881 citations · 1.9k across the 36 of their papers we have counts for
8 papers · 2 filters
Virtual Reality via Object Pose Estimation and Active Learning: Realizing Telepresence Robots with Aerial Manipulation Capabilities
Jongseok Lee, Ribin Balachandran, Konstantin Kondak +6
This article presents a novel telepresence system for advancing aerial manipulation in dynamic and unstructured environments. The proposed system not only features a haptic device,…
Bringing motion taxonomies to continuous domains via GPLVM on hyperbolic manifolds
Noémie Jaquier, Leonel Rozo, Miguel González-Duque +2
Human motion taxonomies serve as high-level hierarchical abstractions that classify how humans move and interact with their environment. They have proven useful to analyse grasps,…
Riemannian geometry as a unifying theory for robot motion learning and control
Noémie Jaquier, Tamim Asfour
Riemannian geometry is a mathematical field which has been the cornerstone of revolutionary scientific discoveries such as the theory of general relativity. Despite early uses in r…
SpeedFolding: Learning Efficient Bimanual Folding of Garments
Yahav Avigal, Lars Berscheid, Tamim Asfour +2
Folding garments reliably and efficiently is a long standing challenge in robotic manipulation due to the complex dynamics and high dimensional configuration space of garments. An…
K-VIL: Keypoints-based Visual Imitation Learning
Jianfeng Gao, Zhi Tao, Noémie Jaquier +1
Visual imitation learning provides efficient and intuitive solutions for robotic systems to acquire novel manipulation skills. However, simultaneously learning geometric task const…
A Riemannian Take on Human Motion Analysis and Retargeting
Holger Klein, Noémie Jaquier, Andre Meixner +1
Dynamic motions of humans and robots are widely driven by posture-dependent nonlinear interactions between their degrees of freedom. However, these dynamical effects remain mostly…
Deep Learning Approaches to Grasp Synthesis: A Review
Rhys Newbury, Morris Gu, Lachlan Chumbley +9
Grasping is the process of picking up an object by applying forces and torques at a set of contacts. Recent advances in deep-learning methods have allowed rapid progress in robotic…
Learning to Sequence and Blend Robot Skills via Differentiable Optimization
Noémie Jaquier, You Zhou, Julia Starke +1
In contrast to humans and animals who naturally execute seamless motions, learning and smoothly executing sequences of actions remains a challenge in robotics. This paper introduce…