Method for generating lowest energy consumption path of unmanned plant protection machine in orchard environment

Abstract

The invention discloses a method for generating a lowest energy consumption path of an unmanned plant protection machine in an orchard environment, an orchard environment map is generated through the orchard environment, an energy consumption model is constructed according to the orchard environment map, the energy consumption model is used for calculating path energy consumption of the unmanned plant protection machine on different nodes on the orchard environment map, and thus the lowest energy consumption path is generated. Under comprehensive consideration of orchard terrain factors, energy consumption can be remarkably reduced, the working time of the unmanned plant protection machine can be prolonged, the working efficiency can be improved, and energy waste can be reduced. Besides, the method provided by the invention has wide applicability, can be flexibly applied in a complex environment, and provides an efficient and energy-saving intelligent solution for agricultural production.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning for unmanned plant protection aircraft, and particularly to a method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment. Background Art

[0002] With the development of modern agriculture, the application of automated agricultural equipment in agricultural production has gradually increased. As a new type of agricultural machinery, unmanned plant protection aircraft are widely used in scenarios such as orchards and farmlands, mainly for tasks such as pest control, fertilization, and spraying. Unmanned plant protection aircraft have the advantages of high efficiency, precision, and environmental protection, and can improve the operation efficiency, reduce pesticide waste, and reduce environmental pollution.

[0003] There are still some challenges in the path planning problem of existing unmanned plant protection aircraft, especially in complex orchard environments. Unmanned plant protection aircraft usually need to travel for a long time, but the problem of energy consumption control is often ignored. Therefore, how to plan a low-energy consumption path has become the key to improving operation efficiency and extending operation time.

[0004] Existing path planning technologies mainly include traditional graph search algorithms (such as A* algorithm, Dijkstra algorithm, etc.), and some heuristic optimization algorithms (such as ant colony algorithm, genetic algorithm, etc.). Existing path planning methods usually focus on the shortest path or obstacle avoidance ability, while ignoring the energy consumption optimization during the operation. The energy consumption of unmanned plant protection aircraft is affected by various factors, including traveling speed, traveling distance, terrain undulation, load condition, etc. Traditional path planning algorithms fail to effectively combine these factors for optimization, resulting in the fact that although the path planning results are feasible, they often cannot meet the requirements of the lowest energy consumption. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment, which uses intelligent algorithms to combine with orchard environment modeling to generate the lowest energy consumption path, ensuring that the unmanned plant protection aircraft realizes the optimization of energy consumption while completing the task, further improving the operation efficiency, reducing energy consumption, and promoting the development of intelligent agriculture.

[0006] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0007] A method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment, comprising the following steps:

[0008] S1. A mapping unmanned aircraft scans the orchard environment to obtain a high-resolution image and RTK data of the orchard environment;

[0009] S2. Generate an orchard environment map based on the high-resolution image and RTK data and construct an energy consumption model according to the orchard environment map;

[0010] S3. Select a node in the orchard environment map as the starting node and a node as the ending node. The minimum energy consumption of the initial starting node is 0. Obtain the minimum path energy consumption of the unmanned plant protection aircraft from the starting node to the ending node and from the starting node to each other node through the energy consumption model.

[0011] S4. If the minimum path energy consumption of the ending node is less than the minimum path energy consumption of other nodes, connect the starting node and the ending node to obtain the minimum energy consumption path of the unmanned plant protection aircraft; otherwise, select a node with the minimum minimum path energy consumption among other nodes as the current node.

[0012] S5. Update the neighbor nodes of the current node. Obtain the path energy consumption from the current node to each neighbor node through the energy consumption model. Select a neighbor node with the minimum path energy consumption as the preferred neighbor node. Record the sum of the minimum path energy consumption of the current node and the path energy consumption of the preferred neighbor node as the total path energy consumption. If the total path energy consumption is less than the minimum path energy consumption of the preferred neighbor node, update the total path energy consumption to the minimum path energy consumption of the preferred neighbor node, and record the current node as the predecessor node of the preferred neighbor node.

[0013] S6. Take the preferred neighbor node as the current node, repeat S5 until the predecessor node of the ending node is found, connect the ending node and each predecessor node in sequence, and finally connect to the starting node to obtain the minimum energy consumption path of the unmanned plant protection aircraft.

[0014] Furthermore, in S1, use the high-definition camera and RTK positioning system integrated in the unmanned plant protection aircraft to scan the orchard environment to obtain a high-resolution image and RTK data of the orchard environment.

[0015] Furthermore, the energy consumption calculation formula of the energy consumption model is as follows:

[0016] E total = E move + E resistance + E terrain ;

[0017] Where:

[0018] E total : Total energy consumption, representing the total energy consumption of the unmanned plant protection aircraft;

[0019] E move : Moving energy consumption, representing the moving energy consumption of the unmanned plant protection aircraft under ideal road conditions;

[0020] E resistance : Ground resistance energy consumption, representing the energy consumption of overcoming the resistance generated by the uneven ground;

[0021] E terrain: Terrain slope energy consumption, representing the energy consumption caused by the terrain.

[0022] Furthermore, the movement energy consumption E move is calculated as follows:

[0023]

[0024] Where:

[0025] m: The mass of the unmanned plant protection aircraft, including the payload on the unmanned plant protection aircraft;

[0026] v: The traveling speed of the unmanned plant protection aircraft;

[0027] The ground resistance energy consumption E resistance is calculated as follows:

[0028] E resistance = C r ·m·g·d

[0029] Where:

[0030] C r : The ground friction coefficient, and different grounds have different friction coefficients;

[0031] m: The mass of the unmanned plant protection aircraft, including the payload on the unmanned plant protection aircraft;

[0032] g: The acceleration due to gravity, with a value of 9.81 m / s 2 ;

[0033] d: The moving distance of the unmanned plant protection aircraft on a certain path;

[0034] The terrain slope energy consumption E terrain is calculated as follows:

[0035] E terrain = m·g·d'·sin(θ);

[0036] Where:

[0037] θ: The slope angle of the terrain;

[0038] d': The moving distance of the unmanned plant protection aircraft on the slope.

[0039] Furthermore, set an empty set, add the current node to the set, indicating that the lowest energy consumption path of the current node has been determined, and the lowest energy consumption path of the current node is the path formed by connecting the current node with each predecessor node and the starting node in sequence.

[0040] Furthermore, set an array of predecessor nodes, and add the predecessor node of each node and the corresponding lowest path energy consumption to the array of predecessor nodes. Add them to the array of predecessor nodes.

[0041] Further, in S4, if the minimum path energy consumption of multiple other nodes is the same and the smallest, any one of them is selected as the current node.

[0042] Further, in S5, if the path energy consumption of multiple neighbor nodes is the same and the smallest, any one of them is selected as the preferred neighbor node.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] By comprehensively considering the orchard terrain factors, the present invention uses an energy consumption model to generate the lowest energy consumption path of the unmanned plant protection aircraft, which can significantly reduce energy consumption, extend the working time of the unmanned plant protection aircraft, improve the operation efficiency, and reduce energy waste. In addition, the method of the present invention has wide applicability and can be flexibly applied in complex environments, providing an efficient and energy-saving intelligent solution for agricultural production. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0047] As Figure 1 shown, a method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment provided by the present invention includes the following steps:

[0048] S1. A mapping unmanned aircraft scans the orchard environment to obtain a high-resolution image and RTK data of the orchard environment;

[0049] S2. Based on the high-resolution image and RTK data, an orchard environment map is generated and an energy consumption model is constructed according to the orchard environment map;

[0050] S3. Select a node in the orchard environment map as the starting node, the minimum energy consumption of the initial starting node is 0, and the minimum path energy consumption from the starting node to each other node is obtained through the energy consumption model;

[0051] S4. Select a node with the smallest minimum path energy consumption among other nodes as the current node;

[0052] S5. Update the neighbor nodes of the current node. Obtain the path energy consumption from the current node to each neighbor node through the energy consumption model. Select the neighbor node with the minimum path energy consumption as the preferred neighbor node. Denote the sum of the minimum path energy consumption of the current node and the path energy consumption of the preferred neighbor node as the total path energy consumption. If the total path energy consumption is less than the minimum path energy consumption of the preferred neighbor node, update the total path energy consumption to the minimum path energy consumption of the preferred neighbor node, and record the current node as the predecessor node of the preferred neighbor node.

[0053] S6. Take the preferred neighbor node as the current node, and repeat S5 until the predecessor node of the last node is found. Connect the last node to each predecessor node in sequence, and finally connect it to the starting node to obtain the lowest energy consumption path of the unmanned plant protection aircraft.

[0054] The present invention first uses the high-definition camera and RTK positioning system integrated in the unmanned plant protection aircraft to scan the orchard environment to obtain the high-resolution image and RTK data of the orchard environment; then uses professional software to process the high-resolution image and RTK data to generate an orchard environment map. Professional software such as Pix4D, Autel Mapper, etc., and then constructs an energy consumption model based on the orchard environment map. The energy consumption model constructed by the present invention can consider the influence of factors such as driving speed, driving distance, terrain undulation, and load conditions on energy consumption.

[0055] Specifically, the energy consumption calculation formula of the energy consumption model is as follows:

[0056] E total =E move +E resistance +E terrain ;

[0057] Where:

[0058] E total : Total energy consumption, representing the total energy consumption of the unmanned plant protection aircraft;

[0059] E move : Moving energy consumption, representing the moving energy consumption of the unmanned plant protection aircraft under ideal road conditions;

[0060] E resistance : Ground resistance energy consumption, representing the energy consumption for overcoming the resistance caused by the uneven ground;

[0061] E terrain : Terrain slope energy consumption, representing the energy consumption caused by the terrain.

[0062] The moving energy consumption is mainly related to the speed and mass of the unmanned plant protection aircraft. The calculation of the moving energy consumption E move is as follows:

[0063]

[0064] Wherein:

[0065] m: the mass of the unmanned plant protection aircraft, including the payload on the unmanned plant protection aircraft;

[0066] v: the traveling speed of the unmanned plant protection aircraft.

[0067] Due to the variable ground conditions in the orchard, the contact area between the crawler of the unmanned plant protection aircraft and the ground is large, and the rolling resistance is mainly determined by the ground friction coefficient and the mass of the plant protection aircraft. The ground resistance energy consumption E resistance is calculated as follows:

[0068] E resistance = C r ·m·g·d

[0069] Wherein:

[0070] C r : the ground friction coefficient, and different grounds have different friction coefficients;

[0071] m: the weight of the unmanned plant protection aircraft, including the payload on the unmanned plant protection aircraft;

[0072] g: the acceleration due to gravity, with a value of 9.81 m / s 2 ;

[0073] d: the moving distance of the unmanned plant protection aircraft on a certain path.

[0074] The terrain slope has a great influence on the energy consumption, especially when there are uphill and downhill sections. The terrain slope energy consumption E terrain is calculated as follows:

[0075] E terrain = m·g·d'·sin(θ);

[0076] Wherein:

[0077] θ: the slope angle of the terrain, the energy consumption increases when going uphill and decreases when going downhill;

[0078] d': the moving distance of the unmanned plant protection aircraft on the slope.

[0079] In summary, the energy consumption model is as follows:

[0080]

[0081] ]Then, select a node in the orchard environment map as the starting node and a node as the ending node. The path of the unmanned plant protection aircraft is the path between the starting node and the ending node. The minimum energy consumption of the initial starting node is 0. The minimum path energy consumption of the unmanned plant protection aircraft from the starting node to the ending node and from the starting node to each other node is obtained through the energy consumption model. The path corresponding to the minimum path energy consumption is preferably the straight-line path between the two nodes.

[0082] If the minimum path energy consumption of the ending node is less than the minimum path energy consumption of other nodes, connect the starting node and the ending node to obtain the minimum energy consumption path of the unmanned plant protection aircraft, that is, the straight-line path between the starting node and the ending node is the minimum energy consumption path of the unmanned plant protection aircraft; otherwise, select a node with the minimum minimum path energy consumption among other nodes as the current node, denoted as node U.

[0083] Update the neighbor nodes of the current node. The path energy consumption from the current node to each neighbor node is obtained through the energy consumption model. The path corresponding to the path energy consumption is preferably the straight-line path between the two nodes. Select a neighbor node with the minimum path energy consumption as the preferred neighbor node, denoted as node V. Denote the sum of the minimum path energy consumption of the current node (denoted as energy_cost[U]) and the path energy consumption of the preferred neighbor node (denoted as ω(U,V)) as the total path energy consumption. If the total path energy consumption is less than the minimum path energy consumption of the preferred neighbor node (i.e., energy_cost[U]+ω(U,V)<energy_cost[V]), update the total path energy consumption to the minimum path energy consumption of the preferred neighbor node (i.e., energy_cost[V] = energy_cost[U]+ω(U,V)). Reach node V from the starting node through node U, and record the current node (node U) as the predecessor node of the preferred neighbor node (node V). Preferably, set up a predecessor node array prev_node[]. The predecessor node array prev_node[] facilitates the subsequent reconstruction of the minimum energy consumption path. Add node V and the corresponding minimum path energy consumption energy_cost[V] (updated) to the predecessor node array prev_node[]. Preferably, set up an empty set S. Add the current node to set S. The nodes in the subsequent steps do not include the nodes in set S, indicating that the minimum energy consumption path of the current node has been determined. The minimum energy consumption path of the current node is the path formed by connecting the current node with each predecessor node and the starting node in sequence.

[0084] Next, take the preferred neighbor node (node V) as the current node (node U), and repeat the above steps until the predecessor node of the end node is found. Connect the end node and each predecessor node in sequence, and finally connect to the start node to obtain the lowest energy consumption path of the unmanned plant protection aircraft. The set S contains all the nodes for which the lowest energy consumption path has been determined. Connect the nodes in it in sequence, and connect the start node and the end node at the head and tail to obtain the lowest energy consumption path of the unmanned plant protection aircraft. Through the predecessor node array prev_node[], the lowest path energy consumption of the end node can also be obtained, that is, the energy consumption of the lowest energy consumption path of the unmanned plant protection aircraft, which is the lowest energy consumption of the unmanned plant protection aircraft.

[0085] Finally, it should be noted that the above embodiments are only relatively preferred embodiments of the present invention to illustrate the technical solutions of the present invention, rather than limiting it, and certainly not limiting the patent scope of the present invention; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present invention; that is to say, any meaningless changes or polishings made in the main design idea and spirit of the present invention, as long as the technical problems solved are still the same as those of the present invention, should be included in the protection scope of the present invention; in addition, directly or indirectly applying the technical solutions of the present invention to other related technical fields shall also be included in the patent protection scope of the present invention by the same token.

Claims

1. A method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment, characterized in that, The following steps are involved: S1. The mapping drone scans the orchard environment to obtain high-resolution images and RTK data of the orchard environment; S2, generate an orchard environment map based on high-resolution images and RTK data and construct an energy consumption model based on the orchard environment map; S3. Select a node in the orchard environment map as the starting node and a node as the ending node. The minimum energy consumption of the initial starting node is 0. The energy consumption model is used to obtain the minimum path energy consumption of the UAV from the starting node to the ending node and from the starting node to each other node. S4. If the minimum path energy consumption of the end node is less than the minimum path energy consumption of other nodes, connect the starting node and the end node to obtain the minimum energy consumption path of the unmanned plant protection machine; otherwise, select the node with the smallest minimum path energy consumption among other nodes as the current node; S5. Update the neighbor nodes of the current node. Use the energy consumption model to obtain the path energy consumption from the current node to each neighbor node. Select the neighbor node with the lowest path energy consumption as the preferred neighbor node. Record the sum of the lowest path energy consumption of the current node and the path energy consumption of the preferred neighbor node as the total path energy consumption. If the total path energy consumption is less than the lowest path energy consumption of the preferred neighbor node, update the total path energy consumption to the lowest path energy consumption of the preferred neighbor node, and record the current node as the predecessor node of the preferred neighbor node. S6. Use the preferred neighbor node as the current node and repeat S5 until the predecessor node of the end node is found. Connect the end node to each predecessor node in sequence, and finally connect it to the starting node to obtain the lowest energy consumption path of the unmanned plant protection machine.

2. The method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment according to claim 1, wherein, In S1, the orchard environment is scanned using the high-definition camera and RTK positioning system integrated in the unmanned plant protection aircraft to obtain high-resolution images and RTK data of the orchard environment.

3. A method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment according to claim 1, characterized in that, The energy consumption calculation formula of the energy consumption model is as follows: E total = E move + E resistance + E terrain ; in: E total : Total energy consumption, representing the total energy consumption of the unmanned plant protection aircraft; E move : Mobile energy consumption, representing the mobile energy consumption of the unmanned plant protection aircraft under ideal road surface conditions; E resistance : Ground resistance energy consumption, representing the energy consumption for overcoming the resistance generated by uneven ground E terrain : Terrain slope energy consumption, representing the energy consumption caused by the terrain.

4. A method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment according to claim 3, characterized in that, The mobile energy consumption E move is calculated as follows: in: m: The mass of the UAV, including the load on the UAV; v: the speed of the UAV; The ground resistance energy consumption E resistance is calculated as follows: E resistance = C r ·m·g·d in: C r : Coefficient of ground friction. Different grounds have different friction coefficients; m: The mass of the UAV, including the load on the UAV; g: acceleration due to gravity, with a value of 9.81 m / s 2 ; d: The distance the UAV moves along a certain path; The terrain slope energy consumption E terrain is calculated as follows: E terrain = m·g·d'·sin(θ); in: θ: slope angle of the terrain; d': The distance the UAV moves on the slope.

5. A method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment according to claim 1, characterized in that Set an empty set and add the current node to the set, indicating that the minimum energy consumption path of the current node has been determined. The minimum energy consumption path of the current node is the path formed by connecting the current node with each predecessor node and the starting node in sequence.

6. The method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment according to claim 1, wherein Set a predecessor node array, and add the predecessor node of each node and the corresponding minimum path energy consumption to the predecessor node array.

7. A method for generating the minimum energy consumption path of an unmanned plant protection aircraft in an orchard environment according to claim 1, characterized in that In S4, if the minimum path energy consumptions of multiple other nodes are the same and the smallest, any one of them is selected as the current node.

8. A method for generating the lowest energy consumption path of an unmanned plant protection aircraft in an orchard environment according to claim 1, characterized in that, In S5, if the path energy consumptions of multiple neighboring nodes are the same and the smallest, one of them is selected as the preferred neighboring node.

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