MODELING AND TESTING PROXEMIC BEHAVIOR FOR HUMANOID ROBOTS

被引:10
|
作者
Torta, Elena [1 ]
Cuijpers, Raymond H. [1 ]
Juola, James F. [1 ]
Van Der Pol, David [1 ]
机构
[1] Eindhoven Univ Technol, NL-5600 MB Eindhoven, Netherlands
关键词
Behavior based robotics; proxemics; user models; social robotics; context awareness; particle filter;
D O I
10.1142/S0219843612500284
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Humanoid robots that share the same space with humans need to be socially acceptable and effective as they interact with people. In this paper we focus our attention on the definition of a behavior-based robotic architecture that (1) allows the robot to navigate safely in a cluttered and dynamically changing domestic environment and (2) encodes embodied non-verbal interactions: the robot respects the users personal space (PS) by choosing the appropriate distance and direction of approach. The model of the PS is derived from human-robot interaction tests, and it is described in a convenient mathematical form. The robot's target location is dynamically inferred through the solution of a Bayesian filtering problem. The validation of the overall behavioral architecture shows that the robot is able to exhibit appropriate proxemic behavior.
引用
收藏
页数:24
相关论文
共 50 条
  • [1] Modeling and Control of Humanoid Robots
    Monje, Concepcion A.
    Martinez de la Casa, Santiago
    INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS, 2019, 16 (06)
  • [2] Evolutionary behavior acquisition for humanoid robots
    Aydemir, Deniz
    Iba, Hitoshi
    PARALLEL PROBLEM SOLVING FROM NATURE - PPSN IX, PROCEEDINGS, 2006, 4193 : 651 - 660
  • [3] Slide modeling and detecting analysis for humanoid robots
    Yu, Leibin
    Cao, Qixin
    Qiu, Changwu
    Gaojishu Tongxin/Chinese High Technology Letters, 2008, 18 (02): : 147 - 150
  • [4] Self-modeling in humanoid soccer robots
    Cristobal Zagal, Juan
    Delpiano, Jose
    Ruiz-del-Solar, Javier
    ROBOTICS AND AUTONOMOUS SYSTEMS, 2009, 57 (08) : 819 - 827
  • [5] Behavior Generation of Humanoid Robots Depending on Mood
    Itoh, Kazuko
    Miwa, Hiroyasu
    Nukariya, Yuko
    Zecca, Massimiliano
    Takanobu, Hideaki
    Roccella, Stefano
    Carrozza, Maria Chiara
    Dario, Paolo
    Takanishi, Atsuo
    INTELLIGENT AUTONOMOUS SYSTEMS 9, 2006, : 965 - +
  • [6] Using humanoid robots to study human behavior
    Atkeson, CG
    Hale, JG
    Pollick, F
    Riley, M
    Kotosaka, S
    Schaal, S
    Shibata, T
    Tevatia, G
    Ude, A
    Vijayakumar, S
    Kawato, M
    IEEE INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 2000, 15 (04): : 46 - 55
  • [7] A behavior level operation system for humanoid robots
    Neo, Ee Sian
    Sakaguchi, Takeshi
    Yokoi, Kazuhito
    Kawai, Yoshihiro
    Maruyama, Kenichi
    2006 6TH IEEE-RAS INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS, VOLS 1 AND 2, 2006, : 327 - +
  • [8] A method determining the reaching behavior of humanoid robots
    Na, Haitao
    Neo, Ee Sian
    Yokoi, Kazuhito
    2006 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS, VOLS 1-3, 2006, : 1535 - +
  • [9] Robots testing robots: ALAN-Arm, a humanoid arm for the testing of robotic rehabilitation systems
    Brookes, Jack
    Kuznecovs, Maksims
    Kanakis, Menelaos
    Grigals, Arturs
    Narvidas, Mazvydas
    Gallagher, Justin
    Levesley, Martin
    2017 INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS (ICORR), 2017, : 676 - 681
  • [10] Experimental Evaluation and Modeling of Passive Falls in Humanoid Robots
    Olivieri, Nicola
    Henze, Bernd
    Braghin, Francesco
    Roa, Maximo A.
    2019 IEEE-RAS 19TH INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS (HUMANOIDS), 2019, : 344 - 350