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arXiv · 1710.00274

A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space

Michael Wollowski·Carlotta Berry·Ryder Winck·Alan Jern·David Voltmer·Alan Chiu·Yosi Shibberu
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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.

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Michael Wollowski, Carlotta Berry, Ryder Winck, Alan Jern, David Voltmer, Alan Chiu, Yosi Shibberu. 2017-10-01. A Data-driven Approach Towards Human-robot Collaborative Problem Solving in a Shared Space. https://arxiv.org/abs/1710.00274

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