WO2020215252A1 - 测距装置点云滤噪的方法、测距装置和移动平台 - Google Patents

测距装置点云滤噪的方法、测距装置和移动平台 Download PDF

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Publication number
WO2020215252A1
WO2020215252A1 PCT/CN2019/084095 CN2019084095W WO2020215252A1 WO 2020215252 A1 WO2020215252 A1 WO 2020215252A1 CN 2019084095 W CN2019084095 W CN 2019084095W WO 2020215252 A1 WO2020215252 A1 WO 2020215252A1
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Prior art keywords
point cloud
point
measuring device
distance measuring
cloud point
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PCT/CN2019/084095
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English (en)
French (fr)
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王闯
吴特思
陈涵
洪小平
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深圳市大疆创新科技有限公司
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Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to PCT/CN2019/084095 priority Critical patent/WO2020215252A1/zh
Priority to CN201980009042.2A priority patent/CN112136018A/zh
Publication of WO2020215252A1 publication Critical patent/WO2020215252A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures

Definitions

  • the present invention generally relates to the technical field of distance measuring devices, and more specifically to a method for filtering noise of a point cloud of a distance measuring device, a distance measuring device and a mobile platform.
  • the core function of the ranging device of the scanning laser ranging system is to measure the distance by emitting and receiving laser, but if the laser echo entering the system is reflected by multiple objects close to the distance, it will pass through the photoelectric converter The analog signal generated afterwards will be distorted due to the fusion of the waveforms. At this time, there will be errors in calculating the depth with conventional algorithms, resulting in noise. This kind of noise has existed in the industry for a long time and has a great influence on the performance of the system.
  • the present invention proposes a method for filtering noise of a point cloud of a distance measuring device.
  • one aspect of the present invention provides a method for filtering noise from a point cloud of a distance measuring device, and the method includes:
  • the depth value of the current point cloud point and the depth value of the at least one adjacent point cloud point are input to a predetermined filtering model to determine whether the current point cloud point is a noise point.
  • inputting the depth value of the current point cloud point and the depth value of the at least one adjacent point cloud point into a predetermined filtering model to determine whether the current point cloud point is a noise point specifically includes:
  • the judging whether the change of the depth value of the current point cloud point and the at least one adjacent point cloud point is continuous based on the predetermined filtering model to determine whether the current point cloud point is a noise point specifically includes :
  • the acquiring the threshold data set of the difference between the depth value of the current point cloud point and the at least one adjacent point cloud point specifically includes:
  • the filtering threshold coefficient is obtained based on the emission time interval of the light pulse sequence emitted by the distance measuring device, the scanning angular velocity and the included angle of the distance measuring device, and the included angle is the forward direction of the light pulse sequence emitted by the distance measuring device The angle with the reference plane;
  • the threshold data set is obtained based on the filtering threshold coefficient and the depth value of the neighboring point cloud point before the current point cloud point, wherein the threshold value included in the threshold data set and the phase before the current point cloud point
  • the depth value of the adjacent point cloud point is in direct proportion and inversely proportional to the included angle.
  • the filtering threshold coefficient is a fixed value for the predetermined included angle.
  • the scanning angular velocity of the distance measuring device is non-uniform in the field of view
  • the scanning angular velocity in the entire field of view is a two-dimensional data set related to the scanned zenith angle and azimuth angle
  • the filtering threshold coefficient is a two-dimensional data set.
  • the scanning angular velocity of the ranging device is non-uniform in the field of view
  • the scanning angular velocity in the entire field of view is a two-dimensional data set related to the scanned zenith angle and azimuth angle, so
  • the filtering threshold coefficient is obtained based on the transmission time interval of the pulse signal, the maximum scanning angular velocity of the ranging device, and the included angle.
  • the included angle ranges from 0° to 90°.
  • the threshold data set includes the threshold value of the difference between the depth value of the current point cloud point and its previous neighboring point cloud point, and the depth value of the current point cloud point and the previous point cloud point are determined as noise.
  • the difference between the depth values of one adjacent point cloud point is greater than the threshold value.
  • the filter model includes a filter function.
  • the method further includes:
  • the method further includes:
  • the non-noise point cloud points collected by the distance measuring device are output as images or videos.
  • the filtering of point cloud points is performed during the process of collecting point cloud points by the distance measuring device.
  • the adjacent point cloud point is a point cloud point collected before the current point cloud point.
  • the method further includes:
  • acquiring the depth value of the current point cloud point collected by the distance measuring device is specifically:
  • the time difference is received, and the depth value of the current point cloud point is calculated.
  • the distance measuring device includes one or more processors that work together or separately, and the processors are used to:
  • the depth value of the current point cloud point and the depth value of the at least one adjacent point cloud point are input to a predetermined filtering model to determine whether the current point cloud point is a noise point.
  • the processor is specifically configured to:
  • the processor is more specifically used for:
  • the processor is further configured to:
  • the filtering threshold coefficient is obtained based on the emission time interval of the light pulse sequence emitted by the distance measuring device, the scanning angular velocity and the included angle of the distance measuring device, and the included angle is the forward direction of the light pulse sequence emitted by the distance measuring device The angle with the reference plane;
  • the threshold data set is obtained based on the filtering threshold coefficient and the depth value of the neighboring point cloud point before the current point cloud point, wherein the threshold value included in the threshold data set and the phase before the current point cloud point
  • the depth value of the adjacent point cloud point is in direct proportion and inversely proportional to the included angle.
  • the filtering threshold coefficient is a fixed value for the predetermined included angle.
  • the scanning angular velocity of the distance measuring device is non-uniform in the field of view
  • the scanning angular velocity in the entire field of view is a two-dimensional data set related to the scanned zenith angle and azimuth angle
  • the filtering threshold coefficient is a two-dimensional data set.
  • the scanning angular velocity of the ranging device is non-uniform in the field of view
  • the scanning angular velocity in the entire field of view is a two-dimensional data set related to the scanned zenith angle and azimuth angle, so
  • the filtering threshold coefficient is obtained based on the transmission time interval of the pulse signal, the maximum scanning angular velocity of the ranging device, and the included angle.
  • the included angle ranges from 0° to 90°.
  • the threshold data set includes the threshold value of the difference between the depth value of the current point cloud point and its previous neighboring point cloud point, and the depth value of the current point cloud point and the previous point cloud point are determined as noise.
  • the difference between the depth values of one adjacent point cloud point is greater than the threshold value.
  • the filter model includes a filter function.
  • the processor is further configured to:
  • the distance measuring device further includes:
  • the output device is used to output the non-noise point cloud points collected by the distance measuring device as an image or video.
  • the filtering out of point cloud points is performed during the process of collecting point cloud points by the distance measuring device.
  • the adjacent point cloud point is a point cloud point collected by the distance measuring device before the current point cloud point.
  • the processor is further configured to:
  • the distance measuring device further includes:
  • Transmitter used to emit light pulse sequence
  • the receiving circuit is used to convert the received back light reflected by the object into an electrical signal output
  • a sampling circuit configured to sample the output electrical signal to measure the time difference between the transmission and reception of the optical pulse sequence
  • An arithmetic circuit for receiving the time difference and calculating the depth value of the current point cloud point.
  • the processor includes a field programmable gate array.
  • Another aspect of the present invention provides a computer storage medium on which a computer program is stored, and when the program is executed by a processor, the method for filtering noise of the point cloud of the aforementioned distance measuring device is realized.
  • a mobile platform which includes:
  • the platform body, the distance measuring device is installed on the platform body.
  • the mobile platform includes a drone, a robot, a vehicle or a boat.
  • the method of the embodiment of the present invention obtains the depth value of the current point cloud point collected by the distance measuring device and the depth value of at least one adjacent point cloud point adjacent to the current point cloud point;
  • the depth value of the cloud point and the depth value of the at least one adjacent point cloud point are input to a predetermined filtering model to determine whether the current point cloud point is a noise point, and then the point cloud point determined as a noise point is filtered out or Marking can filter a variety of noises including waveform fusion noise, which significantly reduces the "flying line" noise and other abnormal noises between similar objects in the point cloud before and after, and significantly optimizes and improves the quality of the point cloud;
  • the method of the embodiment of the present invention can be implemented with only a small amount of calculation, the processing result has no delay and the accuracy is high, and the process of noise filtering is almost completed in real time along with the point cloud collection.
  • Figure 1 shows a schematic diagram of the principle of generating multiple echoes in a laser ranging system in an embodiment of the present invention
  • FIG. 2 shows a schematic diagram of the principle of the generation of noise points in the waveform fusion of the laser ranging system in an embodiment of the present invention
  • Figure 3 shows a schematic diagram of waveform fusion noise in an embodiment of the present invention
  • Fig. 4 shows a schematic diagram of waveform fusion noise in another embodiment of the present invention.
  • FIG. 5 shows a schematic flowchart of a method for filtering noise from a point cloud of a distance measuring device in an embodiment of the present invention
  • Fig. 6 shows a schematic diagram of marked noise points after applying a point cloud noise filtering method in an embodiment of the present invention
  • FIG. 7 shows a schematic diagram of comparison of point cloud images before and after applying a point cloud noise filtering method in an embodiment of the present invention
  • FIG. 8 shows a schematic structural diagram of a distance measuring device in an embodiment of the present invention.
  • Fig. 9 shows a schematic diagram of a distance measuring device in an embodiment of the present invention.
  • the distance measuring device of the laser distance measuring system is a perception system that uses laser to scan and measure distances to obtain three-dimensional information in the surrounding scene.
  • the basic principle is to actively emit laser pulses to the detected object, capture the laser echo signal and calculate the distance of the measured object according to the time difference between laser emission and reception; obtain the angle of the measured object based on the known emission direction of the laser Information:
  • point cloud Through high-frequency transmission and reception, a large amount of distance and angle information of detection points can be obtained, which is called point cloud. Based on the point cloud, the 3D information of the surrounding scene can be reconstructed.
  • the laser emitted by the laser ranging system usually has a certain divergence angle ⁇ ( ⁇ is a set of parameters, which is related to the design parameters of the laser), which means that from the launch point, the area of the spot will continue to increase as the distance increases . Assuming that the distance from the launch point is d1, the laser spot area is Sd1. Due to the complexity of the actual environment, the spot Sd1 may all fall on one object, or only a part of it may fall on an object A, and the other part may fall far away. On another object B with a distance of d2, as shown in Figure 1.
  • the receiving system will obtain two independent laser echoes; if the distance between d1 and d2 is relatively close, the two The secondary laser echoes will gradually merge; when the distance between d1 and d2 is less than the limit distance dmin, the two laser echoes will be completely merged into one waveform on the analog signal generated by the photoelectric converter.
  • the algorithm of the laser ranging system to calculate the distance based on the laser flight time, unless this special waveform is accurately identified and specially processed, it is likely to calculate an error distance that is neither d1 nor d2, which is called noise.
  • noise there are also abnormal points caused by other reasons, which can also be summarized as noise and filtered out by the present invention.
  • Figures 3 and 4 show two point cloud images with waveform fusion noise.
  • a and B are pillars and walls, respectively.
  • the waveform fusion phenomenon produces noise in the C area.
  • the arrow points to the blank area between the car and the guardrail, but due to the close distance, some noise is also generated.
  • an embodiment of the present invention provides a method for filtering noise from a point cloud of a ranging device.
  • the method includes the following steps: Step S501, acquiring the current point collected by the ranging device The depth value of the cloud point, and the depth value of at least one adjacent point cloud point adjacent to the current point cloud point; step S502, the depth value of the current point cloud point and the at least one adjacent point cloud The depth value of the point is input to a predetermined filtering model to determine whether the current point cloud point is a noise point.
  • the above method requires less calculation and no delay in processing results. It can filter the current point cloud points in real time and has high accuracy. It can filter a variety of noise points including waveform fusion noise, and it can filter the points of the ranging device. Cloud quality has improved significantly.
  • step S501 the depth value of the current point cloud point collected by the distance measuring device and the depth value of at least one adjacent point cloud point adjacent to the current point cloud point are acquired .
  • obtaining the depth value of the current point cloud point collected by the distance measuring device specifically includes: transmitting a light pulse sequence; converting the received back light reflected by the object into an electrical signal output; The signal is sampled to measure the time difference between the transmission and reception of the light pulse sequence; the time difference is received, and the depth value of the current point cloud point is calculated.
  • This method can obtain the depth value of all the point cloud points collected by the ranging device.
  • the adjacent point cloud point adjacent to the current point cloud point refers to the point cloud point collected by the distance measuring device within a specific time period before or after the current point cloud point collected by the distance measuring device Point cloud point.
  • the adjacent point cloud points are point cloud points collected by the distance measuring device before the current point cloud point. Based on the adjacent point cloud points, it is possible to filter whether the current point cloud points are noise points in real time.
  • step S502 the depth value of the current point cloud point and the depth value of the at least one adjacent point cloud point are input to a predetermined filtering model to determine whether the current point cloud point is a noise.
  • inputting the depth value of the current point cloud point and the depth value of the at least one adjacent point cloud point into a predetermined filtering model to determine whether the current point cloud point is a noise point specifically includes: Based on the predetermined filtering model, it is determined whether the current point cloud point and the depth value of the at least one neighboring point cloud point change continuously, so as to determine whether the current point cloud point is a noise point.
  • the method of judging whether the change of the depth value of the current point cloud point and the at least one adjacent point cloud point is continuous, for example, the relative relationship of the depth values of multiple points can be used for analysis and judgment, for example, Take four adjacent point cloud points as an example. Their depth values are d1, d2, d3, and d4, respectively. If the difference between the depth values of d2 and d1, d3 and d2, d4 and d3 continuously changes according to a predetermined rule, and If they are all within the depth difference threshold interval, it is considered that the data of the above-mentioned point cloud points are normal, and they are not noise points.
  • each point cloud point in the point cloud data can be filtered to filter the point cloud data at the distance measuring device, or it can be random. Every time a point cloud point is collected by the ranging device, the point cloud point is filtered according to the filtering method in the embodiment of this application. The process of noise filtering is almost completed in real time with the point cloud collection, and only less The amount of calculation can be realized, and the data delay is extremely small.
  • the determining whether the current point cloud point and the depth value of the at least one neighboring point cloud point change continuously based on the predetermined filtering model, to determine whether the current point cloud point is a noise point specifically The method includes: obtaining a threshold data set of the difference between the depth value of the current point cloud point and the at least one adjacent point cloud point; based on the difference between the current point cloud point and the depth value of the at least one adjacent point cloud point Whether the difference is within the threshold data set, determine whether the current point cloud point is a noise point, wherein the current point cloud point whose depth value difference is within the threshold data set is not a noise point, and the depth value difference exceeds the threshold value data The current point cloud point of the set is a noise point.
  • the current point cloud point is determined to be noise
  • the difference between the depth value of a point and the depth value of its previous neighboring point cloud point is greater than the threshold, and it may be collected after the actual depth value of the current point cloud point and the actual depth value of the previous neighboring point cloud point are collected, Based on the difference between the two actual depth values and the threshold value, if the difference between the actual depth values is less than or equal to the threshold value, the current point cloud point is not a noise, and if the difference between the actual depth values is greater than the threshold value, the current point cloud point Is noise.
  • the above-mentioned filtering is real-time filtering, which can be realized with only a small amount of calculation, and the data delay is extremely small. The process of noise filtering is almost completed in real time with the point cloud collection.
  • the obtaining the threshold data set of the difference between the depth value of the current point cloud point and the at least one adjacent point cloud point specifically includes: The transmission time interval of the light pulse sequence emitted by the distance measuring device, the scanning angular velocity and the included angle of the distance measuring device obtain a filter threshold coefficient, and the included angle is the forward direction of the light pulse sequence emitted by the distance measuring device and The included angle of the reference surface; the threshold data set is obtained based on the filtering threshold coefficient and the depth value of the adjacent point cloud point before the current point cloud point, wherein the threshold value included in the threshold data set and the current The depth value of the adjacent point cloud point before the point cloud point is directly proportional and inversely proportional to the included angle.
  • the included angle ⁇ between the forward direction of the light pulse sequence emitted by the distance measuring device and the reference plane can be reasonably adjusted according to actual filtering requirements.
  • the included angle can range from 0° to 90°, and more Further, the range of the included angle may also be 0-80°, or may also be 0-30°, 0-40°, 0-50°, etc.
  • denoising effects of different intensities can be obtained by adjusting the included angle ⁇ .
  • ⁇ approaches 90° almost all non-normal incidence point clouds will be filtered out according to the solution in the embodiment of the present invention; when ⁇ approaches 0°, almost no point cloud will be filtered according to the solution in the embodiment of the present invention Any point cloud. Adjust ⁇ to get different degrees of filtering of waveform fusion noise or other abnormal noise.
  • different filtering threshold coefficients can be used.
  • the threshold of the difference between the depth value of each current point cloud point and the adjacent point cloud point before it can be the difference between the filtering threshold coefficient and the adjacent point cloud point before the current point cloud point The product of the difference in depth values.
  • the current point cloud point can be any one of the multiple point cloud points, and each different current point Cloud points may correspond to different thresholds of the difference in depth values, or when some of the adjacent point cloud points before the current point cloud point have the same depth value and the filter threshold coefficient is also a fixed value, the current point cloud point of this part is also It can correspond to the same threshold of the difference of depth values.
  • the scanning angular velocity of the distance measuring device is non-uniform in the field of view
  • the scanning angular velocity in the entire field of view is a two-dimensional data set related to the scanned zenith angle and azimuth angle
  • the filtering threshold coefficient is a two-dimensional data set.
  • a threshold data set is obtained based on the two-dimensional data set, so as to filter the point cloud.
  • the scanning angular velocity of the distance measuring device is non-uniform in the field of view
  • the scanning angular velocity in the entire field of view is a two-dimensional data set related to the scanned zenith angle and azimuth angle
  • the filtering threshold coefficient is obtained based on the transmission time interval of the pulse signal, the maximum scanning angular velocity of the ranging device and the included angle
  • the filtering threshold coefficient is applied to obtain the threshold data set, and then applied to the filtering of the current point cloud point.
  • the distance measuring device such as a laser distance measuring system
  • the distance d is d
  • the scanning angular velocity of the laser is ⁇ . If the scanning angular velocity of the distance measuring device is uniform within the field of view, the light pulse sequence (for example, laser) emitted by the distance measuring device scans on plane A
  • the speed is:
  • the distance difference between adjacent point cloud points measured by the ranging device is approximately:
  • the distance difference between adjacent point cloud points measured by the distance measuring device is approximately:
  • ⁇ and t are the fixed values related to the design of the distance measuring device
  • d is the actual distance (ie depth value) of the current point cloud measured by the distance measuring device
  • ⁇ is the design parameter defined in the present invention .
  • ⁇ d' is directly proportional to d and negatively related to ⁇ .
  • the proportional coefficient that is, the filtering threshold coefficient
  • Point cloud point number depth Point difference between adjacent point clouds Threshold 1 d1 / / 2 d2 d2-d1 K*d1 3 d3 d3-d2 K*d2 4 d4 d4-d3 K*d3 5 d5 d5-d4 K*d4
  • the current point cloud point with sequence number 2 if the actual depth value d2 of the current point cloud point with the sequence number 2 and the actual depth value d1 of the previous adjacent point cloud point are greater than the filter coefficient K Multiplying with d1, the current point cloud point with sequence number 2 is considered to be a noise, and the noise is marked and processed; otherwise, the current point cloud point with sequence number 2 is considered to be a normal point instead of a noise and directly output.
  • the above-mentioned filtering is performed on each current point cloud point collected by the ranging device in turn, until all noise points (also called noise) are identified. As shown in FIG. 6, the points in the area pointed by the arrow in FIG. 6 are the noise points to be filtered marked by the present invention, and the other areas are normal points.
  • the filter model includes a filter function, such as a linear filter function, a Gaussian filter function, a spatial frequency distribution filter function, and so on.
  • the filter function that meets the predetermined conditions is used as the judgment condition to identify abnormally fluctuating noise.
  • the current point cloud point determined as noise by the above method can be processed according to the following method.
  • the current point cloud point is filtered out, for example, Set the depth value of the current point cloud point determined as a noise point to 0, that is, direct filtering.
  • the point cloud point filtering is performed in the process of collecting point cloud points by the distance measuring device, In this way, the ranging device can directly output point cloud data with almost no noise.
  • the current point cloud point determined as a noise point is marked, and the depth value and/or reflectivity value of the marked current point cloud point is assigned as a special value or the current point is directly assigned Cloud point filtering, this special value is different from the depth value or reflectivity of other non-noise point cloud points, and then the upper layer algorithm (that is, the upper layer application) determines the processing method, such as the object segmentation recognition algorithm, three-dimensional reconstruction Algorithm etc.
  • the processed value is only used when sending data to the upper application.
  • the original data before filtering is always retained as a reference for the next filtering algorithm.
  • the method in the embodiment significantly reduces the "flying line" noise and other points between the similar objects in the point cloud.
  • Abnormal noise points significantly optimize and improve the quality of point clouds.
  • the method of the embodiment of the present invention obtains the depth value of the current point cloud point collected by the distance measuring device and the depth value of at least one adjacent point cloud point adjacent to the current point cloud point;
  • the depth value of the current point cloud point and the depth value of the at least one adjacent point cloud point are input to a predetermined filtering model to determine whether the current point cloud point is a noise point, and then the point cloud point determined as a noise point is performed
  • Filtering or marking can filter a variety of noises including waveform fusion noise, which significantly reduces the "flying line” noise and other abnormal noises between similar objects in the point cloud before and after, and significantly optimizes the quality of the point cloud And improvement; and, the method of the embodiment of the present invention can be realized with a small amount of calculation, the processing result has no delay and the accuracy is high, and the process of noise filtering is almost completed in real time with the point cloud collection.
  • the distance measuring device includes a lidar.
  • the distance measuring device is only an example.
  • Distance devices can also be applied to this application.
  • the distance measuring device is used to implement the point cloud noise filtering method in the foregoing embodiment.
  • the distance measuring device may be electronic equipment such as lidar and laser distance measuring equipment.
  • the distance measuring device is used to sense external environmental information, for example, distance information, orientation information, reflection intensity information, speed information, etc. of environmental targets.
  • the distance measuring device can detect the distance from the probe to the distance measuring device by measuring the time of light propagation between the distance measuring device and the probe, that is, the time-of-flight (TOF).
  • the ranging device can also detect the distance from the detected object to the ranging device through other technologies, such as a ranging method based on phase shift measurement, or a ranging method based on frequency shift measurement. There is no restriction.
  • the distance measuring device may include a transmitting module, a receiving module, and a temperature control system.
  • the transmitting module is used to emit light pulses;
  • the receiving module is used to receive at least part of the light pulses reflected by the object, and according to The received at least part of the light pulse determines the distance of the object relative to the distance measuring device.
  • the transmitting module includes a transmitting circuit 110; the receiving module includes a receiving circuit 120, a sampling circuit 130 and an arithmetic circuit 140.
  • the transmitting circuit 110 may emit a light pulse sequence (for example, a laser pulse sequence).
  • the receiving circuit 120 may receive the light pulse sequence reflected by the object to be detected, and perform photoelectric conversion on the light pulse sequence to obtain an electrical signal. After processing the electrical signal, it may be output to the sampling circuit 130.
  • the sampling circuit 130 may sample the electrical signal to obtain the sampling result.
  • the arithmetic circuit 140 may determine the distance between the distance measuring device 100 and the detected object based on the sampling result of the sampling circuit 130.
  • the distance measuring device 100 may further include a control circuit 150, which can control other circuits, for example, can control the working time of each circuit and/or set parameters for each circuit.
  • a control circuit 150 can control other circuits, for example, can control the working time of each circuit and/or set parameters for each circuit.
  • the distance measuring device shown in FIG. 8 includes a transmitting circuit, a receiving circuit, a sampling circuit, and an arithmetic circuit for emitting a beam for detection
  • the embodiment of the present application is not limited to this, the transmitting circuit
  • the number of any one of the receiving circuit, the sampling circuit, and the arithmetic circuit can also be at least two, which are used to emit at least two light beams in the same direction or in different directions; wherein, the at least two light paths can be simultaneous Shooting can also be shooting at different times.
  • the light-emitting chips in the at least two transmitting circuits are packaged in the same module.
  • each emitting circuit includes a laser emitting chip, and the dies in the laser emitting chips in the at least two emitting circuits are packaged together and housed in the same packaging space.
  • the distance measuring device 100 may also include a scanning module for changing the propagation direction of at least one light pulse sequence (for example, a laser pulse sequence) emitted by the transmitting circuit, so as to control the field of view.
  • a scanning module for changing the propagation direction of at least one light pulse sequence (for example, a laser pulse sequence) emitted by the transmitting circuit, so as to control the field of view.
  • the scanning area of the scanning module in the field of view of the distance measuring device increases with the accumulation of time.
  • the module including the transmitting circuit 110, the receiving circuit 120, the sampling circuit 130, and the arithmetic circuit 140, or the module including the transmitting circuit 110, the receiving circuit 120, the sampling circuit 130, the arithmetic circuit 140, and the control circuit 150 may be referred to as the measuring circuit.
  • Distance module the distance measurement module can be independent of other modules, for example, scanning module.
  • a coaxial optical path can be used in the distance measuring device, that is, the light beam emitted from the distance measuring device and the reflected light beam share at least part of the optical path in the distance measuring device.
  • the distance measuring device may also adopt an off-axis optical path, that is, the light beam emitted by the distance measuring device and the reflected light beam are respectively transmitted along different optical paths in the distance measuring device.
  • Fig. 9 shows a schematic diagram of an embodiment in which the distance measuring device of the present invention adopts a coaxial optical path.
  • the ranging device 200 includes a ranging module 210, which includes a transmitter 203 (which may include the above-mentioned transmitting circuit), a collimating element 204, a detector 205 (which may include the above-mentioned receiving circuit, sampling circuit, and arithmetic circuit) and Light path changing element 206.
  • the ranging module 210 is used to emit a light beam, receive the return light, and convert the return light into an electrical signal.
  • the transmitter 203 can be used to emit a light pulse sequence.
  • the transmitter 203 may emit a sequence of laser pulses.
  • the laser beam emitted by the transmitter 203 is a narrow-bandwidth beam with a wavelength outside the visible light range.
  • the collimating element 204 is arranged on the exit light path of the emitter, and is used to collimate the light beam emitted from the emitter 203, and collimate the light beam emitted from the emitter 203 into parallel light and output to the scanning module.
  • the collimating element is also used to condense at least a part of the return light reflected by the probe.
  • the collimating element 204 may be a collimating lens or other elements capable of collimating light beams.
  • the transmitting light path and the receiving light path in the distance measuring device are combined before the collimating element 204 through the light path changing element 206, so that the transmitting light path and the receiving light path can share the same collimating element, so that the light path More compact.
  • the emitter 203 and the detector 205 use respective collimating elements, and the optical path changing element 206 is arranged on the optical path behind the collimating element.
  • the optical path changing element can use a small area mirror to The transmitting light path and the receiving light path are combined.
  • the light path changing element may also use a reflector with a through hole, where the through hole is used to transmit the emitted light of the emitter 203 and the reflector is used to reflect the return light to the detector 205. In this way, the shielding of the back light by the bracket of the small mirror in the case of using the small mirror can be reduced.
  • the optical path changing element is deviated from the optical axis of the collimating element 204. In some other implementation manners, the optical path changing element may also be located on the optical axis of the collimating element 204.
  • the distance measuring device 200 further includes a scanning module 202.
  • the scanning module 202 is placed on the exit light path of the distance measuring module 210.
  • the scanning module 202 is used to change the transmission direction of the collimated beam 219 emitted by the collimating element 204 and project it to the external environment, and project the return light to the collimating element 204 .
  • the returned light is collected on the detector 205 via the collimating element 204.
  • the scanning module 202 may include at least one optical element for changing the propagation path of the light beam, wherein the optical element may change the propagation path of the light beam by reflecting, refracting, or diffracting the light beam, for example,
  • the optical element includes at least one light refraction element having a non-parallel exit surface and an entrance surface.
  • the scanning module 202 includes a lens, a mirror, a prism, a galvanometer, a grating, a liquid crystal, an optical phased array (Optical Phased Array), or any combination of the foregoing optical elements.
  • at least part of the optical elements are moving.
  • a driving module is used to drive the at least part of the optical elements to move.
  • the moving optical elements can reflect, refract, or diffract the light beam to different directions at different times.
  • the multiple optical elements of the scanning module 202 may rotate or vibrate around a common axis 209, and each rotating or vibrating optical element is used to continuously change the propagation direction of the incident light beam.
  • the multiple optical elements of the scanning module 202 may rotate at different speeds or vibrate at different speeds.
  • at least part of the optical elements of the scanning module 202 may rotate at substantially the same rotation speed.
  • the multiple optical elements of the scanning module may also be rotated around different axes.
  • the multiple optical elements of the scanning module may also rotate in the same direction or in different directions; or vibrate in the same direction, or vibrate in different directions, which is not limited herein.
  • the scanning module 202 includes a first optical element 214 and a driver 216 connected to the first optical element 214.
  • the driver 216 is used to drive the first optical element 214 to rotate around the rotation axis 209 to change the first optical element 214.
  • the direction of the beam 219 is collimated.
  • the first optical element 214 projects the collimated light beam 219 to different directions.
  • the angle between the direction of the collimated beam 219 changed by the first optical element and the rotation axis 209 changes as the first optical element 214 rotates.
  • the first optical element 214 includes a pair of opposed non-parallel surfaces through which the collimated light beam 219 passes.
  • the first optical element 214 includes a prism whose thickness varies in at least one radial direction.
  • the first optical element 214 includes a wedge prism, and the collimated beam 219 is refracted.
  • the scanning module 202 further includes a second optical element 215, the second optical element 215 rotates around the rotation axis 209, and the rotation speed of the second optical element 215 is different from the rotation speed of the first optical element 214.
  • the second optical element 215 is used to change the direction of the light beam projected by the first optical element 214.
  • the second optical element 215 is connected to another driver 217, and the driver 217 drives the second optical element 215 to rotate.
  • the first optical element 214 and the second optical element 215 can be driven by the same or different drivers, so that the rotation speed and/or rotation of the first optical element 214 and the second optical element 215 are different, so as to project the collimated light beam 219 to the outside space.
  • the controller 218 controls the drivers 216 and 217 to drive the first optical element 214 and the second optical element 215, respectively.
  • the rotational speeds of the first optical element 214 and the second optical element 215 may be determined according to the area and pattern expected to be scanned in actual applications.
  • the drivers 216 and 217 may include motors or other drivers.
  • the second optical element 215 includes a pair of opposite non-parallel surfaces through which the light beam passes. In one embodiment, the second optical element 215 includes a prism whose thickness varies in at least one radial direction. In one embodiment, the second optical element 215 includes a wedge prism.
  • the scanning module 202 further includes a third optical element (not shown) and a driver for driving the third optical element to move.
  • the third optical element includes a pair of opposite non-parallel surfaces, and the light beam passes through the pair of surfaces.
  • the third optical element includes a prism whose thickness varies in at least one radial direction.
  • the third optical element includes a wedge prism. At least two of the first, second, and third optical elements rotate at different rotation speeds and/or rotation directions.
  • the scanning module includes two or three light refraction elements arranged in sequence on the exit light path of the light pulse sequence.
  • at least two of the light refraction elements in the scanning module rotate during the scanning process to change the direction of the light pulse sequence.
  • the scanning module has different scanning paths at at least some different moments.
  • the rotation of each optical element in the scanning module 202 can project light to different directions, for example, the direction of the projected light 211 and the direction 213, so that the distance measuring device 200 is Space to scan.
  • the light 211 projected by the scanning module 202 hits the detection object 201, a part of the light is reflected by the detection object 201 to the distance measuring device 200 in a direction opposite to the projected light 211.
  • the return light 212 reflected by the probe 201 is incident on the collimating element 204 after passing through the scanning module 202.
  • the detector 205 and the transmitter 203 are placed on the same side of the collimating element 204, and the detector 205 is used to convert at least part of the return light passing through the collimating element 204 into an electrical signal.
  • an anti-reflection film is plated on each optical element.
  • the thickness of the antireflection coating is equal to or close to the wavelength of the light beam emitted by the emitter 203, which can increase the intensity of the transmitted light beam.
  • a filter layer is plated on the surface of an element located on the beam propagation path in the distance measuring device, or a filter is provided on the beam propagation path for transmitting at least the wavelength band of the beam emitted by the transmitter, Reflect other bands to reduce the noise caused by ambient light to the receiver.
  • the transmitter 203 may include a laser diode through which nanosecond laser pulses are emitted.
  • the laser pulse receiving time can be determined, for example, the laser pulse receiving time can be determined by detecting the rising edge time and/or the falling edge time of the electrical signal pulse.
  • the distance measuring device 200 can calculate the TOF using the pulse receiving time information and the pulse sending time information, so as to determine the distance between the probe 201 and the distance measuring device 200.
  • the distance and orientation detected by the distance measuring device 200 can be used for remote sensing, obstacle avoidance, surveying and mapping, modeling, navigation, etc.
  • the distance measuring device further includes one or more processors, one or more storage devices, and one or more processors work together or individually.
  • the distance measuring device may further include at least one of an input device (not shown), an output device (not shown), and an image sensor (not shown), and these components are connected through a bus system and/or other forms The mechanisms (not shown) are interconnected.
  • the storage device that is, the memory used for storing processor-executable instructions, is used, for example, for the existence of corresponding steps and program instructions in the method for implementing point cloud noise filtering of the distance measuring device according to the embodiment of the present invention. It may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory.
  • the volatile memory may include random access memory (RAM) and/or cache memory (cache), for example.
  • the non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.
  • the input device may be a device used by a user to input instructions, and may include one or more of a keyboard, a mouse, a microphone, and a touch screen.
  • the output device can output various information (such as images or sounds) to the outside (such as a user), and can include one or more of a display, a speaker, etc., for collecting non-noise points collected by the distance measuring device.
  • the cloud point is output as an image or video.
  • the communication interface (not shown) is used for communication between the ranging device and other devices, including wired or wireless communication.
  • the ranging device can access a wireless network based on a communication standard, such as WiFi, 2G, 3G, 4G, 5G or a combination thereof.
  • the communication interface receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel.
  • the communication interface further includes a near field communication (NFC) module to facilitate short-range communication.
  • the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.
  • RFID radio frequency identification
  • IrDA infrared data association
  • UWB ultra-wideband
  • Bluetooth Bluetooth
  • the processor may be a central processing unit (CPU), an image processing unit (GPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other forms of data processing capabilities and/or instruction execution capabilities Processing unit, and can control other components in the ranging device to perform desired functions.
  • the processor can execute the instructions stored in the storage device to execute the method for filtering noise from a point cloud of a distance measuring device described herein.
  • the processor can include one or more embedded processors, processor cores, microprocessors, logic circuits, hardware finite state machines (FSM), digital signal processors (DSP), or combinations thereof.
  • the processor includes a field programmable gate array (FPGA), wherein the arithmetic circuit of the distance measuring device may be a part of the field programmable gate array (FPGA).
  • the distance measuring device of the embodiment of the present invention can be applied to a mobile platform, and the distance measuring device can be installed on the platform body of the mobile platform.
  • a mobile platform with a distance measuring device can measure the external environment, for example, measuring the distance between the mobile platform and obstacles for obstacle avoidance and other purposes, and for two-dimensional or three-dimensional mapping of the external environment.
  • the mobile platform includes at least one of an unmanned aerial vehicle, a car, a remote control car, a robot, a boat, and a camera.
  • the ranging device is applied to an unmanned aerial vehicle
  • the platform body is the fuselage of the unmanned aerial vehicle.
  • the distance measuring device is applied to a car
  • the platform body is the body of the car.
  • the car can be a self-driving car or a semi-automatic driving car, and there is no restriction here.
  • the platform body is the body of the remote control car.
  • the platform body is a robot.
  • the distance measuring device is applied to a camera, the platform body is the camera itself.
  • both the distance measuring device and the mobile platform have the same advantages as the aforementioned method.
  • the embodiment of the present invention also provides a computer storage medium on which a computer program is stored.
  • One or more computer program instructions can be stored on the computer-readable storage medium, and the processor can run the program instructions stored in the storage device to implement the steps (implemented by the processor) in the embodiments of the present invention described herein.
  • Functions and/or other desired functions for example, to perform the corresponding steps of the method for filtering noise from a point cloud of a distance measuring device according to an embodiment of the present invention, and various application programs and various types of applications may be stored in the computer-readable storage medium.
  • Data such as various data used and/or generated by the application.
  • the computer storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk Read-only memory (CD-ROM), USB memory, or any combination of the above storage media.
  • the computer-readable storage medium may be any combination of one or more computer-readable storage media.
  • a computer-readable storage medium contains computer-readable program code for converting point cloud data into a two-dimensional image, and/or computer-readable program code for three-dimensional reconstruction of point cloud data, which is readable by another computer
  • the storage medium contains computer-readable program codes and the like for object segmentation of the two-dimensional image.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are merely illustrative, for example, the division of the units is only a logical function division, and there may be other divisions in actual implementation, for example, multiple units or components may be combined or It can be integrated into another device, or some features can be ignored or not implemented.
  • the various component embodiments of the present invention may be implemented by hardware, or by software modules running on one or more processors, or by their combination.
  • a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all of the functions of some modules according to the embodiments of the present invention.
  • DSP digital signal processor
  • the present invention can also be implemented as a device program (for example, a computer program and a computer program product) for executing part or all of the methods described herein.
  • Such a program for realizing the present invention may be stored on a computer-readable medium, or may have the form of one or more signals. Such signals can be downloaded from Internet websites, or provided on carrier signals, or provided in any other form.

Abstract

本发明提供一种测距装置点云滤噪的方法、测距装置和移动平台，所述方法包括：获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值(S501)；将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点(S502)。上述方法所需的运算量少，处理结果无延时能够实时的对当前点云点进行过滤且准确度高，可对包括波形融合噪点在内的多种噪点进行过滤，对测距装置的点云质量有显著的提升。

Description

测距装置点云滤噪的方法、测距装置和移动平台
说明书
技术领域
本发明总地涉及测距装置技术领域，更具体地涉及一种测距装置点云滤噪的方法、测距装置和移动平台。
背景技术
例如扫描式激光测距系统的测距装置的核心功能是通过发射和接收激光进行测距的，但如果进入系统的激光回波是由多个距离接近的物体反射回来的，则经过光电转换器之后产生的模拟信号就会因波形融合而产生畸变，此时用常规算法计算深度就会出现误差，从而产生噪点。这种噪点在业界长期存在，且对系统的使用性能有较大影响。
因此，鉴于上述问题的存在，本发明提出一种测距装置点云滤噪的方法。
发明内容
为了解决上述问题中的至少一个而提出了本发明。具体地，本发明一方面提供一种测距装置点云滤噪的方法，所述方法包括：
获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值；
将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点。
示例性地，将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点，具体包括：
基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点。
示例性地，所述基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点，具体包括：
获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集；
基于所述当前点云点和所述至少一个相邻点云点的深度值之差是否在所述阈值数据集内，确定所述当前点云点是否为噪点。
示例性地，所述获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集，具体包括：
基于所述测距装置发射的光脉冲序列的发射时间间隔、所述测距装置的扫描角速度和夹角获得过滤阈值系数，所述夹角为所述测距装置发射的光脉冲序列的前进方向与参考面的夹角；
基于所述过滤阈值系数和所述当前点云点之前的相邻点云点的深度值获得所述阈值数据集，其中，所述阈值数据集包括的阈值和所述当前点云点之前的相邻点云点的深度值呈正比，与所述夹角呈反比。
示例性地，若所述测距装置的扫描角速度在视场角内是均匀的，则对于预定的所述夹角，所述过滤阈值系数为固定值。
示例性地，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，则对于预定的所述夹角，所述过滤阈值系数为二维数据集。
示例性地，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，所述过滤阈值系数为基于所述脉冲信号的发射时间间隔、所述测距装置的最大扫描角速度和所述夹角而获得。
示例性地，所述夹角的范围为0～90°。
示例性地，所述阈值数据集包括所述当前点云点和其前一个相邻点云点的深度值之差的阈值，则确定为噪点的所述当前点云点的深度值和其前一个相邻点云点的深度值之差大于所述阈值。
示例性地，所述滤波模型包括滤波函数。
示例性地，所述方法还包括：
当确定所述当前点云点为噪点时，将所述当前点云点滤除；或者，
对确定为噪点的所述当前点云点进行标记。
示例性地，所述方法还包括：
将所述测距装置采集的非噪点的点云点输出为图像或视频。
示例性地，所述将点云点滤除是在所述测距装置采集点云点的过程中执 行的。
示例性地，所述相邻点云点为在所述当前点云点之前采集的点云点。
示例性地，所述方法还包括：
将被标记的所述当前点云点的深度值和/或反射率值赋为特殊值。
示例性地，获取所述测距装置采集的当前点云点的深度值，具体为：
发射光脉冲序列；
将接收到的经物体反射的回光转换为电信号输出；
对输出的所述电信号进行采样，以测量所述光脉冲序列从发射到接收之间的时间差；
接收所述时间差，计算所述当前点云点的深度值。
本发明再一方面提供一种测距装置，所述测距装置包括一个或多个处理器，共同地或单独地工作，所述处理器用于：
获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值；
将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点。
示例性地，所述处理器具体用于：
基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点。
示例性地，所述处理器更具体地用于：
获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集；
基于所述当前点云点和所述至少一个相邻点云点的深度值之差是否在所述阈值数据集内，确定所述当前点云点是否为噪点。
示例性地，所述处理器还用于：
基于所述测距装置发射的光脉冲序列的发射时间间隔、所述测距装置的扫描角速度和夹角获得过滤阈值系数，所述夹角为所述测距装置发射的光脉冲序列的前进方向与参考面的夹角；
基于所述过滤阈值系数和所述当前点云点之前的相邻点云点的深度值获得所述阈值数据集，其中，所述阈值数据集包括的阈值和所述当前点云点之 前的相邻点云点的深度值呈正比，与所述夹角呈反比。
示例性地，若所述测距装置的扫描角速度在视场角内是均匀的，则对于预定的所述夹角，所述过滤阈值系数为固定值。
示例性地，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，则对于预定的所述夹角，所述过滤阈值系数为二维数据集。
示例性地，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，所述过滤阈值系数为基于所述脉冲信号的发射时间间隔、所述测距装置的最大扫描角速度和所述夹角而获得。
示例性地，所述夹角的范围为0～90°。
示例性地，所述阈值数据集包括所述当前点云点和其前一个相邻点云点的深度值之差的阈值，则确定为噪点的所述当前点云点的深度值和其前一个相邻点云点的深度值之差大于所述阈值。
示例性地，所述滤波模型包括滤波函数。
示例性地，所述处理器还用于：
当确定所述当前点云点为噪点时，将所述当前点云点滤除；或者，
对确定为噪点的所述当前点云点进行标记。
示例性地，所述测距装置还包括：
输出装置，用于将所述测距装置采集的非噪点的点云点输出为图像或视频。
示例性地，所述将点云点滤除是在所述测距装置采集点云点的过程中执行的。
示例性地，所述相邻点云点为在所述当前点云点之前所述测距装置采集的点云点。
示例性地，所述处理器还用于：
将被标记的所述当前点云点的深度值和/或反射率值赋为特殊值。
示例性地，所述测距装置还包括：
发射器，用于发射光脉冲序列；
接收电路，用于将接收到的经物体反射的回光转换为电信号输出；
采样电路，用于对输出的所述电信号进行采样，以测量所述光脉冲序列从发射到接收之间的时间差；
运算电路，用于接收所述时间差，计算所述当前点云点的深度值。
示例性地，所述处理器包括现场可编程门阵列。
本发明另一方面提供一种计算机存储介质，其上存储有计算机程序，所述程序被处理器执行时实现前述测距装置点云滤噪的方法。
本发明又一方面提供一种移动平台，所述移动平台包括：
前述的测距装置；和
平台本体，所述测距装置安装在所述平台本体上。
示例性地，所述移动平台包括无人机、机器人、车或船。
本发明实施例的方法通过获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值；将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点，进而对确定为噪点的点云点进行滤除或标记，可对包括波形融合噪点在内的多种噪点进行过滤，显著减少了点云中前后相近物体之间的“飞线”噪点及其他异常噪点，对点云质量有明显的优化和提升；并且，本发明实施例的方法仅需较少的运算量即可实现，处理结果无延时且准确度高，噪声过滤的过程几乎是随着点云采集实时完成的。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1示出了本发明一实施例中的激光测距系统多回波的产生原理示意图；
图2示出了本发明一实施例中的激光测距系统波形融合噪点产生的原理示意图；
图3示出了本发明一实施例中的波形融合噪点的示意图；
图4示出了本发明另一实施例中的波形融合噪点的示意图；
图5示出了本发明一实施例中的测距装置点云滤噪的方法的示意性流程图；
图6示出了本发明一实施例中的应用点云滤噪的方法后被标记的噪点的示意图；
图7示出了本发明一实施例中的应用点云滤噪的方法前后的点云图的对比示意图；
图8示出了本发明一实施例中的测距装置的架构示意图；
图9示出了本发明一个实施例中的测距装置的示意图。
具体实施方式
为了使得本发明的目的、技术方案和优点更为明显，下面将参照附图详细描述根据本发明的示例实施例。显然，所描述的实施例仅仅是本发明的一部分实施例，而不是本发明的全部实施例，应理解，本发明不受这里描述的示例实施例的限制。基于本发明中描述的本发明实施例，本领域技术人员在没有付出创造性劳动的情况下所得到的所有其它实施例都应落入本发明的保护范围之内。
在下文的描述中，给出了大量具体的细节以便提供对本发明更为彻底的理解。然而，对于本领域技术人员而言显而易见的是，本发明可以无需一个或多个这些细节而得以实施。在其他的例子中，为了避免与本发明发生混淆，对于本领域公知的一些技术特征未进行描述。
应当理解的是，本发明能够以不同形式实施，而不应当解释为局限于这里提出的实施例。相反地，提供这些实施例将使公开彻底和完全，并且将本发明的范围完全地传递给本领域技术人员。
在此使用的术语的目的仅在于描述具体实施例并且不作为本发明的限制。在此使用时，单数形式的“一”、“一个”和“所述/该”也意图包括复数形式，除非上下文清楚指出另外的方式。还应明白术语“组成”和/或“包括”，当在该说明书中使用时，确定所述特征、整数、步骤、操作、元件和/或部件的存在，但不排除一个或更多其它的特征、整数、步骤、操作、元件、部件和/或组的存在或添加。在此使用时，术语“和/或”包括相关所列项目的任何及所有组合。
为了彻底理解本发明，将在下列的描述中提出详细的结构，以便阐释本发明提出的技术方案。本发明的可选实施例详细描述如下，然而除了这些详细描述外，本发明还可以具有其他实施方式。
例如激光测距系统的测距装置是一种利用激光进行扫描和距离测量从而获取周围场景中三维信息的感知系统。其基本原理为主动对被探测物体发射 激光脉冲，捕捉激光回波信号并根据激光发射和接收之间的时间差计算出被测对象的距离；基于激光的已知发射方向，获得被测对象的角度信息；通过高频率的发射和接收，可以获取海量的探测点的距离及角度信息，称为点云。基于点云即可以重建周围场景的三维信息。
激光测距系统发射的激光通常具有一定的发散角θ(θ为一组参数，与激光器的设计参数有关)，这意味着从发射点开始，光斑的面积会随着距离的增加而不断增大。假设在距离发射点为d1处，激光的光斑面积为Sd1，由于实际环境的复杂性，光斑Sd1既可能全部落在一个物体上，也可能只有一部分落在一个物体A上，另一部分落在远处距离为d2的另一个物体B上，如图1所示。
因为光速在特定环境下是恒定的，如图2所示，如果d1与d2的距离较远，则接收系统会获取到两次相互独立的激光回波；如果d1与d2距离较近，则两次激光回波会逐渐融合；在d1与d2的距离小于极限距离dmin的时候，两次激光回波在光电转换器产生的模拟信号上会完全融合为一个波形。在激光测距系统以激光飞行时间计算距离的算法中，除非将这种特殊波形精确识别并作专门处理，否则很可能计算出一个既不是d1，也不是d2的错误距离，称之为噪点。当然，还有其他原因产生的异常点，也可归纳为噪点并由本发明过滤掉。
图3和图4示出了两个具有波形融合噪点的点云图，在图3所示的点云图中，A和B分别为柱子和墙壁，C区域并无任何物体，但由于前文所述的波形融合现象，在C区域产生了噪点。在图4所示的点云图中，箭头指向的位置是车与护栏中间的空白区域，但是由于距离较近，也产生了一些噪点。
目前常规的方案通常有以下几种方法：1)在上层运算平台用图像识别或空间滤波的方法去掉噪点；2)在底层根据波形特征进行识别和去噪；3)不做任何处理；然而上述方案1需要大量的点云数据进行运算，不仅消耗很多资源，同时计算结果存在一定的延时。方案2的难点在于，这种波形与正常的波形非常接近，几乎无法从波形特征上进行区分，或者存在大量的误判；方案3不增加额外的运算量，但是在某些应用中，上述噪点会对点云的物体识别，尤其是距离相近的物体的识别产生较大影响。
鉴于上述问题的存在，本发明实施例中提供一种测距装置点云滤噪的方法，如图5所示，所述方法包括以下步骤：步骤S501，获取所述测距装置采 集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值；步骤S502，将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点。上述方法所需的运算量少，处理结果无延时能够实时的对当前点云点进行过滤且准确度高，可对包括波形融合噪点在内的多种噪点进行过滤，对测距装置的点云质量有显著的提升。
下面结合附图，对本申请的测距装置点云滤噪的方法进行详细说明。在不冲突的情况下，下述的实施例及实施方式中的特征可以相互组合。
首先，如图5所示，在步骤S501中，获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值。
在一个示例中，获取所述测距装置采集的当前点云点的深度值具体包括：发射光脉冲序列；将接收到的经物体反射的回光转换为电信号输出；对输出的所述电信号进行采样，以测量所述光脉冲序列从发射到接收之间的时间差；接收所述时间差，计算所述当前点云点的深度值。由此方法可以获得测距装置采集的所有点云点的深度值。
其中，与当前点云点相邻的相邻点云点是指测距装置采集到当前点云点的当前时刻之前的特定时间段内或者之后的特定时间段内所述测距装置采集到的点云点。
可选地，所述相邻点云点为所述测距装置在当前点云点之前采集的点云点。基于该相邻点云点可以实时的对当前点云点是否为噪点进行过滤。
接着，在步骤S502中，将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点。
在一个示例中，将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点，具体包括：基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点。
示例性地，判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续的方法，例如，可以利用多个点的深度值的相对关系进行分析和判断，例如，以相邻的四个点云点为例，其深度值分别为d1、d2、d3和d4，如果d2和d1、d3和d2、d4和d3之间的深度值之差连续按照预定规律变化， 且均在深度差值阈值区间内，则认为上述点云点的数据正常，均不是噪点。而如果上述深度差值波动较大且不在深度差值阈值区间内，则认为数据异常并进行标记和处理。可以在测距装置采集到预定数量的点云数据后，再对该点云数据中的每个点云点进行过滤，以在测距装置端对点云数据进行过滤，或者，也可以是随着测距装置每采集到一个点云点即对该点云点依据本申请实施例中的过滤方法进行过滤，在噪声过滤的过程几乎是随着点云采集实时完成的，并且仅需较少的运算量即可实现，且数据延时极小。
在一个示例中，所述基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点，具体包括：获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集；基于所述当前点云点和所述至少一个相邻点云点的深度值之差是否在所述阈值数据集内，确定所述当前点云点是否为噪点，其中，深度值之差在所述阈值数据集内的当前点云点不是噪点，而深度值之差超出阈值数据集的当前点云点为噪点，例如，所述阈值数据集包括所述当前点云点和其前一个相邻点云点的深度值之差的阈值，则确定为噪点的所述当前点云点的深度值和其前一个相邻点云点的深度值之差大于所述阈值，可以在采集到当前点云点的实际深度值和其之前的相邻点云点的实际深度值之后，基于两者实际深度值之差与阈值进行比较，若实际深度值之差小于或等于该阈值，则该当前点云点不是噪点，而若实际深度值之差大于该阈值，则当前点云点为噪点。上述过滤为实时过滤，仅需较少的运算量即可实现，且数据延时极小，噪声过滤的过程几乎是随着点云采集实时完成的。
可以通过任意适合的方法获得上述阈值数据集，在一个示例中，所述获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集，具体包括：基于所述测距装置发射的光脉冲序列的发射时间间隔、所述测距装置的扫描角速度和夹角获得过滤阈值系数，所述夹角为所述测距装置发射的光脉冲序列的前进方向与参考面的夹角；基于所述过滤阈值系数和所述当前点云点之前的相邻点云点的深度值获得所述阈值数据集，其中，所述阈值数据集包括的阈值和所述当前点云点之前的相邻点云点的深度值呈正比，与所述夹角呈反比。
所述测距装置发射的光脉冲序列的前进方向与参考面的夹角θ可以根据 实际的过滤效果需要进行合理的调整，可选地，该夹角的范围可以为0°至90°，更进一步，该夹角的范围还可以为0-80°，或者还可以为0-30°、0-40°，0-50°等。本发明实施例中可以通过调节夹角θ，可获得不同强度的去噪效果。当θ趋近于90°时，依据本发明实施例中的方案将过滤掉几乎所有非正入射的点云；当θ趋近于0°时，依据本发明实施例中的方案将几乎不过滤任何点云。调节θ，即可得到将波形融合噪点或其他异常噪点进行不同程度的过滤。
依据不同的类型的测距装置其可以采用不同的过滤阈值系数，在一个示例中，若所述测距装置的扫描角速度在视场角内是均匀的，则对于预定的所述夹角，所述过滤阈值系数为固定值，则每个当前点云点和其之前的相邻点云点的深度值之差的阈值可以为该过滤阈值系数与当前点云点之前的相邻点云点的深度值之差的乘积。由于测距装置在探测目标场景时所采集到的点云中包括多个点云点，该当前点云点可以是多个点云点中的任意一个点云点，则每个不同的当前点云点则可能对应不同的深度值之差的阈值，或者部分当前点云点之前的相邻点云点具有相同的深度值而过滤阈值系数也为固定值时，则该部分当前点云点也可以对应相同的深度值之差的阈值。
在另一个示例中，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，则对于预定的所述夹角，所述过滤阈值系数为二维数据集。基于该二维数据集获得阈值数据集，从而对点云进行过滤。
在其他示例中，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，在该二维数据集中找出所述测距装置的最大扫描角速度，所述过滤阈值系数为基于所述脉冲信号的发射时间间隔、所述测距装置的最大扫描角速度和所述夹角而获得，并将该过滤阈值系数应用于获得阈值数据集，进而应用于对当前点云点的过滤。该方法具有节约资源以及计算量等的优点，并且能对点云起到预定的过滤效果。
在一个具体示例中，以基于相邻点深度差值为例，假设在空间中存在一个足够大的平面A(也即参考面)，该平面A与例如激光测距系统的测距装置之间的距离为d，激光的扫描角速度为α，若所述测距装置的扫描角速度在视 场角内是均匀的，则测距装置发射的光脉冲序列(例如激光)在平面A上扫描的线速度为：
v＝αd
如果测距装置设计的相邻光脉冲序列的发射时间间隔为t，在平面A与光脉冲序列的前进方向相垂直时，测距装置测得的相邻点云点的距离差值近似为：
Δd＝αdt
更进一步的，如果平面A与光脉冲序列的前进方向呈预定的夹角θ，则测距装置测得的相邻点云点的距离差值近似为：
Figure PCTCN2019084095-appb-000001
在上式中，α、t都是测距装置的设计有关的定值，d为测距装置测得的当前点云点的实际距离(也即深度值)，θ为本发明定义的设计参数。显然，Δd‘与d呈正比，与θ呈负相关。对于预定的夹角θ，在距离d处，即有确定的Δd‘，其比例系数(也即过滤阈值系数)定义为K。如果连续测得深度值依次为d1、d2、d3、d4和d5的几个点云点，其前后点云点的深度值之差及阈值如表格1所示：
表格1相邻点的差值计算和阈值生成
点云点序号 深度 相邻点云点差值 阈值
1 d1 / /
2 d2 d2-d1 K*d1
3 d3 d3-d2 K*d2
4 d4 d4-d3 K*d3
5 d5 d5-d4 K*d4
例如，对于序号为2的当前点云点，如果实际测得的序号为2的当前点云点的深度值d2和其之前的相邻点云点的实际深度值d1的差值大于过滤系数K与d1的乘积，则认为序号为2的当前点云点为噪点，对该噪点进行标记并处理；否则认为该序号为2的当前点云点不是噪点而为正常点，直接输出。同理依次对测距装置采集到的每个当前点云点进行上述过滤，直到识别 出所有的噪点(也称噪声)。如图6所示，在图6中箭头所指区域内的点为本发明标记的待过滤的噪点，其他区域为正常点。
本发明的其他实施例中，所述滤波模型包括滤波函数，例如线性滤波函数、高斯滤波函数、空间频率分布滤波函数等。利用符合预定条件的滤波函数作为判断条件，识别出异常波动的噪点。
对于通过上述方法确定为噪点的当前点云点可以按照下述方法进行处理，在一个示例性地，当确定所述当前点云点为噪点时，将所述当前点云点滤除，例如，将确定为噪点的当前点云点的深度值设置为0，也即直接过滤，可选地，所述将点云点滤除是在所述测距装置采集点云点的过程中执行的，这样测距装置可以直接输出几乎不含噪点的点云数据。在另一个示例中，对确定为噪点的所述当前点云点进行标记，将被标记的所述当前点云点的深度值和/或反射率值赋为特殊值或直接将所述当前点云点滤除，该特殊值区别于其他非噪点的点云点的深度值或反射率至，之后由上层算法(也即上层应用)决定处理方式，该上层算法例如物体分割识别算法、三维重建算法等。需要注意的是，本发明实施例中只是在向上层应用发送数据时，才使用处理之后的值，本发明实施例中始终保留过滤前的原始数据，作为下一次过滤算法的参考。
如图7所示，通过在同一场景下应用本发明实施例中的方法前后的对比效果来看，实施例中的方法显著减少了点云中前后相近物体之间的“飞线”噪点及其他异常噪点，对点云质量有明显的优化和提升。
综上，本发明实施例的方法通过获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值；将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点，进而对确定为噪点的点云点进行滤除或标记，可对包括波形融合噪点在内的多种噪点进行过滤，显著减少了点云中前后相近物体之间的“飞线”噪点及其他异常噪点，对点云质量有明显的优化和提升；并且，本发明实施例的方法仅需较少的运算量即可实现，处理结果无延时且准确度高，噪声过滤的过程几乎是随着点云采集实时完成的。
下面，参考图8和图9对本发明实施例中的一种测距装置的结构做更详 细的示例性地描述，测距装置包括激光雷达，该测距装置仅作为示例，对于其他适合的测距装置也可以应用于本申请。该测距装置用于执行前述实施例中的点云滤噪的方法。
本发明各个实施例提供的方案可以应用于测距装置，该测距装置可以是激光雷达、激光测距设备等电子设备。在一种实施方式中，测距装置用于感测外部环境信息，例如，环境目标的距离信息、方位信息、反射强度信息、速度信息等。一种实现方式中，测距装置可以通过测量测距装置和探测物之间光传播的时间，即光飞行时间(Time-of-Flight，TOF)，来探测探测物到测距装置的距离。或者，测距装置也可以通过其他技术来探测探测物到测距装置的距离，例如基于相位移动(phase shift)测量的测距方法，或者基于频率移动(frequency shift)测量的测距方法，在此不做限制。
为了便于理解，以下将结合图8所示的测距装置100对测距的工作流程进行举例描述。
示例性地，所述测距装置可以包括发射模块、接收模块和温度控制系统，所述发射模块用于出射光脉冲；所述接收模块用于接收经物体反射回的至少部分光脉冲，以及根据所述接收的至少部分光脉冲确定所述物体相对所述测距装置的距离。
具体地，如图8所示，所述发射模块包括发射电路110；所述接收模块包括接收电路120、采样电路130和运算电路140。
发射电路110可以出射光脉冲序列(例如激光脉冲序列)。接收电路120可以接收经过被探测物反射的光脉冲序列，并对该光脉冲序列进行光电转换，以得到电信号，再对电信号进行处理之后可以输出给采样电路130。采样电路130可以对电信号进行采样，以获取采样结果。运算电路140可以基于采样电路130的采样结果，以确定测距装置100与被探测物之间的距离。
可选地，该测距装置100还可以包括控制电路150，该控制电路150可以实现对其他电路的控制，例如，可以控制各个电路的工作时间和/或对各个电路进行参数设置等。
应理解，虽然图8示出的测距装置中包括一个发射电路、一个接收电路、一个采样电路和一个运算电路，用于出射一路光束进行探测，但是本申请实施例并不限于此，发射电路、接收电路、采样电路、运算电路中的任一种电路的数量也可以是至少两个，用于沿相同方向或分别沿不同方向出射至少两 路光束；其中，该至少两束光路可以是同时出射，也可以是分别在不同时刻出射。一个示例中，该至少两个发射电路中的发光芯片封装在同一个模块中。例如，每个发射电路包括一个激光发射芯片，该至少两个发射电路中的激光发射芯片中的die封装到一起，容置在同一个封装空间中。
一些实现方式中，除了图8所示的电路，测距装置100还可以包括扫描模块，用于将发射电路出射的至少一路光脉冲序列(例如激光脉冲序列)改变传播方向出射，以对视场进行扫描。示例性地，所述扫描模块在测距装置的视场内的扫描区域随着时间的累积而增加。
其中，可以将包括发射电路110、接收电路120、采样电路130和运算电路140的模块，或者，包括发射电路110、接收电路120、采样电路130、运算电路140和控制电路150的模块称为测距模块，该测距模块可以独立于其他模块，例如，扫描模块。
测距装置中可以采用同轴光路，也即测距装置出射的光束和经反射回来的光束在测距装置内共用至少部分光路。例如，发射电路出射的至少一路激光脉冲序列经扫描模块改变传播方向出射后，经探测物反射回来的激光脉冲序列经过扫描模块后入射至接收电路。或者，测距装置也可以采用异轴光路，也即测距装置出射的光束和经反射回来的光束在测距装置内分别沿不同的光路传输。图9示出了本发明的测距装置采用同轴光路的一种实施例的示意图。
测距装置200包括测距模块210，测距模块210包括发射器203(可以包括上述的发射电路)、准直元件204、探测器205(可以包括上述的接收电路、采样电路和运算电路)和光路改变元件206。测距模块210用于发射光束，且接收回光，将回光转换为电信号。其中，发射器203可以用于发射光脉冲序列。在一个实施例中，发射器203可以发射激光脉冲序列。可选的，发射器203发射出的激光束为波长在可见光范围之外的窄带宽光束。准直元件204设置于发射器的出射光路上，用于准直从发射器203发出的光束，将发射器203发出的光束准直为平行光出射至扫描模块。准直元件还用于会聚经探测物反射的回光的至少一部分。该准直元件204可以是准直透镜或者是其他能够准直光束的元件。
在图9所示实施例中，通过光路改变元件206来将测距装置内的发射光路和接收光路在准直元件204之前合并，使得发射光路和接收光路可以共用同一个准直元件，使得光路更加紧凑。在其他的一些实现方式中，也可以是 发射器203和探测器205分别使用各自的准直元件，将光路改变元件206设置在准直元件之后的光路上。
在图9所示实施例中，由于发射器203出射的光束的光束孔径较小，测距装置所接收到的回光的光束孔径较大，所以光路改变元件可以采用小面积的反射镜来将发射光路和接收光路合并。在其他的一些实现方式中，光路改变元件也可以采用带通孔的反射镜，其中该通孔用于透射发射器203的出射光，反射镜用于将回光反射至探测器205。这样可以减小采用小反射镜的情况中小反射镜的支架会对回光的遮挡。
在图9所示实施例中，光路改变元件偏离了准直元件204的光轴。在其他的一些实现方式中，光路改变元件也可以位于准直元件204的光轴上。
测距装置200还包括扫描模块202。扫描模块202放置于测距模块210的出射光路上，扫描模块202用于改变经准直元件204出射的准直光束219的传输方向并投射至外界环境，并将回光投射至准直元件204。回光经准直元件204汇聚到探测器205上。
在一个实施例中，扫描模块202可以包括至少一个光学元件，用于改变光束的传播路径，其中，该光学元件可以通过对光束进行反射、折射、衍射等等方式来改变光束传播路径，例如所述光学元件包括至少一个具有非平行的出射面和入射面的光折射元件。例如，扫描模块202包括透镜、反射镜、棱镜、振镜、光栅、液晶、光学相控阵(Optical Phased Array)或上述光学元件的任意组合。一个示例中，至少部分光学元件是运动的，例如通过驱动模块来驱动该至少部分光学元件进行运动，该运动的光学元件可以在不同时刻将光束反射、折射或衍射至不同的方向。在一些实施例中，扫描模块202的多个光学元件可以绕共同的轴209旋转或振动，每个旋转或振动的光学元件用于不断改变入射光束的传播方向。在一个实施例中，扫描模块202的多个光学元件可以以不同的转速旋转，或以不同的速度振动。在另一个实施例中，扫描模块202的至少部分光学元件可以以基本相同的转速旋转。在一些实施例中，扫描模块的多个光学元件也可以是绕不同的轴旋转。在一些实施例中，扫描模块的多个光学元件也可以是以相同的方向旋转，或以不同的方向旋转；或者沿相同的方向振动，或者沿不同的方向振动，在此不作限制。
在一个实施例中，扫描模块202包括第一光学元件214和与第一光学元件214连接的驱动器216，驱动器216用于驱动第一光学元件214绕转动轴209转动，使第一光学元件214改变准直光束219的方向。第一光学元件214 将准直光束219投射至不同的方向。在一个实施例中，准直光束219经第一光学元件改变后的方向与转动轴209的夹角随着第一光学元件214的转动而变化。在一个实施例中，第一光学元件214包括相对的非平行的一对表面，准直光束219穿过该对表面。在一个实施例中，第一光学元件214包括厚度沿至少一个径向变化的棱镜。在一个实施例中，第一光学元件214包括楔角棱镜，对准直光束219进行折射。
在一个实施例中，扫描模块202还包括第二光学元件215，第二光学元件215绕转动轴209转动，第二光学元件215的转动速度与第一光学元件214的转动速度不同。第二光学元件215用于改变第一光学元件214投射的光束的方向。在一个实施例中，第二光学元件215与另一驱动器217连接，驱动器217驱动第二光学元件215转动。第一光学元件214和第二光学元件215可以由相同或不同的驱动器驱动，使第一光学元件214和第二光学元件215的转速和/或转向不同，从而将准直光束219投射至外界空间不同的方向，可以扫描较大的空间范围。在一个实施例中，控制器218控制驱动器216和217，分别驱动第一光学元件214和第二光学元件215。第一光学元件214和第二光学元件215的转速可以根据实际应用中预期扫描的区域和样式确定。驱动器216和217可以包括电机或其他驱动器。
在一个实施例中，第二光学元件215包括相对的非平行的一对表面，光束穿过该对表面。在一个实施例中，第二光学元件215包括厚度沿至少一个径向变化的棱镜。在一个实施例中，第二光学元件215包括楔角棱镜。
一个实施例中，扫描模块202还包括第三光学元件(图未示)和用于驱动第三光学元件运动的驱动器。可选地，该第三光学元件包括相对的非平行的一对表面，光束穿过该对表面。在一个实施例中，第三光学元件包括厚度沿至少一个径向变化的棱镜。在一个实施例中，第三光学元件包括楔角棱镜。第一、第二和第三光学元件中的至少两个光学元件以不同的转速和/或转向转动。
在一个实施例中，所述扫描模块包括在所述光脉冲序列的出射光路上依次排布的2个或3个所述光折射元件。可选地，所述扫描模块中的至少2个所述光折射元件在扫描过程中旋转，以改变所述光脉冲序列的方向。
所述扫描模块在至少部分不同时刻的扫描路径不同，扫描模块202中的各光学元件旋转可以将光投射至不同的方向，例如投射的光211的方向和方向213，如此对测距装置200周围的空间进行扫描。当扫描模块202投射出 的光211打到探测物201时，一部分光被探测物201沿与投射的光211相反的方向反射至测距装置200。探测物201反射的回光212经过扫描模块202后入射至准直元件204。
探测器205与发射器203放置于准直元件204的同一侧，探测器205用于将穿过准直元件204的至少部分回光转换为电信号。
一个实施例中，各光学元件上镀有增透膜。可选的，增透膜的厚度与发射器203发射出的光束的波长相等或接近，能够增加透射光束的强度。
一个实施例中，测距装置中位于光束传播路径上的一个元件表面上镀有滤光层，或者在光束传播路径上设置有滤光器，用于至少透射发射器所出射的光束所在波段，反射其他波段，以减少环境光给接收器带来的噪音。
在一些实施例中，发射器203可以包括激光二极管，通过激光二极管发射纳秒级别的激光脉冲。进一步地，可以确定激光脉冲接收时间，例如，通过探测电信号脉冲的上升沿时间和/或下降沿时间确定激光脉冲接收时间。如此，测距装置200可以利用脉冲接收时间信息和脉冲发出时间信息计算TOF，从而确定探测物201到测距装置200的距离。测距装置200探测到的距离和方位可以用于遥感、避障、测绘、建模、导航等。
在一些实施例中，所述测距装置还包括一个或多个处理器，一个或多个存储装置，一个或多个处理器共同地或单独地工作。可选地，测距装置还可以包括输入装置(未示出)、输出装置(未示出)以及图像传感器(未示出)中的至少一个，这些组件通过总线系统和/或其它形式的连接机构(未示出)互连。
所述存储装置也即存储器用于存储处理器可执行指令的存储器，例如用于存在用于实现根据本发明实施例的测距装置点云滤噪的方法中的相应步骤和程序指令。可以包括一个或多个计算机程序产品，所述计算机程序产品可以包括各种形式的计算机可读存储介质，例如易失性存储器和/或非易失性存储器。所述易失性存储器例如可以包括随机存取存储器(RAM)和/或高速缓冲存储器(cache)等。所述非易失性存储器例如可以包括只读存储器(ROM)、硬盘、闪存等。
所述输入装置可以是用户用来输入指令的装置，并且可以包括键盘、鼠标、麦克风和触摸屏等中的一个或多个。
所述输出装置可以向外部(例如用户)输出各种信息(例如图像或声音)， 并且可以包括显示器、扬声器等中的一个或多个，用于将所述测距装置采集的非噪点的点云点输出为图像或视频。
通信接口(未示出)用于测距装置和其他设备之间进行通信，包括有线或者无线方式的通信。测距装置可以接入基于通信标准的无线网络，如WiFi、2G、3G、4G、5G或它们的组合。在一个示例性实施例中，通信接口经由广播信道接收来自外部广播管理系统的广播信号或广播相关信息。在一个示例性实施例中，所述通信接口还包括近场通信(NFC)模块，以促进短程通信。例如，在NFC模块可基于射频识别(RFID)技术，红外数据协会(IrDA)技术，超宽带(UWB)技术，蓝牙(BT)技术和其他技术来实现。
所述处理器可以是中央处理单元(CPU)、图像处理单元(GPU)、专用集成电路(ASIC)、现场可编程门阵列(FPGA)或者具有数据处理能力和/或指令执行能力的其它形式的处理单元，并且可以控制测距装置中的其它组件以执行期望的功能。所述处理器能够执行所述存储装置中存储的所述指令，以执行本文描述的测距装置点云滤噪的方法，该滤噪的方法参考前述实施例中的描述，在此不再重复赘述。例如，处理器能够包括一个或多个嵌入式处理器、处理器核心、微型处理器、逻辑电路、硬件有限状态机(FSM)、数字信号处理器(DSP)或它们的组合。在本实施例中，所述处理器包括现场可编程门阵列(FPGA)，其中，测距装置的运算电路可以是现场可编程门阵列(FPGA)的一部分。
在一种实施方式中，本发明实施方式的测距装置可应用于移动平台，测距装置可安装在移动平台的平台本体。具有测距装置的移动平台可对外部环境进行测量，例如，测量移动平台与障碍物的距离用于避障等用途，和对外部环境进行二维或三维的测绘。在某些实施方式中，移动平台包括无人飞行器、汽车、遥控车、机器人、船、相机中的至少一种。当测距装置应用于无人飞行器时，平台本体为无人飞行器的机身。当测距装置应用于汽车时，平台本体为汽车的车身。该汽车可以是自动驾驶汽车或者半自动驾驶汽车，在此不做限制。当测距装置应用于遥控车时，平台本体为遥控车的车身。当测距装置应用于机器人时，平台本体为机器人。当测距装置应用于相机时，平台本体为相机本身。
本发明实施例中的测距装置由于用于执行前述的方法，而移动平台包括 该测距装置，因此测距装置和移动平台均具有和前述方法相同的优点。
另外，本发明实施例还提供了一种计算机存储介质，其上存储有计算机程序。在所述计算机可读存储介质上可以存储一个或多个计算机程序指令，处理器可以运行存储装置存储的所述程序指令，以实现本文所述的本发明实施例中(由处理器实现)的功能以及/或者其它期望的功能，例如以执行根据本发明实施例的测距装置点云滤噪的方法的相应步骤，在所述计算机可读存储介质中还可以存储各种应用程序和各种数据，例如所述应用程序使用和/或产生的各种数据等。
例如，所述计算机存储介质例如可以包括智能电话的存储卡、平板电脑的存储部件、个人计算机的硬盘、只读存储器(ROM)、可擦除可编程只读存储器(EPROM)、便携式紧致盘只读存储器(CD-ROM)、USB存储器、或者上述存储介质的任意组合。所述计算机可读存储介质可以是一个或多个计算机可读存储介质的任意组合。例如一个计算机可读存储介质包含用于将点云数据转换为二维图像的计算机可读的程序代码，和/或将点云数据进行三维重建的计算机可读的程序代码，另一个计算机可读存储介质包含用于对所述二维图像进行物体分割的计算机可读的程序代码等。
尽管这里已经参考附图描述了示例实施例，应理解上述示例实施例仅仅是示例性的，并且不意图将本发明的范围限制于此。本领域普通技术人员可以在其中进行各种改变和修改，而不偏离本发明的范围和精神。所有这些改变和修改意在被包括在所附权利要求所要求的本发明的范围之内。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本发明的范围。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。例如，以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个设备，或一些特征可以忽略，或不执行。
在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本 发明的实施例可以在没有这些具体细节的情况下实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
类似地，应当理解，为了精简本发明并帮助理解各个发明方面中的一个或多个，在对本发明的示例性实施例的描述中，本发明的各个特征有时被一起分组到单个实施例、图、或者对其的描述中。然而，并不应将该本发明的方法解释成反映如下意图：即所要求保护的本发明要求比在每个权利要求中所明确记载的特征更多的特征。更确切地说，如相应的权利要求书所反映的那样，其发明点在于可以用少于某个公开的单个实施例的所有特征的特征来解决相应的技术问题。因此，遵循具体实施方式的权利要求书由此明确地并入该具体实施方式，其中每个权利要求本身都作为本发明的单独实施例。
本领域的技术人员可以理解，除了特征之间相互排斥之外，可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者设备的所有过程或单元进行组合。除非另外明确陈述，本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的替代特征来代替。
此外，本领域的技术人员能够理解，尽管在此所述的一些实施例包括其它实施例中所包括的某些特征而不是其它特征，但是不同实施例的特征的组合意味着处于本发明的范围之内并且形成不同的实施例。例如，在权利要求书中，所要求保护的实施例的任意之一都可以以任意的组合方式来使用。
本发明的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本发明实施例的一些模块的一些或者全部功能。本发明还可以实现为用于执行这里所描述的方法的一部分或者全部的装置程序(例如，计算机程序和计算机程序产品)。这样的实现本发明的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
应该注意的是上述实施例对本发明进行说明而不是对本发明进行限制，并且本领域技术人员在不脱离所附权利要求的范围的情况下可设计出替换实施例。在权利要求中，不应将位于括号之间的任何参考符号构造成对权利要求的限制。本发明可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若 干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。

Claims (36)

  1. 一种测距装置点云滤噪的方法，其特征在于，所述方法包括：
    获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值；
    将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点。
  2. 如权利要求1所述的方法，其特征在于，将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点，具体包括：
    基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点。
  3. 如权利要求2所述的方法，其特征在于，所述基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点，具体包括：
    获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集；
    基于所述当前点云点和所述至少一个相邻点云点的深度值之差是否在所述阈值数据集内，确定所述当前点云点是否为噪点。
  4. 如权利要求3所述的方法，其特征在于，所述获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集，具体包括：
    基于所述测距装置发射的光脉冲序列的发射时间间隔、所述测距装置的扫描角速度和夹角获得过滤阈值系数，所述夹角为所述测距装置发射的光脉冲序列的前进方向与参考面的夹角；
    基于所述过滤阈值系数和所述当前点云点之前的相邻点云点的深度值获得所述阈值数据集，其中，所述阈值数据集包括的阈值和所述当前点云点之前的相邻点云点的深度值呈正比，与所述夹角呈反比。
  5. 如权利要求4所述的方法，其特征在于，若所述测距装置的扫描角速度在视场角内是均匀的，则对于预定的所述夹角，所述过滤阈值系数为固定值。
  6. 如权利要求4所述的方法，其特征在于，若所述测距装置的扫描角速 度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，则对于预定的所述夹角，所述过滤阈值系数为二维数据集。
  7. 如权利要求4所述的方法，其特征在于，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，所述过滤阈值系数为基于所述脉冲信号的发射时间间隔、所述测距装置的最大扫描角速度和所述夹角而获得。
  8. 如权利要求4所述的方法，其特征在于，所述夹角的范围为0～90°。
  9. 如权利要求3所述的方法，其特征在于，所述阈值数据集包括所述当前点云点和其前一个相邻点云点的深度值之差的阈值，则确定为噪点的所述当前点云点的深度值和其前一个相邻点云点的深度值之差大于所述阈值。
  10. 如权利要求1所述的方法，其特征在于，所述滤波模型包括滤波函数。
  11. 如权利要求1至10任一项所述的方法，其特征在于，所述方法还包括：
    当确定所述当前点云点为噪点时，将所述当前点云点滤除；或者，
    对确定为噪点的所述当前点云点进行标记。
  12. 如权利要求1至10任一项所述的方法，其特征在于，所述方法还包括：
    将所述测距装置采集的非噪点的点云点输出为图像或视频。
  13. 如权利要求11所述的方法，其特征在于，
    所述将点云点滤除是在所述测距装置采集点云点的过程中执行的。
  14. 如权利要求1所述的方法，其特征在于，所述相邻点云点为在所述当前点云点之前采集的点云点。
  15. 如权利要求11所述的方法，其特征在于，所述方法还包括：
    将被标记的所述当前点云点的深度值和/或反射率值赋为特殊值。
  16. 如权利要求1至10任一项所述的方法，其特征在于，获取所述测距装置采集的当前点云点的深度值，具体为：
    发射光脉冲序列；
    将接收到的经物体反射的回光转换为电信号输出；
    对输出的所述电信号进行采样，以测量所述光脉冲序列从发射到接收之间的时间差；
    接收所述时间差，计算所述当前点云点的深度值。
  17. 一种测距装置，其特征在于，所述测距装置包括一个或多个处理器，共同地或单独地工作，所述处理器用于：
    获取所述测距装置采集的当前点云点的深度值，以及与所述当前点云点相邻的至少一个相邻点云点的深度值；
    将所述当前点云点的深度值和所述至少一个相邻点云点的深度值输入至预定的滤波模型，以确定所述当前点云点是否为噪点。
  18. 如权利要求17所述的测距装置，其特征在于，所述处理器具体用于：
    基于所述预定的滤波模型判断当前点云点和所述至少一个相邻点云点的深度值的变化是否连续，以确定所述当前点云点是否为噪点。
  19. 如权利要求18所述的测距装置，其特征在于，所述处理器更具体地用于：
    获取所述当前点云点和所述至少一个相邻点云点的深度值之差的阈值数据集；
    基于所述当前点云点和所述至少一个相邻点云点的深度值之差是否在所述阈值数据集内，确定所述当前点云点是否为噪点。
  20. 如权利要求19所述的测距装置，其特征在于，所述处理器还用于：
    基于所述测距装置发射的光脉冲序列的发射时间间隔、所述测距装置的扫描角速度和夹角获得过滤阈值系数，所述夹角为所述测距装置发射的光脉冲序列的前进方向与参考面的夹角；
    基于所述过滤阈值系数和所述当前点云点之前的相邻点云点的深度值获得所述阈值数据集，其中，所述阈值数据集包括的阈值和所述当前点云点之前的相邻点云点的深度值呈正比，与所述夹角呈反比。
  21. 如权利要求20所述的测距装置，其特征在于，若所述测距装置的扫描角速度在视场角内是均匀的，则对于预定的所述夹角，所述过滤阈值系数为固定值。
  22. 如权利要求20所述的测距装置，其特征在于，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫 描的天顶角和方位角相关的二维数据集，则对于预定的所述夹角，所述过滤阈值系数为二维数据集。
  23. 如权利要求20所述的测距装置，其特征在于，若所述测距装置的扫描角速度在视场角内是非均匀的，则整个视场角内的扫描角速度是一个与扫描的天顶角和方位角相关的二维数据集，所述过滤阈值系数为基于所述脉冲信号的发射时间间隔、所述测距装置的最大扫描角速度和所述夹角而获得。
  24. 如权利要求20所述的测距装置，其特征在于，所述夹角的范围为0～90°。
  25. 如权利要求19所述的测距装置，其特征在于，所述阈值数据集包括所述当前点云点和其前一个相邻点云点的深度值之差的阈值，则确定为噪点的所述当前点云点的深度值和其前一个相邻点云点的深度值之差大于所述阈值。
  26. 如权利要求17所述的测距装置，其特征在于，所述滤波模型包括滤波函数。
  27. 如权利要求17至26任一项所述的测距装置，其特征在于，所述处理器还用于：
    当确定所述当前点云点为噪点时，将所述当前点云点滤除；或者，
    对确定为噪点的所述当前点云点进行标记。
  28. 如权利要求17至26任一项所述的测距装置，其特征在于，所述测距装置还包括：
    输出装置，用于将所述测距装置采集的非噪点的点云点输出为图像或视频。
  29. 如权利要求27所述的测距装置，其特征在于，所述将点云点滤除是在所述测距装置采集点云点的过程中执行的。
  30. 如权利要求17所述的测距装置，其特征在于，所述相邻点云点为在所述当前点云点之前所述测距装置采集的点云点。
  31. 如权利要求27所述的测距装置，其特征在于，所述处理器还用于：
    将被标记的所述当前点云点的深度值和/或反射率值赋为特殊值。
  32. 如权利要求17至26任一项所述的测距装置，其特征在于，所述测距装置还包括：
    发射器，用于发射光脉冲序列；
    接收电路，用于将接收到的经物体反射的回光转换为电信号输出；
    采样电路，用于对输出的所述电信号进行采样，以测量所述光脉冲序列从发射到接收之间的时间差；
    运算电路，用于接收所述时间差，计算所述当前点云点的深度值。
  33. 如权利要求17至26任一项所述的测距装置，其特征在于，所述处理器包括现场可编程门阵列。
  34. 一种计算机存储介质，其上存储有计算机程序，其特征在于，所述程序被处理器执行时实现权利要求1至16中任一项所述的方法。
  35. 一种移动平台，其特征在于，所述移动平台包括：
    权利要求17至33任一项所述的测距装置；和
    平台本体，所述测距装置安装在所述平台本体上。
  36. 如权利要求35所述的移动平台，其特征在于，所述移动平台包括无人机、机器人、车或船。
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