collaborators

9 papers

physics.flu-dyn2026

Smart strategies to navigate turbulent odor plumes reorienting to local wind

Lorenzo Piro, Maurizio Carbone, Luca Biferale +4

Olfactory search in turbulent environments is a sensorimotor problem that many animals solve with remarkable efficiency, yet replicating this ability in artificial systems is an en…

physics.bio-ph2026

Clock-state olfactory search in turbulent flows using Q-learning: The geometry of plume recovery

Marco Rando, Robin A. Heinonen, Yujia Qi +1

Finding an odor source in a turbulent flow requires effectively leveraging the history of olfactory observations into a robust navigation strategy. In this work, we use tabular Q-l…

cs.RO2026

Olfactory pursuit: catching a moving odor source in complex flows

Maurizio Carbone, Lorenzo Piro, Robin A. Heinonen +3

Locating and intercepting a moving target from possibly delayed, intermittent sensory signals is a paradigmatic problem in decision-making under uncertainty, and a fundamental chal…

math.OC2026

Asymptotics of solutions to the linear search problem

Robin A. Heinonen

The exact leading asymptotics of solutions to the symmetric linear search problem are obtained for any positive probability density on the real line with a monotonic, sufficiently…

physics.flu-dyn2025

TURB-Smoke. A database of Lagrangian pollutants emitted from point-sources and dispersed in turbulent flows

Luca Biferale, Fabio Bonaccorso, Niccolò Cocciaglia +2

Identifying the location and characteristics of pollution sources in turbulent flows is challenging, especially for environmental monitoring and emergency response, due to sparse,…

physics.flu-dyn2025

Policy heterogeneity improves collective olfactory search in 3-D turbulence

Lorenzo Piro, Robin A. Heinonen, Maurizio Carbone +2

We investigate the role of policy heterogeneity in enhancing the olfactory search capabilities of cooperative agent swarms operating in complex, real-world turbulent environments.…