2 citations · 2 across the 4 of their papers we have counts for
6 papers
Learning Predictive Models for Ergonomic Control of Prosthetic Devices
Geoffrey Clark, Joseph Campbell, Heni Ben Amor
We present Model-Predictive Interaction Primitives -- a robot learning framework for assistive motion in human-machine collaboration tasks which explicitly accounts for biomechanic…
Language-Conditioned Imitation Learning for Robot Manipulation Tasks
Simon Stepputtis, Joseph Campbell, Mariano Phielipp +3
Imitation learning is a popular approach for teaching motor skills to robots. However, most approaches focus on extracting policy parameters from execution traces alone (i.e., moti…
Predictive Modeling of Periodic Behavior for Human-Robot Symbiotic Walking
Geoffrey Clark, Joseph Campbell, Seyed Mostafa Rezayat Sorkhabadi +2
We propose in this paper Periodic Interaction Primitives - a probabilistic framework that can be used to learn compact models of periodic behavior. Our approach extends existing fo…
Learning Whole-Body Human-Robot Haptic Interaction in Social Contexts
Joseph Campbell, Katsu Yamane
This paper presents a learning-from-demonstration (LfD) framework for teaching human-robot social interactions that involve whole-body haptic interaction, i.e. direct human-robot c…
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…
Modeling Concurrency and Reconfiguration in Vehicular Systems: A -calculus Approach
Joseph Campbell, Cumhur Erkan Tuncali, Theodore P. Pavlic +1
As autonomous or semi-autonomous vehicles are deployed on the roads, they will have to eventually start communicating with each other in order to achieve increased efficiency and s…