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Elena Gribovskaya

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Publications associées (8)

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Imitation Learning of Motion Coordination in Robots

Elena Gribovskaya

The ease with which humans coordinate all their limbs is fascinating. Such a simplicity is the result of a complex process of motor coordination, i.e. the ability to resolve the biomechanical redundancy in an efficient and repeatable manner. Coordination e ...

EPFL2012

Learning Nonlinear Multivariate Dynamics of Motion in Robotic Manipulators [accepted]

Aude Billard, Seyed Mohammad Khansari Zadeh, Elena Gribovskaya

Motion imitation requires reproduction of a dynamical signature of a movement, i.e. a robot should be able to encode and reproduce a particular path together with a specific velocity and/or an acceleration profile. Furthermore, a human provides only few de ...

SAGE Publications2011

Motion Learning and Adaptive Impedance for Robot Control during Physical Interaction with Humans

Aude Billard, Elena Gribovskaya

One of the hallmarks of physical interaction between humans is haptic communication, i.e. an informa- tion exchange through force signals. Humans excel in tasks that require such interaction by adapting impedance and anticipating the partner’s intentions. ...

2011

Learning Motion Dynamics to Catch a Moving Object

Aude Billard, Elena Gribovskaya, Seungsu Kim

In this paper, we consider a novel approach to control the timing of motions when these are encoded with autonomous dynamical systems (DS). Accurate timing of motion is crucial if a robot must synchronize its movement with that of a fast moving object. In ...

2010

Teaching Physical Collaborative Tasks: Object-Lifting Case Study with a Humanoid

Aude Billard, Sylvain Calinon, Elena Gribovskaya

This paper presents the application of a statistical framework that allows to endow a humanoid robot with the ability to perform a collaborative manipulation task with a human operator. We investigate to what extent the dynamics of the motion and the hapti ...

IEEE2009

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This paper presents a method by which a robot can learn through observation to perform a collaborative manipulation task, namely lifting an object. The task is first demonstrated by a user controlling the robot's hand via a haptic interface. Learning extra ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009

Learning Nonlinear Multi-Variate Motion Dynamics for Real- Time Position and Orientation Control of Robotic Manipulators

Aude Billard, Elena Gribovskaya

We present a generic framework that allows learning non- linear dynamics of motion in manipulation tasks and generating dynamical laws for control of position and orientation. This work follows a recent trend in Programming by Demonstration in which the dy ...

2009

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 ...

2008