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Extensions of sampling-based approaches to path planning in complex cost spaces: applications to robotics and structural biology

Devaurs, Didier. Extensions of sampling-based approaches to path planning in complex cost spaces: applications to robotics and structural biology. PhD, Institut National Polytechnique de Toulouse, 2014

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Official URL: http://ethesis.inp-toulouse.fr/archive/00002817/

Abstract

Planning a path for a robot in a complex environment is a crucial issue in robotics. So-called probabilistic algorithms for path planning are very successful at solving difficult problems and are applied in various domains, such as aerospace, computer animation, and structural biology. However, these methods have traditionally focused on finding paths avoiding collisions, without considering the quality of these paths. In recent years, new approaches have been developed to generate high-quality paths: in robotics, this can mean finding paths maximizing safety or control; in biology, this means finding motions minimizing the energy variation of a molecule. In this thesis, we propose several extensions of these methods to improve their performance and allow them to solve ever more difficult problems. The applications we present stem from robotics (industrial inspection and aerial manipulation) and structural biology (simulation of molecular motions and exploration of energy landscapes).

Item Type:PhD Thesis
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
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Research Director:
Cortés, Juan
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Deposited By: admin admin
Deposited On:18 Dec 2014 23:00

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