Method for eliminating dynamic obstacle artifacts in laser point cloud map

A laser point cloud and dynamic technology, applied in image analysis, graphics and image conversion, image data processing, etc., can solve the problems that dynamic obstacles cannot obtain good detection results, geometric features and motion features are not obvious, and achieve fast segmentation results , save computing time, and have adaptive effects

Active Publication Date: 2021-01-01
YANSHAN UNIV
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  • Summary
  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing methods for detecting dynamic obstacles mainly use dynamic tracking technology to track and detect dynamic obstacles with fixed models. Such methods often rely on the geometric model or motion model of dynamic obstacles, and cannot obtain good test result

Method used

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  • Method for eliminating dynamic obstacle artifacts in laser point cloud map
  • Method for eliminating dynamic obstacle artifacts in laser point cloud map
  • Method for eliminating dynamic obstacle artifacts in laser point cloud map

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Embodiment 1

[0052] Embodiment 1, a method for removing dynamic obstacle artifacts in a laser point cloud map includes the following specific processes:

[0053] S1: The lidar collects point cloud data of the surrounding environment of the vehicle, the IMU collects the attitude data of the vehicle, and the GPS collects the position data of the vehicle, and performs data fusion of all collected radar point cloud data, attitude data and position data to eliminate the radar point cloud Distortion, and convert all the radar point cloud data that eliminates distortion to the UTM coordinate system, and obtain n frames of radar data that have completed rough registration, and take k=5;

[0054] S2: The coarse registration radar point cloud data of the 4 frames before the kth frame of coarse registration is completed, and the radar point cloud data of the kth frame of rough registration is used as the reference point cloud for fine registration stitching to generate The dense point cloud data P of...

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Abstract

The invention discloses a method capable of quickly removing dynamic obstacle artifacts from a static background map in real time, and the method comprises the steps: collecting laser radar, IMU and GPS data, and converting n frames of radar point clouds into a UTM coordinate system, obtaining the kth frame of dense point cloud map by registering N-1 frames of point clouds before the kth frame tothe Nth frame, and for the frames of k being larger than 2N-2 frames, obtaining the kth frame of dense point cloud map by registering N-1 frames of static point clouds before the kth frame to the Nthframe; performing ground segmentation on the kth frame of dense point cloud map and the kth cloud, and reserving non-ground points No and Ni; rasterizing the point clouds No and Ni, and judging the dynamic and static attributes of each grid; and registering the static point clouds obtained by processing from the Nth frame to the (n-1) th frame to the nth frame of point clouds to generate a point cloud map which is the multi-frame point cloud dense map for eliminating the dynamic obstacle artifacts. The method greatly reduces the calculation amount while ensuring the precision, saves the calculation time, and achieves the purpose of quickly generating the dense point cloud map for eliminating the dynamic obstacle artifacts.

Description

technical field [0001] The invention relates to the technical field of radar data processing, in particular to a method for removing dynamic obstacle artifacts in a laser point cloud map. Background technique [0002] With the rapid development of autonomous driving and assisted driving, environmental awareness is crucial. At present, the main content of terrain detection in front of the vehicle is to detect the location information of road obstacles in front of the vehicle, with obstacle avoidance as the main purpose, and a single frame of laser point cloud can complete this purpose. For vehicles with obstacle-surpassing and active suspension control capabilities, it is of great significance to quickly generate accurate terrain maps in front of the vehicle. However, a single-frame point cloud is too sparse to accurately reflect the ups and downs of the ground terrain, so it is often necessary to register multiple frames of point clouds together to form a dense point cloud ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S17/89G01S17/86G06T7/11G06T3/40G06T7/30
CPCG01S17/89G01S17/86G06T7/11G06T7/30G06T3/4038
Inventor 刘爽刘轩赵丁选倪涛
Owner YANSHAN UNIV
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