73 citations · 126 across the 33 of their papers we have counts for
4 papers · 1 filter
Imitation Learning of Robot Policies by Combining Language, Vision and Demonstration
Simon Stepputtis, Joseph Campbell, Mariano Phielipp +2
In this work we propose a novel end-to-end imitation learning approach which combines natural language, vision, and motion information to produce an abstract representation of a ta…
Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient
Kevin Sebastian Luck, Mel Vecerik, Simon Stepputtis +2
Model-free reinforcement learning algorithms such as Deep Deterministic Policy Gradient (DDPG) often require additional exploration strategies, especially if the actor is of determ…
Learning Interactive Behaviors for Musculoskeletal Robots Using Bayesian Interaction Primitives
Joseph Campbell, Arne Hitzmann, Simon Stepputtis +3
Musculoskeletal robots that are based on pneumatic actuation have a variety of properties, such as compliance and back-drivability, that render them particularly appealing for huma…
Probabilistic Multimodal Modeling for Human-Robot Interaction Tasks
Joseph Campbell, Simon Stepputtis, Heni Ben Amor
Human-robot interaction benefits greatly from multimodal sensor inputs as they enable increased robustness and generalization accuracy. Despite this observation, few HRI methods ar…