TW202235910A - Lidar system capable of reducing environmental noise - Google Patents

Abstract

A lidar system capable of reducing environmental noise includes a lidar and a processing module. The lidar acquires a point cloud model data from a detection environment. The processing module is electrically connected with the lidar. The processing module includes a vicinal point cloud filtering unit and a Kalman filtering unit. The vicinal point cloud filtering unit receives the point cloud model data and conduct a processing operation, so as to output a filter model data. The Kalman filtering unit receives the filter model data and processes the data, so as to output a low noise environment model data. Thus, the environmental noise of the lidar system in an adverse environment is reduced.

Description

LiDAR system capable of reducing environmental noise

The present invention relates to a LiDAR system capable of reducing environmental noise. The noise is filtered through two algorithms to reduce the environmental noise of the LiDAR system in a harsh environment.

Press, Advanced Driver Assistance Systems (Advanced Driver Assistance Systems; ADAS) is one of the vehicle technologies actively developed by car manufacturers in recent years, and the main function of ADAS is to provide drivers with relevant information such as the driving situation of the vehicle and changes in the external environment for analysis , and pre-warning of possible dangerous situations, allowing drivers to take countermeasures in advance to avoid traffic accidents.

However, with the rapid development of ADAS, more and more car manufacturers are also beginning to devote themselves to the development of self-driving cars, so self-driving cars are definitely the future trend of the automotive industry.

Optical radar is one of the indispensable and important components in self-driving cars. Through optical radar, it can sense the environmental conditions outside the vehicle. However, optical radar also has limitations in use. For example, optical radar is affected by many factors, mainly The impacts include: optical radar transmission and reception noise, noise caused by vehicle movement, environmental noise, etc.

Among them, environmental noise includes signals from stars, the earth, the sun, the atmosphere, clouds, or any radiation sources that should not be irradiated or reflected to the receiving end. In addition, severe weather is also a type of environmental noise, such as heavy rain and snow. , dense fog, etc. will greatly reduce the detection ability of the optical radar echo, resulting in misjudgment of the optical radar due to environmental noise. For example, in heavy rain or dense fog, water droplets may be misjudged as objects in front of the vehicle, making the The vehicle stops, so how to improve the noise problem faced by the optical radar is one of the problems to be solved by the present invention.

In order to solve the above problems, the present invention discloses a lidar system capable of reducing environmental noise, which uses two calculations to filter the noise in harsh environments, so as to prevent the harsh environment from affecting the sensing accuracy of the optical radar.

To achieve the above purpose, an embodiment of the present invention provides a lidar system capable of reducing environmental noise, which includes an optical radar and a processing module. The optical radar obtains point cloud model data from the detection environment; and the processing module is electrically connected to the optical radar. The processing module includes a neighboring point cloud filtering unit and a Kalman filtering unit, and the neighboring point cloud filtering unit receives the point cloud The model data is processed to output a filtered model data, and the Kalman filter unit receives the filtered model data to filter and output a low-noise environment model data.

In another embodiment of the present invention, the point cloud model data includes an environment frame with an X axis, a Y axis, and a Z axis, and complex point clouds located inside and outside the environment frame, wherein the point cloud exceeding a certain distance outside the environment frame can be ignored.

In another embodiment of the present invention, the adjacent point cloud filtering unit samples the point cloud with a plurality of sampling circles within and outside the environment frame, and two adjacent sampling circles partially overlap, when within the scope of the sampling circle When the number of obtained point clouds is greater than a critical judgment value, the sampling circle is retained.

In another embodiment of the present invention, the sampling circle has a sampling radius, and the sampling radius is 2 cm.

In another embodiment of the present invention, the distance between the centers of two adjacent sampling circles is between 1 cm and 3 cm.

In another embodiment of the present invention, the critical judgment value is 10, and when the number of point clouds within the sampling circle is less than the critical judgment value, the point cloud is regarded as noise and is filtered out.

In another embodiment of the present invention, it further includes an on-board computer, a positioning module and a power supply, which are respectively electrically connected to the processing module.

In this way, the present invention utilizes the adjacent point cloud filter unit and the Kalman filter unit to sequentially perform calculations to filter noise in harsh environments, so as to prevent the harsh environment from affecting the sensing accuracy of the optical radar.

Exemplary embodiments of the present invention are described in detail below with reference to the accompanying drawings, and it is not intended to limit the technical principles of the present invention to specific disclosed embodiments, but the scope of the present invention is only limited by the scope of the patent application, covering substitutions, modifications and equivalent.

Please refer to FIG. 1 to FIG. 5, which is a laser system 100 capable of reducing environmental noise according to the present invention, which is applied to vehicles, including but not limited to RVs, trucks, trucks, sports cars, etc. The radar system 100 includes a processing module 10 , an optical radar 20 , an on-board computer 30 , a positioning module 40 and a power supply 50 . The optical radar 20, the trip computer 30, the positioning module 40 and the power supply 50 are respectively electrically connected to the processing module 10, and in other embodiments, the trip computer 30 is not a component of the lidar system 100, so that the lidar system 100 can also be electrically connected to the trip computer 30 of the vehicle. In the embodiment of the present invention, the positioning module 40 is a global satellite positioning system (GPS), which is used to receive satellite positioning signals and provide the processing module 10 for vehicle positioning; the power supply 50 is 9v, 1A or 18v, 2A A transformer for electrical connection to the vehicle's battery or storage battery. Optical radar 20 is selected from Velodyne LiDAR radar company's 16-layer 360-degree three-dimensional lidar sensor (model VLP-16), which has 300,000 points per second, 360-degree horizontal field of view and 30-degree vertical Field of view, and the farthest effective sensing range is 100 meters, and the closest effective range is 30 cm.

The optical radar 20 system obtains a little cloud model data from the detection environment. The point cloud model data includes an environment frame S with X-axis, Y-axis, and Z-axis and a complex point cloud P (Point Cloud) located inside and outside the environment frame S, so the point cloud P has at least geometric In addition to the position information, it may also contain color information or information about the intensity of the reflective surface of the target. Among them, when judging whether it is classified as noise, the point cloud P beyond a certain distance outside the environment frame S is ignored.

The processing module 10 includes a neighboring point cloud filtering unit 11 and a Kalman filtering unit 12. The neighboring point cloud filtering unit 11 receives the point cloud model data and processes them so as to output a filtering model data. The Kalman filtering unit 12 receives the filtering model data in order to filter and output a low-noise environment model data, thereby, when the vehicle is driving in a harsh environment such as rain, snow, and fog, the environmental noise can be reduced through the two filtering processes of the processing module 10 It affects the sensing and performance of the optical radar 20 , thereby improving the judgment of the optical radar 20 .

The processing method for reducing environmental noise of the present invention is further described below:

The adjacent point cloud filter unit 11 samples the point cloud P with a plurality of sampling circles C within and outside the environment frame S. Please refer to FIG. 3, the sampling circle C has a sampling radius R, in the embodiment of the present invention , the sampling radius R is 2 centimeters, and the center distance D between two adjacent sampling circles C is between 1 centimeter and 3 centimeters, so that two adjacent sampling circles C partially overlap, which can avoid During sampling, a gap is generated between two sampling circles C, and the point cloud P in the gap is not included in the sampling information, making the sampling information inaccurate.

When the number of point clouds P obtained within the scope of each sampling circle C is greater than a critical judgment value, the sampling circle C is retained; otherwise, when the number of point clouds P obtained within the scope of the sampling circle C is less than the critical judgment value, the point cloud P is filtered out as noise. In the embodiment of the present invention, the critical judgment value is 10. Therefore, when the number of point clouds P obtained by a certain sampling circle C is less than 10, the point clouds P within the range of this sampling circle C will be filtered out as noise. Minor noise can be ignored, as shown in Figure 4. For example, when the vehicle encounters drizzle while driving, the noise caused by the raindrops can be filtered out through the aforementioned method, so that the vehicle will not stop due to the misjudgment of the raindrops as objects. However, the neighboring point cloud filtering unit 11 can filter most of the environmental noise, but the optical radar 20 still cannot establish accurate spatial model data when the vehicle encounters dense fog.

時刻的最佳結果狀態

去計算在k時刻的預估值

； （2）利用

時刻最佳結果狀態的雜訊

去計算在k時刻預估值的雜訊

； （3）利用k時刻預估值的雜訊

和k時刻測量值得雜訊r去計算k時刻的卡爾曼增益

； （4）利用k時刻的預估值

、k時刻的測量值

和k時刻的卡爾曼增益

去計算k時刻的最佳結果狀態

； （5）利用k時刻預估值的雜訊

和k時刻的卡爾曼增益

去計算k時刻最佳結果狀態

的誤差

。 Therefore, in the present invention, the Kalman filter unit 12 receives the filtering model data, and filters and outputs the low-noise environment model data. In the embodiment of the present invention, the Kalman filter unit 12 is a Kalman filter, which has the advantages of real-time, rapidity, high efficiency and anti-interference. Wherein, the Kalman filtering unit 12 includes two steps in processing, and mainly calculates an estimated value first, and performs weighted summation on the estimated value and the measured value, so as to obtain the best result state. Further explanation, the Kalman filter unit 12 will mainly carry out five procedures: (1) utilize

best results at all times

To calculate the estimated value at time k

; (2) use

Noise of best results at all times

to calculate the noise of the estimated value at time k

; (3) Use the noise of estimated value at time k

and the measured noise r at time k to calculate the Kalman gain at time k

; (4) Use the estimated value at time k

, measured value at time k

and the Kalman gain at time k

To calculate the best result state at time k

; (5) Use the noise of estimated value at time k

and the Kalman gain at time k

To calculate the best result state at time k

error

.

Therefore, the space model data is improved through the Kalman filter unit 12, and the low-noise environment model data is filtered to output, thereby reducing the interference of environmental noise on the sensing of the optical radar 20. In particular, the Kalman filter unit 12 can be used to filter Remove the noise caused by dense fog, as shown in Figure 5.

Accordingly, the present invention performs two filtering processes with the adjacent point cloud filtering unit 11 and the Kalman filtering unit 12, so as to filter and correct the point cloud model data sensed by the optical radar 20, so that the point cloud model data can be compared with the calculation before filtering. The filtered error value can be significantly reduced by about 10% to 30%, so that the LiDAR system 100 of the present invention can improve the sensing signal in bad weather and environment, and reduce the adverse effect of environmental noise on the optical sensor 20 .

Therefore, the present invention can be applied to self-driving cars, reducing the use of other auxiliary equipment for self-driving cars to improve the accuracy of sensing in harsh environments, so the present invention saves the installation of other detection equipment and reduces the cost of self-driving cars.

Although the present invention has been described in terms of a preferred embodiment, those skilled in the art can make various changes without departing from the spirit and scope of the present invention. The above-mentioned embodiments are only used to illustrate the present invention, and are not intended to limit the scope of the present invention. All modifications or changes that do not violate the spirit of the present invention belong to the patent scope of the present invention.

100:Lidar system 10: Processing module 11: Neighboring point cloud filtering unit 12: Kalman filter unit 20: Optical Radar 30: Trip computer 40:Positioning module 50: Power supply X:X axis Y: Y-axis Z: Z-axis S: Environmental framework P: point cloud C: Sampling circle R: sampling radius D: Center distance

[Fig. 1] is a schematic diagram of the structure of the LiDAR system of the present invention. [Fig. 2] is a three-dimensional schematic diagram of the point cloud model data obtained by the present invention. [Fig. 3] is the top view of the point cloud model data obtained by the present invention, and shows the sampling status. [Fig. 4] is a three-dimensional schematic diagram of the filtered model data after the point cloud model data of the present invention is filtered through the first calculation. [Fig. 5] is a three-dimensional schematic diagram of the low-noise environment model data after the point cloud model data of the present invention is filtered through the second calculation.

100:Lidar system

10: Processing module

11: Adjacent point cloud filter unit

12: Kalman filter unit

20: Optical radar

30: Trip computer

40: Positioning module

50: Power supply

Claims (7)

A lidar system capable of reducing environmental noise, comprising: an optical radar, which obtains a point cloud model data from the detection environment; and A processing module is electrically connected to the optical radar. The processing module includes a neighboring point cloud filtering unit and a Kalman filtering unit. The neighboring point cloud filtering unit receives and processes the point cloud model data for output A filter model data, the Kalman filter unit receives the filter model data, so as to filter and output a low-noise environment model data. The lidar system capable of reducing environmental noise as described in Claim 1, wherein the point cloud model data includes an environment frame with X-axis, Y-axis, and Z-axis and complex point clouds located inside and outside the environment frame , where the point clouds beyond a certain distance outside the environment frame are ignored. The lidar system capable of reducing environmental noise as described in claim 2, wherein the adjacent point cloud filtering unit samples the point clouds with a plurality of sampling circles within and outside the environment frame, and two The adjacent sampling circles partially overlap, and when the number of point clouds obtained within the range of the sampling circles is greater than a critical judgment value, the sampling circles are kept. The lidar system capable of reducing environmental noise as described in Claim 3, wherein each of the sampling circles has a sampling radius, and the sampling radius is 2 cm. The lidar system capable of reducing environmental noise as described in Claim 4, wherein the distance between the centers of two adjacent sampling circles is between 1 cm and 3 cm. The lidar system capable of reducing environmental noise as described in claim 3 or 4, wherein the critical judgment value is 10, and when the number of point clouds within the sampling circle is less than the critical judgment value, the Some point clouds are filtered out as noise. The LiDAR system capable of reducing environmental noise as described in Claim 1 further includes an on-board computer, a positioning module and a power supply, which are respectively electrically connected to the processing module.

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