@inproceedings{bf6558feedc64e1798b11c72fdadb127,
title = "Policy adaptation with tactile feedback",
abstract = "Behavior adaptation with execution experience is a practical feature for any policy learning system. Our work provides performance feedback to a robot learner in the form of tactile corrections from a human teacher, for the purpose of policy refinement as well as policy reuse. Multiple variants of our general approach have been validated on the iCub robot, as building blocks towards a high-DoF humanoid system that integrates tactile sensing on the hands and arms into complex behaviors and sophisticated learning routines.",
keywords = "Demonstration learning, Humanoid robots, Tactile feedback",
author = "Argall, {Brenna D.} and Sauser, {Eric L.} and Billard, {Aude G.}",
year = "2011",
doi = "10.1145/1957656.1957684",
language = "English (US)",
isbn = "9781450305617",
series = "HRI 2011 - Proceedings of the 6th ACM/IEEE International Conference on Human-Robot Interaction",
pages = "107--108",
booktitle = "HRI 2011 - Proceedings of the 6th ACM/IEEE International Conference on Human-Robot Interaction",
note = "6th ACM/IEEE International Conference on Human-Robot Interaction, HRI 2011 ; Conference date: 06-03-2011 Through 09-03-2011",
}