STATIC OBJECT DETECTION FOR OPERATING AUTONOMOUS VEHICLE
A system to use submaps to control operation of a vehicle is disclosed. A storage system may be provided with a vehicle to store a collection of submaps that represent a geographic area where the vehicle may be driven. A programmatic interface may be provided to receive submaps and submap updates independently of other submaps.
1 . A method for autonomously operating a vehicle, the method comprising:
obtaining sensor data collected by the vehicle traversing an area of a road segment;
accessing data, determined from sensor data previously captured from the area of the road segment, to determine a set of static objects; and
processing the sensor data collected by the vehicle to determine one or more objects that are present in the traversed area, including reducing a quantity of sensor data that is processed based on the accessed data that identifies the set of static objects.
2 . The method of claim 1 , wherein accessing the data includes obtaining a submap for the road segment, the submap identifying a set of static objects that have previously been determined to be present in an area of the road segment.
3 . The method of claim 2 , wherein accessing the data includes obtaining image data of a scene as the vehicle traverses over the road segment, and wherein the submap includes image data to identify the set of static objects.
4 . The method of claim 3 , wherein the image data includes one of depth image data or Lidar data.
5 . The method of claim 1 , wherein reducing the quantity of the sensor data includes processing only a portion of sensor data collected from a scene of the area for the road segment, the portion of sensor data excluding the set of static objects.
6 . The method of claim 1 , wherein processing the sensor data includes determining a set of present objects from the sensor data obtained of the scene; and
determining a subset of the present objects which are dynamic objects based on the set of static objects.
7 . The method of claim 1 , wherein obtaining sensor data includes obtaining Lidar data of a scene as the vehicle traverses over the road segment, and wherein the accessed data includes Lidar data to identify the set of static objects.
8 . The method of claim 1 , wherein processing the sensor data includes limiting sensor processing of a scene of the road segment, based at least in part on one or more static objects in the set of static objects.
9 . The method of claim 8 , wherein limiting sensor processing of the scene includes processing image data at discrete regions near each static object in the set of static objects.
10 . The method of claim 2 , further comprising:
previously recording sensor data from a sensor set of the vehicle when the vehicle is on a trip that includes the road segment;
determining one or more of the set of static objects from the recorded sensor data; and
incorporating image data with the submap for the road segment to identify the set of static objects.
11 . The method of claim 10 , wherein obtaining the submap includes retrieving the submap from a network submap service.
12 . The method of claim 1 , wherein the accessed data includes data collected from sensors of one or more vehicles traversing the area of the road segment at one or more previous instances.
13 . The method of claim 12 , wherein the accessed data includes semantic labels for one or more static objects that are present in a scene of the road segment.
14 . The method of claim 13 , wherein processing sensor data includes processing image data captured by at least one of a Lidar, video camera, or stereoscopic camera in regions of the scene that substantially exclude the set of static objects.
15 . The method of claim 14 , wherein processing the sensor data includes:
processing image data of the scene, as captured by one or more image sensors of the vehicle, to detect one or more objects that are present in the scene; and
making a determination, from the stored data, as to whether any one or more of the detected objects are one of the set of static objects.
16 . The method of claim 15 , wherein making the determination includes implementing a transformation to the image data of the scene to account for an approximate difference as between a location of the vehicle where the image data is captured for processing and a location where image data for determining the set of static objects is captured.
17 . The method of claim 16 , wherein implementing the transformation includes warping image data captured by the one or more image sensors of the vehicle.
18 . The method of claim 15 , wherein making the determination includes implementing a transformation to the image data of the scene to account for an approximate difference between an environmental or lighting condition for the vehicle when the image data is captured for processing and an environmental or lighting condition for when image data for determining the set of static objects is captured.
19 . A computer system comprising:
a memory to store a set of instructions;
one or more processors to use the set of instructions to:
obtain sensor data collected by the vehicle traversing an area of a road segment;
access data, determined from sensor data previously captured from the area of the road segment, to determine a set of static objects; and
process the sensor data collected by the vehicle to determine one or more objects, including reducing a quantity of sensor data that is processed based on the accessed data that identifies the set of static objects.
20 . The computer system of claim 19 , wherein the computer system is provided on an autonomous vehicle.
21 . The computer system of claim 19 , wherein the computer system communicates with an autonomous vehicle over a network.