Self-adaptive steering calibration method for outdoor unmanned sweeper

Abstract

The invention belongs to the related technical field of vehicle control, and particularly relates to an adaptive steering calibration method for an outdoor unmanned sweeper, which comprises the following steps of: obtaining a calibration starting point and a calibration reference line based on a vehicle-mounted GNSS (Global Navigation Satellite System) INS (Inertial Navigation Satellite System) of the outdoor unmanned sweeper; according to a known vehicle steering angle, a steering calibration angle set is generated according to equal-interval division; a control instruction is issued to the vehicle, the coordinate value of the center point of the rear axle of the vehicle is obtained and added to the advancing track point set, the turning radius corresponding to the steering angle of the set is fitted according to the recorded advancing track point set, and the actual steering angle is calculated and recorded. And repeating the steps until all the steering angles in the preset steering calibration angle set are calibrated, and then fitting a calibration curve between the preset steering angle and the actual steering angle to obtain a cubic term relation function between the preset steering angle and the actual steering angle. The calibration method is simple and reliable, and can ensure the steering control precision when the vehicle executes complex actions such as welt cleaning.

Description

Technical Field

[0001] The present invention mainly relates to the technical fields of vehicle control and autonomous driving. Specifically, it is an adaptive steering calibration method for outdoor unmanned road sweepers, which is applicable to the control of unmanned road sweepers in complex operation scenarios such as urban sanitation and industrial parks. Background Art

[0002] In practical applications, the operation range of outdoor unmanned road sweepers involves various types such as urban roads, communities, parks, and industrial parks, and often faces complex scenarios such as narrow roads and sharp turns. In addition, when cleaning urban roads, due to road design reasons, it is easier for garbage to accumulate at positions close to the road edge on both sides of the road. Therefore, it is necessary for the road sweeper to perform side cleaning. All of the above situations pose extremely high requirements for the path planning and steering control accuracy of outdoor unmanned road sweepers.

[0003] To improve the vehicle steering control accuracy, the current common practice is to separately calibrate the steering of each vehicle after it leaves the factory. By mounting a 6-axis gyroscope on the front steering wheel axle, after the front wheels rotate at a set angle, record the actual steering angle output by the gyroscope, so as to obtain the error between the preset steering angle and the actual steering angle. By repeatedly performing the above steps many times, ensure that the angle covers from 0 degrees to the maximum steering angle. This process is extremely cumbersome, and manual operations are required step by step during the process. In addition, the gyroscope is not a standard configuration of outdoor unmanned road sweepers and needs to be configured additionally. In addition, since the steering angle of the front wheels is directly recorded, the gyroscope needs to be installed on the steering wheel, and the installation error of the gyroscope and the temperature drift error it itself will directly affect the accuracy of steering calibration. Summary of the Invention

[0004] To solve the deficiencies of the current technology, the present invention combines the existing technology and starts from practical applications to provide an adaptive steering calibration method for outdoor unmanned road sweepers to ensure the steering control accuracy when the vehicle performs complex actions such as side cleaning.

[0005] The technical solution of the present invention is as follows: An adaptive steering calibration method for an outdoor unmanned road sweeper, comprising the following steps: S1. Based on the in-vehicle GNSS_INS system of the outdoor unmanned road sweeper, obtain the position and attitude values of the center point of the rear axle of the vehicle as the calibration starting point, and adaptively generate a straight line along the extension line of the rear wheel axle of the vehicle as the subsequent calibration reference line; S2. According to the known maximum steering angles of the vehicle's front wheels to the left and right, generate a set of steering calibration angles according to equal-spacing division; S3. Send a control command to the vehicle, and obtain the coordinate value of the center point of the vehicle's rear axle in real time at a set frequency. Add it to the set of travel trajectory points. When it is detected that the vehicle reaches the calibration reference line, stop sending the control command. According to the recorded set of travel trajectory points, fit the turning radius corresponding to this group of steering angles, calculate and record the actual steering angle, and at the same time switch to the next set of control commands; S4. Repeat step S3 until all the steering angle calibrations in the preset steering calibration angle set are completed. Then, according to the set of actual steering angles calculated in the above process, fit the calibration curve between the preset steering angle and the actual steering angle to obtain the cubic term relationship function between the two.

[0006] Further, step S1 specifically includes: S11. Return the front steering wheel of the unmanned sweeper to the zero position, and at the same time check the working status of the GNSS_INS system to confirm that it is working properly; S12. The vehicle-mounted controller reads the position and attitude values output by the GNSS_INS system. According to the relative position of the GNSS_INS installation to the center point of the vehicle's rear axle, project it to the center point of the vehicle's rear axle to obtain new position and attitude values, and use this value as the starting point of calibration; S13. Generate a straight line along the extension line of the vehicle's rear wheel axle from the calibration starting point of the vehicle as the subsequent calibration reference line.

[0007] Further, step S2 specifically includes: After determining that the number of groups to be calibrated is n groups, based on the known maximum left steering angle of the vehicle's front wheels, generate a set of left steering calibration angles at equal intervals within the interval [0, maximum left steering angle]. Similarly, generate a set of right steering calibration angles, and merge the left and right steering calibration angle sets into a steering calibration angle set.

[0008] Further, step S3 specifically includes: S31. Send a control command to the vehicle, where the control command includes a fixed speed value and the values of the steering calibration angle set generated in step S2; S32. During the vehicle's travel, obtain the coordinate value of the center point of the vehicle's rear axle in real time at a set frequency. This value is converted from the original output value of the GNSS_INS system to the coordinate and attitude of the center point of the rear axle, and added to the set of trajectory points; S33. During the vehicle's travel, after obtaining the coordinate value of the center point of the vehicle's rear axle, judge whether it has run to the calibration reference line based on this value; S34. If the vehicle reaches the calibration reference line, stop sending the control command. According to the recorded set of travel trajectory points, fit the turning radius corresponding to this group of steering angles. The vehicle trajectory running according to the control command will be in a semi-circular arc shape. Use the pratt algorithm to perform circular radius fitting calculation to obtain the turning radius value; S35. Obtain the turning radius value, and calculate the actual steering angle according to the relationship between the turning radius and the steering angle. S36. After calculating the actual steering angle, add the actual steering angle to the set of actual steering angles and switch to the next set of control instructions.

[0009] Furthermore, in step S33, the judgment basis for determining whether the vehicle has run to the calibration reference line is that the Euclidean distance from the vehicle coordinate point to the reference line is less than the set threshold.

[0010] Furthermore, in step S4, the calibration curve between the preset steering angle and the actual steering angle is fitted by the least squares method to obtain a cubic term relationship function between the two.

[0011] Advantages of the present invention: By equipping the vehicle with a GNSS_INS system, the present invention can obtain the motion trajectory of the outdoor unmanned cleaning vehicle in real time. By equally dividing the left and right steering angles, a set of all steering angles to be calibrated can be obtained; at the same time, according to the initial position and attitude of the vehicle, a calibration reference line for the vehicle is automatically generated. After issuing the automatic control instructions, the vehicle starts to move autonomously. When the vehicle reaches the calibration reference line, it can be considered that the calibration of the steering angle of this group is completed, and then it switches to the next group of steering angles. After all steering angles have been calibrated, a cubic polynomial relationship function representing the corresponding relationship between the preset steering angle and the actually executed steering angle will be automatically calculated. This method makes full use of the GNSS_INS system configured in the outdoor unmanned cleaning vehicle itself, without the need to add additional sensors as calibration references; after setting the maximum left and right steering angles, the above calibration process can be automatically completed, greatly reducing the workload of manual calibration; in addition, by sampling more steering angle groups, the angle fitting accuracy can be effectively improved, thus ensuring the steering control accuracy of the vehicle when performing complex operations such as edge cleaning. Brief Description of the Drawings

[0012] Figure 1 It is a detailed flowchart of the present invention.

[0013] Figure 2 It is a schematic diagram for explaining the steering angle of the present invention.

[0014] Figure 3 It is a schematic diagram for vehicle coordinate conversion of the present invention.

[0015] Figure 4 It is a schematic diagram of the calibration reference line automatically generated by the present invention.

[0016] Figure 5 It is a schematic diagram for calculating the steering angle of the present invention.

[0017] Figure 6 It is a schematic diagram for curve fitting of the preset steering angle and the actual steering angle of the present invention. Specific Embodiment

[0018] In combination with the accompanying drawings and specific embodiments, the present invention will be further described. It should be understood that these embodiments are only used to illustrate the present invention and not to limit the scope of the present invention. In addition, it should be understood that after reading the content taught by the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by this application.

[0019] This embodiment provides an adaptive steering calibration method for an outdoor unmanned sweeper. After obtaining the real-time position and attitude of the unmanned sweeper through the on-vehicle GNSS_INS system, an adaptive calibration reference line is generated, and the calibration of multiple groups of steering is automatically completed. After the calibration is completed, a cubic curve function between the preset steering angle and the actual steering angle is automatically generated. Refer to Figure 1 As shown, the specific technical solution of this embodiment includes the following steps: S1. The on-vehicle GNSS_INS system of the outdoor unmanned sweeper outputs the position and attitude values , and after coordinate translation, the position and attitude values of the center point of the rear axle of the vehicle are obtained Taking this point as the calibration starting point, along the extension line of the rear wheel axle of the vehicle, an adaptive straight line is generated as the subsequent calibration reference line. Specifically, it includes: S11. The unmanned sweeper is parked in an open outdoor environment, and the front steering wheel is returned to the zero position. At the same time, check the working status of the GNSS_INS system to confirm that it is working properly; S12. Refer to Figure 3 As shown, the vehicle-mounted controller reads the position and attitude values output by the GNSS_INS system . Generally, the GNSS_INS system uses the northeast celestial coordinate system. is the position in the northeast celestial coordinate system, is the vehicle attitude orientation. According to the relative position of the GNSS_INS installation to the center point of the rear axle of the vehicle (delta_x, delta_y) , project it to the center point of the rear axle of the vehicle to obtain the new position and attitude values , and use this value as the starting point of the calibration. The calculation formula is as follows: , ; S13. Refer to Figure 4 As shown, starting from the vehicle calibration starting point along the extension line of the rear wheel axle of the vehicle, a straight line is generated as the subsequent calibration reference line ， 、 Straight line The direction of this straight line in the GNSS_INS coordinate system is 90° , and it passes through the vehicle calibration starting point .

[0020] The calibration starting point and the calibration reference line are determined through the above steps for subsequent steering calibration.

[0021] S2. According to the known maximum left and right steering angles of the vehicle's front wheels, generate a steering angle calibration set according to equal-spacing division . Specifically, it includes: Determine that the number of groups to be calibrated is n groups ( n is an even number). According to the known maximum left steering angle of the vehicle's front wheels, generate a left steering calibration angle set at equal intervals within the range of [0, maximum left steering angle], Similarly, according to the known maximum right steering angle of the vehicle's front wheels, generate a right steering calibration set at equal intervals within the range of [0, maximum right steering angle] . Combine the left and right steering calibration sets into .

[0022] S3. Send a control command to the vehicle , and obtain the coordinate value of the center point of the vehicle's rear axle in real time according to the set frequency , and add it to the set of travel trajectory points. When it is detected that the vehicle reaches the calibration reference line, stop sending the control command, and according to the recorded set of travel trajectory points { }, fit the turning radius corresponding to the steering angle of this group , calculate and record the actual steering angle , and at the same time switch to the next set of control commands . Specifically, it includes: S31. Send a control command to the vehicle , where speed is a fixed speed value. To ensure a smaller positioning error during travel, it can usually be set to 0.2 - 0.5 m / s; is the steering calibration angle set generated in step S2 value, i starts from 1.

[0023] S32. During the vehicle's travel, obtain the coordinate value of the center point of the vehicle's rear axle in real time according to the set frequency , which is the same as in step S12, and convert the GNSS_INS original output value into the coordinate and attitude of the center point of the rear axle, and add it to the set of trajectory points { }.

[0024] S33. During the vehicle's travel, obtain the coordinate value After that, based on this value, it is determined whether the vehicle has reached the calibration baseline generated in step S13 , and the judgment basis is that the Euclidean distance from the vehicle coordinate point to this baseline is less than , and the formula is as follows: .

[0025] S34. When the vehicle reaches the calibration baseline, stop issuing control instructions. According to the set of recorded travel trajectory points { }, fit the turning radius corresponding to this group of steering angles . The vehicle trajectory running according to the control instruction will be semi-circular. The pratt algorithm can be used to perform circular radius fitting calculation to obtain the turning radius value. The pratt algorithm is a commonly used method for fitting circles for scattered points that is robust to noise and suitable for large curvatures.

[0026] S35. As shown in Figure 5 , obtain the turning radius value. According to the relationship formula between the turning radius and the steering angle, calculate the actual steering angle , and the calculation formula is as follows: .

[0027] S36. After calculating the actual steering angle , add to the set of actual steering angles and switch to the next set of control instructions .

[0028] S4. Repeat step S3 until all the steering angles in the preset steering angle set are calibrated. Then, according to the set of actual steering angles calculated in the above process, fit the calibration curve between the preset steering angle and the actual steering angle (refer to Figure 6 shown), and obtain the cubic relationship function between the two, a, b, c, d are the corresponding coefficients of the function. Generally speaking, n will be greater than 4. Therefore, the relationship between the preset steering angle set and the actual steering angle set is fitted by the least squares method to obtain the relationship function, and the entire calibration process ends.

[0029] During the process of vehicle autonomous driving, if the front wheels need to reach a specific steering angle , only need to substitute it into the above relationship formula to obtain the corresponding preset steering angle .

[0030] The method provided in this embodiment makes full use of the GNSS_INS system configured in the outdoor unmanned sweeper, without the need to add additional sensors as calibration references; after setting the maximum left and right steering angles, the above calibration process can be automatically completed, greatly reducing the workload of manual calibration; in addition, by sampling more steering angle groups, the angle fitting accuracy can be effectively improved, thus ensuring the steering control accuracy of the vehicle when performing complex operations such as edge cleaning.

Claims

1. An adaptive steering calibration method for an outdoor unmanned sweeper, characterized in that, It includes the following steps: S1. Based on the on-vehicle GNSS_INS system of the outdoor unmanned sweeper, obtain the position and attitude values of the center point of the rear axle of the vehicle as the calibration starting point, and adaptively generate a straight line along the extension line of the rear wheel axle of the vehicle as the subsequent calibration reference line; S2. According to the known maximum left and right steering angles of the vehicle's front wheels, generate a set of steering calibration angles according to equal intervals; S3. Send control commands to the vehicle, and obtain the coordinate values of the center point of the rear axle of the vehicle in real time according to the set frequency, and add them to the set of travel trajectory points. When it is detected that the vehicle reaches the calibration reference line, stop sending control commands. According to the recorded set of travel trajectory points, fit the turning radius corresponding to this group of steering angles, calculate and record the actual steering angle, and at the same time switch to the next group of control commands; S4. Repeat step S3 until all the steering angles in the preset set of steering calibration angles are calibrated. Then, according to the set of actual steering angles calculated in the above process, fit the calibration curve between the preset steering angle and the actual steering angle to obtain the cubic relationship function between the two.

2. The adaptive steering calibration method for an outdoor unmanned sweeper according to claim 1, wherein Step S1 specifically includes: S11. Turn the front steering wheel of the unmanned sweeper back to the zero position, and at the same time check the working status of the GNSS_INS system to confirm that it is working properly; S12. The vehicle-mounted controller reads the position and attitude values output by the GNSS_INS system, projects them according to the relative position of the GNSS_INS installation to the center point of the rear axle of the vehicle to the center point of the rear axle to obtain new position and attitude values, and use this value as the starting point of calibration; S13. Generate a straight line along the extension line of the rear wheel axle of the vehicle from the calibration starting point of the vehicle as the subsequent calibration reference line.

3. The adaptive steering calibration method for an outdoor unmanned sweeper according to claim 1, wherein Step S2 specifically includes: After determining that the number of groups to be calibrated is n groups, according to the known maximum left steering angle of the vehicle's front wheels, generate a set of left steering calibration angles at equal intervals in the interval [0, maximum left steering angle]. Similarly, generate a set of right steering calibration angles, and merge the left and right steering calibration angle sets into a set of steering calibration angles.

4. The adaptive steering calibration method for an outdoor unmanned sweeper according to claim 1, wherein, Step S3 specifically includes: S31. Send control commands to the vehicle, where the control commands include a fixed speed value and the values of the set of steering calibration angles generated in step S2; S32. During the vehicle's travel, obtain the coordinate values of the center point of the rear axle of the vehicle in real time according to the set frequency. This value is converted from the original output value of the GNSS_INS system to the coordinate and attitude of the center point of the rear axle and added to the set of trajectory points; S33. During the vehicle's travel, after obtaining the coordinate values of the center point of the rear axle of the vehicle, judge whether it runs to the calibration reference line according to this value; S34. If the vehicle reaches the calibration reference line, stop sending control commands. According to the recorded set of travel trajectory points, fit the turning radius corresponding to this group of steering angles. The vehicle trajectory running according to the control commands will be in a semi-circular arc shape, and use the pratt algorithm to perform circular radius fitting calculation to obtain the turning radius value; S35. Obtain the turning radius value, and calculate the actual steering angle according to the relationship formula between the turning radius and the steering angle; S36. After calculating the actual steering angle, add the actual steering angle to the set of actual steering angles and switch to the next group of control commands.

5. The adaptive steering calibration method for an outdoor unmanned sweeper according to claim 4, characterized in that, In step S33, the judgment basis for determining whether it runs to the calibration baseline is that the Euclidean distance from the vehicle coordinate point to the baseline is less than the set threshold.

6. The adaptive steering calibration method for an outdoor driverless sweeper according to claim 1, wherein In step S4, the calibration curve between the preset steering angle and the actual steering angle is fitted by the least squares method to obtain a cubic term relationship function between the two.

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