Kernelized movement primitives

Y Huang, L Rozo, J Silvério… - … International Journal of …, 2019‏ - journals.sagepub.com
Imitation learning has been studied widely as a convenient way to transfer human skills to
robots. This learning approach is aimed at extracting relevant motion patterns from human …

i-sim2real: Reinforcement learning of robotic policies in tight human-robot interaction loops

SW Abeyruwan, L Graesser… - … on Robot Learning, 2023‏ - proceedings.mlr.press
Sim-to-real transfer is a powerful paradigm for robotic reinforcement learning. The ability to
train policies in simulation enables safe exploration and large-scale data collection quickly …

Nonprehensile dynamic manipulation: A survey

F Ruggiero, V Lippiello… - IEEE Robotics and …, 2018‏ - ieeexplore.ieee.org
Nonprehensile dynamic manipulation can be reasonably considered as the most complex
manipulation task. It might be argued that such a task is still rather far from being fully solved …

Learning to play table tennis from scratch using muscular robots

D Büchler, S Guist, R Calandra… - IEEE Transactions …, 2022‏ - ieeexplore.ieee.org
Dynamic tasks such as table tennis are relatively easy to learn for humans, but pose
significant challenges to robots. Such tasks require accurate control of fast movements and …

Real-time dynamic obstacle avoidance for robot manipulators based on cascaded nonlinear MPC with artificial potential field

T Zhu, J Mao, L Han, C Zhang… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Nowadays, the realization of obstacle avoidance for robot manipulators are generally based
on offline path planning, which may be insufficient for real-time dynamic obstacle avoidance …

Robotic table tennis: A case study into a high speed learning system

DB D'Ambrosio, J Abelian, S Abeyruwan, M Ahn… - arxiv preprint arxiv …, 2023‏ - arxiv.org
We present a deep-dive into a real-world robotic learning system that, in previous work, was
shown to be capable of hundreds of table tennis rallies with a human and has the ability to …

[HTML][HTML] Online optimal trajectory generation for robot table tennis

O Koç, G Maeda, J Peters - Robotics and Autonomous Systems, 2018‏ - Elsevier
In highly dynamic tasks that involve moving targets, planning is necessary to figure out
when, where and how to intercept the target. In robotic table tennis in particular, motion …

Robotic table tennis with model-free reinforcement learning

W Gao, L Graesser, K Choromanski… - 2020 IEEE/RSJ …, 2020‏ - ieeexplore.ieee.org
We propose a model-free algorithm for learning efficient policies capable of returning table
tennis balls by controlling robot joints at a rate of 100Hz. We demonstrate that evolutionary …

Imitating via manipulability: Geometry-aware combined DMP with via-point and speed adaptation

X Xu, K Qian, B Zhou, F Fang, X Ma - Computers and Electrical …, 2024‏ - Elsevier
Manipulability ellipsoid on the Riemannian manifold provides an effective criterion for
guiding the regulation of robot postures in an efficient and natural manner. While many …