The impact of human-robot multimodal communication on mental workload, usability preference, and expectations of robot behavior

被引:11
|
作者
Abich, Julian [1 ]
Barber, Daniel J. [2 ]
机构
[1] Univ Cent Florida, Inst Simulat & Training, 3100 Technol Pkwy,Suite 333, Orlando, FL 32826 USA
[2] Univ Cent Florida, Inst Simulat & Training, 3100 Technol Pkwy,Suite 306-B, Orlando, FL 32826 USA
关键词
Human-robot interaction; Human-robot teams; Multimodal communication; Multimodal interface; Mental workload; Usability; HAND GESTURES; RECOGNITION; ANXIETY; SPEECH; RECALL; SELF; CUES;
D O I
10.1007/s12193-016-0237-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Multimodal communication between humans and autonomous robots is essential to enhance effectiveness of human-robot team performance in complex, novel environments, such as in military intelligence, surveillance, and reconnaissance operations in urban settings. It is imperative that a systematic approach be taken to evaluate the factors that each modality contributes to the user's ability to perform successfully and safely. This paper addresses the effects of unidirectional speech and gesture methods of communication on perceived workload, usability preferences, and expectations of robot behavior while commanding a robot teammate to perform a spatial-navigation task. Each type of communication was performed alone or simultaneously. Results reveal that although the speech-alone condition elicited the lowest level of perceived workload, the usability preference and expectations of robot behavior after interacting through each communication condition was the same. Further, workload ratings between the gesture and speech-gesture conditions were similar indicating systems that employ gesture communication could also support speech communication with little to no additional subjectively perceived cognitive burden on the user. Findings also reveal that workload alone should not be used as a sole determining factor of communication preference during system and task evaluation and design. Additionally, perceived workload did not seem to negatively impact the level of expectations regarding the robot's behavior. Recommendations for future human-robot communication evaluation are provided.
引用
收藏
页码:211 / 225
页数:15
相关论文
共 50 条
  • [41] Service robot: Behavior of service robot in human-robot coexisting environment
    Tamura, Yusuke
    Asama, Hajime
    Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering, 2012, 78 (08): : 666 - 669
  • [42] Impact of Robot Size and Number on Human-Robot Persuasion
    Alam, Abeer
    Lwin, Michael
    Khan, Aila
    Mubin, Omar
    INFORMATION, 2024, 15 (12)
  • [43] Recent advancements in multimodal human-robot interaction
    Su, Hang
    Qi, Wen
    Chen, Jiahao
    Yang, Chenguang
    Sandoval, Juan
    Laribi, Med Amine
    FRONTIERS IN NEUROROBOTICS, 2023, 17
  • [44] Robotic Telemedicine for Mental Health: A Multimodal Approach to Improve Human-Robot Engagement
    Lima, Maria R.
    Wairagkar, Maitreyee
    Natarajan, Nirupama
    Vaitheswaran, Sridhar
    Vaidyanathan, Ravi
    FRONTIERS IN ROBOTICS AND AI, 2021, 8
  • [45] The MOBOT Human-Robot Communication Model
    Fotinea, Stavroula-Evita
    Efthimiou, Eleni
    Koutsombogera, Maria
    Dimou, Athanasia-Lida
    Goulas, Theodore
    Maragos, Petros
    Tzafestas, Costas
    2015 6TH IEEE INTERNATIONAL CONFERENCE ON COGNITIVE INFOCOMMUNICATIONS (COGINFOCOM), 2015, : 201 - 206
  • [46] Facial expression of robot face for human-robot mutual communication
    Fukuda, T
    Taguri, J
    Arai, F
    Nakashima, M
    Tachibana, D
    Hasegawa, Y
    2002 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, VOLS I-IV, PROCEEDINGS, 2002, : 46 - 51
  • [47] A multimodal teleoperation interface for human-robot collaboration
    Si, Weiyong
    Zhong, Tianjian
    Wang, Ning
    Yang, Chenguang
    2023 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS, ICM, 2023,
  • [48] A Dialogue System for Multimodal Human-Robot Interaction
    Lucignano, Lorenzo
    Cutugno, Francesco
    Rossi, Silvia
    Finzi, Alberto
    ICMI'13: PROCEEDINGS OF THE 2013 ACM INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 2013, : 197 - 204
  • [49] Multimodal Information Fusion for Human-Robot Interaction
    Luo, Ren C.
    Wu, Y. C.
    Lin, P. H.
    2015 IEEE 10TH JUBILEE INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI), 2015, : 535 - 540
  • [50] Human-robot communication and machine learning
    Universitaet Dortmund, Dortmund, Germany
    Appl Artif Intell, 7-8 (719-746):