4D-RCS Reference Model Architecture
[2] 4D/RCS is a reference model architecture that provides a theoretical foundation for designing, engineering, integrating intelligent systems software for unmanned ground vehicles.
To meet the goal systems of this kind attempts to compute a path through a multi-dimensional space contained in the real world".
In this system, the world model contains a pre-computed dictionary of possible vehicle trajectories known as an ego-graph as well as information from the real-time sensor processing.
[4] The National Institute of Standards and Technology's (NIST) Intelligent Systems Division (ISD) has been developing the RCS reference model architecture for over 30 years.
4D/RCS is the most recent version of RCS developed for the Army Research Lab Experimental Unmanned Ground Vehicle program.
The 4D in 4D/RCS signifies adding time as another dimension to each level of the three-dimensional (sensor processing, world modeling, behavior generation), hierarchical control structure.
[2] 4D/RCS integrates the NIST Real-time Control System (RCS) architecture with the German (Bundeswehr University of Munich) VaMoRs 4-D approach to dynamic machine vision.
Demo III (2001)[6] demonstrated the ability of unmanned ground vehicles to navigate miles of difficult off-road terrain, avoiding obstacles such as rocks and trees.
The 2004 and 2005 DARPA competitions allowed international teams to compete in fully autonomous vehicle races over rough unpaved terrain and in a non-populated suburban setting.
[2] 4D/RCS prescribes a hierarchical control principle that decomposed high level commands into actions that employ physical actuators and sensors.
The figure for example shows a high level block diagram of a 4D/RCS reference model architecture for a notional Future Combat System (FCS) battalion.
[2] A high level diagram of the internal structure of the world model and value judgment system is shown in the figure.
The connections to the Operator Interface enable a human operator to input commands, to override or modify system behavior, to perform various types of teleoperation, to switch control modes (e.g., automatic, teleoperation, single step, pause), and to observe the values of state variables, images, maps, and entity attributes.
[5] The figure is a computational hierarchy view of the first five levels in the chain of command containing the Autonomous Mobility Subsystem in the 4D/RCS architecture developed for Demo III.
This enables the vehicle to make small path corrections to avoid bumps and ruts during the 500 ms planning horizon of the Primitive level.
To meet the demands of dynamic battlefield environments, the 4D/RCS architecture specifies that replanning should occur within about one-tenth of the planning horizon at each level.
