Integrating Partial-Order Planning into the Orca Schema-Based Mission Controller

Reasoning about plans and actions is fundamental to intelligent control of real-world systems such as AUVs. These plans can come from a library of existing plans or from creating a new plan if no appropriate plan exists for the situation. The Orca project [Turner, 1994] is an ongoing effort to creat...

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Bibliographic Details
Main Authors: Prabha Ramakrishnan, Roy Turner
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 1997
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.6013
http://cdps.umcs.maine.edu/Papers/1997/UUST-pop/paper.ps
Description
Summary:Reasoning about plans and actions is fundamental to intelligent control of real-world systems such as AUVs. These plans can come from a library of existing plans or from creating a new plan if no appropriate plan exists for the situation. The Orca project [Turner, 1994] is an ongoing effort to create an intelligent system for mission-level control of autonomous underwater vehicles. Orca's primary means of achieving goals is to retrieve existing plans from memory and to apply them by doing their steps. This paper describes our effort to integrate partial-order planning into Orca's schema-based planning mechanism. With this work, Orca first looks for an appropriate plan in its repertoire of plans to achieve a goal or a set of goals. If such a plan is not available, it considers more general plans. For some goals, even a generalized plan may not be readily available. In such cases, Orca uses partial-order planning to generate a specific plan "from scratch" for the problem-solving situati.