US 12,468,041 B2
System, method, and components providing compressive active range sampling
Jerramy Lee Gipson, Willits, CA (US)
Assigned to VOLKSWAGEN AKTIENGESELLSCHAFT, (DE); AUDI AG, (DE); and DR. ING. H.C.F. PORSCHE AKTIENGESELLSCHAFT, (DE)
Appl. No. 17/420,468
Filed by VOLKSWAGEN AKTIENGESELLSCHAFT, Wolfsburg (DE); AUDI AG, Ingolstadt (DE); and DR. ING. H.C.F. PORSCHE AKTIENGESELLSCHAFT, Stuttgart (DE)
PCT Filed Jan. 3, 2020, PCT No. PCT/US2020/012166
§ 371(c)(1), (2) Date Jul. 2, 2021,
PCT Pub. No. WO2020/142675, PCT Pub. Date Jul. 9, 2020.
Claims priority of provisional application 62/787,934, filed on Jan. 3, 2019.
Prior Publication US 2022/0082701 A1, Mar. 17, 2022
Int. Cl. G01S 17/931 (2020.01); G01S 7/481 (2006.01); G01S 17/58 (2006.01)
CPC G01S 17/931 (2020.01) [G01S 7/4815 (2013.01); G01S 7/4817 (2013.01); G01S 17/58 (2013.01)] 23 Claims
OG exemplary drawing
 
1. A system utilizing a random access scanning LiDAR sensor for object detection to implement assistive and/or autonomous driving functionality in a transportation vehicle, the system comprising:
at least one random access scanning LiDAR sensor; and
at least one data processor running a software algorithm stored in memory, the software algorithm being configured to control scheduling of individual rays for emission of range determining laser pulses generated by the at least one random access scanning LiDAR sensor to generate ray samples which are then analyzed to calculate expected potential range changes for the rays,
wherein the calculated expected potential range changes are then used to schedule subsequent emission of range determining laser pulses by the at least one random access scanning LiDAR sensor such that laser pulse generation and ray sample generation for individual rays with a larger expected potential range change is performed more frequently than laser pulse generation and ray sample generation for individual rays with a smaller expected potential change so as to provide compressive active range scanning,
wherein the compressive active range scanning maximizes information delivery by the at least one data processor running the software algorithm to generate ray request packets that request rays where the most change from a previous sampling of that ray is expected, whereby a given ray, as considered in a reference frame of the at least one random access scanning LiDAR sensor, is re-sampled more quickly based on an increased uncertainty of a likely result, thereby indicating an information-rich sample location.