Model-Unified Planning and Execution for Distributed Autonomous System Control

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

[1]  Brian C. Williams,et al.  Model-Based Programming of Fault-Aware Systems , 2004, AI Mag..

[2]  Tara Estlin,et al.  The CLARAty architecture for robotic autonomy , 2001, 2001 IEEE Aerospace Conference Proceedings (Cat. No.01TH8542).

[3]  Tara Estlin,et al.  Using Continous Planning Techniques to Coordinate Multiple Rovers , 1999 .

[4]  Ève Coste-Manière,et al.  The ORCCAD Architecture , 1998, Int. J. Robotics Res..

[5]  P. Pandurang Nayak,et al.  Remote Agent: To Boldly Go Where No AI System Has Gone Before , 1998, Artif. Intell..

[6]  C. Douglas Locke,et al.  Software architecture for hard real-time applications: Cyclic executives vs. fixed priority executives , 1992, Real-Time Systems.

[7]  Nicola Muscettola,et al.  Planning in Interplanetary Space: Theory and Practice , 2000, AIPS.

[8]  Maarten Sierhuis,et al.  Field Demonstration of Surface Human-Robotic Exploration Activity , 2006, AAAI Spring Symposium: To Boldly Go Where No Human-Robot Team Has Gone Before.

[9]  Erann Gat,et al.  Experiences with an architecture for intelligent, reactive agents , 1997, J. Exp. Theor. Artif. Intell..

[10]  Nicola Muscettola,et al.  Intelligent Rover Execution for Detecting Life in the Atacama Desert , 2006, AAAI Fall Symposium: Spacecraft Autonomy.