We present a comprehensive survey of robot Learning from Demonstration (LfD), a technique
that develops policies from example state to action mappings. We introduce the LfD design …

In this paper, we propose a mathematical framework which formalizes user-driven
customization of shared autonomy in assistive robotics as a nonlinear optimization problem. Our …

Robots come into physical contact with humans in both experimental and operational settings.
Many potential factors motivate the detection of human contact, ranging from safe robot …

Two categories of objects in the environment—animals and man-made manipulable objects
(tools)—are easily recognized by either their auditory or visual features. Although these …

Although early sensory cortex is organized along dimensions encoded by receptor organs,
little is known about the organization of higher areas in which different modalities are …

Surface-based brain imaging analysis is increasingly being used for detailed analysis of the
topology of brain activation patterns and changes in cerebral gray matter. Here we present …

Task and group comparisons in functional magnetic resonance imaging (fMRI) studies are
often accomplished through the creation of intersubject average activation maps. Compared …

As we progress towards a world where robots play an integral role in society, a critical
problem that remains to be solved is the pickup team challenge; that is, dynamically formed …

Effective human-robot collaboration in shared autonomy requires reasoning about the
intentions of the human partner. To provide meaningful assistance, the autonomy has to first …

Learning by demonstration can be a powerful and natural tool for developing robot control
policies. That is, instead of tedious hand-coding, a robot may learn a control policy by …