Inverse kinematics (IK) is the use of kinematic equations to determine the joint parameters of
a manipulator so that the end effector moves to a desired position; IK can be applied in many …

The goal of this survey is to inform the design and usage of nonverbal signals for human-
robot interaction. With robots being increasingly utilized for tasks that require them to not …

Reproducing the diverse and agile locomotion skills of animals has been a longstanding
challenge in robotics. While manually-designed controllers have been able to emulate many …

This paper presents a simple method for" do as I do" motion transfer: given a source video of
a person dancing, we can transfer that performance to a novel (amateur) target after only a …

Generating digital humans that move realistically has many applications and is widely
studied, but existing methods focus on the major limbs of the body, ignoring the hands and …

Humans live within a 3D space and constantly interact with it to perform tasks. Such
interactions involve physical contact between surfaces that is semantically meaningful. Our …

In recent years, there has been a proliferation of works on human action classification from
depth sequences. These works generally present methods and/or feature representations …

We introduce a novel deep learning framework for data-driven motion retargeting between
skeletons, which may have different structure, yet corresponding to homeomorphic graphs …

A key requirement for seamless human-robot collaboration is for the robot to make its
intentions clear to its human collaborator. A collaborative robot's motion must be legible, or …

We propose a recurrent neural network architecture with a Forward Kinematics layer and
cycle consistency based adversarial training objective for unsupervised motion retargetting …