DocumentCode :
3223480
Title :
Intent inference using a potential field model of environmental influences
Author :
Glinton, Robin ; Owens, Sean ; Giampapa, Joseph ; Sycara, Katia ; Lewis, Michael ; Grindle, Chuck
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume :
2
fYear :
2005
fDate :
25-28 July 2005
Abstract :
Intent inferencing is the ability to predict an opposing force´s (OPFOR) high level goals. This is accomplished by the interpretation of the OPFOR´s disposition, movements, and actions within the context of known OPFOR doctrine and knowledge of the environment. For example, given likely OPFOR force size, composition, disposition, observations of recent activity, obstacles in the terrain, cultural features such as bridges, roads, and key terrain, intent inferencing will be able to predict the opposing force´s high level goal and likely behavior for achieving it. This paper describes an algorithm for intent inferencing on an enemy force with track data, recent movements by OPFOR forces across terrain, terrain from a GIS database, and OPFOR doctrine as input. This algorithm uses artificial potential fields to discover field parameters of paths that best relate sensed track data from the movements of individual enemy aggregates to hypothesized goals. Hypothesized goals for individual aggregates are then combined with enemy doctrine to discover the intent of several aggregates acting in concert.
Keywords :
geographic information systems; inference mechanisms; sensor fusion; terrain mapping; tracking; GIS database; OPFOR doctrine; artificial potential field; data tracking; hypothesized goal; information fusion; intent inferencing; opposing force prediction; Aggregates; Bridges; Cultural differences; Data mining; Hidden Markov models; Inference algorithms; Robots; Statistics; Tracking; Working environment noise; Intent inference; artificial potential field; information fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Fusion, 2005 8th International Conference on
Print_ISBN :
0-7803-9286-8
Type :
conf
DOI :
10.1109/ICIF.2005.1591965
Filename :
1591965
Link To Document :
بازگشت