Algorithms for Linguistic Robot Policy Inference from Demonstration of Assembly Tasks

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/43194

Title: Algorithms for Linguistic Robot Policy Inference from Demonstration of Assembly Tasks
Author: Dantam, Neil ; Essa, Irfan ; Stilman, Mike
Abstract: We describe several algorithms used for the inference of linguistic robot policies from human demonstration. First, tracking and match objects using the Hungarian Algorithm. Then, we convert Regular Expressions to Nondeterministic Finite Automata (NFA) using the McNaughton-Yamada-Thompson Algorithm. Next, we use Subset Construction to convert to a Deterministic Finite Automaton. Finally, we minimize finite automata using either Hopcroft's Algorithm or Brzozowski's Algorithm.
Type: Technical Report
URI: http://hdl.handle.net/1853/43194
Date: 2012
Contributor: Georgia Institute of Technology. Center for Robotics and Intelligent Machines
Relation: GT-GOLEM-2012-002
Publisher: Georgia Institute of Technology
Subject: Deterministic finite automaton
Hopcroft's algorithm
Human demonstration
Hungarian algorithm
McNaughton-Yamada-Thompson
Nondeterministic finite automata
Robot control policies
Subset construction

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