AUTHOR=Wallbridge Christopher D. , Lemaignan Séverin , Senft Emmanuel , Belpaeme Tony TITLE=Generating Spatial Referring Expressions in a Social Robot: Dynamic vs. Non-ambiguous JOURNAL=Frontiers in Robotics and AI VOLUME=6 YEAR=2019 URL=https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2019.00067 DOI=10.3389/frobt.2019.00067 ISSN=2296-9144 ABSTRACT=

Generating spatial referring expressions is key to allowing robots to communicate with people in an environment. The focus of most algorithms for generation is to create a non-ambiguous description, and how best to deal with the combination explosion this can create in a complex environment. However, this is not how people naturally communicate. Humans tend to give an under-specified description and then rely on a strategy of repair to reduce the number of possible locations or objects until the correct one is identified, what we refer to here as a dynamic description. We present here a method for generating these dynamic descriptions for Human Robot Interaction, using machine learning to generate repair statements. We also present a study with 61 participants in a task on object placement. This task was presented in a 2D environment that favored a non-ambiguous description. In this study we demonstrate that our dynamic method of communication can be more efficient for people to identify a location compared to one that is non-ambiguous.