François Gaillard

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The usual way to design a simulation of a given phenomenon is to first build a model and then to implement it. The study of the simulation and its outcomes tells if the model is adequate and can explain the phenomenon. In this paper, we reverse this process by building a browser in simulations space: we study an automatically built simulation to understand(More)
Virtual reality offers new possibilities of cooperation for the concept phase of a product development. The deployment of a cooperative system suffers mainly from the client-server approach that is inefficient in many ways and attributes a leading role to a server site. Moreover, requiring a specific quality from the under-laying communication restricts(More)
— DKP (Deterministic Kinodynamic Planning) is a bottom-up trajectory planner for robots with flatness properties. DKP builds an exploration tree of which the branches are spline trajectories. DKP employs an A *-like algorithm to select which branch of the tree to grow. The selected trajectories are then grown in a propagation process which respects the(More)
Computational Auditory Scene Analysis (CASA) aims to model our ability to structure our acoustical environment. In a CASA context, this paper deals with a method for time-frequency labeling based on harmonic properties. The method is based on a classical pitch extraction algorithm, termed the « zero-crossing method », which is known to be particularly(More)
The usual way to design a simulation of a phenomenon is to first build a model and then to implement it. The study of the simulation and its outcomes tells if the model is adequate and can explain the phenomenon. With LEIA, we reverse this process by studying an automatically built simulation by exploring the simulations space in order to identify(More)
We present a two-layer architecture for two-wheeled robots trajectory planning. This architecture can be used to describe steering behaviours and to generate candidate trajectories that will be evaluated by a higher-level layer before choosing which one will be followed. The higher layer uses a TAEMS tree to describe the current robot goal and its(More)
The usual way to design a simulation of a phenomenon is to create its model and then implement it: its study allows to know if the model is adequate and can explain the phenomenon. We propose to reverse this process by exploring the simulation space in order to identify remarkable phenomena until understanding the underlying mechanisms. This paper deals(More)
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