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.
The propulsion systems employed on unmanned ground vehicle platforms in Future Force Units of Action will likely involve electric or hybrid-electric drive. Power storage systems for these platforms will therefore be driven largely by expected power depletion rates. Resistances that propulsion systems must overcome during maneuvers will be a major factor affecting power depletion rates, and the resistance forces will vary drastically depending on the mission. Therefore, realistic mission-related considerations need to be applied when defining power storage requirements. The US Army has developed numerous models and simulations that use terra-mechanics algorithms to predict maneuver capability for ground vehicles as limited by terrain and environmental factors, and the algorithms employed for predicting maneuver capability in most of these models and simulations are founded on the terra-mechanics algorithms contained in the NATO Reference Mobility Model. The NATO Reference Mobility Model uses physics-based force balancing algorithms with terra-mechanics relationships that were empirically derived from decades of vehicle-terrain interaction research, and it also incorporates proven methodologies for assessing mission effectiveness in terms of maneuver capabilities. The terra-mechanics algorithms and methodologies for assessing mission effectiveness that are implemented in this model and in other related software tools, such as those used for route analysis, can be used to generate realistic mission-related resistance profiles for defining power storage requirements.