Evidence map›Paper›PMID 34207193›Full record

ArticleSensors (Basel, Switzerland)2021

Estimate the Unknown Environment with Biosonar Echoes-A Simulation Study.

Muhammad Hassan Tanveer, Antony Thomas, Waqar Ahmed, Hongxiao Zhu

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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

4 authors.

Muhammad Hassan TanveerDepartment of Robotics and Mechatronics Engineering, Kennesaw State University, Marietta, GA 30060, USA.ORCID 0000-0001-9266-6368
Antony ThomasDepartment of Informatics, Bioengineering, Robotics, and Systems Engineering, University of Genoa, 16145 Genoa, Italy.ORCID 0000-0003-1285-0048
Waqar AhmedPAVIS, Istituto Italiano di Tecnologia, 16152 Genoa, Italy.ORCID 0000-0001-5416-149X
Hongxiao ZhuDepartment of Statistics, Virginia Tech, Blacksburg, VA 24061, USA.ORCID 0000-0001-5674-6483

Funding

National Science Foundation 1762577
6 · The paper itself

Abstract

Unmanned aerial vehicles (UAVs) have shown great potential in various applications such as surveillance, search and rescue. To perform safe and efficient navigation, it is vitally important for a UAV to evaluate the environment accurately and promptly. In this work, we present a simulation study for the estimation of foliage distribution as a UAV equipped with biosonar navigates through a forest. Based on a simulated forest environment, foliage echoes are generated by using a bat-inspired bisonar simulator. These biosonar echoes are then used to estimate the spatial distribution of both sparsely and densely distributed tree leaves. While a simple batch processing method is able to estimate sparsely distributed leaf locations well, a wavelet scattering technique coupled with a support vector machine (SVM) classifier is shown to be effective to estimate densely distributed leaves. Our approach is validated by using multiple setups of leaf distributions in the simulated forest environment. Ninety-seven percent accuracy is obtained while estimating thickly distributed foliage.

Indexed as

ForestsTreesComputer SimulationPlant LeavesSupport Vector Machinebio-inspired sensingbiosonarsimulationsupport vector machineUnmanned aerial vehicleswavelet scattering

Identifiers

PMID34207193
PMCPMC8233705

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.