RT info:eu-repo/semantics/article
T1 ACO-Path : ACO-based informative path planning with Gaussian processes for water monitoring with a fleet of ASVs
A1 Jara Ten Kathen, Micaela Carolina
A1 Benítez, Natalia
A1 Arzamendia López, Mario Eduardo
A1 Gutierrez Reina, Daniel
AB Autonomous surface vehicles can support water-quality monitoring, but they require planners that place measurements where they most improve the environmental estimate under mission constraints. This paper proposes ACO-Path, an informative path planner that couples Ant Colony Optimization -Ant System- with online Gaussian Process mapping. During the mission, the Gaussian Process updates a mean or contamination map and a variance or uncertainty map, from which dynamic action zones are derived and used to guide an explicit explore then exploit policy.The method is evaluated in a simulated water resource monitoring scenario inspired by Lake Ypacaraí, considering three exploration distances and two heuristic weights. In a comparison against five baseline planners, ACOPath achieves the lowest hotspot error, Errorpeak = 0.19896 0.39400, while remaining competitive in global reconstruction, MSEmap = 0.00144 0.00348, R2 = 0.96066 0.09861. In addition, a turning analysis based on the absolute heading change between consecutive segments shows that ACO-Path produces smoother trajectories, with fewer sharp turns 45 than counterpart baselines under the same mission constraints.
PB Multidisciplinary Digital Publishing Institute
YR 2026
FD 2026-02-04
LK http://hdl.handle.net/20.500.14066/4759
UL http://hdl.handle.net/20.500.14066/4759
LA eng
NO Jara Ten Kathen, M., Benitez, N., Arzamendia, M., & Gutiérrez Reina, D. (2026). ACO-Path: ACO-Based Informative Path Planning with Gaussian Processes for Water Monitoring with a Fleet of ASVs. Electronics, 15(3), 676. https://doi.org/10.3390/electronics15030676
NO Correspondence: dgutierrezreina@us.es.
NO This article belongs to the Special Issue Path Planning and Navigation for Autonomous Vehicles and Intelligent Robots.
NO Consejo Nacional de Ciencia y Tecnología
DS MINDS@UW
RD 08-jun-2026