Paul W. Richmond

Estimating Off-Road Ground Contact Forces for a Real Time Motion Simulator

Researchers at the US Army Engineer Research and Development Center (ERDC), working in the field of vehicle mobility, have developed methods to predict the physical interactions of vehicles with soil surfaces. This set of methods use research conducted at the ERDC over the last 40 years to predict the physical interactions of vehicles and terrain surfaces under all seasons. Methodologies to measure pertinent terrain properties and assess vehicle performance have also been developed. Much of the work focused on practical applications and is the result of extensive vehicle performance testing and the subsequent analysis of the test results. While there have been attempts to identify and characterize soil media properties using standard soil classification techniques and to assess their effects on vehicle mobility using classical soil mechanics and other theoretical approaches, the current state-of-the-art is such that these approaches have limited practical application. The ERDCs approach has been to quantify and relate a set of fundamental vehicle traction element performances to easily obtainable terrain properties. This empirical and lumped parameter approach has provided relevant and verifiable results for decades, but due to its nature, is difficult to extrapolate and manipulate mathematically. Nevertheless, the ease of obtaining suitable terrain properties, its historical success in vehicle performance predictions, and its maturity and broad validation database have made it an attractive choice for implementation into a simulated terrain mechanics model for real time dynamics vehicle simulators. This paper describes the algorithms selected for estimating longitudinal force coefficients for soils (frozen and non-frozen), snow, and ice, and the underlying assumptions.

Using an Ontology for Entity Situational Awareness in a Simple Scenario

The use of ontologies to represent data and knowledge combined with service-based software provides new opportunities for the integration of command and control systems, simulations, and dynamic data. The U.S. Department of Defenses Global Information Grid (GIG) is envisioned to integrate complex communications networks, data from disparate sources, and services-oriented applications. The GIG will provide analysis, decision support, and information visualization to both human and automated users. This paper describes concepts and architecture for an experiment which demonstrates the use of knowledge-based technologies to support tactical maneuver. Open source and in-house software were linked together to conduct a simple simulation of a realistic mission (move from A to B along a “safe” route). Events which may affect the route are injected, reported, and stored in the knowledge base to simulate battlespace dynamics. Through the use of an automated reasoner, events which affect the route are identified and passed to the decision maker to stimulate possible replanning. Follow-on efforts will convert the maneuver related software into web services, moving closer to the GIG concept. Discussed is the value of a formal ontology within the domain of military maneuver, architectural approach, and lessons learned.

Co-Adaptive Behavior Algorithms for Insurgent and Counter-Insurgent Techniques in Combat Simulations

This paper proposes an overall strategy and technical approach that allows development of sophisticated behavior algorithms which model insurgent and counter-insurgent techniques in military combat simulations. This capability will allow Department of Defense force providers to estimate, in a combat model, the effects of different approaches to counter-insurgency operations, reconstruction operations, stability operations, and information operations. The overall approach proposes development of robust application programming interfaces that can be employed in several different combat simulations. In a phased strategy, technical development will first focus on task-level behaviors. It will then shift to short-term planning behaviors and long-term planning behaviors. These planning behaviors will make significant use of geospatial reasoning and course of action analysis via simulation. It will also consider civilian behaviors as they relate to supporting either the insurgents or the government security forces. Armed with these simulation capabilities, the military services will be able to make better decisions about the proper mix of forces, equipment, and tactics to provide for use in the different theaters of operation.