A Negative Obstacle Detection Method Based on Local Structural Features of LiDAR Point Clouds

An obstacle detection and lidar technology, applied in computer parts, instruments, scene recognition, etc., can solve problems such as poor detection effect of negative obstacles

Active Publication Date: 2020-03-03
ZHEJIANG UNIV
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Problems solved by technology

The disadvantage of this method is that it requires a large number of sample training in advance, and the detection effect on untrained negative obstacle types is poor

Method used

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  • A Negative Obstacle Detection Method Based on Local Structural Features of LiDAR Point Clouds
  • A Negative Obstacle Detection Method Based on Local Structural Features of LiDAR Point Clouds
  • A Negative Obstacle Detection Method Based on Local Structural Features of LiDAR Point Clouds

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Embodiment Construction

[0120] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0121] Such as figure 1 Shown, the embodiment of the inventive method and implementation process thereof are as follows:

[0122] A typical example of a scene containing negative obstacles is used to more clearly represent the process of the present invention.

[0123] The point cloud data of the embodiment is collected by two lidars installed in the front of the vehicle. The arrangement and acquisition methods of the two lidars are as follows: figure 2 and image 3 As shown, the laser radar works in the way of multi-line laser rotary scanning, and one laser line corresponds to a continuous distribution of point clouds.

[0124] Scene opinion Figure 4 , where the upper left is the top view of the lidar point cloud, the upper right is the real image of the scene, the middle right is the corresponding grid attribute map, and the lower is the 3D rend...

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Abstract

The invention discloses a negative obstacle detection method based on the local structural features of laser radar point clouds. The collected lidar point cloud data is detected line by line for the three structural features of local point cloud distance jump, local point cloud distribution density and local point cloud height drop, and is obtained by extracting and filtering in the single-line laser point cloud according to the three structural features Candidate point pairs that may belong to negative obstacles; all candidate point pairs obtained from the laser point cloud of each laser line are clustered according to point pair length consistency and spatial position consistency to obtain negative obstacle candidate areas, and then pass through the area Filtering, point-to-number filtering to get the negative obstacle area. The invention can effectively detect negative obstacles in the environment, has good detection success rate, low calculation cost and strong real-time performance.

Description

technical field [0001] The invention relates to a robot obstacle avoidance detection method, in particular to a negative obstacle detection method based on local structural features of laser radar point cloud for unmanned vehicle navigation. Background technique [0002] Traditional methods for negative obstacle detection include detection methods based on thermal infrared images, color images and binocular vision. The negative obstacle detection method based on thermal infrared images uses a thermal infrared camera to collect images, and detects negative obstacles in the environment according to the characteristics of the temperature difference between the negative obstacles and the ambient temperature. The disadvantage of this detection method is that it is very sensitive to changes in ambient temperature. The color image-based negative obstacle detection method uses a color camera to collect images, and extracts color models and geometric models from image sequences to d...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/58G06F18/23
Inventor 林辉项志宇邹楠张佳鹏
Owner ZHEJIANG UNIV
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