For robots to seamlessly interact with humans, we first need to make sure that humans and
robots understand one another. Diverse algorithms have been developed to enable robots …

AI-enabled agents designed to assist humans are gaining traction in a variety of domains
such as healthcare and disaster response. It is evident that, as we move forward, these …

With the increasing presence of robots in our everyday environments, improving their social
skills is of utmost importance. Nonetheless, social robotics still faces many challenges. One …

Offline imitation learning (IL) refers to learning expert behavior solely from demonstrations,
without any additional interaction with the environment. Despite significant advances in …

For robots to seamlessly interact with humans, we first need to make sure that humans and
robots understand one another. Diverse algorithms have been developed to enable robots …

This article proposes a Learning-from-Demonstration (LfD) method using probability
densities on the workspaces of robot manipulators. The method, named PRobabilistically …

The growing presence of modern learning robots necessitates a fundamental shift in design,
as these robots must learn skills from human inputs. Two main components close the loop in …

In this work, we develop an optimization-based solution for a manipulation planning among
obstacles. This task is particularly challenging for collaborative manipulators when the …