Evidence map›Paper›PMID 41682442›Full record

ArticleSensors (Basel, Switzerland)2026

UAV-Based Coverage Path Planning for Unmanned Agricultural Vehicles.

Guangjie Xue, Engen Zhang, Guangshun An, Juan Du, Xiang Yin, Peng Zhou, Xuening Zhang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. 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. 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

7 authors.

Guangjie XueSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Engen ZhangSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Guangshun AnSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Juan DuSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.
Xiang YinSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.ORCID 0000-0002-1620-1224
Peng ZhouSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.ORCID 0000-0002-6345-5307
Xuening ZhangSchool of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo 255000, China.

Funding

Agricultural Engineering Foundation of SDUT of China NZY-2025-07Key R&D Program of Shandong Province, China 2022SFGC0201National Key Research and Development Program of China 2021YFD2000502National Natural Science Foundation of China 32171910
6 · The paper itself

Abstract

Accurate path planning was the prerequisite for autonomous navigation of agricultural vehicles. An Unmanned Aerial Vehicle (UAV)-based coverage path planning was developed in this research for automating guidance of agricultural vehicles and reducing the operator maneuver in the creation of navigation maps. High-resolution orthophoto maps of the field were constructed by using low-altitude UAV photogrammetry to obtain spatial information. Travel paths and working paths were automatically generated from anchor points selected by the operator under the image coordinate domain. The navigation path for unmanned agricultural vehicles was generated by Mercator projection-based conversion for the anchor pixel coordinates into latitude and longitude geographic coordinates. A Graphical User Interface (GUI) was developed for path generation, visualization, and performance evaluation, through which the proposed path planning method was implemented for autonomous agricultural vehicle navigation. Calculation accuracy tests demonstrated the mean planar coordinate error was 2.23 cm and the maximum error was 3.37 cm for path planning. Field tests showed that lateral navigation errors remained within ±5.5 cm for the unmanned high-clearance sprayer, which indicated that the developed UAV-based coverage path planning method was feasible and featured high accuracy. It provided an effective solution for achieving fully autonomous agricultural vehicle operations.

Indexed as

agricultural vehiclescoordinate transformationpath planningUAV

Identifiers

PMID41682442
PMCPMC12899004

What OpenQuestion holds

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Registered trials

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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.