Coverage Path Planning in Precision Agriculture: Algorithms, Applications, and Key Benefits
Jahid Chowdhury Choton, William H. Hsu

TL;DR
This paper reviews coverage path planning algorithms for precision agriculture, demonstrating methods for single and multiple robots to optimize field coverage, data collection, and farm management.
Contribution
It introduces a wavefront coverage algorithm for single robots and a two-step multi-robot division and path generation approach for efficient field coverage.
Findings
Single robot coverage path optimized with wavefront algorithm
Multi-robot division of field into convex polygons for efficient coverage
Proposed methods reduce coverage time and improve data collection
Abstract
Coverage path planning (CPP) is the task of computing an optimal path within a region to completely scan or survey an area of interest using one or multiple mobile robots. Robots equipped with sensors and cameras can collect vast amounts of data on crop health, soil conditions, and weather patterns. Advanced analytics can then be applied to this data to make informed decisions, improving overall farm management. In this paper, we will demonstrate one approach to find the optimal coverage path of an agricultural field using a single robot, and one using multiple robots. For the single robot, we used a wavefront coverage algorithm that generates a sequence of locations that the robot needs to follow. For the multi-robot approach, the proposed approach consists of two steps: dividing the agricultural field into convex polygonal areas to optimally distribute them among the robots, and…
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Taxonomy
TopicsSoil Mechanics and Vehicle Dynamics · Irrigation Practices and Water Management · Smart Agriculture and AI
