Dynamical system for learning the waveform and frequency of periodic signals - application to drumming
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In this paper we combine kinesthetic demonstrations and dynamical systems to enable a humanoid robot to imitate constrained reaching gestures directed toward a target. Using a learning algorithm based on Gaussian Mixture Regression, the task constraints ar ...
We present a Programming by Demonstration (PbD) framework for generically extracting the relevant features of a given task and for addressing the problem of generalizing the acquired knowledge to different contexts. We validate the architecture through a s ...
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We aim at developing autonomous micro-flyers capable of navigating within houses or small built environments. The severe weight and energy constraints of indoor flying platforms led us to take inspiration from flying insects for the selection of sensors, s ...
The purpose of this thesis is to develop new methods for automatic transcription of melody and harmonic parts of real-life music signal. Music transcription is here defined as an act of analyzing a piece of music signal and writing down the parameter repre ...
The online generation of trajectories in humanoid robots remains a difficult problem. In this contribution, we present a system that allows the superposition, and the switch between, discrete and rhythmic movements. Our approach uses nonlinear dynamical sy ...
Robot PbD started about 30 years ago, growing importantly during the past decade. The rationale for moving from purely preprogrammed robots to very flexible user-based interfaces for training the robot to perform a task is three-fold. First and foremost, P ...
We present a generic framework that combines Dynamical Systems movement control with Programming by Demon- stration (PbD) to teach a robot bimanual coordination task. The model consists of two systems: a learning system that processes data collected during ...
In this thesis, we present a dynamical systems approach to adaptive controllers for locomotion control. The approach is based on a rigorous mathematical framework using nonlinear dynamical systems and is inspired by theories of self-organization. Nonlinear ...
Nonlinear oscillators are widely used in biology, physics and engineering for modeling and control. They are interesting because of their synchronization properties when coupled to other dynamical systems. In this paper, we propose a learning rule for osci ...