View source for Waymo llc (20240201391). Differential Methods for Environment Estimation, Lidar Impairment Detection, and Filtering simplified abstract

=Differential Methods for Environment Estimation, Lidar Impairment Detection, and Filtering=


==Organization Name==

[[:Category:waymo llc|waymo llc]]


[[Category:waymo llc]]

==Inventor(s)==

[[:Category:Jingyuan Linda Zhang of Menlo Park CA (US)|Jingyuan Linda Zhang of Menlo Park CA (US)]][[Category:Jingyuan Linda Zhang of Menlo Park CA (US)]]

[[:Category:Kanika Sachdev of Sunnyvale CA (US)|Kanika Sachdev of Sunnyvale CA (US)]][[Category:Kanika Sachdev of Sunnyvale CA (US)]]

[[:Category:Caner Onal of Palo Alto CA (US)|Caner Onal of Palo Alto CA (US)]][[Category:Caner Onal of Palo Alto CA (US)]]

[[:Category:Michael Marx of Mountain View CA (US)|Michael Marx of Mountain View CA (US)]][[Category:Michael Marx of Mountain View CA (US)]]

[[:Category:Yuchi Wang of Ann Arbor MI (US)|Yuchi Wang of Ann Arbor MI (US)]][[Category:Yuchi Wang of Ann Arbor MI (US)]]

==Differential Methods for Environment Estimation, Lidar Impairment Detection, and Filtering - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240201391 titled 'Differential Methods for Environment Estimation, Lidar Impairment Detection, and Filtering

'''Simplified Explanation:'''
The patent application discusses a method for determining environmental estimation, detecting lidar impairment, and filtering using differential techniques.

'''Key Features and Innovation:'''
* Division of lidar device channels into two groups and interleaving them.
* Applying a threshold to one group of channels to sample return light pulses.
* Determining a differential in statistical distribution to detect atmospheric scattering medium.

'''Potential Applications:'''
This technology can be used in autonomous vehicles, environmental monitoring, and industrial automation for accurate environmental estimation and detection of lidar impairment.

'''Problems Solved:'''
This technology addresses the challenges of accurately estimating environmental conditions and detecting lidar impairment in various applications.

'''Benefits:'''
* Enhanced accuracy in environmental estimation.
* Improved detection of lidar impairment.
* Efficient filtering of lidar data for better decision-making.

'''Commercial Applications:'''
The technology can be applied in autonomous vehicles, smart cities, agricultural monitoring, and industrial automation for improved safety and efficiency.

'''Prior Art:'''
Readers can explore prior research on lidar technology, environmental estimation methods, and atmospheric scattering detection to understand the background of this innovation.

'''Frequently Updated Research:'''
Stay updated on advancements in lidar technology, environmental sensing, and statistical analysis techniques for continuous improvement in environmental estimation and lidar impairment detection.

'''Questions about Lidar Impairment Detection:'''
1. How does this technology improve the accuracy of lidar impairment detection?
2. What are the potential challenges in implementing this differential method for lidar impairment detection?

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==Original Abstract Submitted==

example embodiments relate to differential methods for determining environment estimation, lidar impairment detection, and filtering. an example embodiment includes dividing a plurality of lidar device channels into a first group and a second group and interleaving the channels. the embodiment includes applying a threshold to the first group. the embodiment further includes emitting light pulses from a lidar device into an environment surrounding the lidar device, and detecting return light pulses. the return light pulses in the first group of channels are sampled from the signals that exceed the threshold. the embodiment may further include determining a differential in a statistical distribution between the return light pulses in the first group and the return light pulses in the second group. based on the differential, the method can include detecting an atmospheric scattering medium in the environment surrounding the lidar device.



[[Category:G01S17/95]]
[[Category:G01S7/487]]
[[Category:G01S17/42]]
[[Category:CPC_G01S17/95]]