Engineering acceptance method and system based on cooperation of unmanned aerial vehicle and unmanned vehicle

Abstract

The invention provides a project acceptance method and system based on cooperation of an unmanned aerial vehicle and an unmanned vehicle, and the method comprises the steps: obtaining a first cruise trajectory of the unmanned aerial vehicle in a target region land, and obtaining a second cruise trajectory of the unmanned vehicle in the target region land; controlling the unmanned aerial vehicle to perform first cruise shooting in the target area land according to the first cruise trajectory to obtain a first image sequence collected by the unmanned aerial vehicle, and controlling the unmanned vehicle to perform second cruise shooting in the target area land according to the second cruise trajectory to obtain a second image sequence collected by the unmanned vehicle; associating and screening the first image sequence and the second image sequence to obtain an effective image sequence set; and analyzing the effective image sequence set to obtain a land reclamation acceptance result of the target area land. The accuracy of land reclamation acceptance is improved, the intelligence of image acquisition is guaranteed, and the efficiency of land reclamation acceptance is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and particularly relates to an engineering acceptance method and system based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle. Background Art

[0002] At present, with the rapid development of industrialization and urbanization, a large amount of land has been mined, excavated or damaged, such as activities like open-pit coal mining and earth excavation for construction projects. Land reclamation aims to restore this damaged land to a utilizable state, which is of crucial significance for protecting land resources, maintaining ecological balance, ensuring agricultural production, and meeting the land demand for social development.

[0003] However, traditional land reclamation acceptance mainly relies on manual on-site inspection. This method has many limitations. Firstly, manual inspection is inefficient and requires a large amount of manpower, material resources and time. For large areas of reclaimed land, it is very time-consuming to conduct on-site measurements and evaluations one by one. Secondly, the accuracy of manual inspection is limited by the subjective factors and technical levels of the inspectors. Different inspectors may have differences in the understanding and implementation of acceptance standards, resulting in the reliability of acceptance results being affected. In addition, some complex terrain and environmental conditions, such as steep slopes and muddy wetlands, may cause difficulties and even dangers to manual inspection.

[0004] Therefore, in order to overcome the above technical problems, the present invention provides an engineering acceptance method and system based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle. Summary of the Invention

[0005] The present invention provides an engineering acceptance method and system based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle, which can effectively ensure the integrity and comprehensiveness of land image acquisition by obtaining a first image sequence through the unmanned aerial vehicle based on a first cruise trajectory and a second image sequence through the unmanned vehicle based on a second cruise trajectory, achieving the goal of multi-angle analysis of land reclamation acceptance. By correlating the first image sequence and the second image sequence, it helps to conduct land reclamation acceptance of the target area land from different angles. Through screening, the accuracy and quality of the obtained effective image sequence can be effectively guaranteed. By analyzing the set of effective image sequences, the land reclamation acceptance result of the target area land can be obtained, which can effectively realize the multi-source data acceptance of land reclamation acceptance, thereby improving the accuracy of land reclamation acceptance. At the same time, by controlling the unmanned aerial vehicle and the unmanned vehicle to take pictures, the intelligence of image acquisition is effectively guaranteed, and thus the efficiency of land reclamation acceptance is improved.

[0006] The present invention provides an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle, including:

[0007] Step 1: Obtain the first cruise trajectory of the drone over the land in the target area. Meanwhile, obtain the second cruise trajectory of the unmanned vehicle over the land in the target area;

[0008] Step 2: Control the drone to conduct the first cruise shooting over the land in the target area according to the first cruise trajectory, and obtain the first image sequence collected by the drone. Meanwhile, control the unmanned vehicle to conduct the second cruise shooting over the land in the target area according to the second cruise trajectory, and obtain the second image sequence collected by the unmanned vehicle;

[0009] Step 3: Correlate and screen the first image sequence and the second image sequence to obtain a set of effective image sequences;

[0010] Step 4: Analyze the set of effective image sequences to obtain the result of the land reclamation acceptance for the land in the target area.

[0011] Preferably, for an engineering acceptance method based on the cooperation of a drone and an unmanned vehicle, in Step 1, obtaining the first cruise trajectory of the drone over the land in the target area includes:

[0012] Obtain the land in the target area for land reclamation acceptance, and obtain the location distribution characteristics of the land in the target area;

[0013] Locate the boundary contour of the land in the target area according to the location distribution characteristics of the land in the target area, and the position points of the boundary contour of the land in the target area;

[0014] Obtain the terrain characteristics of the land in the target area;

[0015] Determine the geometric parameters of the land in the target area according to the position points of the boundary contour of the land in the target area and the terrain characteristics of the land in the target area, and formulate the first cruise trajectory of the drone over the land in the target area according to the geometric parameters.

[0016] Preferably, for an engineering acceptance method based on the cooperation of a drone and an unmanned vehicle, in Step 1, obtaining the second cruise trajectory of the unmanned vehicle over the land in the target area includes:

[0017] Collect the land characteristics of the land in the target area and determine the static obstacles in the land in the target area;

[0018] Obtain the set of land boundary points of the land in the target area, and take any land boundary point in the set of land boundary points as the coordinate origin to construct a two-dimensional coordinate system of the land in the target area;

[0019] Obtain the first relative position relationships between the remaining land boundary points in the set of land boundary points and the coordinate origin, and determine the multiple first coordinate points of the remaining land boundary points in the two-dimensional coordinate system according to the first relative position relationships, and perform the first annotation on the multiple first coordinate points in the two-dimensional coordinate system to obtain the first regional plane;

[0020] Obtain the set of obstacle boundary points of the static obstacle, obtain the second relative position relationship between each obstacle boundary point in the set of obstacle boundary points and the coordinate origin, and determine the second coordinate points of the set of obstacle boundary points in the two-dimensional coordinate system according to the second relative position relationship. At the same time, perform second annotation on multiple second coordinate points in the two-dimensional coordinate system to obtain the second region plane;

[0021] Construct the second cruise trajectory of the driverless vehicle on the target area land according to the position distribution of the second region plane in the first region plane.

[0022] Preferably, in an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and a driverless vehicle, in step 2, control the unmanned aerial vehicle to perform first cruise shooting in the target area land according to the first cruise trajectory, and obtain the first image sequence collected by the unmanned aerial vehicle, including:

[0023] Read the first cruise trajectory to determine the first cruise trajectory data. At the same time, obtain the instruction reading format of the unmanned aerial vehicle;

[0024] Convert the first cruise trajectory data into the first instruction element according to the instruction reading format of the unmanned aerial vehicle. At the same time, obtain the preset image acquisition frequency of the unmanned aerial vehicle and generate the second instruction element according to the preset image acquisition frequency of the unmanned aerial vehicle;

[0025] Generate the first shooting instruction according to the first instruction element and the second instruction element, and control the unmanned aerial vehicle to perform first cruise shooting in the target area land according to the first shooting instruction;

[0026] Sort and store the first images after shooting according to the shooting sequence to obtain the first image sequence collected by the unmanned aerial vehicle.<00fffff

[0027] Preferably, in an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and a driverless vehicle, in step 2, control the driverless vehicle to perform second cruise shooting in the target area land according to the second cruise trajectory, and obtain the second image sequence collected by the driverless vehicle, including:

[0028] Obtain the instruction reading format of the driverless vehicle, and perform format conversion on the second cruise trajectory according to the instruction reading format of the driverless vehicle to obtain the third instruction element;

[0029] Read the preset image acquisition frequency of the driverless vehicle and generate the fourth instruction element according to the preset image acquisition frequency of the driverless vehicle;

[0030] Generate the second shooting instruction according to the third instruction element and the fourth instruction element, and control the driverless vehicle to perform second cruise shooting in the target area land according to the second shooting instruction, and obtain the second image sequence collected by the driverless vehicle according to the shooting sequence.

[0031] Preferably, for an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle, in step 3, the first image sequence and the second image sequence are associated and screened to obtain a set of effective image sequences, including:

[0032] Obtain the obtained first image sequence and second image sequence, and sequentially perform frame division on the first image sequence and the second image sequence to obtain a set of image frames;

[0033] Perform edge detection on each image frame in the set of image frames to determine the object edge features recorded in each image frame. At the same time, based on the object edge features, determine the image acquisition perspectives of the unmanned aerial vehicle and the unmanned vehicle, and respectively determine the different presentation features of the same object under the image acquisition perspectives of the unmanned aerial vehicle and the unmanned vehicle based on the first cruise trajectory and the second cruise trajectory;

[0034] Traverse the image frames of the first image sequence and the second image sequence based on the different presentation features of the same object, and associate the first image sequence and the second image sequence according to the same object index based on the object traversal result to obtain an image pair sequence;

[0035] Screen the first image sequence and the second image sequence based on the image pair sequence to obtain a set of effective image sequences.

[0036] Preferably, for an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle, screen the first image sequence and the second image sequence based on the association result to obtain a set of effective image sequences, including:

[0037] Obtain the image pairs of the first image sequence and the second image sequence, and determine the mapping relationship of the image frames of the same object in the first image sequence and the second image sequence based on the image pairs;

[0038] Based on the mapping relationship, determine whether there are multiple-to-one in the image pairs of the same object. When there are multiple-to-one, determine that there are duplicate image frames, and retain one of the duplicate image frames;

[0039] Obtain effective image pairs based on the result of retaining one, and perform integrated association on the effective image pairs to obtain a set of effective image sequences.

[0040] Preferably, for an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle, in step 4, analyze the set of effective image sequences to obtain the land reclamation acceptance result of the target area land, including:

[0041] Obtain the acceptance dimensions for the land reclamation acceptance of the target area land, analyze the set of effective image sequences according to the acceptance dimensions, and determine the land features of the target area land corresponding to each acceptance dimension according to the analysis result;

[0042] Obtain the acceptance criteria for each acceptance dimension, match the land features corresponding to each acceptance dimension with the acceptance criteria for each acceptance dimension to obtain the matching degree corresponding to each acceptance dimension, and use the matching degree corresponding to each acceptance dimension as the target score for each acceptance dimension;

[0043] Obtain the target weight of each acceptance dimension in the land reclamation acceptance result, and calculate according to the target weight of each acceptance dimension in the land reclamation acceptance result and the target score corresponding to each acceptance dimension to obtain the comprehensive score of the land reclamation acceptance for the land in the target area, where the comprehensive score of the land reclamation acceptance is the land reclamation acceptance result for the land in the target area.

[0044] Preferably, an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle, formulating a first cruise trajectory of the unmanned aerial vehicle in the land of the target area according to geometric parameters, including:

[0045] Read the geometric parameters to determine the geometric shape of the land in the target area and the longitudinal height distribution state of the land in the target area;

[0046] Simulate in the computer according to the geometric shape of the land in the target area and the longitudinal height distribution state of the land in the target area to obtain a virtual target area of land;

[0047] Divide the closed areas with different longitudinal heights in the virtual target area of land according to the longitudinal height distribution state of the land in the target area to obtain a plurality of sub-virtual areas, where the longitudinal height of each sub-virtual area is the same;

[0048] Obtain the preset flight starting point and flight direction, and sequentially add serial number tags to each sub-virtual area according to the flight starting point and flight direction;

[0049] Determine the first trajectory element of the unmanned aerial vehicle in the virtual target area of land according to the serial number tag;

[0050] Match and map multiple sub-virtual areas in the geometric shape of the virtual target area of land, and divide the geometric shape of the virtual target area of land into multiple sub-geometric shapes according to the matching result, where the sub-geometric shapes correspond to the sub-virtual areas one by one;

[0051] Obtain the preset trajectory flight management library;

[0052] Input the sub-geometric shape into the preset trajectory flight management library for matching, and output the second trajectory element of the sub-virtual area corresponding to each sub-geometric shape;

[0053] Determine the connection points between every two adjacent sub-virtual areas according to the serial number tag, and determine the flight starting point and flight ending point in each sub-virtual area according to the serial number values of every two adjacent sub-virtual areas and the connection points;

[0054] Adaptive adjustment is performed on the second trajectory elements of each sub-virtual area according to the flight starting point and flight ending point in each sub-virtual area to obtain third trajectory elements;

[0055] Read the longitudinal height of each sub-virtual area, and label the longitudinal height of each sub-virtual area as a target label in the third trajectory elements to obtain target third trajectory elements;

[0056] Associate the first trajectory elements with multiple target third trajectory elements to obtain the first cruise trajectory of the drone in the target area land.

[0057] The present invention provides an engineering acceptance system based on the cooperation of drones and unmanned vehicles, including:

[0058] A cruise trajectory determination module, configured to obtain the first cruise trajectory of the drone in the target area land, and at the same time, obtain the second cruise trajectory of the unmanned vehicle in the target area land;

[0059] An image acquisition module, configured to control the drone to perform the first cruise shooting in the target area land according to the first cruise trajectory to obtain the first image sequence collected by the drone, and at the same time, control the unmanned vehicle to perform the second cruise shooting in the target area land according to the second cruise trajectory to obtain the second image sequence collected by the unmanned vehicle;

[0060] An image processing module, configured to associate and screen the first image sequence and the second image sequence to obtain a set of effective image sequences;

[0061] An acceptance module, configured to analyze the set of effective image sequences to obtain the land reclamation acceptance result of the target area land.

[0062] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0063] By obtaining the first image sequence through the drone shooting based on the first cruise trajectory and the second image sequence through the unmanned vehicle shooting based on the second cruise trajectory, it can effectively ensure the integrity and comprehensiveness of the land picture acquisition, realize the multi-angle analysis goal of land reclamation acceptance, the association of the first image sequence and the second image sequence helps to conduct land reclamation acceptance on the target area land from different angles, screening can effectively ensure the accuracy and quality of the obtained effective image sequences, and analyzing the set of effective image sequences to obtain the land reclamation acceptance result of the target area land can effectively realize the multi-source data acceptance of land reclamation acceptance, thereby improving the accuracy of land reclamation acceptance. At the same time, by controlling the drone and the unmanned vehicle to shoot, it effectively ensures the intelligence of image acquisition, and further improves the efficiency of land reclamation acceptance.

[0064] Other features and advantages of the present invention will be set forth in the following description, and in part will be obvious from the description, or may be learned by practice of the present invention. The objectives and other advantages of the present invention may be realized and attained by the structure particularly pointed out in this application document.

[0065] The technical solution of the present invention will be further described in detail below through the accompanying drawings and embodiments. Description of the Drawings

[0066] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, but do not constitute a limitation to the present invention. In the drawings:

[0067] Figure 1 It is a flowchart of a method for engineering acceptance based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle in an embodiment of the present invention;

[0068] Figure 2 It is a flowchart of step 1 in a method for engineering acceptance based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle in an embodiment of the present invention;

[0069] Figure 3 It is a structural diagram of a system for engineering acceptance based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle in an embodiment of the present invention. Detailed Embodiments

[0070] The following describes the preferred embodiments of the present invention with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not used to limit the present invention.

[0071] Embodiment 1:

[0072] This embodiment provides a method for engineering acceptance based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle, as Figure 1 shown, including:

[0073] Step 1: Obtain the first cruise trajectory of the unmanned aerial vehicle on the land of the target area. At the same time, obtain the second cruise trajectory of the unmanned vehicle on the land of the target area;

[0074] Step 2: Control the unmanned aerial vehicle to perform the first cruise shooting in the land of the target area according to the first cruise trajectory, and obtain the first image sequence collected by the unmanned aerial vehicle. At the same time, control the unmanned vehicle to perform the second cruise shooting in the land of the target area according to the second cruise trajectory, and obtain the second image sequence collected by the unmanned vehicle;

[0075] Step 3: Correlate and screen the first image sequence and the second image sequence to obtain a set of effective image sequences;

[0076] Step 4: Analyze the set of valid image sequences to obtain the land reclamation acceptance result for the target area of land.

[0077] In this embodiment, the first cruise trajectory can be used to represent the operating trajectory of the drone during image acquisition in the target area of land, and the images it acquires form the first image sequence.

[0078] In this embodiment, the second cruise trajectory can be used to represent the operating trajectory of the unmanned vehicle during image acquisition in the target area of land, and the images it acquires form the second image sequence.

[0079] In this embodiment, the target area of land can be a land area that requires land reclamation acceptance (i.e., project acceptance).

[0080] In this embodiment, the first image sequence and the second image sequence are associated and filtered. Here, association means associating the first image sequence and the second image sequence according to the same area, that is, achieving the purpose of being able to read the first image acquired by the drone and the second image acquired by the unmanned vehicle simultaneously in the same area; filtering means removing the duplicate images in the first image sequence and the duplicate images in the second image sequence, so as to obtain the valid image sequences.

[0081] In this embodiment, the set of valid image sequences is an image set that can represent the target area of land after removing duplicates.

[0082] In this embodiment, the acceptance result is the comprehensive score of land reclamation acceptance obtained after analyzing the valid image sequences.

[0083] The working principle and beneficial effects of the above technical solution are as follows: By using the drone to take pictures based on the first cruise trajectory to obtain the first image sequence and the unmanned vehicle to take pictures based on the second cruise trajectory to obtain the second image sequence, it can effectively ensure the integrity and comprehensiveness of the land picture acquisition, achieve the goal of multi-angle analysis of land reclamation acceptance. Associating the first image sequence and the second image sequence helps to conduct land reclamation acceptance for the target area of land from different angles. Filtering can effectively ensure the accuracy and quality of the obtained valid image sequences. Analyzing the set of valid image sequences to obtain the land reclamation acceptance result for the target area of land can effectively achieve the multi-source data acceptance of land reclamation acceptance, thereby improving the accuracy of land reclamation acceptance. At the same time, by controlling the drone and the unmanned vehicle to take pictures, it effectively ensures the intelligence of image acquisition, and further improves the efficiency of land reclamation acceptance.

[0084] Embodiment 2:

[0085] Based on Embodiment 1, this embodiment provides an engineering acceptance method based on the cooperation of a drone and an unmanned vehicle, as Figure 2As shown in the figure, in step 1, obtaining the first cruise trajectory of the drone over the land in the target area includes:

[0086] Obtaining the land in the target area for land reclamation acceptance, and obtaining the location distribution characteristics of the land in the target area;

[0087] Positioning the boundary contour of the land in the target area according to the location distribution characteristics of the land in the target area, and the position points of the boundary contour of the land in the target area;

[0088] Obtaining the terrain characteristics of the land in the target area;

[0089] Determining the geometric parameters of the land in the target area according to the position points of the boundary contour of the land in the target area and the terrain characteristics of the land in the target area, and formulating the first cruise trajectory of the drone over the land in the target area according to the geometric parameters.

[0090] In this embodiment, the terrain characteristic is the height distribution state of the land in the target area.

[0091] In this embodiment, the location distribution characteristic is the contour distribution of the terrain in the target area.

[0092] In this embodiment, the boundary contour position points refer to the boundary distribution points of the land in the target area.

[0093] In this embodiment, the first cruise trajectory refers to the flight trajectory of the drone over the land in the target area.

[0094] The working principle and beneficial effects of the above technical solution are: by determining the location distribution characteristics of the land in the target area, effectively determining the boundary contour points of the land in the target area, and then effectively obtaining the geometric parameters, and formulating the first cruise trajectory of the drone over the land in the target area according to the geometric parameters, effectively realizing the effectiveness and accuracy of the drone flying over the target area and the land, and improving the working efficiency of the drone.

[0095] Embodiment 3:

[0096] Based on Embodiment 1, this embodiment provides an engineering acceptance method based on the cooperation of a drone and an unmanned vehicle. In step 1, obtaining the second cruise trajectory of the unmanned vehicle over the land in the target area includes:

[0097] Collecting the land characteristics of the land in the target area and determining the static obstacles in the land in the target area;

[0098] Obtaining the land boundary point set of the land in the target area, and taking any land boundary point in the land boundary point set as the coordinate origin to construct a two-dimensional coordinate system of the land in the target area;

[0099] Obtain the first relative position relationship between the remaining land boundary points in the land boundary point set and the coordinate origin, determine the multiple first coordinate points of the remaining land boundary points in the two-dimensional coordinate system according to the first relative position relationship, and perform the first annotation on the multiple first coordinate points in the two-dimensional coordinate system to obtain the first regional plane;

[0100] Obtain the obstacle boundary point set of the static obstacle, obtain the second relative position relationship between each obstacle boundary point in the obstacle boundary point set and the coordinate origin, and determine the second coordinate points of the obstacle boundary point set in the two-dimensional coordinate system according to the second relative position relationship. At the same time, perform the second annotation on the multiple second coordinate points in the two-dimensional coordinate system to obtain the second regional plane;

[0101] Construct the second cruise trajectory of the unmanned vehicle on the land in the target area according to the position distribution of the second regional plane in the first regional plane.

[0102] In this embodiment, the static obstacle is an object that cannot move and hinders the movement of the unmanned vehicle, such as a stone.

[0103] In this embodiment, the land feature is the distribution of obstacle buildings and the like on the land in the target area.

[0104] In this embodiment, the first regional plane is the plane formed by the land boundary points in the two-dimensional coordinate system (two-dimensional rectangular coordinate system).

[0105] In this embodiment, the second regional plane is the plane formed by the obstacle boundary point set of the static obstacle in the two-dimensional coordinate system, where the second regional plane belongs to the first regional plane.

[0106] In this embodiment, the second cruise trajectory is the walking path of the unmanned vehicle on the land in the target area.

[0107] The working principle and beneficial effects of the above technical solution are: by determining the first regional plane and the second regional plane, the second cruise trajectory of the unmanned vehicle on the land in the target area is effectively constructed, thereby effectively ensuring the effectiveness and accuracy of the walking path of the unmanned vehicle and improving the operation efficiency of the unmanned vehicle on the land in the target area.

[0108] Embodiment 4:

[0109] Based on Embodiment 1, this embodiment provides an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle. In step 2, control the unmanned aerial vehicle to perform the first cruise shooting in the land in the target area according to the first cruise trajectory to obtain the first image sequence collected by the unmanned aerial vehicle, including:

[0110] Read the first cruise trajectory to determine the first cruise trajectory data. At the same time, obtain the instruction reading format of the unmanned aerial vehicle;

[0111] Convert the first cruise trajectory data into the first instruction element according to the instruction reading format of the drone. Meanwhile, obtain the preset image acquisition frequency of the drone and generate the second instruction element according to the preset image acquisition frequency of the drone;

[0112] Generate the first shooting instruction according to the first instruction element and the second instruction element. Meanwhile, control the drone to perform the first cruise shooting in the target area land according to the first shooting instruction;

[0113] Sort and store the captured first images in the order of shooting to obtain the first image sequence collected by the drone.

[0114] In this embodiment, the instruction reading format is set in advance and is used to represent the inherent format when the drone reads instructions.

[0115] In this embodiment, the first shooting instruction is used to implement the instruction for the drone to perform the first cruise shooting in the target area land, and it is composed of the first instruction element and the second instruction element.

[0116] In this embodiment, the first image sequence refers to the image set collected by the drone.

[0117] The working principle and beneficial effects of the above technical solution are as follows: By performing format conversion on the instruction reading format of the drone, the first instruction element is effectively obtained, and the second instruction element is obtained through the image acquisition frequency. Furthermore, the first shooting instruction is effectively obtained based on the first instruction element and the second instruction element, which is beneficial to ensuring the accuracy and intelligence of the flight control of the drone in the target area land. By obtaining the first image sequence, the relevance and orderliness of image acquisition are effectively ensured.

[0118] Embodiment 5:

[0119] Based on Embodiment 1, this embodiment provides an engineering acceptance method based on the cooperation of a drone and an unmanned vehicle. In step 2, control the unmanned vehicle to perform the second cruise shooting in the target area land according to the second cruise trajectory to obtain the second image sequence collected by the unmanned vehicle, including:

[0120] Obtain the instruction reading format of the unmanned vehicle and perform format conversion on the second cruise trajectory according to the instruction reading format of the unmanned vehicle to obtain the third instruction element;

[0121] Read the preset image acquisition frequency of the unmanned vehicle and generate the fourth instruction element according to the preset image acquisition frequency of the unmanned vehicle;

[0122] Generate the second shooting instruction according to the third instruction element and the fourth instruction element, control the unmanned vehicle to perform the second cruise shooting in the target area land according to the second shooting instruction, and obtain the second image sequence collected by the unmanned vehicle according to the shooting sequence.

[0123] In this embodiment, the third instruction element is the result of format conversion of the second cruise trajectory based on the instruction reading format of the driverless vehicle, where the instruction reading format of the driverless vehicle is also set in advance and known.

[0124] In this embodiment, the second shooting instruction is an instruction used to control the second cruise shooting of the drone in the target area land, and it is composed of a third instruction element and a fourth instruction element.

[0125] In this embodiment, the second image sequence refers to the image set collected by the driverless vehicle.

[0126] The working principle and beneficial effects of the above technical solution are: by generating the second shooting instruction, the accuracy and intelligence of the second cruise shooting of the driverless vehicle are effectively realized, and by obtaining the second image sequence, the relevance and orderliness of image collection are effectively guaranteed.

[0127] Embodiment 6:

[0128] Based on Embodiment 1, this embodiment provides an engineering acceptance method based on the cooperation of drones and driverless vehicles. In step 3, the first image sequence and the second image sequence are associated and screened to obtain an effective image sequence set, including:

[0129] Obtain the first image sequence and the second image sequence obtained, and sequentially perform frame division on the first image sequence and the second image sequence to obtain an image frame set;

[0130] Perform edge detection on each image frame in the image frame set to determine the object edge features recorded in each image frame. At the same time, based on the object edge features, determine the image acquisition perspectives of the drone and the driverless vehicle, and respectively determine the different presentation features of the same object under the image acquisition perspectives of the drone and the driverless vehicle based on the first cruise trajectory and the second cruise trajectory;

[0131] Traverse the image frame sets of the first image sequence and the second image sequence based on the different presentation features of the same object, and associate the first image sequence and the second image sequence according to the same object index based on the object traversal result to obtain an image pair sequence;

[0132] Screen the first image sequence and the second image sequence based on the image pair sequence to obtain an effective image sequence set.

[0133] In this embodiment, frame division refers to splitting the images corresponding to each moment in the first image sequence and the second image sequence, that is, obtaining the static images corresponding to each moment.

[0134] In this embodiment, edge detection refers to analyzing the image edges of each image frame, aiming to determine the edge features of the objects recorded in each image frame (i.e., edge shapes, etc.).

[0135] In this embodiment, different presentation features refer to the different appearance features of the same object presented from the image acquisition perspectives of the drone and the unmanned vehicle.

[0136] In this embodiment, object traversal refers to determining the land areas or objects recorded in each frame of the image frame sets of the first image sequence and the second image sequence.

[0137] In this embodiment, the same object index refers to the unified recording subject.

[0138] In this embodiment, the image pair sequence refers to associating the images of the unified object recorded in the first image sequence and the second image sequence, that is, each image pair sequence contains a drone image and an unmanned vehicle image.

[0139] The working principle and beneficial effects of the above technical solution are as follows: By performing frame division on the first image sequence and the second image sequence, the determination of the image frame set is realized. At the same time, edge detection is performed on each image frame in the image frame set to lock the image acquisition perspectives of the drone and the unmanned vehicle according to the edge detection results. Secondly, different presentation features of the same object from the image acquisition perspectives of the drone and the unmanned vehicle are determined respectively. Finally, the image frames of the unified object in the image frame sets of the first image sequence and the second image sequence are associated according to the presentation features, and the association results are screened, and finally the determination of the effective image sequence set is realized, providing reliable image support and convenience for land reclamation acceptance.

[0140] Embodiment 7:

[0141] Based on Embodiment 6, this embodiment provides an engineering acceptance method based on the cooperation of a drone and an unmanned vehicle. Screening the first image sequence and the second image sequence based on the association results to obtain an effective image sequence set, including:

[0142] Obtain the image pairs of the first image sequence and the second image sequence, and determine the mapping relationship of the image frames of the same object in the first image sequence and the second image sequence based on the image pairs;

[0143] Based on the mapping relationship, determine whether there are multiple-to-one in the image pairs of the same object. When there are multiple-to-one, it is determined that there are duplicate image frames, and one of the duplicate image frames is selected and retained;

[0144] Obtain effective image pairs based on the result of selecting and retaining one, and perform integrated association on the effective image pairs to obtain an effective image sequence set.

[0145] The working principle and beneficial effects of the above technical solution are as follows: By analyzing the mapping relationship of the image frames of the same object in the first image sequence and the second image sequence in the image pair, it is effectively realized that when there is a one-to-many situation, it is determined as a duplicate image frame, and thus the duplicate images are selectively retained, effectively ensuring the accuracy of obtaining the effective image sequence set, and providing effective data support for the engineering acceptance of the cooperation between the unmanned aerial vehicle and the unmanned vehicle.

[0146] Embodiment 8:

[0147] Based on Embodiment 1, this embodiment provides an engineering acceptance method based on the cooperation between an unmanned aerial vehicle and an unmanned vehicle. In step 4, the effective image sequence set is analyzed to obtain the land reclamation acceptance result of the target area land, including:

[0148] Obtain the acceptance dimensions for the land reclamation acceptance of the target area land, analyze the effective image sequence set according to the acceptance dimensions, and determine the land characteristics of the target area land corresponding to each acceptance dimension according to the analysis results;

[0149] Obtain the acceptance criteria for each acceptance dimension, match the land characteristics corresponding to each acceptance dimension with the acceptance criteria for each acceptance dimension to obtain the matching degree corresponding to each acceptance dimension, and use the matching degree corresponding to each acceptance dimension as the target score for each acceptance dimension;

[0150] Obtain the target weight of each acceptance dimension in the land reclamation acceptance result, and calculate according to the target weight of each acceptance dimension in the land reclamation acceptance result and the target score corresponding to each acceptance dimension to obtain the comprehensive score of the land reclamation acceptance of the target area land, where the comprehensive score of the land reclamation acceptance is the land reclamation acceptance result of the target area land.

[0151] In this embodiment, the acceptance dimensions for the land reclamation acceptance of the target area land include: vegetation coverage acceptance, soil quality acceptance (characteristics such as soil color and texture), and terrain transformation acceptance.

[0152] In this embodiment, the acceptance criteria are the qualified indicators corresponding to each acceptance dimension. For example: the standard vegetation coverage, the soil color, texture and other characteristics that conform to good soil characteristics, and the standard terrain characteristics, etc.

[0153] In this embodiment, the target weight is the influence degree of each acceptance dimension on the land reclamation acceptance result, which is beneficial to realizing the objectivity and effectiveness of obtaining the comprehensive score of the land reclamation acceptance based on the target weight.

[0154] The working principle and beneficial effects of the above technical solution are as follows: By obtaining the acceptance dimensions for the land reclamation acceptance of the target area land and the land characteristics of the target area land corresponding to each acceptance dimension, the matching degree corresponding to each acceptance dimension can be effectively obtained. Furthermore, the matching degree corresponding to each acceptance dimension is used as the target score for each acceptance dimension, and the target score is comprehensively calculated according to the target weight of each acceptance dimension in the land reclamation acceptance result, so as to effectively obtain the land reclamation acceptance result of the target area land, improve the accuracy of obtaining the land reclamation acceptance result of the target area land, be conducive to ensuring the objectivity and effectiveness of obtaining the comprehensive score of the land reclamation acceptance, and further improve the efficiency of the land reclamation acceptance.

[0155] Embodiment 9:

[0156] Based on Embodiment 2, this embodiment provides an engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle. The first cruise trajectory of the unmanned aerial vehicle in the target area land is formulated according to geometric parameters, including:

[0157] Read the geometric parameters to determine the geometric shape of the target area land and the longitudinal height distribution state of the target area land;

[0158] Simulate in the computer according to the geometric shape of the target area land and the longitudinal height distribution state of the target area land to obtain a virtual target area land;

[0159] Divide the closed areas with different longitudinal heights in the virtual target area land according to the longitudinal height distribution state of the target area land to obtain a plurality of sub-virtual areas, where the longitudinal height of each sub-virtual area is the same;

[0160] Obtain the preset flight starting point and flight direction, and sequentially add serial number tags to each sub-virtual area according to the flight starting point and flight direction;

[0161] Determine the first trajectory element of the unmanned aerial vehicle in the virtual target area land according to the serial number tag;

[0162] Match and map the multiple sub-virtual areas in the geometric shape of the virtual target area land, and divide the geometric shape of the virtual target area land into multiple sub-geometric shapes according to the matching result, where the sub-geometric shapes correspond to the sub-virtual areas one by one;

[0163] Obtain the preset trajectory flight management library;

[0164] Input the sub-geometric shapes into the preset trajectory flight management library for matching, and output the second trajectory element of the sub-virtual area corresponding to each sub-geometric shape;

[0165] Determine the connection points of every two adjacent sub-virtual regions according to the serial number tags, and determine the flight starting points and flight ending points in each sub-virtual region according to the serial number values of every two adjacent sub-virtual regions and the connection points;

[0166] Adaptively adjust the second trajectory elements of each sub-virtual region according to the flight starting points and flight ending points in each sub-virtual region to obtain the third trajectory elements;

[0167] Read the longitudinal height of each sub-virtual region, and mark the longitudinal height of each sub-virtual region as a target label in the third trajectory elements to obtain the target third trajectory elements;

[0168] Associate the first trajectory elements with multiple target third trajectory elements to obtain the first cruise trajectory of the drone in the target area land.

[0169] In this embodiment, the geometric parameters refer to the data information that can characterize the shape of the target area.

[0170] In this embodiment, the longitudinal height distribution state refers to the terrain distribution of different horizontal heights in the target area land. For example, the different ground heights corresponding to the valleys and peaks of the target area land are the longitudinal height distribution state.

[0171] In this embodiment, the virtual target area land refers to the simulation model of the target area land obtained by simulating the longitudinal height distribution state of the target area land in the computer. <id=

[0172] In this embodiment, the closed area refers to the planes of different longitudinal heights in the virtual target area land, and a ground plane at one height is a closed area.

[0173] In this embodiment, the sub-virtual region refers to the land areas corresponding to different heights obtained by dividing the closed areas of different longitudinal heights in the virtual target area land.

[0174] In this embodiment, the serial number tag refers to the symbol for marking different sub-virtual regions. Through the serial number tag, the order of image acquisition for the land areas corresponding to different sub-virtual regions can be determined.

[0175] In this embodiment, the first trajectory elements are determined according to the serial number tags and are determined in the increasing order of the serial number tags.

[0176] In this embodiment, the sub-geometric shape refers to the result obtained by dividing each sub-virtual region in the geometric shape of the virtual target area land after matching and mapping multiple sub-virtual regions in the geometric shape of the virtual target area land.

[0177] In this embodiment, the preset trajectory flight library pre-stores a plurality of geometric shapes and the optimal cruise trajectories corresponding to each sub-geometric shape.

[0178] In this embodiment, the second trajectory element refers to the flight route in the land area corresponding to each sub-virtual area when image acquisition is performed on the land area corresponding to each sub-virtual area.

[0179] In this embodiment, the connection point refers to the boundary line between two adjacent sub-virtual areas.

[0180] In this embodiment, determining the flight starting point and flight ending point in each sub-virtual area according to the serial number values of every two adjacent sub-virtual areas and the connection point means determining the flight order of each sub-virtual area according to the increasing order of the serial number labels (i.e., serial number values), and determining the flight starting point and flight ending point of each sub-virtual area according to the connection point can be setting the connection point as the flight starting point and flight ending point of each sub-virtual area, aiming to ensure that the UAV conducts comprehensive and effective image acquisition of the corresponding land area.

[0181] In this embodiment, the third trajectory element refers to the result obtained by adjusting the second trajectory element of each sub-virtual area according to the determined flight starting point and flight ending point in each sub-virtual area, that is, the finally corresponding trajectory.

[0182] In this embodiment, the target third trajectory element refers to the result obtained by adding flight altitude markings to the obtained third trajectory element, aiming to guide the flight altitude of the UAV.

[0183] The working principle and beneficial effects of the above technical solution are as follows: By determining the geometric shape and longitudinal height distribution state of the land in the target area, a simulation of the land in the target area is realized in the computer to obtain an accurate and effective virtual target area land. Secondly, according to the longitudinal height distribution state of the land in the target area, the closed areas with different longitudinal heights in the virtual target area land are divided to determine the sub-virtual areas, and serial number tags are added to multiple sub-virtual areas according to the preset flight starting point and flight direction to determine the first trajectory element of the UAV in the virtual target area land. Finally, multiple sub-virtual areas are matched and mapped in the geometric shape of the virtual target area land to determine the sub-geometric small yellow corresponding to each sub-virtual area, and the second trajectory element of the sub-virtual area corresponding to each sub-geometric shape is determined according to the preset trajectory flight management library. At the same time, according to the serial number tag and the connection points of every two adjacent sub-virtual areas, the flight starting point and flight ending point in each sub-virtual area are determined. Finally, according to the flight starting point and flight ending point in each sub-virtual area, the second trajectory element of each sub-virtual area is adaptively adjusted to obtain the third trajectory element, and the flight height of the third trajectory element is marked according to the longitudinal height of each sub-virtual area. Finally, according to the marking result, the first trajectory element is associated with multiple target third trajectory elements to lock the first cruise trajectory of the UAV on the land in the target area, improving the efficiency and accuracy of the land reclamation acceptance.

[0184] Embodiment 10:

[0185] This embodiment provides an engineering acceptance system based on the cooperation of an unmanned aerial vehicle (UAV) and an unmanned vehicle, as Figure 3 shown, including:

[0186] A cruise trajectory determination module, configured to obtain the first cruise trajectory of the UAV on the land in the target area, and at the same time, obtain the second cruise trajectory of the unmanned vehicle on the land in the target area;

[0187] An image acquisition module, configured to control the UAV to perform the first cruise shooting in the land of the target area according to the first cruise trajectory to obtain the first image sequence collected by the UAV, and at the same time, control the unmanned vehicle to perform the second cruise shooting in the land of the target area according to the second cruise trajectory to obtain the second image sequence collected by the unmanned vehicle;

[0188] An image processing module, configured to associate and screen the first image sequence and the second image sequence to obtain a set of effective image sequences;

[0189] An acceptance module, configured to analyze the set of effective image sequences to obtain the land reclamation acceptance result of the land in the target area.

[0190] The working principle and beneficial effects of the above technical solution are as follows: By using a drone to capture a first image sequence based on a first cruise trajectory and a self-driving vehicle to capture a second image sequence based on a second cruise trajectory, the integrity and comprehensiveness of land image acquisition can be effectively ensured, achieving the goal of multi-angle analysis for land reclamation acceptance. Associating the first image sequence with the second image sequence helps to conduct land reclamation acceptance for the target area from different perspectives. Through screening, the accuracy and quality of the obtained valid image sequences can be effectively guaranteed. By analyzing the set of valid image sequences, the land reclamation acceptance result for the target area can be obtained, effectively realizing the multi-source data acceptance for land reclamation acceptance, thereby improving the accuracy of land reclamation acceptance. At the same time, by controlling the drone and the self-driving vehicle to capture images, the intelligence of image acquisition is effectively ensured, and thus the efficiency of land reclamation acceptance is improved.

[0191] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. An engineering acceptance method based on the collaboration of drones and unmanned vehicles, characterized in that, Including: Step 1: Obtain the first cruise trajectory of the drone over the target area of the land. Meanwhile, obtain the second cruise trajectory of the unmanned vehicle over the target area of the land. Step 2: Control the drone to perform the first cruise shooting over the target area of the land according to the first cruise trajectory, and obtain the first image sequence collected by the drone. Meanwhile, control the unmanned vehicle to perform the second cruise shooting over the target area of the land according to the second cruise trajectory, and obtain the second image sequence collected by the unmanned vehicle. Step 3: Correlate and screen the first image sequence and the second image sequence to obtain a set of effective image sequences. Step 4: Analyze the set of effective image sequences to obtain the result of the land reclamation acceptance for the target area of the land.

2. The engineering acceptance method based on the cooperation of drones and driverless vehicles according to claim 1, wherein In Step 1, obtaining the first cruise trajectory of the drone over the target area of the land includes: Obtain the target area of the land for land reclamation acceptance, and obtain the location distribution characteristics of the target area of the land. Locate the boundary contour of the target area of the land according to the location distribution characteristics of the target area of the land, and obtain the position points of the boundary contour of the target area of the land. Obtain the terrain characteristics of the target area of the land. Determine the geometric parameters of the target area of the land according to the position points of the boundary contour of the target area of the land and the terrain characteristics of the target area of the land, and formulate the first cruise trajectory of the drone over the target area of the land according to the geometric parameters.

3. The engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle according to claim 1, wherein, In Step 1, obtaining the second cruise trajectory of the unmanned vehicle over the target area of the land includes: Collect the land characteristics of the target area of the land and determine the static obstacles in the target area of the land. Obtain the set of land boundary points of the target area of the land, and take any land boundary point in the set of land boundary points as the coordinate origin to construct a two-dimensional coordinate system for the target area of the land. Obtain the first relative position relationships between the remaining land boundary points in the set of land boundary points and the coordinate origin, and determine the multiple first coordinate points of the remaining land boundary points in the two-dimensional coordinate system according to the first relative position relationships. Meanwhile, perform the first annotation on the multiple first coordinate points in the two-dimensional coordinate system to obtain the first regional plane. Obtain the set of obstacle boundary points of the static obstacles, and obtain the second relative position relationships between each obstacle boundary point in the set of obstacle boundary points and the coordinate origin. Meanwhile, determine the second coordinate points of the set of obstacle boundary points in the two-dimensional coordinate system according to the second relative position relationships. At the same time, perform the second annotation on the multiple second coordinate points in the two-dimensional coordinate system to obtain the second regional plane. Construct the second cruise trajectory of the unmanned vehicle over the target area of the land according to the position distribution of the second regional plane in the first regional plane.

4. The engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle according to claim 1, wherein In Step 2, controlling the drone to perform the first cruise shooting over the target area of the land according to the first cruise trajectory and obtaining the first image sequence collected by the drone includes: Read the first cruise trajectory to determine the first cruise trajectory data. Meanwhile, obtain the command reading format of the drone. Convert the first cruise trajectory data into the first command element according to the command reading format of the drone. Meanwhile, obtain the preset image acquisition frequency of the drone, and generate the second command element according to the preset image acquisition frequency of the drone. Generate the first shooting command according to the first command element and the second command element. Meanwhile, control the drone to perform the first cruise shooting over the target area of the land according to the first shooting command. Sort and store the first images taken according to the shooting sequence to obtain the first image sequence collected by the drone.

5. The engineering acceptance method based on the cooperation of an unmanned aerial vehicle and an unmanned vehicle according to claim 1, wherein In step 2, control the unmanned vehicle to perform a second cruise shooting in the target area land according to the second cruise trajectory, and obtain the second image sequence collected by the unmanned vehicle, including: Obtain the instruction reading format of the unmanned vehicle, and perform format conversion on the second cruise trajectory according to the instruction reading format of the unmanned vehicle to obtain the third instruction element; Read the preset image acquisition frequency of the unmanned vehicle, and generate a fourth instruction element according to the preset image acquisition frequency of the unmanned vehicle; Generate a second shooting instruction according to the third instruction element and the fourth instruction element, and control the unmanned vehicle to perform a second cruise shooting in the target area land according to the second shooting instruction, and obtain the second image sequence collected by the unmanned vehicle according to the shooting sequence.

6. The engineering acceptance method based on the cooperation of drones and unmanned vehicles according to claim 1, wherein In step 3, associate and screen the first image sequence and the second image sequence to obtain a set of effective image sequences, including: Obtain the obtained first image sequence and the second image sequence, and perform frame division on the first image sequence and the second image sequence in turn to obtain an image frame set; Perform edge detection on each image frame in the image frame set to determine the object edge features recorded in each image frame. At the same time, determine the image acquisition perspectives of the drone and the unmanned vehicle based on the object edge features, and respectively determine the different performance features of the same object under the image acquisition perspectives of the drone and the unmanned vehicle based on the first cruise trajectory and the second cruise trajectory; Perform object traversal on the image frame sets of the first image sequence and the second image sequence based on the different performance features of the same object, and associate the first image sequence and the second image sequence according to the same object index based on the object traversal result to obtain an image pair sequence; Screen the first image sequence and the second image sequence based on the image pair sequence to obtain a set of effective image sequences.

7. The engineering acceptance method based on the cooperation of drones and unmanned vehicles according to claim 6, wherein Screen the first image sequence and the second image sequence based on the association result to obtain a set of effective image sequences, including: Obtain the image pairs of the first image sequence and the second image sequence, and determine the mapping relationship of the image frames of the same object in the first image sequence and the second image sequence based on the image pairs; Determine whether there are multiple-to-one in the image pairs of the same object based on the mapping relationship, and when there are multiple-to-one, determine that there are duplicate image frames, and select one of the duplicate image frames to be retained; Obtain effective image pairs based on the result of selecting one to be retained, and perform integrated association on the effective image pairs to obtain a set of effective image sequences.

8. The engineering acceptance method based on the cooperation of drones and driverless vehicles according to claim 1, characterized in that In step 4, analyze the set of effective image sequences to obtain the land reclamation acceptance result of the target area land, including: Obtain the acceptance dimensions for land reclamation acceptance of the target area land, analyze the set of effective image sequences according to the acceptance dimensions, and determine the land features of the target area land corresponding to each acceptance dimension according to the analysis result; Obtain the acceptance criteria for each acceptance dimension, match the land features corresponding to each acceptance dimension with the acceptance criteria for each acceptance dimension, obtain the matching degree corresponding to each acceptance dimension, and use the matching degree corresponding to each acceptance dimension as the target score for each acceptance dimension. Obtain the target weight of each acceptance dimension in the land reclamation acceptance result, and calculate according to the target weight of each acceptance dimension in the land reclamation acceptance result and the target score corresponding to each acceptance dimension to obtain the comprehensive score of the land reclamation acceptance of the target area land. Among them, the comprehensive score of the land reclamation acceptance is the land reclamation acceptance result of the target area land.

9. The engineering acceptance method based on the cooperation of drones and unmanned vehicles according to claim 2, wherein, Formulate the first cruise trajectory of the drone in the target area land according to the geometric parameters, including: Read the geometric parameters to determine the geometric shape of the target area land and the longitudinal height distribution state of the target area land; Simulate in the computer according to the geometric shape of the target area land and the longitudinal height distribution state of the target area land to obtain a virtual target area land; Divide the closed areas with different longitudinal heights in the virtual target area land according to the longitudinal height distribution state of the target area land to obtain multiple sub-virtual areas, where the longitudinal height of each sub-virtual area is the same; Obtain the preset flight starting point and flight direction, and add serial number labels to each sub-virtual area in turn according to the flight starting point and flight direction; Determine the first trajectory element of the drone in the virtual target area land according to the serial number label; Match and map multiple sub-virtual areas in the geometric shape of the virtual target area land, and divide the geometric shape of the virtual target area land into multiple sub-geometric shapes according to the matching result, where the sub-geometric shapes correspond to the sub-virtual areas one by one; Obtain the preset trajectory flight management library; Input the sub-geometric shape into the preset trajectory flight management library for matching, and output the second trajectory element of the sub-virtual area corresponding to each sub-geometric shape; Determine the connection points between every two adjacent sub-virtual areas according to the serial number label, and determine the flight starting point and flight ending point in each sub-virtual area according to the serial number values of every two adjacent sub-virtual areas and the connection points; Adaptive adjustment is performed on the second trajectory element of each sub-virtual area according to the flight starting point and flight ending point in each sub-virtual area to obtain the third trajectory element; Read the longitudinal height of each sub-virtual area, and mark the longitudinal height of each sub-virtual area as a target label in the third trajectory element to obtain the target third trajectory element; Associate the first trajectory element with multiple target third trajectory elements to obtain the first cruise trajectory of the drone in the target area land.

10. An engineering acceptance system based on the cooperation of drones and unmanned vehicles, characterized in that, Including: A cruise trajectory determination module, which is used to obtain the first cruise trajectory of the drone in the target area land, and at the same time, obtain the second cruise trajectory of the unmanned vehicle in the target area land; An image acquisition module, which is used to control the drone to perform the first cruise shooting in the target area land according to the first cruise trajectory to obtain the first image sequence collected by the drone, and at the same time, control the unmanned vehicle to perform the second cruise shooting in the target area land according to the second cruise trajectory to obtain the second image sequence collected by the unmanned vehicle; An image processing module, which is used to associate and screen the first image sequence and the second image sequence to obtain an effective image sequence set; An acceptance module, which is used to analyze the effective image sequence set to obtain the land reclamation acceptance result of the target area land.

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