This paper uses a behavioral hierarchy approach to reduce the mission solution space and make the mission design
easier. A UAV behavioral hierarchy is suggested, which is derived from three levels of behaviors: basic, individual and
group. The individual UAV behavior is a combination of basic, lower level swarming behaviors with priorities. Mission
design can be simplified by picking the right combination of individual swarming behaviors, which will emerge the
needed group behaviors. Genetic Algorithm is used in both lower-level basic behavior design and mission design.
Visualizing information in three dimensions provides an increased understanding of the data presented. Furthermore, the ability to manipulate or interact with data visualized in three dimensions is superior. Within the medical community, augmented reality is being used for interactive, three-dimensional (3D) visualization. This type of visualization, which enhances the real world with computer generated information, requires a display device, a computer to generate the 3D data, and a system to track the user. In addition to these requirements, however, the hardware must be properly integrated to insure correct visualization. To this end, we present components of an integrated augmented reality system consisting of a novel head-mounted projective display, a Linux-based PC, and a commercially available optical tracking system. We demonstrate the system with the visualization of anatomical airways superimposed on a human patient simulator.
The control of the Unmanned Combat Air Vehicle's swarm behavior is studied. One command string controls the motion of all Unmanned Combat Air Vehicles in a mission. Each Unmanned Combat Air Vehicle moves according to the control decoded from the same control command string. There is no explicit coordination among them. However, the decoding of a control command string partially depends on other Unmanned Combat Air Vehicles surrounding it. If the control command string is properly chosen, the motion of the swarm of Unmanned Combat Air Vehicles will perform well collectively. Genetic algorithm is used to evolve the control command string. The robustness of the control is studied. Monte Carlo simulation in conjunction with Genetic Algorithm is used to evolve the robust control when wind-gust disturbance exists. The results of different approached are compared.
Simulation technology has been widely used in all aspects of military applications. In different applications, the fidelity requirements are also different, and so are the simulation models. Using the development of new military aircraft as an example, the simulation fidelity requirement would be very high. In this case, the simulation model has to include many details. On the other hand, the pilot training simulator has to satisfy the real-time simulation requirement; its fidelity cannot be very high and the model has to be simplified. Therefore, the reusability of military platform's simulation models is very low. This paper suggests an Object-Oriented approach to the modeling of military platforms. A helicopter is chosen to be the sample platform. To limit the scope of the problem, only the dynamical model of the helicopter is considered. This model includes equations of motion, kinematics, power plant, and interaction with the environment. The helicopter dynamical models can have many levels of detail. In a constructive simulation, it is possible that only the positions of the helicopter are of interest; therefore, a simple kinematic model may be sufficient. On the other hand, in a wargame simulation, the helicopter responds to control commands and moves from one position to another. A point-mass model can represent such motion. In a helicopter pilot trainer, though, a six-degree-of-freedom model is needed to represent both linear motion and the roll-pitch-yaw orientation. However, the real-time simulation requirement prohibits the model to use sophisticated aerodynamic models. Thus, in some applications, only two-dimensional motion is needed; in other applications, a four-degree-of-freedom model is sufficient. The object-oriented approach uses the concept of hierarchy and inheritance to build classes ofcomponents. Based on the fidelity requirements, classes and sub-classes can be replaced. This approach greatly increases the reusability ofthe model.
In this paper, the infrastructure of designing a multi-user wargaming environment over the WWW architecture is proposed. The proposed infrastructure is based upon the existence of a multi-user virtual reality system on top of the WWW environment. Hence, the necessary conditions for a network- based virtual reality system to support designing a wargaming environment are analyzed and studied in this paper. Finally, a prototype of a multi-user wargaming system was implemented with the SharedWeb system. The SharedWeb system is a multi-user virtual reality system built over the WWW environment. The SharedWeb system provides a seamless integration of virtual reality technique with the WWW architecture, which makes it an excellent platform for our experiment. The 3D tank combat simulation is the result of this prototyping process. The scenario of this 3D tank wargame is a two-company drill and each company has two tanks. Since this application is simply a proof of principle, the player can only control the movement and direction of each tank as well as issue the fire command. The experience presented in this paper may provide some though on designing a new generation of war game system for the year 2000.
This paper analyzes the use of dead reckoning in Distributed Interactive Simulation. The purpose of dead reckoning is to reduce the updates required by each simulator on the network to better utilize the available bandwidth. Extrapolation formulas are derived and discussed based on network communication traffic and the amount of computation performed by simulators. Smoothing and delay compensation algorithms are also discussed. Numerical and human perspective experiment are conducted. A software tool that assesses the performance of the read reckoning algorithm is introduced.