Evidence map›Paper›PMID 35009946›Full record

ArticleSensors (Basel, Switzerland)2022

Proactive Guidance for Accurate UAV Landing on a Dynamic Platform: A Visual-Inertial Approach.

Ching-Wei Chang, Li-Yu Lo, Hiu Ching Cheung, Yurong Feng, An-Shik Yang, Chih-Yung Wen, Weifeng Zhou

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Autonomous Quadcopter Landing on a Moving Target.Sensors (Basel, Switzerland) · 2022
    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

7 authors.

Ching-Wei ChangDepartment of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.ORCID 0000-0001-7307-6039
Li-Yu LoDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.ORCID 0000-0001-8570-563X
Hiu Ching CheungDepartment of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
Yurong FengDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.
An-Shik YangDepartment of Energy and Refrigerating Air-Conditioning Engineering, National Taipei University of Technology, Taipei 10608, Taiwan.
Chih-Yung WenDepartment of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong.ORCID 0000-0002-1181-8786
Weifeng ZhouSchool of Professional Education and Executive Development, The Hong Kong Polytechnic University, Kowloon, Hong Kong.ORCID 0000-0001-7386-2945

Funding

Innovation and Technology Commission of Hong Kong ITT/027/19GP
6 · The paper itself

Abstract

This work aimed to develop an autonomous system for unmanned aerial vehicles (UAVs) to land on moving platforms such as an automobile or a marine vessel, providing a promising solution for a long-endurance flight operation, a large mission coverage range, and a convenient recharging ground station. Unlike most state-of-the-art UAV landing frameworks that rely on UAV onboard computers and sensors, the proposed system fully depends on the computation unit situated on the ground vehicle/marine vessel to serve as a landing guidance system. Such a novel configuration can therefore lighten the burden of the UAV, and the computation power of the ground vehicle/marine vessel can be enhanced. In particular, we exploit a sensor fusion-based algorithm for the guidance system to perform UAV localization, whilst a control method based upon trajectory optimization is integrated. Indoor and outdoor experiments are conducted, and the results show that precise autonomous landing on a 43 cm × 43 cm platform can be performed.

Indexed as

autonomous landingdeep learningkalman filterobject trackingoptimal trajectorysensor fusionUAVVTOL

Identifiers

PMID35009946
PMCPMC8749553

What OpenQuestion holds

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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.