Evidence map›Paper›PMID 38676111›Full record

ArticleSensors (Basel, Switzerland)2024

A Compact Handheld Sensor Package with Sensor Fusion for Comprehensive and Robust 3D Mapping.

Peng Wei, Kaiming Fu, Juan Villacres, Thomas Ke, Kay Krachenfels, Curtis Ryan Stofer, Nima Bayati, Qikai Gao, Bill Zhang, Eric Vanacker and 1 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Peng WeiDepartment of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA.ORCID 0000-0003-0491-2480
Kaiming FuDepartment of Electrical and Computer Engineering, University of California, Davis, CA 95616, USA.ORCID 0000-0001-5562-0213
Juan VillacresDepartment of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA.ORCID 0000-0001-7113-9497
Thomas KeDepartment of Computer Science, University of California, Davis, CA 95616, USA.ORCID 0009-0005-3865-2842
Kay KrachenfelsDepartment of Computer Science, University of California, Davis, CA 95616, USA.ORCID 0009-0008-9326-7658
Curtis Ryan StoferDepartment of Computer Science, University of California, Davis, CA 95616, USA.
Nima BayatiDepartment of Computer Science, University of California, Davis, CA 95616, USA.
Qikai GaoDepartment of Mechanical and Aerospace Engineering, University of California, Davis, CA 95616, USA.
Bill ZhangDepartment of Mechanical and Aerospace Engineering, University of California, Davis, CA 95616, USA.ORCID 0009-0000-0368-9438
Eric VanackerDepartment of Mechanical and Aerospace Engineering, University of California, Davis, CA 95616, USA.
Zhaodan KongDepartment of Mechanical and Aerospace Engineering, University of California, Davis, CA 95616, USA.ORCID 0000-0002-2493-1366

Funding

National Science Foundation 2200221
6 · The paper itself

Abstract

This paper introduces an innovative approach to 3D environmental mapping through the integration of a compact, handheld sensor package with a two-stage sensor fusion pipeline. The sensor package, incorporating LiDAR, IMU, RGB, and thermal cameras, enables comprehensive and robust 3D mapping of various environments. By leveraging Simultaneous Localization and Mapping (SLAM) and thermal imaging, our solution offers good performance in conditions where global positioning is unavailable and in visually degraded environments. The sensor package runs a real-time LiDAR-Inertial SLAM algorithm, generating a dense point cloud map that accurately reconstructs the geometric features of the environment. Following the acquisition of that point cloud, we post-process these data by fusing them with images from the RGB and thermal cameras and produce a detailed, color-enriched 3D map that is useful and adaptable to different mission requirements. We demonstrated our system in a variety of scenarios, from indoor to outdoor conditions, and the results showcased the effectiveness and applicability of our sensor package and fusion pipeline. This system can be applied in a wide range of applications, ranging from autonomous navigation to smart agriculture, and has the potential to make a substantial benefit across diverse fields.

Indexed as

3D mappingsensor fusionSLAMthermal camera

Identifiers

PMID38676111
PMCPMC11055049

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.