4D-RCS Reference Model Architecture: Difference between revisions

Revision as of 19:53, 13 January 2021

Latest revision as of 14:59, 22 July 2023

(4 intermediate revisions by 4 users not shown)

Line 1:

{{Short description|Reference model for military unmanned vehicles to identify and organize their software components}}

[[File:4D-RCS reference model architecture for an individual vehicle.jpg|thumb|420px|4D-RCS reference model architecture for an individual vehicle. It contains many layers of computational nodes each containing elements of sensory processing, world modeling, value judgment, and behavior generation.]]

The '''4D/RCS Reference Model Architecture''' is a [[reference model]] for military [[unmanned vehicle]]s on how their [[software]] components should be identified and organized.

Line 4 ⟶ 5:

The 4D/RCS has been developed by the Intelligent Systems Division (ISD) of the [[National Institute of Standards and Technology]] (NIST) since the 1980s.<ref>Danil Prokhorov (2008) ''Computational Intelligence in Automotive Applications''. p. 315</ref>

This reference model is based on the general [[Real-time Control System]] (RCS) Reference Model Architecture, and has been applied to many kinds of robot control, including autonomous vehicle control.<ref name="Albus06">Albus, J.S. et al. (2006). "[https://www.nist.gov/cgi-bin//get_pdf.cgi?pub_id=822702 Learning in a Hierarchical Control System: 4D/RCS in the DARPA LAGR Program]{{Dead link|date=July 2023 |bot=InternetArchiveBot |fix-attempted=yes }}". NIST June 26, 2006. in: ''ICINCO 06 - International Conference in Control, Automation and Robotics, Setubal, Portugal, August 2006''</ref>

==Overview==

Line 14 ⟶ 15:

==History==

The National Institute of Standards and Technology’sTechnology'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. ISD has studied the use of 4D/RCS in defense mobility, transportation, robot cranes, manufacturing, and several other applications.<ref name="Albus06"/>

4D/RCS integrates the NIST Real-time Control System (RCS) architecture with the German ([[Bundeswehr University of Munich]]) [[Ernst Dickmanns|VaMoRs 4-D approach]] to dynamic machine vision. It incorporates many concepts developed under the U.S. Department of Defense Demo I, Demo II, and Demo III programs, which demonstrated increasing levels of robotic vehicle autonomy. The theory embodied in 4D/RCS borrows heavily from cognitive psychology, semiotics, neuroscience, and artificial intelligence.<ref name="Albus02">Albus et al. (2002). ''4D-RCS A Reference Model Architecture For Unmanned Vehicle Systems Version 2.0''. National Institute of Standards and Technology, Gaithersburg, Maryland 20899Aug 2002.</ref>

Line 53 ⟶ 54:

# sensory processing, and

# value judgment.

There is also a [[knowledge base|knowledge database]] that represents the node’snode's best estimate of the state of the world at the

range and resolution that are appropriate for the behavioral decisions that are the responsibility of that node.

Line 84 ⟶ 85:

==External links==

{{commons category|4D-RCS Reference Model Architecture}}

* [https://web.archive.org/web/20091010082639/http://www.isd.mel.nist.gov/projects/rcs/ RCS The Real-time Control Systems Architecture] NIST Homepage

Line 90 ⟶ 91:

[[Category:Control theory]]

[[Category:Industrial computing]]

[[Category:UnmannedUncrewed vehicles]]