A Control Architecture for Multiple Submarines in Coordinated Search Missions

Abstract

A control architecture for executing multi-vehicle search algorithms is presented. The proposed hierarchical structure consists of three control layers: maneuver controllers, vehicle supervisors and team controllers. The system model is described as a dynamic network of hybrid automata in the programming language Shift and allows reasoning about specification and dynamical properties in a formal setting. The particular search problem that is studied is that of finding the minimum of a scalar field using a team of autonomous submarines. As an illustration, a coordination scheme based on the Nelder-Mead simplex optimization algorithm is presented and illustrated through simulations.

Optimal motion planning for the rendezvous of nonholonomic vehicles under disturbances

“…The waypoints can be generated either on-line or off-line. For a description of a possible global system architecture, along with the mechanisms for data exchange, coordination between vehicles and fault handling, see [9].…”

Optima localization by vehicle formations imitating the Nelder-Mead simplex algorithm

“…As early as 1996, the authors of (Burian et al 1996) propose the use of the simplex method as one which is especially suited to underwater applications. In ), de Sousa et al (2005, 2006, and , formation coordination strategies based on the simplest form of simplex search are proposed. In Kalantar andZimmer (2007a, 2007b), the simple simplex method has been extended to incorporate the capability to traverse isocontours.…”

Modeling Objects Moving in a Complex Environment with World Automata

“…4 In our example, the environment is given by a sandy area. At level 1, WA called Environment in Fig.…”

“…We call this kind of communication implicit. The main sources of motivation for these studies are real applications presented in the European project C4C, such as agents performing a search mission, e.g., UAVs [3] or autonomous underwater vehicles [4], but also road traffic problems [5,6] and autonomous straddle carriers in harbors [7]. In all these situations, we have a collection of agents that need to communicate and coordinate to achieve a common goal; hence, distributed systems.…”