Title: A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space,
Abstract: We are developing a system for human-robot communication that enables people
to communicate with robots in a natural way and is focused on solving problems
in a shared space. Our strategy for developing this system is fundamentally
data-driven: we use data from multiple input sources and train key components
with various machine learning techniques. We developed a web application that
is collecting data on how two humans communicate to accomplish a task, as well
as a mobile laboratory that is instrumented to collect data on how two humans
communicate to accomplish a task in a physically shared space. The data from
these systems will be used to train and fine-tune the second stage of our
system, in which the robot will be simulated through software. A physical robot
will be used in the final stage of our project. We describe these instruments,
a test-suite and performance metrics designed to evaluate and automate the data
gathering process as well as evaluate an initial data set.