Evidence map›Paper›PMID 35632053›Full record

ArticleSensors (Basel, Switzerland)2022

Error Reduction in Vision-Based Multirotor Landing System.

Juan Pedro Llerena Caña, Jesús García Herrero, José Manuel Molina López

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

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

3 authors.

Juan Pedro Llerena CañaApplied Artificial Intelligence Group (GIAA), Carlos III University of Madrid, 28270 Madrid, Spain.ORCID 0000-0002-3476-6261
Jesús García HerreroApplied Artificial Intelligence Group (GIAA), Carlos III University of Madrid, 28270 Madrid, Spain.ORCID 0000-0003-1768-2688
José Manuel Molina LópezApplied Artificial Intelligence Group (GIAA), Carlos III University of Madrid, 28270 Madrid, Spain.ORCID 0000-0002-7484-7357

Funding

Madrid-Spain Government EPUC3M17Spanish Ministry of Science and Innovation PID2020-118249RB-C22
6 · The paper itself

Abstract

New applications are continuously appearing with drones as protagonists, but all of them share an essential critical maneuver-landing. New application requirements have led the study of novel landing strategies, in which vision systems have played and continue to play a key role. Generally, the new applications use the control and navigation systems embedded in the aircraft. However, the internal dynamics of these systems, initially focused on other tasks such as the smoothing trajectories between different waypoints, can trigger undesired behaviors. In this paper, we propose a landing system based on monocular vision and navigation information to estimate the helipad global position. In addition, the global estimation system includes a position error correction module by cylinder space transformation and a filtering system with a sliding window. To conclude, the landing system is evaluated with three quality metrics, showing how the proposed correction system together with stationary filtering improves the raw landing system.

Indexed as

Optical DevicesAircraftautonomous landingcomputer visionfilteringglobal positionhelipad contextnavigation systemSITLUAV

Identifiers

PMID35632053
PMCPMC9285663

What OpenQuestion holds

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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.