicle (2) passes through the obstacle, the locking mechanism is activated to automatically close the obstacle; the first specific frequency ultrasonic wave is different from the obstacle clearing ultrasonic wave, and the first specific frequency ultrasonic wave is a specially set frequency used to open the smart lock (3).

4. The UAV obstacle removal device based on ultrasonic detection according to claim 1, characterized in that, The unmanned obstacle clearing vehicle (2) navigation includes: the drone (1) autonomously plans its path based on the mountain environment map and the location of the obstacle, and plans the flight path to perform the obstacle clearing operation; the drone (1) flies according to the flight path to perform the obstacle clearing operation, and sends its location information to the unmanned obstacle clearing vehicle (2) connected to it in real time via Bluetooth, and the unmanned obstacle clearing vehicle (2) moves along the road according to the location information sent by the drone (1).

5. The UAV obstacle removal device based on ultrasonic detection according to claim 1, characterized in that, The identification of the object locator (4) includes: when the drone (1) leads the corresponding unmanned obstacle clearing vehicle (2) to the obstacle location information, identifying the object locator (4) placed around it, obtaining the location information of the object locator (4), and guiding the corresponding unmanned obstacle clearing vehicle (2) to move the obstacle to the object locator (4).

6. The UAV obstacle removal device based on ultrasonic detection according to claim 1, characterized in that, The unmanned obstacle clearing vehicle (2) has a drone (1) landing platform on its top, which includes: the unmanned obstacle clearing vehicle (2) is a modified obstacle clearing vehicle with a drone (1) landing platform on its top and an on-board intelligent sensing and control integrated machine; the drone (1) landing platform is used to park the drone (1) when it is not in operation, and the on-board intelligent sensing and control integrated machine has an obstacle sensing module, an intelligent algorithm module and an execution control interface; the obstacle sensing module is used to identify the position and size of obstacles; the intelligent algorithm module includes: obstacle recognition algorithm, size estimation algorithm, path planning algorithm and pusher action control algorithm; the execution control interface is used to control the pusher to push the obstacle to the designated area.

7. The UAV obstacle removal device based on ultrasonic detection according to claim 1, characterized in that, The smart lock (3) includes an embedded control board, which is used to analyze the received ultrasonic signal and determine whether the signal is valid; if the signal is valid, the electronic lock is controlled to unlock; if the signal is invalid, no response is made.

8. The UAV obstacle removal device based on ultrasonic detection according to claim 1, characterized in that, The object locator (4) includes: a drone (1) hovering 2 meters directly above the object locator (4) and emitting a second specific frequency ultrasonic wave to the object locator (4). After receiving the second specific frequency ultrasonic wave, the object locator (4) immediately emits an ultrasonic wave of the same frequency as the second specific frequency ultrasonic wave to the drone (1). After receiving the ultrasonic wave of the same frequency as the second specific frequency ultrasonic wave, the drone (1) extracts the location information of the object locator (4) and sends the location information to the unmanned obstacle clearing vehicle (2), which moves the obstacle to the location of the object locator (4). The second specific frequency ultrasonic wave is a specially set designated frequency used to identify the object locator (4). The second specific frequency ultrasonic wave is different from the first specific frequency ultrasonic wave and the obstacle clearing ultrasonic wave. Therefore, the first specific frequency ultrasonic wave and the second specific frequency ultrasonic wave are two different specific frequency ultrasonic waves, while the obstacle clearing ultrasonic wave is an ultrasonic wave with a freely selectable frequency that is different from the first specific frequency ultrasonic wave and the second specific frequency ultrasonic wave.

9. A method for clearing obstacles from a drone based on ultrasonic detection, characterized in that, The method is based on the obstacle removal device of UAV (1) based on ultrasonic detection as described in claim 1. The method includes: S100, after receiving the obstacle removal task, the UAV (1) leaves the UAV (1) landing platform of the unmanned obstacle removal vehicle (2) and cruises along the mountain road to obtain obstacle location information; S200, the UAV (1) flies to the entrance of the mountain area and identifies the unmanned obstacle removal vehicle (2) by obtaining image information of the unmanned obstacle removal vehicle (2) and establishing a connection with the unmanned obstacle removal vehicle (2); then, the UAV (1) hovers 2 meters above the smart lock (3) and activates the unlocking mechanism of the smart lock (3) by emitting a first specific frequency ultrasonic wave to the smart lock (3). The smart lock (3) unlocks the road obstacle and allows the unmanned obstacle removal vehicle to open. (2) Entering a closed section of the mountain road; S300, the UAV (1) performs autonomous path planning based on the mountain environment map and the location of the obstacle, and plans the flight path for performing obstacle removal operation; the UAV (1) flies according to the flight path for performing obstacle removal operation, and sends location information to the unmanned obstacle removal vehicle (2) connected to it via Bluetooth in real time, and the unmanned obstacle removal vehicle (2) moves along the road according to the location information sent by the UAV (1); S400, the UAV (1) arrives at the location of the obstacle, identifies the location of the object locator (4) by emitting a second specific frequency ultrasonic wave, and sends the location of the object locator (4) to the unmanned obstacle removal vehicle (2), and the unmanned obstacle removal vehicle (2) moves the obstacle to the location of the corresponding object locator (4).

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