Multi-Resolution Maps for Localization

Patent metadata

Field	Value
Publication number	US-2020003897-A1
Application number	US-201816022048-A
Country	US
Kind code	A1
Filing date	Jun 28, 2018
Priority date	Jun 28, 2018
Publication date	Jan 2, 2020
Grant date	—

Abstract

Techniques are discussed for using multi-resolution maps, for example, for localizing a vehicle. Map data of an environment can be represented by discrete map tiles. In some cases, a set of map tiles can be precomputed as contributing to localizing the vehicle in the environment, and accordingly, the set of map tiles can be loaded into memory when the vehicle is at a particular location in the environment. Further, a level of detail represented by the map tiles can be based at least in part on a distance between a location associated with the vehicle and a location associated with a respective region in the environment. The level of detail can also be based on a speed of the vehicle in the environment. The vehicle can determine its location in the environment based on the map tiles and/or the vehicle can generate a trajectory based on the map tiles.

First claim

What is claimed is:

1 . A system comprising:
one or more processors; and one or more computer-readable media storing instructions executable by the one or more processors, wherein the instructions, when executed, cause the system to perform operations comprising:
capturing LIDAR data using a LIDAR sensor of an autonomous vehicle;
determining, based at least in part on the LIDAR data, a first location associated with the autonomous vehicle in an environment;
determining a distance between the first location and a second location associated with a region in the environment;
determining that the distance meets or exceeds a threshold distance;
selecting, based at least in part on the distance meeting or exceeding the threshold distance, a resolution level from at least a first resolution level and a second resolution level;
loading, into a working memory accessible to the one or more processors, map data associated with the region, wherein the region in the environment is represented at the resolution level in the map data; and
localizing the autonomous vehicle based at least in part on the map data and the LIDAR data.

2 . The system of claim 1 , wherein the first location is associated with a first time, wherein the distance is a first distance associated with the first time, wherein the resolution level is the first resolution level, and wherein the map data is first map data, the operations further comprising:
determining a second distance between a third location of the autonomous vehicle and the second location associated with the region in the environment at a second time; determining that the second distance is below the threshold distance; selecting, based at least in part on the second distance being below the threshold distance, the second resolution level, wherein the second resolution level is higher than the first resolution level; unloading, from the working memory and based at least in part on second distance being below the threshold distance, the first map data; and loading, into the working memory, second map data associated with the region, wherein the second map data represents the region in the environment at the second resolution level.

3 . The system of claim 2 , wherein the region is a first region, the operations further comprising:
determining that third map data is stored in the working memory, wherein the third map data represents a second region in the environment at the second resolution level; determining a third distance between the third location associated with the autonomous vehicle and a fourth location associated with the second region in the environment; determining that the third distance meets or exceeds the threshold distance; unloading, from the working memory and based at least in part on the third distance meeting or exceeding the threshold distance, the third map data; and loading, into the working memory, fourth map data associated with the second region, wherein the fourth map data represents the second region in the environment at the first resolution level.

4 . The system of claim 1 , wherein the map data comprises a three-dimensional mesh of the region in the environment.

5 . The system of claim 1 , wherein:
the resolution level is the first resolution level; the map data comprises a map tile representing the region in the environment; an area representing a least a portion of the environment around the autonomous vehicle is represented by a plurality of map tiles individually loaded into the working memory; a first portion of the area is represented by one or more first map tiles associated with the first resolution level; and a second portion of the area is represented by one or more second map tiles associated with the second resolution level that is different than the first resolution level.

6 . A method comprising:
determining a first location associated with a sensor system in an environment; determining a distance between the first location and a second location associated with a region in the environment; loading, into a working memory associated with a computing device of the sensor system, map data representing the region in the environment, wherein a level of detail associated with the map data is based at least in part on the distance; capturing, by the sensor system, sensor data; and performing an action based at least in part on the map data and the sensor data, wherein the action includes at least one of a localization action, a perception action, a prediction action, or a planning action.

7 . The method of claim 6 , the localization action further comprising:
receiving LIDAR data captured by a LIDAR sensor of the sensor system; and localizing the sensor system in the environment based at least in part on the LIDAR data and the map data.

8 . The method of claim 6 , wherein the first location is associated with a first time, wherein the distance is a first distance associated with the first time, wherein the map data is first map data, and wherein the level of detail is a first level of detail, the method further comprising:
determining a third location associated with the sensor system at a second time; determining a second distance between the third location and the second location associated with the region in the environment; determining that the second distance is under a threshold distance; unloading, from the working memory, the first map data; and loading, into the working memory, second map data representing the region of the environment at a second level of detail.

9 . The method of claim 8 , the method further comprising:
determining a fourth location associated with the sensor system at a third time; determining a third distance between the fourth location and the second location associated with the region at the third time; determining that the third distance meets or exceeds the threshold distance; unloading, from the working memory, the second map data; and loading, into the working memory, the first map data representing the region of the environment at the first level of detail.

10 . The method of claim 8 , wherein the second level of detail comprises a higher level of detail than the first level of detail.

11 . The method of claim 8 , wherein the first map data comprises a first three-dimensional (3D) mesh associated with a first decimation level and the second map data comprises a second 3D mesh associated with a second decimation level.

12 . The method of claim 6 , wherein the working memory is random access memory accessible to a graphics processing unit.

13 . The method of claim 6 , wherein:
the level of detail is a first level of detail; the map data comprises a map tile representing the region in the environment; an area representing a least a portion of the environment around the sensor system is represented by a plurality of map tiles individually loaded into the working memory; a first portion of the area is represented by one or more first map tiles associated with the first level of detail; and a second portion of the area is represented by one or more second map tiles associated with a second level of detail that is different than the first level of detail.

14 . The method of claim 6 , wherein:
the map data is one of a plurality of map tiles representing an area of the environment; a size of the area is based at least in part on a range of a sensor of the sensor system; and wherein a number of map tiles of the plurality of map tiles is based at least in part on a size of the working memory allocated to localizing the sensor system or a memory size

Assignees

• Zoox Inc

Inventors

• Shroff Nitesh
• Rebsamen Brice
• Stumm Elena Stephanie

Classifications

• G06T17/05 Primary

  Geographic models · CPC title

• G01S17/86 Primary

  Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders · CPC title

• G06T2210/36

  Level of detail · CPC title

• G01C21/28

  with correlation of data from several navigational instruments · CPC title

• G01S17/10

  using transmission of interrupted, pulse-modulated waves (determination of distance by phase measurements G01S17/32) · CPC title