4D-RCS Reference Model Architecture: Difference between revisions

Revision as of 07:57, 30 April 2019

Revision as of 16:30, 20 September 2019

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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>

Three [[United States Government|US Government]] funded military efforts known as Demo I (US Army), Demo II (DARPA), and Demo III ([[US Army]]), are currently underway. Demo III (2001)<ref>{{cite conference|url=http://www.isd.mel.nist.gov/documents/albus/4DRCS.pdf |format=PDF |title=4-D/RCS reference model architecture for unmanned ground vehicles |first=J.A. |last=Albus |booktitle=Proc. of Symposium on Aerospace/Defense Sensing, Simulation and Controls |___location=Orlando, FL |year=2002 |deadurlurl-status=yesdead |archiveurl=https://web.archive.org/web/20040725051856/http://www.isd.mel.nist.gov/documents/albus/4DRCS.pdf |archivedate=2004-07-25 }}</ref> demonstrated the ability of unmanned ground vehicles to navigate miles of difficult off-road terrain, avoiding obstacles such as rocks and trees. [[James Albus]] at [[NIST]] provided the [[Real-time Control System]] which is a [[hierarchical control system]]. Not only were individual vehicles controlled (e.g. throttle, steering, and brake), but groups of vehicles had their movements automatically coordinated in response to high level goals.

In 2002, the [[DARPA Grand Challenge]] competitions were announced. The [[DARPA Grand Challenge (2005)|2004]] and [[DARPA Grand Challenge (2005)|2005 DARPA competitions]] allowed international teams to compete in fully autonomous vehicle races over rough unpaved terrain and in a non-populated suburban setting. The [[DARPA Grand Challenge (2007)|2007 DARPA challenge]], the DARPA urban challenge, involved autonomous cars driving in an urban setting.

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* At the ''Platoon level'' : Multiple sections containing a total of 10 or more vehicles of different types are coordinated to generate platoon tactics.

* At the ''Company level'' : Multiple platoons containing a total of 40 or more vehicles of different types are coordinated to generate company tactics.

* At the ''Battalion level'' : Multiple companies containing a total of 160 or more vehicles of different types are coordinated to generate battalion tactics.

At all levels, task commands are decomposed into jobs for lower level units and coordinated schedules for subordinates are generated. At all levels, communication between peers enables coordinated actions. At all levels, feedback from lower levels is used to cycle subtasks and to compensate for deviations from the planned situations.<ref name="Albus02"/>