SMARTTALK: A Learning-based Framework for Natural Human-Robot Interaction

被引:1
|
作者
Fabbri, Cameron [1 ]
Sattar, Junaed [2 ]
机构
[1] US Air Force, Res Lab, Informat Directorate, Rome, NY 13441 USA
[2] Univ Minnesota, Comp Sci & Engn, Minneapolis, MN USA
关键词
LANGUAGE; DIALOGUE;
D O I
10.1109/CRV.2016.67
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
This paper presents a learning-based framework named SMARTTALK for natural-language human-robot interaction (HRI). The primary goal of this framework is to enable non-expert users to control and program a mobile robot using natural language commands. SMARTTALK is modality-agnostic, and is capable of integrating with both speech and non-speech (e.g., gesture-based) communication. Initially, robots using this mechanism are equipped with a limited vocabulary of primitive commands and functionality; however, through extended use and interaction, the robots are able to learn new commands and adapt to user's behaviors and habits. This makes the proposed framework highly desirable for long-term deployment in a variety of HRI tasks. We present the design of this framework and experimental data on a number of realistic scenarios to evaluate its performance. A qualitative experiment on a robotic platform is also presented.
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页码:376 / 382
页数:7
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