The proliferation of Large Language Models (LLMs) has s fueled a shift in robot learning
from automation towards general embodied Artificial Intelligence (AI). Adopting foundation …

Imitation Learning has empowered recent advances in learning robotic manipulation tasks
by addressing shortcomings of Reinforcement Learning such as exploration and reward …

This paper examines the main robot programming strategies and how they are used in the
educational context. We analyze the advantages and drawbacks of the most common …

Diligently gathered human demonstrations serve as the unsung heroes empowering the
progression of robot learning. Today, demonstrations are collected by training people to use …

Transferring the motion from a human operator to a humanoid robot is a crucial step to
enable robots to learn from and replicate human movements. The ability to retarget in …

Motivated by recent advances in Deep Learning for robot control, this paper considers two
learning algorithms in terms of how they acquire demonstrations from fallible human …

Learning from Demonstration (LfD) enables novice users to teach robots new skills.
However, many LfD methods do not facilitate skill maintenance and adaptation. Changes in …

Programming by Demonstration (PbD) is an efficient way for non-experts to teach new skills
to a robot. PbD can be carried out in different ways, for instance, by kinesthetic guidance …

While teleoperation provides a possibility for a robot to operate at extreme conditions
instead of a human, teleoperating a robot still demands a heavy mental workload from a …

Contact-rich tasks continue to present many challenges for robotic manipulation. In this
work, we leverage a multimodal visuotactile sensor within the framework of imitation …