Title :
A high-fidelity ocean sampling mobile network (SAMON) simulator testbed for evaluating intelligent control of unmanned underwater vehicles
Author :
Phoha, Shashi ; Peluso, Eileen M. ; Culver, R.L.
Author_Institution :
Appl. Res. Lab., Pennsylvania State Univ., University Park, PA, USA
fDate :
10/1/2001 12:00:00 AM
Abstract :
The Ocean Sampling Mobile Network (SAMON) simulator testbed has been developed at Penn State for designing and evaluating multirobot ocean-mapping missions, in realistic underwater environments, prior to in-water testing. The goal in developing the testbed is to enable web-based integration of high-fidelity simulators of heterogeneous autonomous undersea vehicles from multiple organizations and a variety of on-board and fixed sensors in a realistic ocean environment in order to formulate and evaluate intelligent control strategies for mission execution. A formal control language facilitates real-time interactions between heterogeneous autonomous components. A simulation experiment is described that demonstrates multistage inferencing and decision/control strategies for spatio-temporal coordination and multilayered adaptation of group behavior in response to evolving environmental physics or operational dynamics
Keywords :
intelligent control; knowledge representation; multi-agent systems; multi-robot systems; remotely operated vehicles; state feedback; underwater vehicles; Ocean Sampling Mobile Network simulator testbed; SAMON testbed; automaton-based model; dynamically adaptive sampling techniques; fixed sensors; formal control language; group behavior; heterogeneous autonomous components; high-fidelity simulators; intelligent control; knowledge representations; mission reconfiguration decisions; multilayered adaptation; multirobot ocean-mapping missions; multistage inferencing strategies; on-board sensors; real-time interactions; realistic ocean environment; spatio-temporal coordination; state feedback mapping; supervisory controllers; synergistic research interactions; unmanned underwater vehicles; web-based integration; Intelligent control; Intelligent sensors; Marine vehicles; Mobile robots; Oceans; Physics; Remotely operated vehicles; Sampling methods; Testing; Vehicle dynamics;
Journal_Title :
Oceanic Engineering, IEEE Journal of