Ubiquitous robot control and human-robot collaboration using smart devic...
This paper introduces a novel state estimation framework for robots usin...
This paper introduces a novel approach for modeling the dynamics of soft...
Guaranteeing safety in human-centric applications is critical in robot
l...
Assistive robotic devices are a particularly promising field of applicat...
We introduce an imitation learning-based physical human-robot interactio...
In this paper, we discuss a framework for teaching bimanual manipulation...
In this paper, we propose a framework to repair a pre-trained feed-forwa...
Robotic systems for retail have gained a lot of attention due to the
lab...
We present Model-Predictive Interaction Primitives – a robot learning
fr...
Imitation learning is a popular approach for teaching motor skills to ro...
The goal of this paper is to generate simulations with real-world collis...
Accurate real-time pose estimation of spacecraft or object in space is a...
As digital worlds become ubiquitous via video games, simulations, virtua...
In this paper, we propose SwarmNet – a neural network architecture that ...
In this work we propose a novel end-to-end imitation learning approach w...
Model-free reinforcement learning algorithms such as Deep Deterministic
...
Humans and animals are capable of quickly learning new behaviours to sol...
A hug is a tight embrace and an expression of warmth, sympathy and
camar...
Musculoskeletal robots that are based on pneumatic actuation have a vari...
Human-robot interaction benefits greatly from multimodal sensor inputs a...
All reinforcement learning algorithms must handle the trade-off between
...
In this paper, we investigate a predictive approach for collision risk
a...
We present a learning approach for localization and segmentation of obje...