A dTOF laser radar-based ranging method and device for a sweeping machine

Abstract

The application provides a kind of dTOF laser radar-based sweeping machine ranging method and device, the method comprises: generating single-point dTOF histogram according to the time difference of dTOF laser radar emission and receiving optical signal;Get initial peak from single-point dTOF histogram;Respectively calculate the confidence of initial peak;Judge whether there is tailing false peak in each initial peak, mark the confidence of tailing false peak as 0;Get the bin position POS_X and peak value Peak_X of the calibration crosstalk peak of the cover of sweeping machine;According to POS_X and Peak_X, judge whether there is crosstalk peak in initial peak, and identify the flag bit representing dust condition, mark the confidence of initial peak as 0 if crosstalk peak exists and flag bit does not satisfy preset condition;Select the peak with the highest confidence in initial peak as confidence peak output, and calculate the distance of the target to be measured through confidence peak.The ranging method provided by the application avoids the interference caused by too much dust on the sweeping machine, removes the interference of the tailing false peak of the target peak, and improves the accuracy of the ranging of the sweeping machine.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of distance measurement, in particular to a dTOF laser radar based distance measurement method and device for a robot vacuum cleaner. BACKGROUND

[0002] At present, the application scenarios of dTOF laser radar are increasingly wide, including but not limited to commercial scenarios, home scenarios, outdoor environments, augmented reality technology, and smart home and security monitoring fields. As a kind of full-automatic household cleaning tool, the robot vacuum cleaner has entered thousands of households. The dTOF laser radar is widely used in various robot vacuum cleaners due to its advantages of high distance measurement accuracy and low cost. However, during the working process of the robot vacuum cleaner, dirt is easily attached to the outer cover, which will affect the emission and reception of the light signal of the internal dTOF laser radar and interfere with the distance measurement accuracy. SUMMARY

[0003] Therefore, the present application provides a dTOF laser radar based distance measurement method and device for a robot vacuum cleaner.

[0004] The present application provides a dTOF laser radar based distance measurement method for a robot vacuum cleaner, which comprises the following steps: S1, generating a single-point dTOF histogram according to the time difference of the emission and reception of the light signal of the dTOF laser radar; S2, reading a plurality of peaks with the maximum peak value from the single-point dTOF histogram and outputting the initial peaks in the order of bin position; S3, calculating the confidence of the initial peaks according to the noise level of the single-point dTOF histogram and the peak value of the initial peaks; S4, judging whether each initial peak is a trailing false peak according to the bin position of the initial peak and the relative size of the initial peak value, and marking the confidence of the initial peak of the trailing false peak as 0; S5, obtaining the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak of the outer cover of the robot vacuum cleaner in the single-point dTOF histogram; S6, judging whether there is a crosstalk peak in the initial peaks according to the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak, identifying the flag bit representing the dust condition, and marking the confidence of the initial peak with the crosstalk peak and the flag bit not satisfying the preset condition as 0; and S7, selecting the peak with the highest confidence in the initial peaks as the confidence peak output, and calculating the distance of the target to be measured through the confidence peak.

[0005] In some embodiments, the dTOF lidar comprises a laser, a photodetection avalanche diode, a time-to-digital converter, and a processor, and the step 1 specifically comprises: step S1.1, the laser emits N times of pulsed light signals to the target to be measured within a single frame measurement time; step S1.2, the photodetection avalanche diode receives the light signals reflected by the target to be measured; step S1.3, the time-to-digital converter records the time of flight between the emission and the reception of the light signals; and step S1.4, the processor makes a histogram statistics of the N times of the time of flight, and generates a single-point dTOF histogram through low-pass filtering.

[0006] In some embodiments, the step S2 specifically comprises: step S2.1, traversing the generated single-point dTOF histogram to select all peaks satisfying the three-point peak condition; step S2.2, arranging all peaks satisfying the condition in descending order of peak value, and selecting a plurality of peaks with the largest peak value as initial peaks; and step S2.3, rearranging the initial peaks in order of their bin positions from front to back, and outputting.

[0007] In some embodiments, the step S3 specifically comprises: calculating the confidence of each initial peak by calculating the ratio of the peak value of each initial peak to the noise of the single-point dTOF histogram.

[0008] In some embodiments, the step S4 specifically comprises: sequentially calculating the slope of the line connecting the peak value of each initial peak and the peak value of each initial peak behind it; when the slope is lower than a threshold value, taking the initial peak at the bin position behind as a tailing false peak of the initial peak at the bin position in front; and marking the confidence of the tailing false peak as 0.

[0009] In some embodiments, in the step S5, the marking process of the calibration crosstalk peak of the outer cover of the sweeping robot comprises: step S5.1, truncating the single-point dTOF histogram at a preset position; step S5.2, traversing the truncated single-point dTOF histogram, selecting all peaks satisfying the peak forming condition, and outputting in order; and step S5.3, selecting one peak with the largest peak value as the calibration crosstalk peak, and outputting the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak in the single-point dTOF histogram.

[0010] In some embodiments, step S6 specifically comprises: step S6.1, initializing a flag bit representing dust condition as 0, obtaining redundancy gap1 representing bin position and redundancy gap2 representing dust identification position, and threshold ratio of peak value; step S6.2, identifying an initial peak as a crosstalk peak when the peak value of the initial peak is less than Peak_X and the bin position of the peak value of the initial peak is less than POS_X+gap1; step S6.3, setting the flag bit as 2 when the peak value of an initial peak is greater than Peak_X, and if the bin position of the peak value of the initial peak is less than POS_X+gap2 and the peak value is greater than Peak_Xxratio, judging whether the flag bit meets a preset condition; and step S6.4, marking the confidence degree of the initial peak with a crosstalk peak and the flag bit not meeting the preset condition as 0.

[0011] In some embodiments, step S7 specifically comprises: converting the bin position of the confidence peak into a length unit and outputting, to obtain the distance of the target to be measured.

[0012] Embodiments of the present application provide a dTOF laser radar-based distance measuring device for a sweeping robot, which comprises: a dTOF laser radar, configured to generate a single-point dTOF histogram according to the time difference between the emission and reception of a light signal by the single-point dTOF laser radar; a reading unit, configured to read a plurality of peaks with the largest peak value from the single-point dTOF histogram and output the initial peaks in order of bin position; a confidence degree calculation unit, configured to calculate the confidence degree of each initial peak according to the noise level of the single-point dTOF histogram and the peak value of the initial peak; a trailing false peak judgment unit, configured to judge whether each initial peak has a trailing false peak according to the bin position of the initial peak and the relative size of the peak value of the initial peak, and mark the confidence degree of the trailing false peak as 0; a crosstalk peak judgment unit, configured to obtain the bin position POS_X and the peak value Peak_X of a calibration crosstalk peak of the sweeping robot cover in the single-point dTOF histogram, judge whether there is a crosstalk peak in the initial peaks according to the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak, and identify a flag bit representing dust condition, and mark the confidence degree of the initial peak with the crosstalk peak and the flag bit meeting a preset condition as 0; and a calculation unit, configured to select the peak with the highest confidence degree in the initial peaks as a confidence peak and output, and calculate the distance of the target to be measured through the confidence peak.

[0013] The dTOF laser radar-based distance measuring method for the sweeping machine provided in the embodiments of the present application can be applied to the sweeping machine, avoids the interference of excessive dust on the outer cover of the sweeping machine on distance measurement, improves the accuracy of distance measurement of the sweeping machine, and can remove the interference of the tailing false peak of the target peak, thereby improving the accuracy of distance measurement of the sweeping machine. In addition, the present application is suitable for different distances and different structures of the outer cover, and can process and cope with different degrees of dirt on the outer cover, and has universality and robustness. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 The flowchart of the dTOF laser radar-based distance measuring method for the sweeping machine provided in the embodiments of the present application is shown in the figure.

[0015] Figure 2 The histogram containing four obvious signal peaks provided in the embodiments of the present application is shown in the figure.

[0016] Figure 3 The example graph for calculating the tailing false peak provided in the embodiments of the present application is shown in the figure.

[0017] Figure 4 The schematic diagram of the peak forming condition provided in the embodiments of the present application is shown in the figure.

[0018] Figures 5 to 8 The judgment process of step S6 in the embodiments of the present application is shown in the figure. DETAILED DESCRIPTION

[0019] The specific embodiments of the present application will be described in more detail below with reference to the accompanying drawings. The advantages and features of the present application will be more apparent according to the following description. It should be noted that the drawings are very simplified and use non-precise proportions, and are only used to facilitate and clarify the purpose of assisting in the description of the embodiments of the present application.

[0020] In laser radar distance measurement, the histogram is an important means for calculating the distance of the target to be measured. The distance measurement principle of dToF is as follows: the transmitting end transmits a light beam to the distance measurement area. The reflected light beam is formed after the transmitted light beam reaches the target object and is reflected by the target object. Part of the photon signals of the reflected light beam are received by the receiving end. Each single photon in the photon signal is incident to the SPAD array (Singe Photon Avalanche Diode) to generate an avalanche signal. Then, the SAPD outputs the avalanche signal to the TDC. The TDC detects the time interval from the transmitting end to the avalanche. According to the time interval of each photon, the histogram of each photon is counted and counted. Finally, the statistical histogram is formed. The ordinate of the histogram represents the peak value, and the abscissa represents the bin position. According to the time corresponding to the peak value, the time T required for the light beam to be emitted from the transmitting end and received by the receiving end is determined, thereby completing the distance measurement process.

[0021] The embodiment of the present application provides a dTOF laser radar-based distance measuring method for a sweeping machine, Figure 1 The embodiment of the present application provides a dTOF laser radar-based distance measuring method for a sweeping machine, Figure 1 The method comprises the following steps:

[0022] In the embodiment of the present application, the dTOF laser radar comprises a laser, a photodetector avalanche diode, a time-to-digital converter and a processor, and the step 1 specifically comprises the following steps:

[0023] In the embodiment of the present application, the dTOF laser radar comprises a laser, a photodetector avalanche diode, a time-to-digital converter and a processor, and the step 1 specifically comprises the following steps:

[0024] In the embodiment of the present application, the dTOF laser radar comprises a laser, a photodetector avalanche diode, a time-to-digital converter and a processor, and the step 1 specifically comprises the following steps: Figure 2 As shown in the histogram provided in the embodiment of the present application and containing four obvious signal peaks, Figure 2 In the histogram, the three peaks with the highest peak values are taken as initial peaks, and the output order from large to small is (303, 4330), (803, 3483) and (103, 1782). In step S23, the three initial peaks are rearranged according to the bin position order from front to back and output. The output order of the initial peaks from front to back according to the bin position order is (103, 1782), (304, 4330) and (804, 3483).

[0025] Step S3, according to the noise level of the single-point dTOF histogram and the peak value of the initial peak, the confidence of the initial peak is calculated respectively; here, for the output initial peak, its credibility needs a measurement standard. In the present application, the confidence is used to describe the credibility of each peak, when the confidence is 100, the peak is considered as a credible signal peak, when the confidence is 0, the peak is considered as an uncredible signal peak; when the confidence is between 0 and 100, the confidence represents the credibility of the peak. According to the noise level of the single-point dTOF histogram and the peak value of the initial peak, the confidence of the three peaks is calculated respectively in the embodiment of the present application, and step S3 specifically includes: the confidence of each initial peak is obtained by calculating the ratio of the peak value of each initial peak to the noise of the single-point dTOF histogram. Here, the process of calculating the confidence of each initial peak includes:

[0026] if peak value >= upper

[0027] confidence = 100;

[0028] else if peak value <= lower

[0029] confidence = 0;

[0030] else

[0031] confidence = 100*(peak value-lower) / (upper-lower);

[0032] End

[0033] Here, when the ratio is higher than the preset ratio upper, the confidence of the initial peak is marked as 100, when the ratio is lower than the preset ratio lower, the confidence of the initial peak is marked as 0; if the ratio is between upper and lower, the confidence is calculated as a corresponding value between 100 and 0.

[0034] Due to the ringing phenomenon of the dTOF lidar well known to those skilled in the art, there will be a tailing false peak in the tailing of the signal peak of the dTOF histogram. In step S4, it is judged whether there is an abnormal tailing false peak and marked according to the relative position of the initial peak in the histogram and the relative size of the peak value. In step S4, it is judged whether each initial peak is a tailing false peak according to the bin position of the initial peak and the relative size of the initial peak value, and the initial peak confidence of the tailing false peak is marked as 0. Here, step S4 specifically includes: calculating the slope of the line connecting the peak values of each initial peak and each initial peak after it in turn; when the slope is lower than a threshold value, the initial peak at the bin position after is taken as a tailing false peak of the initial peak at the bin position before; and the confidence of the tailing false peak is marked as 0. For example, three initial peaks are in turn: the first peak, the middle peak and the last peak according to the bin position. First, the slope of the line connecting the peak values of the first peak and the middle peak is calculated. If the slope is higher than a threshold value, the middle peak is taken as a tailing false peak of the first peak, and the confidence of the tailing false peak middle peak is marked as 0. Figure 3 An example graph for calculating the tailing false peak provided for the embodiments of the present application is shown in FIG. 1. Figure 3 , Figure 3 A part of the single-point dTOF histogram is intercepted in FIG. 1, (103, 1193) is the first peak, and (127, 493) is the middle peak. The peak values of the first peak and the middle peak are connected, and the slope of the line connecting the peak values is calculated. When the absolute value of the slope exceeds a threshold value Th, it indicates that the slope of the line connecting the middle peak and the first peak is large, and the middle peak is judged to be a tailing false peak of the first peak, and the confidence of the middle peak is marked as 0. Then, the slope of the line connecting the first peak and the last peak is calculated. If the slope is higher than a threshold value, the last peak is considered to be a tailing peak of the first peak, and the confidence of the last peak is marked as 0. Then, the slope of the line connecting the middle peak and the last peak is calculated. If the slope is higher than a threshold value, the last peak is taken as a tailing false peak of the middle peak, and the confidence of the last peak is marked as 0.

[0035] In step S5, the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak of the robot cleaner cover in the single-point dTOF histogram are obtained. When the robot cleaner product is shipped, the robot cleaner cover will be calibrated, and the peak value and position of the crosstalk peak generated by the cover will be saved to facilitate dust recognition in the next step. The calibration crosstalk peak of the robot cleaner cover obtained here is the one obtained by the robot cleaner factory calibration. The marking process, i.e., step S5, specifically includes the following steps.

[0036] In step S5.1, the single-point dTOF histogram is truncated at a preset position. The preset position here needs to be determined according to the distance between the robot cleaner cover and the lidar. In the embodiments of the present application, the default truncation position is 60 cm. The truncation position is configured externally first, and then step S5.2 is performed.

[0037] Step S5.2, traverse the truncated single-point dTOF histogram, select all peaks meeting the peak forming condition and output in order; here, all peaks meeting the peak forming condition are output in order from small to large. In this embodiment, the peak forming condition is three-point peak forming, i.e. the low values Pn-1 and Pn+i at both ends and the high value Pn+i-1 between the low values Pn-1 and Pn+i exist in one peak, i is a positive integer greater than or equal to 1, for example, the low values at both ends are Pn-1 and Pn+3 respectively, and there are 3 high values Pn, Pn+1 and Pn+2. Figure 4 Figure 4

[0038] Step S5.3, select one peak with the largest peak value as the calibration crosstalk peak, and output the bin position POS_X of the calibration crosstalk peak in the single-point dTOF histogram and the peak value Peak_X.

[0039] Since the cover will be contaminated by dirt during the working process of the robot, a large crosstalk peak will be formed, which will affect the ranging, so it is necessary to identify and delete the crosstalk peak. After obtaining the position and size of the crosstalk peak caused by the cover, it is determined whether there is a crosstalk peak in the initial peak after deleting the tailing false peak, and the dust condition is identified, and the flag bit is uploaded to the whole machine. Step S6, according to the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak, it is determined whether there is a crosstalk peak in the initial peak, and the flag bit representing the dust condition is identified, and the confidence of the initial peak with the crosstalk peak and the flag bit not meeting the preset condition is marked as 0. Step S6 specifically includes:

[0040] Step S6.1, initialize the flag bit representing the dust condition to 0, obtain the redundancy gap1 representing the bin position and the redundancy gap2 representing the dust identification position, and the threshold ratio of the peak value. Here, the flag bit is initialized to 0, indicating that there is no dust or slight dust on the cover at this time. The gap1 can be configured as a positive integer between 2 and 8, and the threshold ratio of the peak value can be configured as a value between 0 and 1. The gap2 can be configured as a positive integer, and the value of the gap2 cannot be greater than the minimum value of the gap1 and 5. In this embodiment, the gap1 is 5 by default, the ratio is 0.5 by default, and the gap2 is 2 by default.

[0041] ​​Step S6.2: If the peak value of an initial peak is less than Peak_X, and the bin position of the peak value is less than POS_X+gap1, the initial peak is identified as a crosstalk peak. Step S6.3: If the peak value of an initial peak is greater than Peak_X, and the bin position of the peak value is less than POS_X+gap2, and its peak value is greater than Peak_X×ratio, the flag is set to 2, indicating that the flag meets a preset condition. The preset condition here is whether the flag is 2. When the flag is 2, the preset condition is met, indicating that there is a large signal nearby. It is uncertain whether this is caused by a nearby target or excessive dust on the outer casing, requiring joint judgment from other modules of the entire machine.

[0042] Step S6.4: Mark the confidence level of initial peaks that have crosstalk peaks and whose flags do not meet the preset conditions as 0. For each initial peak, determine whether its peak value is less than Peak_X and whether its bin position in the histogram is less than POS_X+gap1. If both conditions are met, the initial peak is considered to be a crosstalk peak generated by the outer casing. Then, determine whether the crosstalk peak value is greater than Peak_X×ratio. If the peak value is less than Peak_X×ratio, the flag remains at 0; if the peak value is greater than Peak_X×ratio, the flag is set to 1. If the flag is 0 or 1, it is determined that the flag does not meet the preset conditions, indicating that there is dust on the outer casing, the initial peak has crosstalk peaks, and the flag does not meet the preset conditions (i.e., the flag is not 2). Set both its peak value and confidence level to 0, that is, delete the crosstalk peak.

[0043] Figures 5 to 8 This is a schematic diagram of the judgment process in step S6 of this application embodiment, as shown below. Figure 5 As shown, the crosstalk peak (i.e.) is calibrated. Figure 4 The peak value is (63, 571), and the highest peak measured is (i.e. Figure 5 The measured peak is (73, 3517). At this time, no peak simultaneously satisfies the condition that the peak value is less than Peak_X and the position is less than POS_X+gap1, that is, there is no crosstalk peak. The flag bit is still 0, indicating that there is no dust on the outer cover at this time.

[0044] like Figure 6 As shown, the crosstalk peak (i.e.) is calibrated. Figure 6 The peak value is (63, 567), and the highest peak measured is (i.e. Figure 5 The measured peak is (67, 536). This peak simultaneously satisfies the condition that the peak value is less than Peak_X and the position is less than POS_X+gap1. This peak is identified as a crosstalk peak. Then, it is determined that the peak value is greater than ratio×Peak_X. The flag position is set to 1. At this time, it is determined that the preset conditions are not met. The peak value and confidence level are set to 0, indicating that there is a lot of dust on the outer cover at this time.

[0045] As shown in Figure 7 , the calibrated crosstalk peak (i.e., the calibrated peak in Figure 7 ) is (63, 603), and the measured first peak (i.e., the measured peak in Figure 7 ) is (67, 262), which satisfies both the condition of the peak value being less than Peak_X and the condition of the position being less than POS_X+gap1. This peak is identified as a crosstalk peak, but the peak value is less than ratio*Peak_X, and the flag bit is still 0. It is determined that the flag bit does not satisfy the preset condition, and the peak value and the confidence flag are marked as 0, indicating that there is less dust on the cover at this time.

[0046] As shown in Figure 8 , the calibrated crosstalk peak (i.e., the calibrated peak in Figure 8 ) is (63, 581), and the measured first peak (i.e., the measured peak in Figure 8 ) is (64, 747). The peak value is greater than Peak_X, and according to step S6.3, it is determined that the peak value bin position is less than POS_X+gap2 and the peak value is greater than ratio*Peak_X. The flag bit is set to 2, and it is determined that the flag bit satisfies the preset condition, indicating that there is a large peak at close range, and it is not determined whether it is caused by a close-range target or too much dust on the cover of the robot cleaner. It needs to be determined in combination with other modules of the whole machine.

[0047] Step S7: Select the peak with the highest confidence in the initial peaks as the confidence peak output, and calculate the distance of the target to be measured through the confidence peak. Through the above steps S1-S6, the confidence of some initial peaks that do not satisfy the condition is marked as 0. Therefore, the peak with the highest confidence is only selected from the remaining initial peaks as the confidence peak output in the following step S7. Step S7 specifically includes: converting the bin position of the confidence peak into a length unit and outputting to obtain the distance of the target to be measured. The conversion formula is shown in formula (1):

[0048] TOF = POS*LSB*C / 2 (1)

[0049] Where POS represents the bin position of the final selected confidence peak, LSB is the length of each time interval, which is 104 ps in the embodiments of the present application, and C represents the speed of light in a vacuum.

[0050] The dTOF laser radar based sweeping machine ranging method provided by the embodiment of the application can not only avoid the interference caused by too much dust on the sweeping machine cover, but also remove the interference of the tailing false peak of the target peak, thereby improving the accuracy of the sweeping machine ranging. In addition, the ranging method provided by the application can be applied to sweeping machine covers with different distances and different structures, and can process and cope with different degrees of dirt on the cover. Moreover, due to the consideration of multiple peaks, in complex scenes such as mirrors and glass, the most front signal peak can be selected for obstacle avoidance, and the ranging method has universality and robustness.

[0051] The embodiment of the application provides a dTOF laser radar based sweeping machine ranging device, and the device comprises:

[0052] The dTOF laser radar is used for generating a single-point dTOF histogram according to the time difference between the emission and reception of the light signal by the single-point dTOF laser radar; the reading unit is used for reading a plurality of peaks with the maximum peak value from the single-point dTOF histogram, and outputting the initial peaks in the order of bin positions; the confidence calculation unit is used for calculating the confidence of each initial peak according to the noise level of the single-point dTOF histogram and the peak value of the initial peak; the tailing false peak judgment unit is used for judging whether each initial peak has a tailing false peak according to the bin position of the initial peak and the relative size of the peak value of the initial peak, and marking the confidence of the tailing false peak as 0; the crosstalk peak judgment unit is used for obtaining the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak of the sweeping machine cover in the single-point dTOF histogram, judging whether there is a crosstalk peak in the initial peak according to the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak, and identifying a flag bit representing the dust condition, and marking the confidence of the initial peak with the crosstalk peak and the flag bit satisfying the preset condition as 0; and the calculation unit is used for selecting the peak with the highest confidence in the initial peak as a confidence peak for output, and calculating the distance of the target to be measured through the confidence peak.

[0053] In some embodiments, the dTOF laser radar comprises a laser, a photodetector avalanche diode, a time-to-digital converter and a processor, the laser is used for emitting N times of pulsed light signals to the target to be measured within a single frame measurement time; the photodetector avalanche diode is used for receiving the light signal reflected by the target to be measured; the time-to-digital converter is used for recording the time of flight between the emission and reception of the light signal; and the processor is used for histogram statistics of the N times of time of flight, and generates a single-point dTOF histogram through low-pass filtering.

[0054] The embodiment of the application provides a computer readable storage medium, and the computer readable storage medium stores an executable program, and the executable program is executed by a processor to implement any of the dTOF laser radar based sweeping machine ranging methods.

[0055] Any technical features in the above embodiments can be combined, and for brevity, not all possible combinations are described, however, any combination of the technical features is considered to be within the scope of the present disclosure.

[0056] The above only describes the preferred embodiments of the present application, and is not intended to limit the present application. Any skilled person in the art can make various changes, modifications, replacements and variations to these embodiments without departing from the principles and the scope of the present application, and the scope of the present application is defined by the claims and their equivalents.

Claims

1. A dTOF lidar-based ranging method for a robot vacuum cleaner, the method comprising: The method comprises: Step S1, generating a single-point dTOF histogram according to the time difference of the emission and reception of the light signal of the dTOF laser radar; Step S2, reading several peaks with the largest peak value from the single-point dTOF histogram, and outputting the initial peaks in the order of bin positions; Step S3, calculating the confidence of each initial peak according to the noise level of the single-point dTOF histogram and the peak value of the initial peak; Step S4, judging whether each initial peak is a tailing false peak according to the bin position of the initial peak and the relative size of the peak value of the initial peak, and marking the confidence of the tailing false peak as 0; Step S5, obtaining the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak of the robot cleaner cover in the single-point dTOF histogram; Step S6, judging whether there is a crosstalk peak in the initial peak according to the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak, and identifying a flag representing the dust condition, and marking the confidence of the initial peak with the crosstalk peak and the flag not satisfying the preset condition as 0; Step S7, selecting the peak with the highest confidence in the initial peak as the confidence peak output, and calculating the distance of the target to be measured through the confidence peak.

2. The method of claim 1, wherein, The dTOF laser radar comprises a laser, a photoelectric detection avalanche diode, a time-to-digital converter and a processor, and the step S1 specifically comprises: Step S1.1, the laser emits N times of pulsed light signals to the target to be measured within a single-frame measurement time; Step S1.2, the photoelectric detection avalanche diode receives the light signal reflected by the target to be measured; Step S1.3, the time-to-digital converter records the time of flight between the emission and the reception of the light signal; Step S1.4, the processor performs histogram statistics on the N times of the time of flight, and generates a single-point dTOF histogram through low-pass filtering.

3. The method of claim 2, wherein, Step S2 specifically comprises: Step S2.1, traversing the generated single-point dTOF histogram, and selecting all peaks meeting the peak forming condition; Step S2.2, arranging all peaks meeting the condition in descending order of peak value, and selecting several peaks with the largest peak value as initial peaks; Step S2.3, rearranging the several initial peaks in the order of their bin positions from front to back, and outputting.

4. The method of claim 3, wherein, Step S3 specifically comprises: The confidence of each initial peak is obtained by calculating the ratio of the peak value of each initial peak to the noise of the single-point dTOF histogram.

5. The method of claim 3, wherein, Step S4 specifically comprises: The slope of the connecting line of the peak value of each initial peak and the peak value of each initial peak after it is calculated in sequence; When the slope is lower than a threshold value, the initial peak at the latter bin position is taken as a tailing false peak of the initial peak at the former bin position; The confidence of the tailing false peak is marked as 0.

6. The method of claim 3, wherein, In step S5, the marking process of the calibration crosstalk peak of the robot cleaner cover comprises: Step S5.1, truncating the single-point dTOF histogram at a preset position; Step S5.2, traversing the truncated single-point dTOF histogram, selecting all peaks meeting the peak forming condition, and outputting in sequence; Step S5.3, selecting one peak with the largest peak value as a calibration crosstalk peak, and outputting the bin position POS_X of the calibration crosstalk peak in the single-point dTOF histogram and the peak value Peak_X.

7. The method of claim 3, wherein, Step S6 specifically includes: Step S6.1, initializing a flag representing the dust condition to 0, obtaining the redundancy gap1 representing the bin position and the redundancy gap2 representing the dust identification position, and the threshold ratio of the peak value; Step S6.2, identifying the initial peak as a crosstalk peak when the peak value of the initial peak is less than Peak_X, and the bin position of the peak value of the initial peak is less than POS_X+gap1; Step S6.3, setting the flag to 2 when the peak value of the initial peak is greater than Peak_X, and the bin position of the peak value of the initial peak is less than POS_X+gap2, and the peak value is greater than Peak_X×ratio, and determining whether the flag meets the preset condition; Step S6.4, marking the confidence of the initial peak with the crosstalk peak and the flag not meeting the preset condition as 0.

8. The method of claim 3, wherein, Step S7 specifically includes: Converting the bin position of the confidence peak into a length unit and outputting to obtain the distance of the target to be measured. 9.A dTOF laser radar based ranging device for a robot vacuum cleaner, characterized in that, The device includes: a dTOF laser radar for generating a single-point dTOF histogram according to the time difference between the emission and reception of the optical signal by the single-point dTOF laser radar; a reading unit for reading a plurality of peaks with the largest peak value from the single-point dTOF histogram, and outputting the initial peaks in order of bin position; a confidence calculation unit for calculating the confidence of each initial peak according to the noise level of the single-point dTOF histogram and the peak value of the initial peak; a tailing false peak judgment unit for judging whether each initial peak is a tailing false peak according to the bin position of the initial peak and the relative size of the peak value of the initial peak, and marking the confidence of the initial peak of the tailing false peak as 0; a crosstalk peak judgment unit for obtaining the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak of the outer cover of the sweeping machine in the single-point dTOF histogram, judging whether there is a crosstalk peak in the initial peak according to the bin position POS_X and the peak value Peak_X of the calibration crosstalk peak, and identifying a flag representing the dust condition, and marking the confidence of the initial peak with the crosstalk peak and the flag meeting the preset condition as 0; a calculation unit for selecting the peak with the highest confidence in the initial peak as a confidence peak output, and calculating the distance of the target to be measured through the confidence peak.

10. A computer-readable storage medium storing an executable program, the computer-readable storage medium comprising: The executable program is executed by the processor to implement the dTOF laser radar-based sweeping machine ranging method of any one of claims 1-8. The executable program is executed by the processor to implement the dTOF laser radar-based sweeping machine ranging method of any one of claims 1-8.

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