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The continuous increase, witnessed in the last decade, of both the amount of available data and the areas of application of machine learning, has lead to a demand for both learning and planning algorithms that are capable of handling large-scale problems. ...
This chapter surveys the main approaches developed to date to endow robots with the ability to learn from human guidance. The field is best known as robot programming by demonstration, robot learning from/by demonstration, apprenticeship learning and imita ...
We consider an imitation learning approach to model robot point-to-point (also known as discrete or reaching) movements with a set of autonomous Dynamical Systems (DS). Each DS model codes a behavior (such as reaching for a cup and swinging a golf club) at ...
Praxic functions are frequently altered following brain lesion, giving rise to apraxia - a complex pattern of impairments that has proven difficult to assess or interpret. Here we revisit a study on imitation of meaningless gestures in a patient with disco ...
Purpose – Intelligent control for unidentified systems with unstable equilibriums is not always a proper control strategy, which results in inferior performance in many cases. Because of the existing trial and error manner of the procedure in former durati ...
Apraxia is a poorly understood disorder of voluntary movement that is not due to basic sensory, motor or cognitive deficits. We conducted a study on the imitation of meaningless gestures in apraxic patients with left fronto-temporo-parietal lesions. In a f ...
Most of the Central Pattern Generator (CPG) models are based on defining explicit dynamical systems and finding the appropriate parameters. In this paper, we propose a novel CPG model that is based on altering a nonlinear oscillator to obtain desired limit ...
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2009
We present a probabilistic approach to learn robust models of human motion through imitation. The association of Hidden Markov Model (HMM), Gaussian Mixture Regression (GMR) and dynamical systems allows us to extract redundancies across multiple demonstrat ...
This paper presents a method to learn arbitrary discrete motions from a set of demonstrations. We model a motion as a nonlinear autonomous (i.e. time-invariant) dynamical system, and define the sufficient conditions to make such a system globally asymptoti ...
Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2010
This paper proposes a novel strategy for grasping 3D unknown objects in accordance with their corresponding task. We define the handle or the natural grasping component of an object as the part chosen by humans to pick up this object. When humans reach out ...