CN113778084A - Complex grassland environment intelligent obstacle avoidance system based on multispectral detection - Google Patents
Complex grassland environment intelligent obstacle avoidance system based on multispectral detection Download PDFInfo
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- CN113778084A CN113778084A CN202111004482.4A CN202111004482A CN113778084A CN 113778084 A CN113778084 A CN 113778084A CN 202111004482 A CN202111004482 A CN 202111004482A CN 113778084 A CN113778084 A CN 113778084A
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- G05D1/02—Control of position or course in two dimensions
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- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
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Abstract
The invention provides an intelligent obstacle avoidance system based on multispectral detection for a complex grassland environment, which is characterized by comprising a data acquisition module, a data receiving module, an obstacle judgment module, a data processing module and an obstacle avoidance path planning module; the data acquisition module is used for acquiring data information; the data receiving module receives the data information acquired by the data acquisition module, generates obstacle analysis information and sends the obstacle analysis information to the obstacle judgment module; the obstacle judging module receives obstacle analysis information of the data acquisition module and analyzes obstacles; the data processing module receives the obstacle analysis generated by the obstacle judging module, processes and controls the obstacle avoiding path planning module, is suitable for grassland environments, can eliminate high weeds, avoids meaningless brake, and achieves intelligent obstacle avoidance.
Description
Technical Field
The invention relates to the technical field of intelligent vehicle auxiliary driving, in particular to an intelligent obstacle avoidance system for a complex grassland environment based on multispectral detection.
Background
In recent years, with the enhancement of environmental awareness of people, herbicides are not generally used for cleaning weeds, so that intelligent mowers are increasingly popular. The existing lawn mower obstacle avoidance modes comprise an infrared line type technology, an ultrasonic wave type technology, a graph recognition technology and the like, but the obstacle avoidance devices have respective defects in the application of the technologies, the infrared obstacle avoidance devices can only process obstacles with the same height as the infrared module, the ultrasonic wave obstacle avoidance devices cannot accurately detect the short-distance obstacles, and the post-processing of the graph recognition technology is not mature enough.
Disclosure of Invention
The invention aims to provide an intelligent obstacle avoidance system for a complex grassland environment based on multispectral detection, which can intelligently identify obstacles, distinguish the types of the obstacles and avoid meaningless brake when the obstacles are high saplings or weeds.
In order to achieve the purpose, the invention provides the following technical scheme: an intelligent obstacle avoidance system based on multispectral detection for a complex grassland environment comprises a data acquisition module, a data receiving module, an obstacle judgment module, a data processing module and an obstacle avoidance path planning module; the data acquisition module is used for acquiring data information; the data receiving module receives the data information acquired by the data acquisition module, generates obstacle analysis information and sends the obstacle analysis information to the obstacle judgment module; the obstacle judging module receives obstacle analysis information of the data acquisition module and analyzes obstacles; and the data processing module receives the obstacle analysis generated by the obstacle judgment module and processes and controls the obstacle avoidance path planning module.
As a further improvement of the above technical solution, the data receiving module is connected to the data collecting module and the obstacle judging module respectively; and the data processing module is respectively connected with the obstacle judgment module and the obstacle avoidance path planning module.
As a further improvement of the above technical solution, the data processing module acquires the speed, distance and position information of the obstacle.
As a further improvement of the above technical solution, the obstacle avoidance path planning module includes bypassing an obstacle and re-planning a path.
As a further improvement of the technical scheme, the data acquisition module comprises a millimeter wave radar and a thermal infrared imager.
As a further improvement of the above technical solution, the data acquisition module sets a detection range in front of the mower during information acquisition, detects in a specific area, and does not perform calculation and determination for a target that is not in the detection area.
As a further improvement of the above technical solution, the data processing module analyzes the thermal infrared image of the obstacle in the detection area, if the gray value of the thermal infrared image is within the threshold range of the plant, the obstacle is determined to be vegetation, and the data processing module sends an instruction to the mower to clear the obstacle, otherwise, the next step is performed.
As a further improvement of the above technical solution, when the data processing module filters the millimeter wave radar, the millimeter wave radar periodically scans the beam in the effective detection area, the returned data are the distance, speed, and angle of each corresponding periodic target point, and a clustering analysis algorithm is used to classify the traces of the same object into one class.
As a further improvement of the above technical solution, the millimeter wave radar calculates the distance to the front obstacle by using the time difference between the transmission signal and the reception signal of the millimeter wave radar, and the calculation formula is R ═ Δ t × c/2.
Compared with the prior art, the invention has the beneficial effects that: the invention integrates the millimeter wave radar and the infrared thermal image, is suitable for grassland environment, can eliminate high weeds, avoids meaningless brake and realizes intelligent obstacle avoidance.
Drawings
FIG. 1 is a schematic view of the structural framework of the present invention;
FIG. 2 is a schematic view of the azimuth measurement of a monitored target according to the present invention;
fig. 3 is a schematic diagram of an obstacle avoidance process according to the present invention.
Reference numerals: the system comprises a data acquisition module 1, a data receiving module 2, an obstacle judgment module 3, a data processing module 4 and an obstacle avoidance path planning module 5.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-3 together, the invention discloses an intelligent obstacle avoidance system based on multispectral detection for a complex grassland environment, which comprises a data acquisition module 1, a data receiving module 2, an obstacle judgment module 3, a data processing module 4 and an obstacle avoidance path planning module 5; the data receiving module 2 is respectively connected with the data acquisition module 1 and the barrier judgment module 3; the data processing module 4 is respectively connected with the obstacle judgment module 3 and the obstacle avoidance path planning module 5.
Specifically, the data acquisition module is used for acquiring data information; the data receiving module receives the data information acquired by the data acquisition module, generates obstacle analysis information and sends the obstacle analysis information to the obstacle judgment module; the obstacle judging module receives obstacle analysis information of the data acquisition module and analyzes obstacles; and the data processing module receives the obstacle analysis generated by the obstacle judgment module and processes and controls the obstacle avoidance path planning module.
Specifically, the data acquisition module comprises a millimeter wave radar and a thermal infrared imager; the millimeter wave radar and the thermal infrared imager are used for acquiring data information;
specifically, the data receiving module: receiving data information collected by a millimeter wave radar and a thermal infrared imager;
specifically, the obstacle judgment module: analyzing the thermal infrared image of the surface of the obstacle obtained by the data receiving module, judging whether the obstacle is a plant or not, and if the obstacle is the plant, removing the obstacle; if the plants are not plants, entering a data processing module;
specifically, the data processing module: acquiring specific information such as speed, distance, position and the like of an obstacle;
specifically, the obstacle avoidance path planning module: to bypass the obstacle, the path is re-planned.
Specifically, the intelligent obstacle avoidance system for the complex grassland environment based on multispectral detection comprises the following specific implementation steps:
the method comprises the following steps: the data acquisition module acquires information, a detection range is arranged in front of the mower, detection is carried out in a specific area, and calculation and judgment are not carried out on targets which are not in the detection area;
step two: the data processing module analyzes the thermal infrared image of the obstacle in the detection area, if the gray value of the thermal infrared image is within the range of the threshold value of the plant, the obstacle is judged to be vegetation, and a clearing instruction is sent to the mower, otherwise, the next step is carried out;
step three: when the data processing module filters the millimeter wave radar, the millimeter wave radar carries out periodic scanning on wave beams in an effective detection area, returned data are the distance, the speed and the angle of a corresponding target point in each period, and a clustering analysis algorithm is adopted to realize the purpose of classifying the traces of the same object into one class. The distance to the front obstacle is calculated through the time difference between the transmitting signal and the receiving signal of the millimeter wave radar, and the calculation formula is as follows:
R＝Δt*c/2，(c＝300000km/s)
in the above embodiment, when the azimuth angle of the monitored target is measured, after the millimeter wave is transmitted by the transmitting antenna of the millimeter wave radar, the millimeter wave encounters the monitored object and is reflected back, and the azimuth angle of the monitored target is calculated by receiving the phase difference of the millimeter waves reflected back by the same monitored target through the receiving antennas arranged in parallel to the millimeter wave radar.
With continued reference to fig. 2, the azimuth angle α AZ is the geometric distance d between the millimeter wave radar receiving antenna RX1 and the receiving antenna RX2, and the phase difference b between the reflected echoes received by the two millimeter wave radar antennas, and then the value of the azimuth angle α AZ is obtained through trigonometric function calculation, so that the azimuth angle of the monitored target can be obtained.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. An intelligent obstacle avoidance system based on multispectral detection for a complex grassland environment is characterized by comprising a data acquisition module, a data receiving module, an obstacle judgment module, a data processing module and an obstacle avoidance path planning module; the data acquisition module is used for acquiring data information; the data receiving module receives the data information acquired by the data acquisition module, generates obstacle analysis information and sends the obstacle analysis information to the obstacle judgment module; the obstacle judging module receives obstacle analysis information of the data acquisition module and analyzes obstacles; and the data processing module receives the obstacle analysis generated by the obstacle judgment module and processes and controls the obstacle avoidance path planning module.
2. The complex grassland environment intelligent obstacle avoidance system based on multispectral detection as claimed in claim 1, wherein the data receiving module is connected to the data acquisition module and the obstacle judgment module respectively; and the data processing module is respectively connected with the obstacle judgment module and the obstacle avoidance path planning module.
3. The complex grassland environment intelligent obstacle avoidance system based on multispectral detection as claimed in claim 2, wherein the data processing module comprises obtaining obstacle speed, distance and position information.
4. The complex grassland environment intelligent obstacle avoidance system based on multispectral detection as claimed in claim 2, wherein the obstacle avoidance path planning module comprises bypassing obstacles and re-planning a path.
5. The complex grassland environment intelligent obstacle avoidance system based on multispectral detection as claimed in claim 2, wherein the data acquisition module comprises a millimeter wave radar and a thermal infrared imager.
6. The system of claim 1, wherein the data acquisition module sets a detection range in front of the mower during information acquisition, detects in a specific area, and does not calculate and distinguish a target not in the detection area.
7. The complex grassland environment intelligent obstacle avoidance system based on multispectral detection as claimed in claim 5, wherein the data processing module analyzes a thermal infrared image of an obstacle in the detection area, if the gray value of the image is within a threshold range of plants, the obstacle is determined to be vegetation, the data processing module sends a clearing instruction to a mower, and if not, the next step is carried out.
8. The system of claim 6, wherein when the data processing module filters the millimeter wave radar, the millimeter wave radar periodically scans the beams in the effective detection area, the returned data are the distance, speed and angle of each corresponding periodic target point, and a clustering analysis algorithm is adopted to classify the traces of the same object into one class.
9. The system of claim 7, wherein the millimeter wave radar calculates the distance to the front obstacle according to the time difference between the millimeter wave radar transmitting signal and the millimeter wave radar receiving signal, and the calculation formula is R- Δ t c/2.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114739451A (en) * | 2022-03-22 | 2022-07-12 | 国网山东省电力公司超高压公司 | Transmission conductor safety early warning method under millimeter wave radar monitoring |
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| CN109541601A (en) * | 2018-11-16 | 2019-03-29 | 南京慧尔视防务科技有限公司 | Differentiating obstacle and its detection method based on millimeter wave |
| WO2020063822A1 (en) * | 2018-09-27 | 2020-04-02 | 苏州宝时得电动工具有限公司 | Automatic mower, method and apparatus for operating and controlling same, and electronic device |
| CN112731412A (en) * | 2020-12-28 | 2021-04-30 | 南京苏美达智能技术有限公司 | Ultrasonic obstacle avoidance method and automatic walking equipment |
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- 2021-08-30 CN CN202111004482.4A patent/CN113778084A/en active Pending
Patent Citations (5)
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| CN108090893A (en) * | 2017-11-23 | 2018-05-29 | 华南农业大学 | Plant protection unmanned plane medicament sprinkling optimization method and device based on thermal infrared identification |
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| WO2020063822A1 (en) * | 2018-09-27 | 2020-04-02 | 苏州宝时得电动工具有限公司 | Automatic mower, method and apparatus for operating and controlling same, and electronic device |
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Application publication date: 20211210 |