630 citations · 1.3k across the 25 of their papers we have counts for
6 papers · 2 filters
Joint Estimation of Expertise and Reward Preferences From Human Demonstrations
Pamela Carreno-Medrano, Stephen L. Smith, Dana Kulic
When a robot learns from human examples, most approaches assume that the human partner provides examples of optimal behavior. However, there are applications in which the robot lea…
Human-in-the-loop Auditory Cueing Strategy for Gait Modification
Tina LY Wu, Anna Murphy, Chao Chen +1
External feedback in the form of visual, auditory and tactile cues has been used to assist patients to overcome mobility challenges. However, these cues can become less effective o…
Learning to Assist Drone Landings
Kal Backman, Dana Kulić, Hoam Chung
Unmanned aerial vehicles (UAVs) are often used for navigating dangerous terrains, however they are difficult to pilot. Due to complex input-output mapping schemes, limited percepti…
Learning from Sparse Demonstrations
Wanxin Jin, Todd D. Murphey, Dana Kulić +2
This paper develops the method of Continuous Pontryagin Differentiable Programming (Continuous PDP), which enables a robot to learn an objective function from a few sparsely demons…
Object Handovers: a Review for Robotics
Valerio Ortenzi, Akansel Cosgun, Tommaso Pardi +3
This article surveys the literature on human-robot object handovers. A handover is a collaborative joint action where an agent, the giver, gives an object to another agent, the rec…
Active Preference Learning using Maximum Regret
Nils Wilde, Dana Kulic, Stephen L. Smith
We study active preference learning as a framework for intuitively specifying the behaviour of autonomous robots. In active preference learning, a user chooses the preferred behavi…