A TRAINING SIMULATION SYSTEM WITH REALISTIC AUTONOMOUS SHIP CONTROL
Monica N. Nicolescu, Ryan Leigh, Adam Olenderski, Sushil J. Louis, Sergiu M. Dascalu, Chris Miles, Juan Carlos Quiroz, Ryan Aleson · Computational Intelligence · 2007
In this article we present a computational approach to developing effective training systems for virtual simulation environments. In particular, we focus on a Naval simulation system, used for training of conning officers. The currently existing training solutions require multiple expert personnel to control each vessel in a training scenario, or are cumbersome to use by a single instructor. The inability of current technology to provide an automated mechanism for competitive realistic boat behaviors thus compromises the goal of flexible, anytime, anywhere training. In this article we propose an approach that reduces the time and effort required for training of conning officers, by integrating novel approaches to autonomous control within a simulation environment. Our solution is to developintelligent, autonomous controllersthat drive the behavior of each boat. To increase the system's efficiency we provide a mechanism for creating such controllers, from the demonstration of a navigation expert, using a simple programming interface. In addition, our approach deals with two significant and related challenges: therealism of behaviorexhibited by the automated boats and theirreal‐time response to changesin the environment. In this article, we describe the control architecture we developed that enables the real‐time response of boats and the repertoire of realistic behaviors we designed for this application. We also present our approach for facilitating the automatic authoring of training scenarios and we demonstrate the capabilities of our system with experimental results.