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Thesis
Home   /   Thesis   /   Generation and control of virtual manikins using learning methods for the simulation of industrial processes using virtual reality

Generation and control of virtual manikins using learning methods for the simulation of industrial processes using virtual reality

Engineering sciences Mathematics - Numerical analysis - Simulation Numerical simulation Technological challenges

Abstract

The thesis is focused on the simulation of virtual manikins in an industrial context using virtual reality. The virtual operator is meant to realize different tasks (manipulate, screw…) in virtual environments with different levels of constraints. The movements of the operator must be as faithful as possible from reality, in terms of posture, efforts and interactions with the environment.
Considering the sophistication of the gestures to reproduce and the number of parameters to define manually, it becomes too complex to use classical control methods. In the literature, studies using imitation learning methods show promising results. These methods however have important drawbacks, such as the use of big samples databases and important training times.
The aim of the thesis is to bring substantial modifications to existing methods and to propose a new one, that can learn and coordinate, using a database of moderate size, movements and interactions of a virtual manikin necessary to the realization of tasks in an industrial context. Great attention will be given to the efforts generated to produce the movements and their adequation with physics realism. The new method will be applied to industrial use cases and simulations using virtual reality.

Laboratory

Département Intelligence Ambiante et Systèmes Interactifs (LIST)
Service Interactions et Réseaux
Laboratoire de Simulation Interactive
Rennes
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