7 accepted papers
This paper proposes a novel autonomous dynamic system (ADS) based controller for trajectory learning from demonstration (LfD). We call our method Learning Stable Dynamics via Iterative Quadratic Programming (LSD-IQP). LSD-IQP learns an energy function and an ADS from demonstrations via semi-infinite…
In this paper, we propose a novel network architecture for visual imitation learning that exploits neural radiance fields (NeRFs) and key-point correspondence for self-supervised visual motor policy learning. The proposed network architecture incorporates a dynamic system output layer for policy lea…
We are interested in learning from demonstration (LfD) that can both learn and execute a trajectory and evaluate the quality of a previously unseen trajectory in the domain of assistive robotics. To this end, we propose a novel continuous inverse optimal control (IOC) formulation that simultaneously…
Imitation learning (IL) frameworks in robotics typically assume that a domain expert's demonstration always contains a correct way of doing the task. Despite its theoretical convenience, this assumption has limited practical values for an IL-powered robot in real world. There are many reasons for an…
This paper proposes a dynamic system based learning from demonstration approach to teach a robot activities of daily living. The approach takes inspiration from human movement literature to formulate trajectory learning as an optimal control problem. We assume a weighted combination of basis objecti…
A major goal of learning from demonstration is task generalization via observation of a teacher. In this paper, we propose a novel framework for learning motion from a single demonstration. Our approach reconstructs the demonstrated trajectory's phase space curve via a linear piece-wise regression m…
High-level human activities often have rich temporal structures that determine the order in which atomic actions are executed. We propose the Temporal Context Graph (TCG), a temporal reasoning model that integrates probabilistic inference with Allen's interval algebra, to capture these temporal stru…