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Please use this identifier to cite or link to this item: http://hdl.handle.net/1993/2824

Title: Learning with ALiCE II
Authors: Lockery, Daniel Alexander
Supervisor: Peters, James F. (Electrical and Computer Engineering)
Examining Committee: Fazel-Rezai, Reza (Electrical and Computer Engineering) Balakrishnan, Subramaniam (Mechanical and Manufacturing Engineering)
Graduation Date: October 2007
Keywords: Reinforcement learning
Line crawling robot
Target tracking
Monocular vision
Rough sets
Approximation spaces
Ethology
Issue Date: 14-Sep-2007
Abstract: The problem considered in this thesis is the development of an autonomous prototype robot capable of gathering sensory information from its environment allowing it to provide feedback on the condition of specific targets to aid in maintenance of hydro equipment. The context for the solution to this problem is based on the power grid environment operated by the local hydro utility. The intent is to monitor power line structures by travelling along skywire located at the top of towers, providing a view of everything beneath it including, for example, insulators, conductors, and towers. The contribution of this thesis is a novel robot design with the potential to prevent hazardous situations and the use of rough coverage feedback modified reinforcement learning algorithms to establish behaviours.
URI: http://hdl.handle.net/1993/2824
Appears in Collection(s):FGS - Electronic Theses & Dissertations (Public)

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