Agricultural machinery operation obstacle early warning method based on real-time environment information

Abstract

The invention discloses an agricultural machinery operation obstacle early warning method based on real-time environment information, and relates to the technical field of agricultural machinery intelligent safety control. The existing agricultural machinery obstacle early warning technology is inaccurate in early warning. Calculating the Euclidean distance between the agricultural machine and each obstacle and the area of each obstacle relative to the heading of the agricultural machine in real time according to the position of the agricultural machine collected in real time and the positions of n obstacles in a preset range; obtaining a preset dynamic early warning distance threshold value corresponding to each obstacle according to the distance, the current agricultural machine operation mode and each obstacle category; according to the Euclidean distance between the agricultural machine and each obstacle and a corresponding preset dynamic early warning distance threshold, a normalized distance ratio of each obstacle is calculated so as to obtain a corresponding risk value, a corresponding risk level is obtained according to each risk value, when the risk levels are all 0, an alarm is not given, and when the risk levels are not all 0, an alarm is given. The method is used for obstacle early warning.

Description

Technical Field

[0001] This invention relates to the field of intelligent safety control technology for agricultural machinery. Background Technology

[0002] With the increasing power and automation of agricultural machinery, tractors, combine harvesters, and other agricultural machines operate continuously for extended periods in field environments, surrounded by various obstacles such as pedestrians, livestock, other agricultural machinery, ditches, and tree stumps. Delayed warnings or frequent false alarms can lead to safety accidents or decreased operational efficiency.

[0003] Existing obstacle warning technologies for agricultural machinery typically employ a single fixed threshold or a method that adjusts linearly with vehicle speed to issue an alarm for detected obstacles. These methods have the following shortcomings:

[0004] The differences in operating modes have not been fully considered: under different operating modes such as high-speed travel, low-speed sowing, spraying, and harvesting, the degree of danger and the allowable approach distance of obstacles around the agricultural machinery are different, and the existing methods do not dynamically change the warning strategy when switching modes.

[0005] Lack of systematic mathematical model support: Many systems only set alarm distances and levels based on experience, lacking a unified mathematical modeling framework, which is not conducive to subsequent parameter calibration and system expansion.

[0006] The warning levels are not precise enough: they mostly use a binary judgment of "alarm / no alarm", which cannot provide graded warning information based on the work scenario and obstacle type.

[0007] Therefore, existing agricultural machinery obstacle warning technologies suffer from inaccurate warnings. Summary of the Invention

[0008] The purpose of this invention is to solve the problem of inaccurate early warning in existing agricultural machinery obstacle warning technologies, and to propose an agricultural machinery operation obstacle warning method based on real-time environmental information.

[0009] A method for early warning of obstacles in agricultural machinery operations based on real-time environmental information, the method comprising the following:

[0010] Step 1: Based on the real-time collected location of the agricultural machinery and the locations of n obstacles within a preset range, calculate in real time the Euclidean distance between the agricultural machinery and each obstacle, as well as the area where each obstacle is located relative to the heading of the agricultural machinery.

[0011] Step 2: Based on the Euclidean distance between the agricultural machinery and each obstacle, the current agricultural machinery operation mode, and the category of each obstacle, obtain the preset dynamic warning distance threshold corresponding to each obstacle;

[0012] Step 3: Based on the Euclidean distance between the agricultural machinery and each obstacle and the corresponding preset dynamic warning distance threshold, calculate the normalized distance ratio of each obstacle to obtain the corresponding risk value. Based on each risk value, obtain the corresponding risk level. When all risk levels are 0, no alarm is triggered; when not all risk levels are 0, an alarm is triggered. Output the obstacle information corresponding to the highest risk level obtained from the risk levels. The obstacle information includes the area where the obstacle is located relative to the agricultural machinery's heading, the obstacle category, and the Euclidean distance between the agricultural machinery and each obstacle. When multiple obstacles have the same maximum risk level, output the obstacle information corresponding to the minimum Euclidean distance between the agricultural machinery and each obstacle.

[0013] Preferably, the Euclidean distance between the agricultural machinery and each obstacle is:

[0014] ,

[0015] In the formula, For agricultural machinery and the first Euclidean distance between obstacles For the position of agricultural machinery and the first The relative position vectors of the obstacles , For the first The location of the obstacle For the location of agricultural machinery, , , The x-axis represents the agricultural machinery. The vertical axis represents the agricultural machinery. For the first The x-coordinate of each obstacle For the first The x-coordinate of each obstacle.

[0016] Preferably, the process of calculating the area where each obstacle is located relative to the heading of the agricultural machinery is as follows:

[0017] The angles of each obstacle relative to the heading of the agricultural machinery are:

[0018] ,

[0019] In the formula, For the first The angle of the obstacle relative to the heading of the agricultural machinery For obstacles relative to the global coordinate system The absolute azimuth of the axis. For agricultural machinery in the global coordinate system The heading angle of the axis, ;

[0020] Preset direction boundary ,get:

[0021] ,

[0022] In the formula, For the first A preset directional boundary, This indicates the area directly in front of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the left and in front of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the left of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the left and rear of the obstacle relative to the heading of the agricultural machinery. This indicates the area directly behind the obstacle relative to the heading of the agricultural machinery. This indicates the area to the right and rear of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the right of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the right front of the obstacle relative to the heading of the agricultural machinery.

[0023] Preferably, based on the Euclidean distance between the agricultural machinery and each obstacle, the current agricultural machinery operation mode, and the category of each obstacle, a preset dynamic warning distance threshold corresponding to each obstacle is obtained. The specific process is as follows:

[0024] Step 21: Preset the warning parameter values ​​corresponding to different agricultural machinery operation modes, obstacle categories and the combination mode of the obstacle relative to the area where the agricultural machinery is heading, including the basic warning distance, speed-related correction coefficient and braking safety margin parameter;

[0025] Step 22: Based on the current agricultural machinery operation mode, obstacle type, and the area where the obstacle is located relative to the agricultural machinery's heading, select the basic warning distance, speed-related correction coefficient, and braking safety margin parameters from the preset warning parameter values;

[0026] Step 23: Collect the linear velocity of the agricultural machinery in real time, and preset the driver's reaction time and the maximum braking deceleration according to the agricultural machinery model;

[0027] Step 24: Based on the selected basic warning distance, speed-related correction coefficient, agricultural machinery linear speed, preset driver reaction time, preset maximum braking deceleration, basic warning distance, speed-related correction coefficient, and braking safety margin parameters, obtain the dynamic warning distance threshold for each obstacle.

[0028] Preferably, the dynamic warning distance threshold function for obstacles is:

[0029] ,

[0030] In the formula, For the first An obstacle at any moment The dynamic warning distance threshold, For agricultural machinery linear velocity, For physical safety distance, , For reaction distance, Braking distance, To preset the driver's reaction time, To preset the maximum braking deceleration, , , For the first Speed-related correction coefficients for each obstacle For the first The basic warning distance for each obstacle For the first Braking safety margin parameters for each obstacle.

[0031] Preferably, the normalized distance ratio of the obstacle for:

[0032] ,

[0033] Risk Value for:

[0034] .

[0035] Preferably, the risk level is obtained based on the risk value, specifically as follows:

[0036] Step 31: Preset risk level classification constraints;

[0037] Step 32: Based on the current agricultural machinery operation mode, obstacle type, and the area where the obstacle is located relative to the agricultural machinery's heading, select risk level classification parameters from the preset risk level classification constraints;

[0038] Step 33: Establish risk levels by classifying parameters based on risk values ​​and risk levels.

[0039] Preferably, the risk level classification constraints are as follows:

[0040] ,

[0041] In the formula, and They are respectively the working modes Obstacle categories and the area where obstacles are located relative to the heading of the agricultural machinery Preset low-risk and medium-risk thresholds and medium-risk and high-risk thresholds under the combination.

[0042] Preferably, risk level for:

[0043] ,

[0044] In the formula, This indicates no prior warning; This represents a low-level warning; This represents a medium-level warning; This indicates a high-level warning.

[0045] The beneficial effects of this invention are:

[0046] This invention combines the obstacle's direction area, agricultural machinery operation mode, and obstacle category to obtain a preset dynamic warning distance threshold. It considers the dynamic changes in warning strategies for different operation models. Furthermore, this invention establishes a risk value using Euclidean distance and performs real-time risk quantification and graded warnings for obstacles around the agricultural machinery. It automatically adjusts the warning sensitivity for different travel speeds and operation modes, effectively reducing false alarms and missed alarms under fixed threshold methods. Therefore, this invention can achieve adaptive adjustment of obstacle warning distance and warning level under different operation modes.

[0047] Compared with existing agricultural machinery obstacle warning methods that mainly employ fixed distance thresholds or simple linear adjustments based on vehicle speed, this invention enables adaptive tuning of warning parameters in complex field operating environments and under varying operating modes, significantly improving the targeting and reliability of warnings. Furthermore, the warning results output by this invention possess both hierarchical and directional characteristics, allowing for easy integration with various human-machine interaction and safety control methods such as audible and visual prompts, voice broadcasts, and speed limit control. This enhances agricultural machinery operation safety and operational comfort while reducing driver cognitive burden, improving the level of intelligent and precise agricultural machinery operation, and demonstrating promising engineering application prospects and widespread application value. Attached Figure Description

[0048] Figure 1 This is a flowchart of an obstacle warning method for agricultural machinery operations based on real-time environmental information. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will be further described below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the scope of the invention.

[0051] Example:

[0052] A method for early warning of obstacles in agricultural machinery operations based on real-time environmental information, the method comprising the following:

[0053] Step 1: Based on the real-time collected location of the agricultural machinery and the locations of n obstacles within a preset range, calculate in real time the Euclidean distance between the agricultural machinery and each obstacle, as well as the area where each obstacle is located relative to the heading of the agricultural machinery.

[0054] When applying this, 1. First, define the set of job modes:

[0055] ,

[0056] in:

[0057] The number of predefined job modes;

[0058] For job mode indexing, for example:

[0059] : Transit driving mode;

[0060] Seeding pattern;

[0061] Spraying mode;

[0062] Harvesting mode;

[0063] At any time The current operating mode of the agricultural machinery is recorded as follows:

[0064]

[0065] Define the set of obstacles and categories:

[0066] At any moment The set of obstacles perceived by the system is as follows:

[0067]

[0068] in:

[0069] :time The number of obstacles;

[0070] : No. Obstacle index.

[0071] The obstacle category set is defined as follows:

[0072]

[0073] : Number of preset obstacle categories;

[0074] : No. The categories of obstacles, for example:

[0075] Pedestrians / Livestock;

[0076] Other agricultural machinery;

[0077] Hard obstacles (stones, tree stumps, etc.);

[0078] : Ditches / field ridges.

[0079] 2. Geometric position of agricultural machinery and obstacles:

[0080] In the global coordinate system In the middle, the location of the agricultural machinery reference point is:

[0081] ,

[0082] No. The locations of the obstacles are:

[0083]

[0084] In the formula, The x-coordinate of the agricultural machinery reference point. The vertical coordinate of the agricultural machinery reference point. For the first The x-coordinate of each obstacle For the first The x-coordinate of each obstacle;

[0085] Agricultural machinery heading angle (relative to) (Axis) is:

[0086]

[0087] Relative position and distance:

[0088] Relative position vector:

[0089]

[0090] European distance:

[0091]

[0092] in, For agricultural machinery and the first The geometric distance between obstacles.

[0093] Relative azimuth and direction region:

[0094] Obstacles relative to the global coordinate system Absolute azimuth of the axis:

[0095]

[0096] The relative azimuth angle to the heading angle of the agricultural machinery:

[0097]

[0098] Define the set of directional regions:

[0099]

[0100] : Directly ahead area

[0101] Left front area

[0102] The area directly to the left

[0103] Left rear area

[0104] The area directly behind;

[0105] The area to the right rear;

[0106] The area directly to the right;

[0107] : The area to the right front.

[0108] By pre-setting direction boundaries (Divided into 8 equal parts), define the region determination function:

[0109]

[0110]

[0111] in Indicates the first The area in the direction to which the obstacle belongs.

[0112] Step 2: Based on the Euclidean distance between the agricultural machinery and each obstacle, the current agricultural machinery operation mode, and the category of each obstacle, obtain the preset dynamic warning distance threshold corresponding to each obstacle;

[0113] Specifically, step 21 involves presetting the warning parameter values ​​corresponding to different agricultural machinery operation modes, obstacle categories, and combination modes of obstacles relative to the area where the agricultural machinery is heading, including basic warning distance, speed-related correction coefficient, and braking safety margin parameters.

[0114] Step 22: Based on the current agricultural machinery operation mode, obstacle type, and the area where the obstacle is located relative to the agricultural machinery's heading, select the basic warning distance, speed-related correction coefficient, and braking safety margin parameters from the preset warning parameter values;

[0115] Step 23: Collect the linear velocity of the agricultural machinery in real time, and preset the driver's reaction time and the maximum braking deceleration according to the agricultural machinery model;

[0116] Step 24: Based on the selected basic warning distance, speed-related correction coefficient, agricultural machinery linear speed, preset driver reaction time, preset maximum braking deceleration, basic warning distance, speed-related correction coefficient, and braking safety margin parameters, obtain the dynamic warning distance threshold for each obstacle.

[0117] When applying, for each job mode Obstacle categories With direction region combination A set of preset warning parameter values, including basic warning distance, speed-related correction coefficient, and braking safety margin parameters, are stored in the database and simultaneously satisfy the following:

[0118] Basic warning distance threshold:

[0119]

[0120] Speed-related correction factor:

[0121]

[0122] Risk level classification parameters:

[0123]

[0124] Braking safety margin parameters:

[0125]

[0126] At any moment , No. The parameters corresponding to each obstacle are determined by the current operating mode. ,category and direction area Select from the database:

[0127]

[0128]

[0129]

[0130]

[0131]

[0132] The above relationship reflects the mechanism by which the early warning threshold and risk level classification adapt to changes in the work mode.

[0133] Vehicle speed and braking distance:

[0134] The linear velocity of agricultural machinery is:

[0135]

[0136] Assume the maximum braking deceleration is constant:

[0137]

[0138] The driver's reaction time is:

[0139]

[0140] The braking distance is:

[0141]

[0142] The reaction distance is:

[0143]

[0144] The physical safety distance is:

[0145]

[0146] Dynamic warning distance threshold:

[0147] Combined operating mode parameters and physical braking distance, the first An obstacle at any moment The dynamic warning distance threshold is defined as:

[0148]

[0149] in:

[0150] First item This reflects the requirements of operating mode and vehicle speed for warning distance;

[0151] Second item It reflects the safety margins related to braking physical constraints and mode.

[0152] By taking the maximum value, the warning distance is guaranteed to be no less than the physical safety requirement.

[0153] The dynamic warning distance calculation simultaneously considers the current vehicle speed and the physical constraints of the agricultural machinery. The basic warning distance, speed correction term, physical braking distance, and safety margin are unified into the same threshold model, and a mapping relationship between continuous risk values ​​and multi-level risk levels is constructed based on this. Through this mechanism, the system can not only perform real-time risk quantification and graded warnings of obstacles around the agricultural machinery, but also automatically adjust the warning sensitivity for different travel speeds and operating modes while ensuring physical safety, effectively reducing false alarms and missed alarms under the fixed threshold method.

[0154] Step 3: Based on the Euclidean distance between the agricultural machinery and each obstacle and the corresponding preset dynamic warning distance threshold, calculate the normalized distance ratio of each obstacle to obtain the corresponding risk value. Based on each risk value, obtain the corresponding risk level. When all risk levels are 0, no alarm is triggered; when not all risk levels are 0, an alarm is triggered. Output the obstacle information corresponding to the highest risk level obtained from the risk levels. The obstacle information includes the area where the obstacle is located relative to the agricultural machinery's heading, the obstacle category, and the Euclidean distance between the agricultural machinery and each obstacle. When multiple obstacles have the same maximum risk level, output the obstacle information corresponding to the minimum Euclidean distance between the agricultural machinery and each obstacle.

[0155] Specifically, continuous risk value:

[0156] Definition of the first Normalized distance ratio of each obstacle:

[0157]

[0158] based on Define risk value :

[0159]

[0160] in:

[0161] when At that time, risk value The closer the distance, the greater the risk;

[0162] when If the risk value is 0, it is considered that the area has not entered the warning zone.

[0163] Discrete risk level:

[0164] Define the risk level set:

[0165]

[0166] in:

[0167] No warning;

[0168] Low-level warning;

[0169] Intermediate warning level;

[0170] Advanced warning.

[0171] Using pattern-related threshold parameters , , define the first Risk level of each obstacle:

[0172]

[0173] By setting different parameters for different work modes , This enables the differentiation of tiered early warning strategies driven by patterns. and They are respectively the working modes Obstacle categories and the area where obstacles are located relative to the heading of the agricultural machinery Preset low-risk and medium-risk thresholds and medium-risk and high-risk thresholds under the combination.

[0174] At any moment The system first selects the obstacle with the highest risk level from all obstacles:

[0175]

[0176] Select the target obstacle index that poses the greatest risk:

[0177]

[0178] If multiple obstacles with the same risk level and the highest risk value exist, further filtering can be done based on the principle of closest proximity:

[0179]

[0180] The final output warning information includes:

[0181] Warning level: ;

[0182] Obstacle direction area: ;

[0183] Obstacle categories: ;

[0184] Obstacle distance: .

[0185] The system according to Different strategies, such as sound and light, voice, and speed limits, are employed to achieve graded and directional early warnings.

[0186] While the invention has been described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the invention. Therefore, it should be understood that many modifications can be made to the exemplary embodiments, and other arrangements can be designed without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that different dependent claims and features described herein can be combined in ways different from those described in the original claims. It is also understood that features described in conjunction with individual embodiments can be used in other described embodiments.

Claims

1. A method for early warning of obstacles in agricultural machinery operations based on real-time environmental information, characterized in that, The method includes the following: Step 1: Based on the real-time collected location of the agricultural machinery and the locations of n obstacles within a preset range, calculate in real time the Euclidean distance between the agricultural machinery and each obstacle, as well as the area where each obstacle is located relative to the heading of the agricultural machinery. Step 2: Based on the Euclidean distance between the agricultural machinery and each obstacle, the current agricultural machinery operation mode, and the category of each obstacle, obtain the preset dynamic warning distance threshold corresponding to each obstacle; Step 3: Based on the Euclidean distance between the agricultural machinery and each obstacle and the corresponding preset dynamic warning distance threshold, calculate the normalized distance ratio of each obstacle to obtain the corresponding risk value. Based on each risk value, obtain the corresponding risk level. When all risk levels are 0, no alarm is triggered; when not all risk levels are 0, an alarm is triggered. Output the obstacle information corresponding to the highest risk level obtained from the risk levels. The obstacle information includes the area where the obstacle is located relative to the agricultural machinery's heading, the obstacle category, and the Euclidean distance between the agricultural machinery and each obstacle. When multiple obstacles have the same maximum risk level, output the obstacle information corresponding to the minimum Euclidean distance between the agricultural machinery and each obstacle.

2. The method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 1, characterized in that, The Euclidean distances between the agricultural machinery and each obstacle are: ， In the formula, For agricultural machinery and the first Euclidean distance between obstacles For the position of agricultural machinery and the first The relative position vectors of the obstacles , For the first The location of the obstacle For the location of agricultural machinery, , , The x-axis represents the agricultural machinery. The vertical axis represents the agricultural machinery. For the first The x-coordinate of each obstacle For the first The x-coordinate of each obstacle.

3. A method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 1 or 2, characterized in that, The process of calculating the area where each obstacle is located relative to the heading of the agricultural machinery is as follows: The angles of each obstacle relative to the heading of the agricultural machinery are: ， In the formula, For the first The angle of the obstacle relative to the heading of the agricultural machinery For obstacles relative to the global coordinate system The absolute azimuth of the axis. For agricultural machinery in the global coordinate system The heading angle of the axis, ; Preset direction boundary ,get: ， In the formula, For the first A preset directional boundary, This indicates the area directly in front of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the left and in front of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the left of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the left and rear of the obstacle relative to the heading of the agricultural machinery. This indicates the area directly behind the obstacle relative to the heading of the agricultural machinery. This indicates the area to the right and rear of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the right of the obstacle relative to the heading of the agricultural machinery. This indicates the area to the right front of the obstacle relative to the heading of the agricultural machinery.

4. The method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 3, characterized in that, Based on the Euclidean distance between the agricultural machinery and various obstacles, the current agricultural machinery operation mode, and the category of each obstacle, the preset dynamic warning distance threshold corresponding to each obstacle is obtained. The specific process is as follows: Step 21: Preset the warning parameter values ​​corresponding to different agricultural machinery operation modes, obstacle categories and the combination mode of the obstacle relative to the area where the agricultural machinery is heading, including the basic warning distance, speed-related correction coefficient and braking safety margin parameter; Step 22: Based on the current agricultural machinery operation mode, obstacle type, and the area where the obstacle is located relative to the agricultural machinery's heading, select the basic warning distance, speed-related correction coefficient, and braking safety margin parameters from the preset warning parameter values; Step 23: Collect the linear velocity of the agricultural machinery in real time, and preset the driver's reaction time and the maximum braking deceleration according to the agricultural machinery model; Step 24: Based on the selected basic warning distance, speed-related correction coefficient, agricultural machinery linear speed, preset driver reaction time, preset maximum braking deceleration, basic warning distance, speed-related correction coefficient, and braking safety margin parameters, obtain the dynamic warning distance threshold for each obstacle.

5. The method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 4, characterized in that, The dynamic warning distance threshold function for obstacles is: ， In the formula, For the first An obstacle at time The dynamic warning distance threshold, For agricultural machinery linear velocity, For physical safety distance, , For reaction distance, Braking distance, To preset the driver's reaction time, To preset the maximum braking deceleration, , , For the first Speed-related correction coefficients for each obstacle For the first The basic warning distance for each obstacle For the first Braking safety margin parameters for each obstacle.

6. The method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 5, characterized in that, Normalized distance ratio of obstacles for: ， Risk Value for: 。 7. The method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 6, characterized in that, The risk level is determined based on the risk value, specifically as follows: Step 31: Preset risk level classification constraints; Step 32: Based on the current agricultural machinery operation mode, obstacle type, and the area where the obstacle is located relative to the agricultural machinery's heading, select risk level classification parameters from the preset risk level classification constraints; Step 33: Establish risk levels by classifying parameters based on risk values ​​and risk levels.

8. The method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 7, characterized in that, The risk level classification constraints are as follows: ， In the formula, and They are respectively the working modes Obstacle categories and the area where obstacles are located relative to the heading of the agricultural machinery Preset low-risk and medium-risk thresholds and medium-risk and high-risk thresholds under the combination.

9. A method for early warning of obstacles in agricultural machinery operations based on real-time environmental information according to claim 8, characterized in that, Risk level for: ， In the formula, This indicates no prior warning; This represents a low-level warning; This represents a medium-level warning; This indicates a high-level warning.

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