589 research outputs found
Using humanoid robots to study human behavior
Our understanding of human behavior advances as our humanoid robotics work progresses-and vice versa. This team's work focuses on trajectory formation and planning, learning from demonstration, oculomotor control and interactive behaviors. They are programming robotic behavior based on how we humans “program” behavior in-or train-each other
FC Portugal 3D Simulation Team: Team Description Paper 2020
The FC Portugal 3D team is developed upon the structure of our previous
Simulation league 2D/3D teams and our standard platform league team. Our
research concerning the robot low-level skills is focused on developing
behaviors that may be applied on real robots with minimal adaptation using
model-based approaches. Our research on high-level soccer coordination
methodologies and team playing is mainly focused on the adaptation of
previously developed methodologies from our 2D soccer teams to the 3D humanoid
environment and on creating new coordination methodologies based on the
previously developed ones. The research-oriented development of our team has
been pushing it to be one of the most competitive over the years (World
champion in 2000 and Coach Champion in 2002, European champion in 2000 and
2001, Coach 2nd place in 2003 and 2004, European champion in Rescue Simulation
and Simulation 3D in 2006, World Champion in Simulation 3D in Bremen 2006 and
European champion in 2007, 2012, 2013, 2014 and 2015). This paper describes
some of the main innovations of our 3D simulation league team during the last
years. A new generic framework for reinforcement learning tasks has also been
developed. The current research is focused on improving the above-mentioned
framework by developing new learning algorithms to optimize low-level skills,
such as running and sprinting. We are also trying to increase student contact
by providing reinforcement learning assignments to be completed using our new
framework, which exposes a simple interface without sharing low-level
implementation details
Beyond Gazing, Pointing, and Reaching: A Survey of Developmental Robotics
Developmental robotics is an emerging field located
at the intersection of developmental psychology
and robotics, that has lately attracted
quite some attention. This paper gives a survey of
a variety of research projects dealing with or inspired
by developmental issues, and outlines possible
future directions
Learning Multimodal Latent Dynamics for Human-Robot Interaction
This article presents a method for learning well-coordinated Human-Robot
Interaction (HRI) from Human-Human Interactions (HHI). We devise a hybrid
approach using Hidden Markov Models (HMMs) as the latent space priors for a
Variational Autoencoder to model a joint distribution over the interacting
agents. We leverage the interaction dynamics learned from HHI to learn HRI and
incorporate the conditional generation of robot motions from human observations
into the training, thereby predicting more accurate robot trajectories. The
generated robot motions are further adapted with Inverse Kinematics to ensure
the desired physical proximity with a human, combining the ease of joint space
learning and accurate task space reachability. For contact-rich interactions,
we modulate the robot's stiffness using HMM segmentation for a compliant
interaction. We verify the effectiveness of our approach deployed on a Humanoid
robot via a user study. Our method generalizes well to various humans despite
being trained on data from just two humans. We find that Users perceive our
method as more human-like, timely, and accurate and rank our method with a
higher degree of preference over other baselines.Comment: 20 Pages, 10 Figure
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