Physics-based simulations of autonomous unmanned ground vehicles (UGV) present unique challenges and advantages
compared to real-time simulations with lower-fidelity models. We have created a high-fidelity simulation
environment, called the Virtual Autonomous Navigation Environment (VANE), to perform physics-based simulations
of UGV. To highlight the capabilities of the VANE, we recently completed a simulation of a robot
performing a reconnaissance mission in a typical Middle Eastern town. The result of the experiment demonstrated
the need for physics-based simulation for certain circumstances such as LADAR returns from razor wire
and GPS dropout and dilution of precision in urban canyons.
It is widely recognized that simulation is pivotal to vehicle development, whether manned or unmanned. There are few
dedicated choices, however, for those wishing to perform realistic, end-to-end simulations of unmanned ground vehicles
(UGVs). The Virtual Autonomous Navigation Environment (VANE), under development by US Army Engineer
Research and Development Center (ERDC), provides such capabilities but utilizes a High Performance Computing
(HPC) Computational Testbed (CTB) and is not intended for on-line, real-time performance. A product of the VANE
HPC research is a real-time desktop simulation application under development by the authors that provides a portal into
the HPC environment as well as interaction with wider-scope semi-automated force simulations (e.g. OneSAF). This
VANE desktop application, dubbed the Autonomous Navigation Virtual Environment Laboratory (ANVEL), enables
analysis and testing of autonomous vehicle dynamics and terrain/obstacle interaction in real-time with the capability to
interact within the HPC constructive geo-environmental CTB for high fidelity sensor evaluations. ANVEL leverages
rigorous physics-based vehicle and vehicle-terrain interaction models in conjunction with high-quality, multimedia
visualization techniques to form an intuitive, accurate engineering tool. The system provides an adaptable and
customizable simulation platform that allows developers a controlled, repeatable testbed for advanced simulations.
ANVEL leverages several key technologies not common to traditional engineering simulators, including techniques
from the commercial video-game industry. These enable ANVEL to run on inexpensive commercial, off-the-shelf
(COTS) hardware. In this paper, the authors describe key aspects of ANVEL and its development, as well as several
initial applications of the system.
This paper describes the application of an Army-standard legacy off-road mobility model to cross-country route planning and negotiation by unmanned ground vehicles. A planned route is created from a movement map generated from existing terrain data. An unmanned ground vehicle negotiates the planned route and makes local routing adjustments based on a trafficability assessment of terrain features which are observed from the platform. This research leverages results from other work investigating the scalability of the existing legacy off-road mobility model to small vehicles (<500 kg). The legacy mobility model is the NATO Reference Mobility Model II (NRMM II), a standard for combat mobility modeling and procurement since the mid-90's.
KEYWORDS: Sensors, Land mines, Visualization, Genetic algorithms, Explosives, Detection and tracking algorithms, Soil science, Data integration, 3D scanning, Interfaces
This paper outlines an approach to extrude two-dimensional existing information to support the prediction of subsurface discrete objects. The goal of this study is to develop one part of a toolkit to generate realistic, simulated subsurface material and property distributions supporting detection of surface and subsurface explosives. A sample one-meter cubic grid of heterogeneous media is simulated along with expected deviations. We explain the method used to generate a volume of soil, number of geologic features included (if any), and location. This method is expected to be used to depict a larger surface area based on representative limited visual and laboratory data. The soil volume will be used to exercise models providing a signature of subsurface media allowing the simulation of detection by various sensors of buried and surface ordnance.
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