Global extremum seeking by Kriging with a multi-agent system

Arthur Kahn (1) , Julien Marzat (1) , Hélène Piet-Lahanier (1) , Michel Kieffer (2, 3, 4)

1 ONERA - The French Aerospace Lab [Palaiseau]
2 L2S - Laboratoire des signaux et systèmes
3 IUF - Institut universitaire de France
4 LTCI - Laboratoire Traitement et Communication de l'Information

This paper presents a method for finding the global maximum of a spatially varying field using a multi-agent system. A surrogate model of the field is determined via Kriging (Gaussian process regression) from a set of sampling measurements collected by the agents. A criterion exploiting Kriging statistical properties is introduced for selecting new sampling points that each vehicle must rally. These new points are obtained as a compromise between improvement of the estimate of the global maximum and traveling distance. A cooperative control law is proposed to move the agents to the desired sampling positions while avoiding collisions. Simulation results show the interest of the method and how it compares with a state-of-art solution.

Mots clés: cooperative exploration; Kriging; global extremum seeking; multi-agent systems

Domaines: Automatique / Robotique

Arthur Kahn, Julien Marzat, Hélène Piet-Lahanier, Michel Kieffer. Global extremum seeking by Kriging with a multi-agent system. 2015. ⟨hal-01170131v2⟩