activity
20162024
most citedExploring Implicit Human Responses to Robot Mistakes in a Learning from Demonstration Task

24 citations · 40 across the 8 of their papers we have counts for

collaborators

8 papers

cs.HC2024★ 2 cited

SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus

Stephanie M. Lukin, Claire Bonial, Matthew Marge +14

We introduce the Situated Corpus Of Understanding Transactions (SCOUT), a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration. The corpus…

cs.HC2024

Human-Robot Dialogue Annotation for Multi-Modal Common Ground

Claire Bonial, Stephanie M. Lukin, Mitchell Abrams +11

In this paper, we describe the development of symbolic representations annotated on human-robot dialogue data to make dimensions of meaning accessible to autonomous systems partici…

cs.RO2020

Towards Preference Learning for Autonomous Ground Robot Navigation Tasks

Cory Hayes, Matthew Marge

We are interested in the design of autonomous robot behaviors that learn the preferences of users over continued interactions, with the goal of efficiently executing navigation beh…

cs.RO2019★ 1 cited

A Research Platform for Multi-Robot Dialogue with Humans

Matthew Marge, Stephen Nogar, Cory J. Hayes +4

This paper presents a research platform that supports spoken dialogue interaction with multiple robots. The demonstration showcases our crafted MultiBot testing scenario in which u…

cs.RO2018★ 2 cited

Balancing Efficiency and Coverage in Human-Robot Dialogue Collection

Matthew Marge, Claire Bonial, Stephanie Lukin +11

We describe a multi-phased Wizard-of-Oz approach to collecting human-robot dialogue in a collaborative search and navigation task. The data is being used to train an initial automa…

cs.CL2018★ 4 cited

ScoutBot: A Dialogue System for Collaborative Navigation

Stephanie M. Lukin, Felix Gervits, Cory J. Hayes +7

ScoutBot is a dialogue interface to physical and simulated robots that supports collaborative exploration of environments. The demonstration will allow users to issue unconstrained…