TY - JOUR
T1 - Generating Spatial Referring Expressions in a Social Robot: Dynamic vs. Non-ambiguous
AU - Wallbridge, CD
AU - Lemaignan, S
AU - Senft, E
AU - Belpaeme, T
PY - 2019/8/2
Y1 - 2019/8/2
N2 - 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.
AB - 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.
UR - https://pearl.plymouth.ac.uk/context/secam-research/article/2273/viewcontent/Wallbridge_20et_20al_20__20Generating_20spatial_20refering_20expressions_20in_20a_20social_20robot_20__202019.pdf
U2 - 10.3389/frobt.2019.00067
DO - 10.3389/frobt.2019.00067
M3 - Article
SN - 2296-9144
VL - 6
JO - Frontiers in Robotics and AI
JF - Frontiers in Robotics and AI
IS - 0
ER -