How Robot Verbal Feedback Can Improve Team Performance in Human-Robot Task Collaborations

被引:62
作者
St Clair, Aaron [1 ]
Mataric, Maja [1 ]
机构
[1] Univ So Calif, Interact Lab, Los Angeles, CA 90089 USA
来源
PROCEEDINGS OF THE 2015 ACM/IEEE INTERNATIONAL CONFERENCE ON HUMAN-ROBOT INTERACTION (HRI'15) | 2015年
关键词
Human-robot collaborations; natural language;
D O I
10.1145/2696454.2696491
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We detail an approach to planning effective verbal feedback during pairwise human-robot task collaboration. The approach is motivated by social science literature as well as existing work in robotics and is applicable to a variety of task scenarios. It consists of a dynamic, synthetic task implemented in an augmented reality environment. The result is combined robot task control and speech production, allowing the robot to actively participate and communicate with its teammate. A user study was conducted to experimentally validate the efficacy of the approach on a task in which a single user collaborates with an autonomous robot. The results demonstrate that the approach is capable of improving both objective measures of team performance and the user's subjective evaluation of both the task and the robot as a teammate.
引用
收藏
页码:213 / 220
页数:8
相关论文
共 22 条
  • [1] [Anonymous], 2013, HRI
  • [2] Effects of nonverbal communication on efficiency and robustness in human-robot teamwork
    Breazeal, C
    Kidd, CD
    Thomaz, AL
    Hoffman, G
    Berlin, M
    [J]. 2005 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-4, 2005, : 383 - 388
  • [3] The mirror neuron system and action recognition
    Buccino, G
    Binkofski, F
    Riggio, L
    [J]. BRAIN AND LANGUAGE, 2004, 89 (02) : 370 - 376
  • [4] Interactive Policy Learning through Confidence-Based Autonomy
    Chernova, Sonia
    Veloso, Manuela
    [J]. JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH, 2009, 34 : 1 - 25
  • [5] Crick C., 2008, P 7 IEEE INT C DEV L, P13
  • [6] Grosz B. J., 1986, Computational Linguistics, V12, P175
  • [7] A novel sequence representation for unsupervised analysis of human activities
    Hamid, Raffay
    Maddi, Siddhartha
    Johnson, Amos
    Bobick, Aaron
    Essa, Irfan
    Isbell, Charles
    [J]. ARTIFICIAL INTELLIGENCE, 2009, 173 (14) : 1221 - 1244
  • [8] Cost-based anticipatory action selection for human-robot fluency
    Hoffman, Guy
    Breazeal, Cynthia
    [J]. IEEE TRANSACTIONS ON ROBOTICS, 2007, 23 (05) : 952 - 961
  • [9] AN ARCHITECTURE FOR UNDERSTANDING INTENT USING A NOVEL HIDDEN MARKOV FORMULATION
    Kelley, Richard
    King, Christopher
    Tavakkoli, Alireza
    Nicolescu, Mircea
    Nicolescu, Monica
    Bebis, George
    [J]. INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS, 2008, 5 (02) : 203 - 224
  • [10] Taking perspective in conversation: The role of mutual knowledge in comprehension
    Keysar, B
    Barr, DJ
    Balin, JA
    Brauner, JS
    [J]. PSYCHOLOGICAL SCIENCE, 2000, 11 (01) : 32 - 38