A vehicle-mounted laser radar adjustment system and method for uphill and downhill

Abstract

The present invention discloses an uphill and downhill vehicle-mounted laser radar adjustment system, which includes a laser radar, a controller and a motor; the laser radar is connected to the controller via Ethernet, the laser radar is used to identify the road conditions in front of the vehicle, and transmits point cloud data of the road in front of the vehicle to the controller in real time; the motor is electrically connected to the controller, the controller controls the movement direction and stroke of the motor by sending a pulse signal, and the motor is used to adjust the illumination angle of the laser radar. The present invention provides an uphill and downhill vehicle-mounted laser radar adjustment system and method thereof, which adaptively adjusts the illumination angle of the laser radar to obtain the maximum effective field of view when the vehicle enters uphill and downhill sections, thereby reducing the field of view blind spots caused by changes in road conditions.

Description

Technical Field

[0001] The invention relates to an uphill and downhill vehicle-mounted laser radar adjustment system and a method thereof. Background Art

[0002] At present, with the increasing popularity of smart cars, more and more cars are equipped with intelligent assisted driving systems, which can realize point-to-point automatic driving of vehicles on highways and some urban roads. Usually, these vehicles with intelligent assisted driving functions are equipped with forward-looking laser radars to sense the road conditions in front of the vehicle and control the vehicle's driving according to the real-time road conditions.

[0003] However, since current LiDARs are fixed on the front grille or roof of the vehicle and cannot be adjusted, there are certain blind spots when encountering steep road conditions, such as elevated bridges, entrances and exits of underground garages, etc. When a vehicle running in autonomous driving mode has a blind spot, it will become very dangerous and easily cause traffic accidents, endangering people's lives and property safety. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide an uphill and downhill vehicle-mounted laser radar adjustment system and method, which adaptively adjusts the illumination angle of the laser radar to obtain the maximum effective field of view when the vehicle enters uphill and downhill sections, thereby reducing the blind spots caused by changes in road conditions.

[0005] In order to solve the above technical problems, the technical solution of the present invention is:

[0006] On one hand, the present invention provides an uphill and downhill vehicle-mounted laser radar adjustment system, which includes a laser radar, a controller and a motor;

[0007] The laser radar is connected to the controller via Ethernet, and is used to identify the road conditions in front of the vehicle and transmit point cloud data of the road in front of the vehicle to the controller in real time;

[0008] The motor is electrically connected to a controller, and the controller controls the movement direction and stroke of the motor by sending a pulse signal. The motor is used to adjust the illumination angle of the laser radar.

[0009] Further, the controller includes a three-axis acceleration sensor and an MCU module;

[0010] The laser radar is connected to the input end of the MCU module;

[0011] The three-axis acceleration sensor is connected to the input end of the MCU module via the SPI bus, and the three-axis acceleration sensor is used to identify the body posture;

[0012] The output end of the MCU module is connected to the motor through a motor drive circuit.

[0013] Furthermore, the chip model used by the three-axis acceleration sensor is SCA3300 produced by Murata of Japan.

[0014] Another aspect of the present invention provides a method for adjusting an uphill and downhill vehicle-mounted laser radar adjustment system, which comprises:

[0015] Step S1, the laser radar identifies the road conditions in front of the vehicle and transmits the point cloud data of the road in front of the vehicle to the controller in real time;

[0016] Step S2: The controller acquires point cloud data transmitted by the laser radar in real time, and sends the received point cloud data to a point cloud preprocessing module of the controller, which preprocesses the point cloud data;

[0017] Step S3: the point cloud preprocessing module sends the preprocessed point cloud data to the ground segmentation algorithm module of the controller, and the ground segmentation algorithm module performs ground segmentation on the point cloud data to obtain vehicle posture parameters;

[0018] Step S4, comparing the vehicle posture parameters obtained by ground segmentation with the true value of the vehicle body posture of the three-axis acceleration sensor to obtain the adjustment angle value of the laser radar;

[0019] Step S5: The controller controls the motor to rotate according to the adjustment angle value of the laser radar to adjust the illumination angle of the laser radar.

[0020] Step S6: The controller determines the driving condition based on the real-time vehicle body posture. When the vehicle is driving on a slope or completely leaves the slope section, the controller controls the motor to return to the initial position and restores the laser radar to the initial position.

[0021] Step S7: re-calibrate the laser radar.

[0022] Further, the step S2 specifically includes the following steps:

[0023] The point cloud preprocessing module filters out noise in the point cloud data by calling the VoxelGrid filter module in the PCL point cloud library, and then extracts key points of the cloud data through the SIFT3D algorithm to reduce the amount of point cloud data.

[0024] Further, the step S3 specifically includes the following steps:

[0025] The ground segmentation algorithm module adopts the PaGO LOAM algorithm based on the SOTA method;

[0026] Project the current point cloud data into the range image and then perform ground segmentation;

[0027] Edge features and plane features are extracted based on the smoothness of the depth image; the position and posture parameters of the vehicle are obtained by obtaining the transformation matrix between consecutive scans using the correspondence between the features.

[0028] Further, the step S4 specifically includes the following steps:

[0029] The controller receives the acceleration G values ​​in the three directions of X, Y, and Z axes output by the three-axis acceleration sensor through the SPI bus, and calculates the instantaneous pitch angle θ of the vehicle through the angle direct calculation module in the software running inside the controller 瞬间 The angle filter module in the software running inside the controller filters out the G value change of the acceleration sensor chip caused by bumps or vibrations, and then outputs the actual pitch angle θ of the vehicle. G ;

[0030] The actual pitch angle θ of the vehicle G The vehicle pitch angle θ in the vehicle attitude value calculated by the laser radar L Compare and output the final vehicle attitude pitch angle θ 最终 , the final vehicle posture pitch angle θ 最终 The expression is as follows:

[0031]

[0032] Among them, 0.7 and 0.3 are the weights of the true value of the body posture of the three-axis acceleration sensor;

[0033] The final vehicle posture pitch angle θ 最终 That is the adjustment angle value of the laser radar.

[0034] Furthermore, the G value change of the acceleration sensor chip caused by the bump or vibration is filtered out by an angle filtering module in the software running inside the controller, which specifically includes the following steps:

[0035] In unit time T P Within, determine the instantaneous pitch angle θ of the vehicle 瞬间 Is it greater than the preset pitch angle calibration value θ? 预设 ;

[0036] If the unit time T P The instantaneous pitch angle of the vehicle is θ 瞬间 Greater than the preset pitch angle calibration value θ 预设 , then calculate the final vehicle posture pitch angle θ 最终 ;

[0037] If the unit time T P The instantaneous pitch angle of the vehicle is θ瞬间 Less than the preset pitch angle calibration value θ 预设 , then it will be less than the pitch angle calibration value θ 预设 The instantaneous pitch angle θ 瞬间 Filter out.

[0038] Further, the step S5 specifically includes the following steps:

[0039] The controller sends an enable signal, a motor rotation direction signal and a continuous pulse signal to the motor through the LIN bus, and controls the motor to run continuously by sending continuous pulse signals. Each pulse signal controls the motor to rotate a motor rotation angle θ per-plus , the controller calculates the final vehicle posture pitch angle θ 最终 After that, the final vehicle posture pitch angle θ 最终 Divide by the motor rotation angle θ per-plus , calculate the number of pulse signals that need to be sent. The controller records the sending time T of each pulse signal through the internal timer and interrupt trigger plus , the controller outputs the corresponding number of pulses to ensure precise control of the lidar position.

[0040] Further, the step S7 specifically includes the following steps:

[0041] By calling the RANSAC plane detection algorithm in the PCL point cloud library, the standard vertical vector preset in the laser radar coordinate system is obtained as (0, 0, 1) according to the general plane equation, and then the rotation matrix from the plane normal vector of the current plane to the standard vertical vector is calculated, and then the rotation matrix is ​​applied to the processing of the point cloud data, the deviation value is calculated, and then the point cloud data is rotated and the reference plane is calibrated;

[0042] The expression of the general equation of the plane is:

[0043] a x +b y +c z +d=0;

[0044] Among them, a x ,b y ,c z is the normal vector of the xyz plane;

[0045] d is a constant term, which represents the intercept of the normal vector with the xyz axis in the xyz plane.

[0046] The above technical solution is adopted. The present invention uses a laser radar to identify the road conditions ahead, uses the three-axis acceleration sensor's perception of the vehicle's posture as the true value, and jointly determines whether the vehicle is about to enter an uphill or downhill section. Then, through the fusion results of the three-axis acceleration sensor and the laser radar, the laser radar's illumination angle can be adaptively adjusted to obtain the maximum effective field of view in uphill and downhill sections, reducing the field of view blind spots caused by changes in road conditions and improving driving safety. The system structure of the present invention is simple and has good compatibility. The acceleration sensor chip is integrated in the controller, which is more friendly to the later installation and upgrade of the vehicle and has better compatibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a schematic diagram of the uphill and downhill vehicle-mounted laser radar adjustment system of the present invention;

[0048] Figure 2 A schematic diagram of a road condition in which a vehicle goes uphill according to the present invention;

[0049] Figure 3 A schematic diagram of a road condition in which a vehicle of the present invention is located on a slope;

[0050] Figure 4 A schematic diagram of a road condition in which a vehicle of the present invention is going downhill;

[0051] Figure 5 is a logic flow chart of the adjustment method of the present invention;

[0052] Figure 6 The figure is a logic flow chart of filtering determination of the three-axis acceleration sensor of the present invention. DETAILED DESCRIPTION

[0053] In order to make the contents of the present invention more clearly understood, the present invention is further described in detail below based on specific embodiments in conjunction with the accompanying drawings.

[0054] Embodiment 1

[0055] like Figure 1 As shown, this embodiment provides an uphill and downhill vehicle-mounted laser radar adjustment system, which includes a laser radar, a controller and a motor. The laser radar is connected to the controller via Ethernet. The laser radar is used to identify the road conditions in front of the vehicle and transmit the point cloud data of the road in front of the vehicle to the controller in real time. The motor is electrically connected to the controller. The controller controls the movement direction and stroke of the motor by sending pulse signals. The motor is used to adjust the illumination angle of the laser radar.

[0056] Specifically, the controller of this embodiment includes a three-axis acceleration sensor and an MCU module;

[0057] The laser radar is connected to the input terminal of the MCU module;

[0058] The three-axis acceleration sensor is connected to the input end of the MCU module through the SPI bus. The three-axis acceleration sensor is used to identify the body posture. The chip model used by the three-axis acceleration sensor is SCA3300 from Murata of Japan.

[0059] The output end of the MCU module is connected to the motor through the motor drive circuit.

[0060] The uphill and downhill vehicle-mounted laser radar adjustment system of this embodiment uses the laser radar to identify the road conditions ahead, and combines the three-axis acceleration sensor's perception of the vehicle's posture as a reference "true value" to jointly determine whether the vehicle is about to enter an uphill or downhill section. Furthermore, the illumination angle of the laser radar is appropriately adjusted through the fusion result of the acceleration sensor and the laser radar. When the vehicle is driving on a slope section and completely leaves the slope section, the controller will control the motor to return to the initial position. At the same time, the controller will re-calibrate the point cloud ground level of the laser radar point cloud data to ensure that point cloud segmentation and classification and other processing are not affected by changes in the laser radar position. When the vehicle is about to go uphill or downhill, the system will adjust the laser radar to a certain angle to ensure that the laser radar has the maximum effective field of view.

[0061] Embodiment 2

[0062] like Figures 2 to 5 As shown, this embodiment provides a method for adjusting an uphill and downhill vehicle-mounted laser radar adjustment system, which includes:

[0063] Step S1, the laser radar identifies the road conditions in front of the vehicle and transmits the point cloud data of the road in front of the vehicle to the controller in real time;

[0064] Step S2: The controller acquires point cloud data transmitted by the laser radar in real time, and sends the received point cloud data to a point cloud preprocessing module of the controller, which preprocesses the point cloud data;

[0065] Step S3: the point cloud preprocessing module sends the preprocessed point cloud data to the ground segmentation algorithm module of the controller, and the ground segmentation algorithm module performs ground segmentation on the point cloud data to obtain vehicle posture parameters;

[0066] Step S4, comparing the vehicle posture parameters obtained by ground segmentation with the true value of the vehicle body posture of the three-axis acceleration sensor to obtain the adjustment angle value of the laser radar;

[0067] Step S5: The controller controls the motor to rotate according to the adjustment angle value of the laser radar to adjust the illumination angle of the laser radar.

[0068] Step S6: The controller determines the driving condition based on the real-time vehicle body posture. When the vehicle is driving on a slope or completely leaves the slope section, the controller controls the motor to return to the initial position and restores the laser radar to the initial position.

[0069] Step S7, however, due to the existence of mechanical errors, the laser radar needs to be recalibrated horizontally to avoid the accumulated errors of multiple motor movements and the inaccuracy of subsequent algorithms in processing point cloud segmentation and classification due to the motor not returning to its original position.

[0070] Specifically, step S2 of this embodiment includes the following steps:

[0071] The point cloud preprocessing module filters out a lot of noise in the point cloud data, that is, a large number of hash points and isolated points, by calling the VoxelGrid filter module in the PCL point cloud library. Then the key points of the cloud data are extracted through the SIFT3D algorithm to greatly reduce the amount of point cloud data and reduce the amount of calculation of the subsequent ground segmentation algorithm module.

[0072] Specifically, step S3 of this embodiment includes the following steps:

[0073] The ground segmentation algorithm module uses the PaGO LOAM algorithm based on the SOTA method; this method can segment the ground more robustly in complex and uneven urban environments with less performance disturbance and in rural environments with more uneven and rugged ground, and is used to judge the road scene in front of the vehicle;

[0074] Project the current point cloud data into the range image and then perform ground segmentation;

[0075] Edge features and plane features are extracted based on the smoothness of the depth image; the position and posture parameters of the vehicle are obtained by obtaining the transformation matrix between consecutive scans using the correspondence between the features.

[0076] Specifically, step S4 of this embodiment includes the following steps:

[0077] In terms of the fusion of LiDAR and three-axis acceleration sensor, the value of the three-axis acceleration sensor is the "true value". The three-axis acceleration sensor outputs the acceleration G value in the three directions of X, Y, and Z. The definitions of X, Y, and Z axes are: the X axis represents the horizontal axis direction horizontal to the ground (the left and right direction of the vehicle); the Y axis represents the vertical axis direction horizontal to the ground (the front and back direction of the vehicle); the Z axis represents the direction perpendicular to the ground (the up and down direction of the vehicle);

[0078] The controller receives the acceleration G values ​​in the three directions of X, Y, and Z axes output by the three-axis acceleration sensor through the SPI bus, and calculates the instantaneous pitch angle θ of the vehicle through the angle direct calculation module in the controller's internal running software 瞬间In the actual driving process of the vehicle, the road surface cannot be absolutely flat in an ideal state. In order to filter out the G value changes of the acceleration sensor chip caused by small bumps or vibrations, the angle filter module in the software running inside the controller will filter out the G value changes of the acceleration sensor chip caused by bumps or vibrations, and then output the actual pitch angle θ of the vehicle. G ;

[0079] The actual pitch angle θ of the vehicle G The vehicle pitch angle θ in the vehicle attitude value calculated by the laser radar L Compare and output the final vehicle attitude pitch angle θ 最终 , the final vehicle posture pitch angle θ 最终 The expression is as follows:

[0080]

[0081] Among them, 0.7 and 0.3 are the weights of the true value of the body posture of the three-axis acceleration sensor. The higher the value, the higher the reliability of the "true value";

[0082] The final vehicle posture pitch angle θ 最终 This is the adjustment angle value of the laser radar.

[0083] Specifically, Figure 6 As shown, the G value change of the acceleration sensor chip caused by bumps or vibrations is filtered out by the angle filtering module in the software running inside the controller, which specifically includes the following steps:

[0084] In unit time T P Within, determine the instantaneous pitch angle θ of the vehicle 瞬间 Is it greater than the preset pitch angle calibration value θ? 预设 ;

[0085] If the unit time T P The instantaneous pitch angle of the vehicle is θ 瞬间 Greater than the preset pitch angle calibration value θ 预设 , then calculate the final vehicle posture pitch angle θ 最终 ;

[0086] If the unit time T P The instantaneous pitch angle of the vehicle is θ 瞬间 Less than the preset pitch angle calibration value θ 预设 , then it will be less than the pitch angle calibration value θ 预设 The instantaneous pitch angle θ 瞬间 Filter out.

[0087] Specifically, step S5 of this embodiment includes the following steps:

[0088] In this embodiment, a stepper motor is used to adjust the illumination angle of the laser radar. The controller sends an enable signal, a motor rotation direction signal and a continuous pulse signal to the motor through the LIN bus. The motor is continuously controlled by sending continuous pulse signals. Each pulse signal controls the motor to rotate a motor rotation angle θ. per-plus , the controller calculates the final vehicle attitude pitch angle θ 最终 After that, the final vehicle posture pitch angle θ 最终 Divide by the motor rotation angle θ per-plus , calculate the number of pulse signals that need to be sent. The controller records the sending time T of each pulse signal through the internal timer and interrupt trigger plus , the controller outputs the corresponding number of pulses to ensure precise control of the lidar position.

[0089] Specifically, step S7 of this embodiment includes the following steps:

[0090] By calling the RANSAC plane detection algorithm in the PCL point cloud library, the standard vertical vector preset in the laser radar coordinate system is obtained as (0, 0, 1) according to the general plane equation, and then the rotation matrix from the plane normal vector of the current plane to the standard vertical vector is calculated, and then the rotation matrix is ​​applied to the processing of the point cloud data, the deviation value is calculated, and then the point cloud data is rotated and the reference plane is calibrated;

[0091] The general equation of a plane is expressed as:

[0092] a x +b y +c z +d=0;

[0093] Among them, a x ,b y ,c z is the normal vector of the xyz plane;

[0094] d is a constant term, which represents the intercept of the normal vector with the xyz axis in the xyz plane.

[0095] The specific embodiments described above further illustrate the technical problems, technical solutions and beneficial effects solved by the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for adjusting an uphill and downhill vehicle-mounted laser radar, characterized in that: It includes: Step S1, the laser radar identifies the road conditions in front of the vehicle and transmits the point cloud data of the road in front of the vehicle to the controller in real time; Step S2: The controller acquires point cloud data transmitted by the laser radar in real time, and sends the received point cloud data to a point cloud preprocessing module of the controller, which preprocesses the point cloud data; Step S3: the point cloud preprocessing module sends the preprocessed point cloud data to the ground segmentation algorithm module of the controller, and the ground segmentation algorithm module performs ground segmentation on the point cloud data to obtain vehicle posture parameters; Step S4, comparing the vehicle posture parameters obtained by ground segmentation with the true value of the vehicle body posture of the three-axis acceleration sensor to obtain the adjustment angle value of the laser radar; Step S5: The controller controls the motor to rotate according to the adjustment angle value of the laser radar to adjust the illumination angle of the laser radar; Step S6: The controller determines the road condition according to the real-time vehicle body posture. When the vehicle is traveling on a slope or completely leaves the slope section, the controller controls the motor to return to the initial position and restores the laser radar to the initial position. Step S7, re-calibrate the laser radar horizontally; The step S2 specifically includes the following steps: The point cloud preprocessing module filters out noise in the point cloud data by calling the VoxelGrid filter module in the PCL point cloud library, and then extracts key points of the cloud data through the SIFT3D algorithm to reduce the amount of point cloud data; The step S3 specifically includes the following steps: The ground segmentation algorithm module adopts the PaGO LOAM algorithm based on the SOTA method; Project the current point cloud data into the range image and then perform ground segmentation; Extract edge features and plane features based on the smoothness of the depth image; obtain the position and posture parameters of the vehicle by obtaining the transformation matrix between consecutive scans using the correspondence between the features; The step S4 specifically includes the following steps: The controller receives the acceleration G values ​​in the three directions of X, Y, and Z axes output by the three-axis acceleration sensor through the SPI bus, and calculates the instantaneous pitch angle θ of the vehicle through the angle direct calculation module in the software running inside the controller 瞬间 The angle filter module in the software running inside the controller filters out the G value change of the acceleration sensor chip caused by bumps or vibrations, and then outputs the actual pitch angle θ of the vehicle. G ; The actual pitch angle θ of the vehicle G The vehicle pitch angle θ in the vehicle attitude value calculated by the laser radar L Compare and output the final vehicle attitude pitch angle θ 最终 , the final vehicle posture pitch angle θ 最终 The expression is as follows: Among them, 0.7 and 0.3 are the weights of the true value of the body posture of the three-axis acceleration sensor; The final vehicle posture pitch angle θ 最终 That is, the adjustment angle value of the laser radar; The step S7 specifically includes the following steps: By calling the RANSAC plane detection algorithm in the PCL point cloud library, the standard vertical vector preset in the laser radar coordinate system is obtained as (0, 0, 1) according to the general plane equation, and then the rotation matrix from the plane normal vector of the current plane to the standard vertical vector is calculated, and then the rotation matrix is ​​applied to the processing of the point cloud data, the deviation value is calculated, and then the point cloud data is rotated and the reference plane is calibrated; The expression of the general equation of the plane is: a x +b y +c z +d=0; Among them, a x ,b y ,c z is the normal vector of the xyz plane; d is a constant term, which represents the intercept of the normal vector with the xyz axis in the xyz plane.

2. The uphill and downhill vehicle-mounted laser radar adjustment method according to claim 1 is characterized in that: The G value change of the acceleration sensor chip caused by bumps or vibrations is filtered out by an angle filtering module in the software running inside the controller, which specifically includes the following steps: In unit time T P Within, determine the instantaneous pitch angle θ of the vehicle 瞬间 Is it greater than the preset pitch angle calibration value θ? 预设 ; If the unit time T P The instantaneous pitch angle of the vehicle is θ 瞬间 Greater than the preset pitch angle calibration value θ 预设 , then calculate the final vehicle posture pitch angle θ 最终 ; If the unit time T P The instantaneous pitch angle θ of the vehicle 瞬间 Less than the preset pitch angle calibration value θ 预设 , then it will be less than the pitch angle calibration value θ 预设 The instantaneous pitch angle θ 瞬间 Filter out.

3. The uphill and downhill vehicle-mounted laser radar adjustment method according to claim 1 is characterized in that: The step S5 specifically includes the following steps: The controller sends an enable signal, a motor rotation direction signal and a continuous pulse signal to the motor through the LIN bus, and controls the motor to run continuously by sending continuous pulse signals. Each pulse signal controls the motor to rotate a motor rotation angle θ per-plus , the controller calculates the final vehicle posture pitch angle θ 最终 After that, the final vehicle posture pitch angle θ 最终 Divide by the motor rotation angle θ per-plus , calculate the number of pulse signals that need to be sent; the controller records the sending time T of each pulse signal through the internal timer and interrupt trigger plus , the controller outputs the corresponding number of pulses to ensure precise control of the lidar position.

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