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EP-3914929-B1 - METHODS AND SYSTEMS FOR DETECTING DEGRADED LIDAR RANGE MEASUREMENT ACCURACY

EP3914929B1EP 3914929 B1EP3914929 B1EP 3914929B1EP-3914929-B1

Inventors

  • GASSEND, BLAISE
  • OSBORN, STEPHEN
  • MORTON, PETER

Dates

Publication Date
20260506
Application Date
20200305

Claims (15)

  1. A method comprising: repeatedly scanning a range of angles in a field-of-view (FOV) of a light detection and ranging (LIDAR) device (200); for each scan of the range of angles, detecting a plurality of light pulses intercepted at a light detector (232) of the LIDAR device during a plurality of successive detection periods, wherein the light detector is configured to intercept light from a different angle in the range of angles during each of the plurality of successive detection periods of the scan; comparing a first scan of the range of angles obtained using the light detector with a second scan subsequent to the first scan; and based on the comparison, detecting onset of a saturation recovery period of the light detector during the first scan or the second scan.
  2. The method of claim 1, further comprising: emitting one or more light pulses (260) from the LIDAR device toward the FOV, wherein the detected plurality of light pulses comprise reflected portions of the one or more emitted light pulses that are reflected back to the LIDAR device from the FOV.
  3. The method of claim 1, further comprising: identifying one or more scans of the range of angles that are obtained during the saturation recovery period of the light detector.
  4. The method of claim 1, wherein comparing the first scan with the second scan comprises comparing first light intensity measurements indicated by first outputs from the light detector for first light pulses detected during the first scan with second light intensity measurements indicated by second outputs from the light detector for second light pulses detected during the second scan.
  5. The method of claim 4, wherein comparing the first light intensity measurements with the second light intensity measurements comprises comparing respective maximum values of the first light intensity measurements and the second light intensity measurements.
  6. The method of claim 5, wherein detecting onset of the saturation recovery period is based on a difference between the respective maximum values exceeding a threshold difference.
  7. The method of claim 1, further comprising: determining, based on at least a light intensity measurement indicated by output from the light detector for a detected light pulse of the detected plurality of light pulses, a time-of-flight of an emitted light pulse emitted from the LIDAR device toward the FOV and at least partially reflected back from the FOV toward the LIDAR device as the detected light pulse.
  8. The method of claim 7, wherein the method further comprises: determining whether the detected light pulse is detected at the light detector during the saturation recovery period, wherein determining the time-of-flight is further based on the determination of whether the detected light pulse is detected during the saturation recovery period.
  9. The method of claim 1, further comprising: detecting foreign object debris (FOD) in the FOV of the LIDAR device based on at least an apparent size of the FOD indicated by data from the LIDAR device being less than an FOD detection threshold.
  10. The method of claim 9, further comprising: generating a three-dimensional (3D) representation of the FOV based on at least light intensity measurements indicated by outputs from the light detector for the detected plurality of light pulses; and excluding the FOD from the generated 3D representation of the FOV.
  11. The method of claim 9, further comprising: in response to detecting the onset of the saturation recovery period, adjusting the FOD detection threshold for one or more scans of the range of angles obtained during the saturation recovery period of the light detector.
  12. Computer executable instructions which, when executed by at least one processor of a light detection and ranging (LIDAR) device according to any of claims 13-15, cause the method of any of claims 1-11 to be performed.
  13. A light detection and ranging (LIDAR) device (200) comprising: a light detector (232); one or more optical elements configured to direct light received by the LIDAR device from a field-of-view (FOV) onto the light detector; a controller (104) configured to cause the LIDAR device to perform operations comprising: repeatedly scanning across a range of angles in the FOV; for each scan of the range of angles, detecting a plurality of light pulses intercepted at the light detector during a plurality of detection periods, wherein the light detector is configured to intercept light from a different angle in the range of angles during each of the plurality of detection periods of the scan; comparing a first scan of the range of angles obtained using the light detector with a second scan subsequent to the first scan; and based on the comparison, detecting onset of a saturation recovery period of the light detector.
  14. The LIDAR device of claim 13, further comprising: a light emitter (222) configured to emit one or more light pulses (260) toward the FOV, wherein the detected plurality of light pulses correspond to reflected portions of the one or more emitted light pulses that are reflected back from the FOV toward the LIDAR device.
  15. The LIDAR device of claim 13, wherein the one or more optical elements comprise: a rotating mirror (244) configured to direct the light received by the LIDAR device from different angles toward the light detector based on corresponding rotational positions of the rotating mirror.

Description

CROSS-REFERENCE TO RELATED APPLICATION This application claims priority to U.S. Provisional Patent Application No. 62/814,236 filed on March 5, 2019. BACKGROUND Active sensors, such as light detection and ranging (LIDAR) sensors, radio detection and ranging (RADAR) sensors, sound navigation and ranging (SONAR) sensors, among others, are sensors that can scan a surrounding environment by emitting signals toward the surrounding environment and detecting reflections of the emitted signals. For example, a LIDAR sensor can determine distances to environmental features while scanning through a scene to assemble a "point cloud" indicative of reflective surfaces in the environment. Individual points in the point cloud can be determined, for example, by transmitting a laser pulse and detecting a returning pulse, if any, reflected from an object in the environment, and then determining a distance to the object according to a time delay between the transmission of the pulse and the reception of the reflected pulse. As a result, for example, a three-dimensional map of points indicative of locations of reflective features in the environment can be generated. 'In situ characterization of grain-scale fluvial morphology using Terrestrial Laser Scanning' by Rebecca Hodge, James Brasington and Keith Richards (Earth Surface Processes and Landforms 34, 954-968), referred to below as "Hodge", presents laboratory and field experiments designed to evaluate close range TLS (Terrestrial Laser Scanning) for sedimentological applications and to develop protocols for data acquisition. In relation to "Experiment 1: Quantifying and Developing a Typology of TLS Errors", Hodge states under a sub heading of "Surface reflectivity" that "[t]he comparison of the TLS data to planes fitted to the TS data enables systematic errors caused by surface reflectivity to be evaluated. It is expected that more reflective surfaces will result in earlier saturation of the scanner sensor, producing shorter flight times and hence an underestimate of the actual range. As above, least-squares planes were fitted to the TS data for each differently coloured surface, which is assumed to be less susceptible to the saturation errors known to confound TLS data." Under a later sub heading of "Target geometry", Hodge introduces "[a] metric, termed repeat scan error value (RSEV), defined as the maximum 3D distance between repeat measurements of a point" (Equation 1). Hodge states under the "Target geometry" sub heading that "[t]he RSEV was found to be a useful discriminator to identify mixed pixel errors". SUMMARY In one example, a method is provided. The method involves repeatedly scanning a range of angles in a field-of-view (FOV) of a light detection and ranging device. The method also involves detecting, for each scan of the range of angles, a plurality of light pulses during a plurality of successive detection periods. The light detector may be configured to intercept light from a different angle in the range of angles during each of the plurality of successive detection periods of the scan. The method also involves comparing a first scan of the range of angles obtained using the light detector with a second scan subsequent to the first scan. The method also involves detecting onset of a saturation recovery period of the light detector during the first scan or the second scan based on the comparison. In another example, a light detection and ranging (LIDAR) device is provided. The LIDAR device includes a light detector and one or more optical elements configured to direct light received by the LIDAR device from a field-of-view (FOV) onto the light detector. The LIDAR device also includes a controller configured to cause the LIDAR device to perform operations. The operations comprise repeatedly scanning the light detector across a range of angles in the FOV. The operations also comprise detecting, for each scan of the range of angles, a plurality of light pulses intercepted at the light detector during a plurality of detection periods. The light detector may be configured to intercept light form a different angle in the range of angles during each of the plurality of detection periods of the scan. The operations also comprise comparing a first scan of the range of angles obtained using the light detector with a second scan subsequent to the first scan. The operations also comprise detecting onset of a saturation recovery period of the light detector based on the comparison. In yet another example, a method is provided. The method involves receiving, from a light detection and ranging (LIDAR) device, an indication of a plurality of scans of a range of angles in a field-of-view (FOV). The LIDAR device may be configured to repeatedly scan the range of angles using a light detector of the LIDAR device. The method also involves identifying, for each scan of the range of angles, a plurality of light pulses received at different angles in the range of angles. The plurali