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Using Model-Based Diagnosis to Build Hypotheses about Spatial Environments


Oliver Obst. Using Model-Based Diagnosis to Build Hypotheses about Spatial Environments. In Daniel Polani, Andrea Bonarini, Brett Browning, and Kazuo Yoshida, editors, RoboCup 2003: Robot Soccer World Cup VII, Lecture Notes in Artificial Intelligence, pp. 518 – 525, Springer, Berlin, Heidelberg, New York, 2004.
Extended version appeared as Fachberichte Informatik 4/2002, Universität Koblenz-Landau.


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Abstract

We present a method to build a hypothesis on the condition of the environment in which a robotic multi-agent team moves. Initially the robots have a default assumption about the conditions of the floor and on how moving under these condition works. For certain parts of the environment however, the default assumption may be wrong and moving around does not work in the expected way. Now the robotic team builds a hypothesis on the conditions of the yet unvisited part of the environment, so resources can be saved by avoiding areas that possibly also contain obstacles.
For a description of the environment and of the observations of the robots, we use propositional formulæ in a way similar to computing a diagnosis for electrical circuits. To actually compute the hypothesis, we need to compute models of the given set of clauses, where the extension of the ab-literal is minimal. The description of the environment can be generated automatically, and the proposed method is flexible so that different kinds of topologies can be covered.

BiBTeX Entry


@incollection{Obst04,
	Abstract = {We present a method to build a hypothesis on the
		   condition of the environment in which a robotic multi-agent team moves.
		   Initially the robots have a default assumption about the conditions of the
		   floor and on how moving under these condition works. For certain parts of
		   the environment however, the default assumption may be wrong and moving
		   around does not work in the expected way. Now the robotic team builds a
		   hypothesis on the conditions of the yet unvisited part of the environment,
		   so resources can be saved by avoiding areas that possibly also contain
		   obstacles. \par For a description of the environment and of the observations
		   of the robots, we use propositional formul{\ae} in a way similar to
		   computing a diagnosis for electrical circuits. To actually compute the
		   hypothesis, we need to compute models of the given set of clauses, where the
		   extension of the \emph{ab}-literal is minimal. The description of the
		   environment can be generated automatically, and the proposed method is
		   flexible so that different kinds of topologies can be covered.},
	Address = {Berlin, Heidelberg, New York},
	Author = {Oliver Obst},
	Booktitle = rc03,
	Editor = {Daniel Polani and Andrea Bonarini and Brett Browning and
		   Kazuo Yoshida},
	Pages = {518 -- 525},
	Publisher = {Springer},
	Series = lnai,
	Title = {Using Model-Based Diagnosis to Build Hypotheses about
		   Spatial Environments},
	Wwwnote = {E
		   xtended version appeared as Fachberichte Informatik 4/2002,
		   Universit{\"a}t Koblenz-Landau.},
	Year = 2004,