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Automatic driving vehicle positioning method and system based on binocular vision SLAM

A binocular vision and automatic driving technology, applied in the field of vehicle positioning system, can solve the problems of poor positioning effect, high cost, unfavorable self-driving vehicles, etc., and achieve the effect of low hardware requirements and cost reduction requirements

Active Publication Date: 2021-02-09
的卢技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, due to the inherent shortcomings of lidar sensors, the positioning effect is poor in rainy, snowy and dusty weather, and lidar sensors often have a high price, which greatly increases the cost
This presents a significant disadvantage to the widespread adoption of self-driving vehicles

Method used

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  • Automatic driving vehicle positioning method and system based on binocular vision SLAM
  • Automatic driving vehicle positioning method and system based on binocular vision SLAM
  • Automatic driving vehicle positioning method and system based on binocular vision SLAM

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Embodiment 1

[0034] refer to Figure 1~2 The schematic diagram is a self-driving vehicle positioning method based on binocular vision SLAM proposed in this embodiment. SLAM is also called CML, real-time positioning and map construction or concurrent map construction and positioning. Automated driving technology includes video cameras , radar sensors, and laser rangefinders to understand surrounding traffic conditions and navigate the road ahead with a detailed map (collected by a manned car). Among them, the most important main control computer of the self-driving car is arranged in the rear compartment. In addition to the computer used for calculation, there is also a ranging information synthesizer. This core equipment will be responsible for the judgment and execution of the driving route and mode of the car. For autonomous driving, positioning is a technology that allows unmanned vehicles to know their exact location. This is an interesting and challenging task, which is very important...

Embodiment 2

[0084] refer to Figure 4 The illustration shows a binocular vision SLAM-based automatic driving vehicle positioning system in this embodiment. The above-mentioned binocular vision SLAM-based automatic driving vehicle positioning method can be implemented relying on the system proposed in this embodiment.

[0085] More specifically, the present embodiment includes a calibration module 100, a binocular vision sensor 200, a coordinate transformation module 300, a detection module 400, and a positioning module 500; where the calibration module 100 is connected to the binocular vision sensor 200 for its calibration; The transformation module 300 is connected with the calibration module 100 for obtaining the transformation matrix from the left eye of the binocular vision sensor 200 to the center of the vehicle body; the detection module 400 is connected with the binocular vision sensor 200 for obtaining the plane detection frame image of the vehicle in front of the road Coordinates...

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Abstract

The invention discloses an automatic driving vehicle positioning method and system based on binocular vision SLAM, and the method comprises the following steps: self-calibration is carried out by a binocular vision sensor by a calibration module; a coordinate transformation module acquires a transformation matrix; the binocular vision sensor collects a camera image in front of a road; the camera image is input into the detection module, and plane detection frame image coordinates of vehicles in front of a road are obtained through an SSD detection algorithm; a detection module is used for calculating a three-dimensional detection frame of a vehicle in front of the road; and a positioning module performs self-tracking positioning. The invention has the beneficial effects that the hardware requirement is low, only one binocular camera sensor needs to be fixed in front of the vehicle, and cost requirement is greatly reduced; meanwhile, compared with a laser radar sensor, the visual sensorhas better advantages in similarity matching, and the function of three-dimensional detection of vehicles in front of a road can be achieved.

Description

technical field [0001] The invention relates to the technical field of automatic driving, in particular to a binocular vision SLAM-based automatic driving vehicle positioning method and a vehicle positioning system. Background technique [0002] Self-driving car, also known as unmanned car, computer-driven car, or wheeled mobile robot, is a kind of intelligent car that realizes unmanned driving through a computer system. Auto-driving technology includes video cameras, radar sensors and laser range finders. Know surrounding traffic conditions and navigate the road ahead with a detailed map. In the field of autonomous driving, accurate positioning is a very important part. The current mainstream positioning solution for autonomous vehicles uses laser radar as the sensor, and the positioning algorithm uses laser SLAM algorithm, which has the advantages of simplicity and mature technology. [0003] However, due to the inherent shortcomings of lidar sensors, the positioning effe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06T7/80G06T7/246G06K9/46G06K9/62
CPCG06T7/80G06T7/246G06T2207/10016G06T2207/20084G06T2207/20081G06T2207/30252G06V20/56G06V10/44G06V10/757G06V2201/07
Inventor 赖美娟戴加婷
Owner 的卢技术有限公司