Kinematic trajectories recorded from surgical robots contain information about surgical
gestures and potentially encode cues about surgeon's skill levels. Automatic segmentation …

In this paper, we propose a novel hybrid adaptive model (HAM) that integrates Gaussian
mixture probabilistic machine learning (ML), Weibull time-to-failure feature, and value of …

The robots are set to penetrate into daily life of human beings. The purpose of a robot is to
accomplish a goal within specified task constraints, thus reducing human effort as well as …

There are many work-related repetitive tasks where the application of exoskeletons could
significantly reduce the physical effort by assisting the user in moving the arms towards the …

We present an approach, based on non-negative matrix factorization, for learning to
recognize parallel combinations of initially unknown human motion primitives, associated …

In many applications, such as virtual agents or humanoid robots, it is difficult to represent
complex human behaviors and the full range of skills necessary to achieve them. Real life …

With advancements in modern technology and the increasing complexity of various
dependable systems, rolling stock system reliability, risk, and maintenance targets are …

With an increase in the demand for complex tasks in industrial applications such as
assembly tasks, industries foresee demand for robots with unique abilities. For example …

Robots are an important resource in many industrial applications. They have replaced
numerous dull, repetitive, dirty and dangerous manual manipulations. Robots have been …

The focus of this work is on robot learning of cyclic motions. The termcyclic'refers to motions
which are repeated, but do not have a strictly defined period. The dynamics of a set of …