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Proceedings ArticleDOI

Knowledge-Based Tactical Terrain Analysis

TLDR
This paper describes a concept of knowledge-based terrain analysis currently being developed to support the information needs of an autonomous helicopter system that consists of five integrated processing stages.
Abstract
The performance of autonomous vehicle systems is currently limited by their inability to accurately analyze their surrounding environment In order to function in a dynamic real world environment, an autonomous vehicle system must be capable of interpreting terrain based upon predetermined mission goals This paper describes a concept of knowledge-based terrain analysis currently being developed to support the information needs of an autonomous helicopter system The terrain analysis system consists of five integrated processing stages Each process is discussed in detail and supported by a number of mission oriented examples Int roduction One of the most unique system concepts being explored today is that of the development of totally autonomous land, sea, and air vehicles [1 - 3] For military applications, autonomous vehicles provide a mechanism for removing humans from modern day battlefields while not impacting the tactical capabilities of the battle force Civilian applications for such a device entail the investigation of hazardous areas (eg nuclear reactors and toxic waste dumps), search over large areas (eg downed aircraft or lost campers) and monitoring of large facilities (eg robot security police) As military funding for these systems is currently at an alltime high, a variety of autonomous system concepts are continually being presented in the technical literature The primary limitation of an autonomous vehicle still lies in its inability to accurately analyze surrounding terrain information in order to generate tactical plans of action This paper describes activities being performed in the Artificial Intelligence Branch of the Georgia Tech Research Institute on knowledge-based terrain analysis, particularly in support of the autonomous helicopter programSystem OverviewThe knowledge-based tactical terrain analysis system consists of five separate processing phases: [1] image segmentation, [2] region classification, [3] visual model, [4] route planning, [5] threat location and coverage Each processing phase is briefly discussed in the following subsections with actual image results given where appropriate

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Citations
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Proceedings ArticleDOI

Tess = The Tactical Expert System

TL;DR: The basic target recognition features of TESS are highlighted and several areas of activity research being performed to enhance the TESS system are described.
Journal ArticleDOI

The performance of KIMS in image recognition tasks

TL;DR: The current performance of KIMS in product inspection decision is presented and rules which are developed through statistical experimentation with thresholding and quality control chart algorithms are presented.
References
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Book

Fundamentals of interactive computer graphics

TL;DR: The foundations of interactive computer graphics are studied in detail in the second part of this monograph on computer graphics theory andUX.
Journal ArticleDOI

Area Segmentation of Images Using Edge Points

TL;DR: A new method for segmenting images using abrupt changes in intensity (edge points) to separate regions of smoothly varying intensity is discussed, using an expansion-contraction technique in which the edge regions are first expanded to close gaps and then contracted after the separate uniform regions have been identified.
Proceedings Article

Terrain navigation through knowledge-based route planning

TL;DR: A heuristic route planning system capable of forming the planning foundation of an autonomous ground vehicle is described.
Proceedings ArticleDOI

The Autonomous Helicopter System

TL;DR: The Autonomous Helicopter System (AHS) as discussed by the authors is a multi-mission system consisting of three distinct sections: vision, planning, and control, where vision provides the local and global scene analysis which is symbolically represented and passed to planning as the initial route planning constraints.
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