IP Library Granted Patent US 11,697,428
Granted Patent B2
US 11,697,428 · App. 17/118,440 · Granted Jul 11, 2023

Method and apparatus for 3D modeling

Inventor: Yiming Liu (Beijing, CN)
Assignee: APOLLO INTELLIGENT DRIVING TECHNOLOGY (BEIJING) CO., LTD.
B60W60/001G06F18/213G06V20/58B60W2554/4049
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Quick Facts
Patent No.
US 11,697,428
App. No.
17/118,440
Granted
Jul 11, 2023
Kind
B2
Abstract

A method for three-dimensional modeling. The method may include: acquiring coordinate points of obstacles in a surrounding environment of an autonomous driving vehicle in a vehicle coordinate system; determining a position of eyes of a passenger in the autonomous driving vehicle, and establishing an eye coordinate system using the position of the eyes as a coordinate origin; converting the coordinate points of the obstacles in the vehicle coordinate system to coordinate points in the eye coordinate system, and determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes; and performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles.

Claims (63)

1. A method for three-dimensional modeling, the method comprising:

acquiring coordinate points of obstacles in a surrounding environment of an autonomous driving vehicle in a vehicle coordinate system;

determining a position of eyes of a passenger in the autonomous driving vehicle, and establishing an eye coordinate system using the position of the eyes as a coordinate origin;

converting the coordinate points of the obstacles in the vehicle coordinate system to coordinate points in the eye coordinate system, and determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes; and

performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles;

wherein the determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes, comprises:

selecting a target area from the surrounding environment,

selecting a reference obstacle from the obstacles in the target area;

generating a ray passing through a coordinate point of the reference obstacle using the coordinate origin of the eye coordinate system as a starting point; and

for each other obstacle in the target area except the reference obstacle, using a coordinate point of the other obstacle as a starting point, making a vertical line of the ray, and determining a length of the vertical line as a visualization distance between the other obstacle and the reference obstacle.

2. The method according to claim 1 , wherein the performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles, comprises:

performing three-dimensional modeling of the reference obstacle based on the coordinate point of the reference obstacle in the eye coordinate system;

determining a position of the other obstacle using the visualization distance between the other obstacle except the reference obstacle in the target area and the reference obstacle; and

performing three-dimensional modeling of the other obstacle using the position of the other obstacle.

3. The method according to claim 2 , wherein the performing three-dimensional modeling of the reference obstacle based on the coordinate point of the reference obstacle in the eye coordinate system, comprises:

determining a visualization distance between the eyes and the reference obstacle, based on the visualization distance between the other obstacle and the reference obstacle, a real distance between the other obstacle and the reference obstacle, and a real distance between the eyes and the reference obstacle;

determining a position of the reference obstacle using the coordinate point of the reference obstacle in the eye coordinate system and the visualization distance between the eyes and the reference obstacle; and

performing three-dimensional modeling of the reference obstacle using the position of the reference obstacle.

4. The method according to claim 1 , wherein the selecting a target area from the surrounding environment, comprises:

dividing the surrounding environment to select the target area from divided areas.

5. An electronic device, comprising:

at least one processor; and

a memory, communicatively connected to the at least one processor;

wherein the memory stores instructions executable by the at least one processor, the instructions, when executed by the at least one processor, cause the at least one processor to perform operations, the operations comprising:

acquiring coordinate points of obstacles in a surrounding environment of an autonomous driving vehicle in a vehicle coordinate system;

determining a position of eyes of a passenger in the autonomous driving vehicle, and establishing an eye coordinate system using the position of the eyes as a coordinate origin;

converting the coordinate points of the obstacles in the vehicle coordinate system to coordinate points in the eye coordinate system, and determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes; and

performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles;

wherein the determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes, comprises:

selecting a target area from the surrounding environment,

selecting a reference obstacle from the obstacles in the target area;

generating a ray passing through a coordinate point of the reference obstacle using the coordinate origin of the eye coordinate system as a starting point; and

for each other obstacle in the target area except the reference obstacle, using a coordinate point of the other obstacle as a starting point, making a vertical line of the ray, and determining a length of the vertical line as a visualization distance between the other obstacle and the reference obstacle.

6. The electronic device according to claim 5 , wherein the performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles, comprises:

performing three-dimensional modeling of the reference obstacle based on the coordinate point of the reference obstacle in the eye coordinate system;

determining a position of the other obstacle using the visualization distance between the other obstacle except the reference obstacle in the target area and the reference obstacle; and

performing three-dimensional modeling of the other obstacle using the position of the other obstacle.

7. The electronic device according to claim 6 , wherein the performing three-dimensional modeling of the reference obstacle based on the coordinate point of the reference obstacle in the eye coordinate system, comprises:

determining a visualization distance between the eyes and the reference obstacle, based on the visualization distance between the other obstacle and the reference obstacle, a real distance between the other obstacle and the reference obstacle, and a real distance between the eyes and the reference obstacle;

determining a position of the reference obstacle using the coordinate point of the reference obstacle in the eye coordinate system and the visualization distance between the eyes and the reference obstacle; and

performing three-dimensional modeling of the reference obstacle using the position of the reference obstacle.

8. The electronic device according to claim 5 , wherein the selecting a target area from the surrounding environment, comprises:

dividing the surrounding environment to select the target area from divided areas.

9. A non-transitory computer readable storage medium, storing computer instructions, wherein the computer instructions, when executed by a processor, cause the processor to perform operations, the operations comprising:

acquiring coordinate points of obstacles in a surrounding environment of an autonomous driving vehicle in a vehicle coordinate system;

determining a position of eyes of a passenger in the autonomous driving vehicle, and establishing an eye coordinate system using the position of the eyes as a coordinate origin;

converting the coordinate points of the obstacles in the vehicle coordinate system to coordinate points in the eye coordinate system, and determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes; and

performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles;

wherein the determining a visualization distance between the obstacles in the surrounding environment based on an observation angle of the eyes, comprises:

selecting a target area from the surrounding environment,

selecting a reference obstacle from the obstacles in the target area;

generating a ray passing through a coordinate point of the reference obstacle using the coordinate origin of the eye coordinate system as a starting point; and

for each other obstacle in the target area except the reference obstacle, using a coordinate point of the other obstacle as a starting point, making a vertical line of the ray, and determining a length of the vertical line as a visualization distance between the other obstacle and the reference obstacle.

10. The non-transitory computer readable storage medium according to claim 9 , wherein the performing three-dimensional modeling of the surrounding environment, based on visualization distance between the coordinate points of the obstacles in the eye coordinate system and the obstacles, comprises:

performing three-dimensional modeling of the reference obstacle based on the coordinate point of the reference obstacle in the eye coordinate system;

determining a position of the other obstacle using the visualization distance between the other obstacle except the reference obstacle in the target area and the reference obstacle; and

performing three-dimensional modeling of the other obstacle using the position of the other obstacle.

11. The non-transitory computer readable storage medium according to claim 10 , wherein the performing three-dimensional modeling of the reference obstacle based on the coordinate point of the reference obstacle in the eye coordinate system, comprises:

determining a visualization distance between the eyes and the reference obstacle, based on the visualization distance between the other obstacle and the reference obstacle, a real distance between the other obstacle and the reference obstacle, and a real distance between the eyes and the reference obstacle;

determining a position of the reference obstacle using the coordinate point of the reference obstacle in the eye coordinate system and the visualization distance between the eyes and the reference obstacle; and

performing three-dimensional modeling of the reference obstacle using the position of the reference obstacle.

12. The non-transitory computer readable storage medium according to claim 9 , wherein the selecting a target area from the surrounding environment, comprises:

dividing the surrounding environment to select the target area from divided areas.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 29, 2022
From: LIU, YIMING
To: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.
Reel/Frame 060928/0191 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 13, 2021
From: BEIJING BAIDU NETCOM SCIENCE AND TECHNOLOGY CO., LTD.
To: APOLLO INTELLIGENT DRIVING TECHNOLOGY (BEIJING) CO., LTD.
Reel/Frame 058241/0248 →
Priority Claims (1)
CN 202010605153.4 · Jun 29, 2020 · national
Continuity (1)
Related Publication 20210403026A1 · Dec 30, 2021