Evidence map›Paper›PMID 37571593›Full record

ReviewSensors (Basel, Switzerland)2023

Review on Type of Sensors and Detection Method of Anti-Collision System of Unmanned Aerial Vehicle.

Navaneetha Krishna Chandran, Mohammed Thariq Hameed Sultan, Andrzej Łukaszewicz, Farah Syazwani Shahar, Andriy Holovatyy, Wojciech Giernacki

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Collision Avoidance Mechanism for Swarms of Drones.Sensors (Basel, Switzerland) · 2025
    Article
  2. Article
  3. Article
  4. Review
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

6 authors.

Navaneetha Krishna ChandranLaboratory of Biocomposite Technology, Institute of Tropical Forestry and Forest Products (INTROP), University Putra Malaysia, Serdang 43400, Selangor Darul Ehsan, Malaysia.
Mohammed Thariq Hameed SultanLaboratory of Biocomposite Technology, Institute of Tropical Forestry and Forest Products (INTROP), University Putra Malaysia, Serdang 43400, Selangor Darul Ehsan, Malaysia.ORCID 0000-0002-5110-0242
Andrzej ŁukaszewiczInstitute of Mechanical Engineering, Faculty of Mechanical Engineering, Bialystok University of Technology, 15-351 Bialystok, Poland.ORCID 0000-0003-0373-4803
Farah Syazwani ShaharDepartment of Aerospace Engineering, Faculty of Engineering, University Putra Malaysia, Serdang 43400, Selangor Darul Ehsan, Malaysia.
Andriy HolovatyyDepartment of Computer-Aided Design Systems, Lviv Polytechnic National University, 79013 Lviv, Ukraine.ORCID 0000-0001-6143-648X
Wojciech GiernackiInstitute of Robotics and Machine Intelligence, Faculty of Control, Robotics and Electrical Engineering, Poznan University of Technology, 60-965 Poznan, Poland.ORCID 0000-0003-1747-4010

Funding

Geran Inisiatif Putra Siswazah (GP-IPS) 9739200Universiti Putra Malaysia 9739200
6 · The paper itself

Abstract

Unmanned aerial vehicle (UAV) usage is increasing drastically worldwide as UAVs are used in various industries for many applications, such as inspection, logistics, agriculture, and many more. This is because performing a task using UAV makes the job more efficient and reduces the workload needed. However, for a UAV to be operated manually or autonomously, the UAV must be equipped with proper safety features. An anti-collision system is one of the most crucial and fundamental safety features that UAVs must be equipped with. The anti-collision system allows the UAV to maintain a safe distance from any obstacles. The anti-collision technologies are of crucial relevance to assure the survival and safety of UAVs. Anti-collision of UAVs can be varied in the aspect of sensor usage and the system's working principle. This article provides a comprehensive overview of anti-collision technologies for UAVs. It also presents drone safety laws and regulations that prevent a collision at the policy level. The process of anti-collision technologies is studied from three aspects: Obstacle detection, collision prediction, and collision avoidance. A detailed overview and comparison of the methods of each element and an analysis of their advantages and disadvantages have been provided. In addition, the future trends of UAV anti-collision technologies from the viewpoint of fast obstacle detection and wireless networking are presented.

Indexed as

anti-collision methodsdetection systemsensorsunmanned aerial vehicle

Identifiers

PMID37571593
PMCPMC10422601

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.