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The 4D/RCS Reference Model Architecture is a reference model for military unmanned vehicles on how their software components should be identified and organized. The 4D/RCS has been developed by the Intelligent Systems Division (ISD) of the National Institute of Standards and Technology (NIST) since the 1980s.〔Danil Prokhorov (2008) ''Computational Intelligence in Automotive Applications''. p. 315〕 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.〔Albus, J.S. et al. (2006). "(Learning in a Hierarchical Control System: 4D/RCS in the DARPA LAGR Program )". NIST June 26, 2006. in: ''ICINCO 06 - International Conference in Control, Automation and Robotics, Setubal, Portugal, August 2006''〕 ==Overview== 4D/RCS is a reference model architecture that provides a theoretical foundation for designing, engineering, integrating intelligent systems software for unmanned ground vehicles.〔Douglas Whitney Gage (2004). ''Mobile robots XVII: 26–28 October 2004, Philadelphia, Pennsylvania, USA''. Society of Photo-optical Instrumentation Engineers. page 35.〕 According to Balakirsky (2003) 4D/RCS is an example of deliberative agent architecture. These architectures "include all systems that plan to meet future goal or deadline. In general, these systems plan on a model of the world rather than planning directly on processed sensor output. This may be accomplished by real-time sensors, a priori information, or a combination of the two in order to create a picture or snapshot of the world that is used to update a world model".〔S.B. Balakirsky (2003). ''A framework for planning with incrementally created graphs in attributed problem spaces''. IOS Press. ISBN 1-58603-370-0. p.10-11.〕 The course of action of a deliberative agent architecture is based on the world model and the commanded mission goal, see image. This goal "may be a given system state or physical location. To meet the goal systems of this kind attempts to compute a path through a multi-dimensional space contained in the real world".〔 The 4D/RCS is a hierarchical deliverative architecture, that "plans up to the subsystem level to compute plans for an autonomous vehicle driving over rough terrain. 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. The trajectories are computed based on a discrete set of possible vehicle velocities and starting steering agles. All of the trajectories are guaranteed to be dynamically correct for the given velocity and steering angle. The systems runs under a fixed planning cycle, with the sensed information being updated into the world model at the beginning of the cycle. These update information include information on what area is currently under observation by the sensors, where detected obstacles exist, and vehicle status".〔 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「4D-RCS Reference Model Architecture」の詳細全文を読む スポンサード リンク
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