Object bounding box estimation

• US 9,256,226 B1
• Filed: 04/15/2014
• Issued: 02/09/2016
• Est. Priority Date: 01/30/2012
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Zhu, Jiajun, Haehnel, Dirk
• Primary Examiner(s): Tweel, Jr., John A
• Application Number:
  US14/252,966
• Time in Patent Office: 665 Days
• Field of Search: 701/26, 701/1, 340/933, 340/937, 180/169, 382/103, 382/104, 348/148
• US Class Current: 1/1
• CPC Class Codes: B60K 31/0008 including means for detecting potential obstacles in vehicle path
• CPC Class Codes: B60W 2552/35 Road bumpiness, e.g. potholes
• CPC Class Codes: G01S 17/42 Simultaneous measurement of distance and other co-ordinates indirect measurement G01S17/46
• CPC Class Codes: G01S 17/931 of land vehicles
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G05D 1/024 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

Abstract

Aspects of the disclosure relate generally to maneuvering autonomous vehicles. Specifically, the vehicle may use a laser to collect scan data for a section of roadway. The vehicle may access a detailed map including the section of the roadway. A disturbance indicative of an object and including a set of data points data may be identified from the scan data based on the detailed map. The detailed map may also be used to estimate a heading of the disturbance. A bounding box for the disturbance may be estimated using the set of data points as well as the estimated heading. The parameters of the bounding box may then be adjusted in order to increase or maximize the average density of data points of the disturbance along the edges of the bounding box visible to the laser. This adjusted bounding box may then used to maneuver the vehicle.

Claims

1. A method for maneuvering a vehicle, the method comprising:

selecting, by one or more processors, a set of points from a plurality of data points generated by a sensor, each data point of the plurality of data points representing a three-dimensional location of a point corresponding to a surface of an object located on a section of roadway, the set of points being indicative of an object in the section of roadway;

estimating, by the one or more processors, a bounding box for the set of points based on a detailed map of the section of roadway;

projecting, by the one or more processors, the set of data points onto a two-dimensional intensity map within the estimated bounding box;

identifying, by the one or more processors, an edge of the bounding box visible to the sensor;

adjusting, by the one or more processors, a parameter of the estimated bounding box in order to increase a number of data points of the set of data points projected along the identified edge; and

using, by the one or more processors, the estimated bounding box including the adjusted parameter to maneuver the vehicle.

2. The method of claim 1, wherein the sensor includes a laser and the plurality of data points are generated from the laser scanning the section of the roadway.

3. The method of claim 1, wherein the set of data points is further identified by selecting data points of the plurality of data points that satisfy a threshold elevation above a surface of the section of roadway identified in the detailed map.

4. The method of claim 1, further comprising estimating a heading of the set of data points based on the detailed map.

5. The method of claim 4, wherein the detailed map includes information indicating a direction of a lane and estimating the heading is further based on the information indicating the direction of the lane.

6. The method of claim 1, wherein the parameter is adjusted in order to maximize the number of data points of the set of data points along the identified edge.

7. The method of claim 1, wherein the parameter of the estimated bounding box includes a location of the identified edge.

8. The method of claim 1, further comprising:

receiving additional data points generated by the sensor corresponding to the object; and

using the estimated bounding box and adjusted parameter to estimate a new bounding box for the object based on the received additional data points.

9. The method of claim 1, further comprising:

receiving sensor data from a second sensor of a different type from the sensor, and

wherein the received sensor data from the second sensor is further used to estimate the estimated bounding box.

10. A system for maneuvering a vehicle, the system comprising:

one or more processors configured to;

select a set of points from a plurality of data points generated by a sensor, each data point of the plurality of data points representing a three-dimensional location of a point corresponding to a surface of an object located on a section of roadway, the set of points being indicative of an object in the section of roadway;

estimate a bounding box for the set of points based on a detailed map of the section of roadway;

project the set of data points onto a two-dimensional intensity map within the estimated bounding box;

identify an edge of the bounding box visible to the sensor;

adjust a parameter of the estimated bounding box in order to increase a number of data points of the set of data points projected along the identified edge; and

use the estimated bounding box including the adjusted parameter to maneuver the vehicle.

11. The system of claim 10, further comprising the vehicle.

12. The system of claim 10, further comprising the sensor, wherein the sensor includes a laser.

13. The system of claim 10, wherein the one or more processors are further configured to identify set of data points by selecting data points of the plurality of data points that satisfy a threshold elevation above a surface of the section of roadway identified in the detailed map.

14. The system of claim 10, wherein the one or more processors are further configured to adjust the parameter in order to maximize the number of data points of the set of data points along the identified edge.

15. The system of claim 10, wherein the parameter of the estimated bounding box includes a location of the identified edge.

16. The system of claim 10, wherein the one or more processors are further configured to:

receive additional data points generated by the sensor corresponding to the object;

use the estimated bounding box and adjusted parameter to estimate a new bounding box for the object based on the received additional data points.

17. The system of claim 10, wherein the one or more processors are further configured to:

receive sensor data from a second sensor of a different type from the sensor, and

wherein the received sensor data from the second sensor is further used to estimate the estimated bounding box.

18. A tangible computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by a processor, cause the processor to perform a method of maneuvering a vehicle, the method comprising:

selecting a set of points from a plurality of data points generated by a sensor, each data point of the plurality of data points representing a three-dimensional location of a point corresponding to a surface of an object located on a section of roadway, the set of points being indicative of an object in the section of roadway;

estimating a bounding box for the set of points based on a detailed map of the section of roadway;

projecting the set of data points onto a two-dimensional intensity map within the estimated bounding box;

identifying, by the one or more processors, an edge of the bounding box visible to the sensor;

adjusting a parameter of the estimated bounding box in order to increase a number of data points of the set of data points projected along the identified edge; and

using the estimated bounding box including the adjusted parameter to maneuver the vehicle.

19. The medium of claim 18, wherein the one or more processors are further configured to adjust the parameter in order to maximize the number of data points of the set of data points along the identified edge.

20. The medium of claim 18, wherein the method further comprises:

receiving additional data points generated by the sensor corresponding to the object; and

using the estimated bounding box and adjusted parameter to estimate a new bounding box for the object based on the received additional data points.