Strategic Path Planning by Sequential Parametric Bayesian Decisions

The objective of this research is to generate a path for a mobile agent that carries sensors used for classification, where the path is to optimize strategic objectives that account for misclassification and the consequences of misclassification, and where the weights assigned to these consequences...

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Bibliographic Details
Main Authors: Baro Hyun, Pierre Kabamba, Anouck Girard
Format: Article
Language:English
Published: SAGE Publishing 2013-11-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/56647
Description
Summary:The objective of this research is to generate a path for a mobile agent that carries sensors used for classification, where the path is to optimize strategic objectives that account for misclassification and the consequences of misclassification, and where the weights assigned to these consequences are chosen by a strategist. We propose a model that accounts for the interaction between the agent kinematics (i.e., the ability to move), informatics (i.e., the ability to process data to information), classification (i.e., the ability to classify objects based on the information), and strategy (i.e., the mission objective). Within this model, we pose and solve a sequential decision problem that accounts for strategist preferences and the solution to the problem yields a sequence of kinematic decisions of a moving agent. The solution of the sequential decision problem yields the following flying tactics: “approach only objects whose suspected identity matters to the strategy”. These tactics are numerically illustrated in several scenarios.
ISSN:1729-8814