Evidence map›Paper›PMID 36679641›Full record

ArticleSensors (Basel, Switzerland)2023

A Method of Setting the LiDAR Field of View in NDT Relocation Based on ROI.

Jian Gu, Yubin Lan, Fanxia Kong, Lei Liu, Haozheng Sun, Jie Liu, Lili Yi

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
2.3field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Jian GuSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.ORCID 0000-0001-7309-1896
Yubin LanSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Fanxia KongSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Lei LiuSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Haozheng SunSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Jie LiuSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Lili YiSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Shandong University of Technology · CN

Funding

Yubin Lan 2019ZBXC200Yubin Lan Lu Zheng Ban Zi [2018]27
6 · The paper itself

Abstract

LiDAR placement and field of view selection play a role in detecting the relative position and pose of vehicles in relocation maps based on high-precision map automatic navigation. When the LiDAR field of view is obscured or the LiDAR position is misplaced, this can easily lead to loss of repositioning or low repositioning accuracy. In this paper, a method of LiDAR layout and field of view selection based on high-precision map normal distribution transformation (NDT) relocation is proposed to solve the problem of large NDT relocation error and position loss when the occlusion field of view is too large. To simulate the real placement environment and the LiDAR obstructed by obstacles, the ROI algorithm is used to cut LiDAR point clouds and to obtain LiDAR point cloud data of different sizes. The cut point cloud data is first downsampled and then relocated. The downsampling points for NDT relocation are recorded as valid matching points. The direction and angle settings of the LiDAR point cloud data are optimized using RMSE values and valid matching points. The results show that in the urban scene with complex road conditions, there are more front and rear matching points than left and right matching points within the unit angle. The more matching points of the NDT relocation algorithm there are, the higher the relocation accuracy. Increasing the front and rear LiDAR field of view prevents the loss of repositioning. The relocation accuracy can be improved by increasing the left and right LiDAR field of view.

Indexed as

AlgorithmsRecordsNormal Distributionautomatic navigationhigh-precision mapsnormal distribution transformation

Identifiers

PMID36679641
PMCPMC9860606
OpenAlexW4315647790

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.