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The centroid of a body is a crucial concept in engineering and physics. Finding the centroid of a body can help determine its stability, its balance point, and even its design. In this context, consider a thin wire bent in the form of a quarter circular arc. Polar coordinates are used to calculate the centroid. The wire is first divided into small differential elements of a length equal to the radius multiplied by the differential angle.
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Calculating areas within irregular boundaries, such as along rivers or curved roads, is crucial in various fields, including surveying, engineering, and environmental management. Surveyors often begin by creating a traverse, a connected series of straight lines approximating the area's boundary. The coordinates of each traverse point are essential for calculating the enclosed area. The double meridian distance formula is a widely used technique for this purpose. This method utilizes the...
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The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
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Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
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Multi-UAV forest area inspection path planning based on concave polygon region decomposition.

Bo Kang1, Chuan'an Wang2, Yu Su1

  • 1College of Intelligent Manufacturing, Anhui Science and Technology University, Chuzhou, 239000, China.

Scientific Reports
|November 25, 2025
PubMed
Summary

This study introduces a new multi-unmanned aerial vehicle (UAV) path planning algorithm for efficient forest monitoring. The method significantly reduces coverage time and path length, improving ecological protection.

Keywords:
Area coverageConcave decompositionConvex polygonPath planningRegion allocationUAVs

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Area of Science:

  • Robotics and Automation
  • Environmental Monitoring
  • Computer Science

Background:

  • Traditional forest patrolling methods (manual, manned aircraft) are inefficient and costly, especially in complex terrains.
  • Unmanned Aerial Vehicles (UAVs) offer a promising alternative for efficient forest surveillance.
  • Existing coverage path planning algorithms struggle with complex, concave regions and multi-UAV coordination.

Purpose of the Study:

  • To develop an efficient multi-UAV coverage path planning algorithm for complex, concave forest regions.
  • To improve forest monitoring efficiency by reducing patrol time and path length.
  • To provide a robust solution for ecological protection, fire prevention, and pest monitoring in forested areas.

Main Methods:

  • A novel algorithm combining spatial position ordering and convex decomposition for concave region partitioning.
  • An improved ear-shearing method to decompose complex areas into convex subregions.
  • A region allocation strategy with adjacency constraints for balanced and contiguous multi-UAV coverage.

Main Results:

  • Simulated forest area tests showed a 54.7% reduction in coverage time and a 26.3% decrease in path length compared to single UAV operation.
  • Real-world validation using Xishuangbanna terrain data achieved a 97.8% coverage rate with a 0.09 shading coefficient via optimized flight altitude.
  • The multi-UAV strategy outperformed existing methods in minimizing coverage time and path length while ensuring balanced task allocation.

Conclusions:

  • The proposed multi-UAV coverage path planning algorithm significantly enhances forest area detection efficiency.
  • The algorithm offers a technically sound solution for dynamic forest resource monitoring and ecological protection.
  • This approach provides a foundation for advanced, automated forest surveillance systems.