4 citations · 5 across the 2 of their papers we have counts for
7 papers · 1 filter
A Non-parametric Skill Representation with Soft Null Space Projectors for Fast Generalization
João Silvério, Yanlong Huang
Over the last two decades, the robotics community witnessed the emergence of various motion representations that have been used extensively, particularly in behavorial cloning, to…
EKMP: Generalized Imitation Learning with Adaptation, Nonlinear Hard Constraints and Obstacle Avoidance
Yanlong Huang
As a user-friendly and straightforward solution for robot trajectory generation, imitation learning has been viewed as a vital direction in the context of robot skill learning. In…
Towards Orientation Learning and Adaptation in Cartesian Space
Yanlong Huang, Fares J. Abu-Dakka, João Silvério +1
As a promising branch of robotics, imitation learning emerges as an important way to transfer human skills to robots, where human demonstrations represented in Cartesian or joint s…
Uncertainty-Aware Imitation Learning using Kernelized Movement Primitives
João Silvério, Yanlong Huang, Fares J. Abu-Dakka +2
During the past few years, probabilistic approaches to imitation learning have earned a relevant place in the literature. One of their most prominent features, in addition to extra…
Probabilistic Learning of Torque Controllers from Kinematic and Force Constraints
João Silvério, Yanlong Huang, Leonel Rozo +2
When learning skills from demonstrations, one is often required to think in advance about the appropriate task representation (usually in either operational or configuration space)…
Kernelized Movement Primitives
Yanlong Huang, Leonel Rozo, João Silvério +1
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…