US 12,270,662 B2
Map generation using two sources of sensor data
Wolfgang Hess, Munich (DE); Luca Del Pero, London (GB); Daniel Sievers, Mountain View, CA (US); and Holger Rapp, Munich (DE)
Assigned to Lyft, Inc., San Francisco, CA (US)
Filed by Lyft, Inc., San Francisco, CA (US)
Filed on Jun. 30, 2020, as Appl. No. 16/917,738.
Prior Publication US 2021/0404814 A1, Dec. 30, 2021
Int. Cl. G01C 21/32 (2006.01); G06T 7/00 (2017.01); G06T 7/73 (2017.01); G06T 17/05 (2011.01); G06V 20/56 (2022.01)
CPC G01C 21/32 (2013.01) [G06T 7/75 (2017.01); G06T 7/97 (2017.01); G06T 17/05 (2013.01); G06V 20/56 (2022.01); G06T 2207/30241 (2013.01); G06T 2207/30252 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving first data of one or more geographical environments from comprising first sensor data captured by a first type of localization sensor associated with a vehicle;
receiving second data of the one or more geographical environments from comprising second sensor data captured by a second type of localization sensor associated with the vehicle;
generating (i) a first set of submaps from the first data and (ii) a second set of submaps from the second data;
determining (i) a first set of constraints from the first data, wherein the first set of constraints comprises one or both of intra-submap constraints or inter-submap constraints for the first set of submaps, and (ii) a second set of constraints from the second data, wherein the second set of constraints comprises one or both of intra-submap constraints or inter-submap constraints for the second set of submaps;
merging the first set of constraints determined from the first data with the second set of constraints determined from the second data to form a combined set of constraints; and
applying a combined optimization process to the first set of submaps, the second set of submaps, and the combined set of constraints, wherein the combined optimization process functions to:
determine a single combined trajectory of the vehicle that minimizes an overall error relative to the combined set of constraints;
generate a first map that is (i) built from both the first data and the second data and (ii) thereafter utilized to localize a first set of vehicles that are installed with the first type of localization sensor but not the second type of localization sensor; and
generate a second map that is (i) built from both the first data and the second data and (ii) thereafter utilized to localize a second set of vehicles that are installed with the second type of localization sensor but not the first type of localization sensor.