Intercepting a moving target: On-line or model-based control?

被引:21
|
作者
Zhao, Huaiyong [1 ,2 ]
Warren, William H. [1 ]
机构
[1] Brown Univ, Dept Cognit Linguist & Psychol Sci, Providence, RI 02912 USA
[2] Tech Univ Darmstadt, Dept Psychol, Darmstadt, Hesse, Germany
来源
JOURNAL OF VISION | 2017年 / 17卷 / 05期
关键词
locomotor interception; action control; online control; model-based control; VISUALLY CONTROLLED LOCOMOTION; INTERMITTENT VISION; SPATIAL-FREQUENCY; BEHAVIORAL DYNAMICS; PERCEIVED VELOCITY; STEERING CONTROL; PERCEPTION; MOVEMENTS; SPEED; TASK;
D O I
10.1167/17.5.12
中图分类号
R77 [眼科学];
学科分类号
100212 ;
摘要
When walking to intercept a moving target, people take an interception path that appears to anticipate the target's trajectory. According to the constant bearing strategy, the observer holds the bearing direction of the target constant based on current visual information, consistent with on-line control. Alternatively, the interception path might be based on an internal model of the target's motion, known as model-based control. To investigate these two accounts, participants walked to intercept a moving target in a virtual environment. We degraded the target's visibility by blurring the target to varying degrees in the midst of a trial, in order to influence its perceived speed and position. Reduced levels of visibility progressively impaired interception accuracy and precision; total occlusion impaired performance most and yielded nonadaptive heading adjustments. Thus, performance strongly depended on current visual information and deteriorated qualitatively when it was withdrawn. The results imply that locomotor interception is normally guided by current information rather than an internal model of target motion, consistent with on-line control.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] A model-based methodology for on-line quality control
    Kazmer, David O.
    Westerdale, Sarah
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2009, 42 (3-4): : 280 - 292
  • [2] A model-based methodology for on-line quality control
    David O. Kazmer
    Sarah Westerdale
    The International Journal of Advanced Manufacturing Technology, 2009, 42 : 280 - 292
  • [3] On-line and model-based approaches to the visual control of action
    Zhao, Huaiyong
    Warren, William H.
    VISION RESEARCH, 2015, 110 : 190 - 202
  • [4] On-line nonlinear model-based estimation and control of a polymer reactor
    Mutha, RK
    Cluett, WR
    Penlidis, A
    AICHE JOURNAL, 1997, 43 (11) : 3042 - 3058
  • [5] On-Line PEMFC Control Using Parameterized Nonlinear Model-Based Predictive Control
    Damour, C.
    Benne, M.
    Kadjo, J. -J. A.
    Deseure, J.
    Grondin-Perez, B.
    FUEL CELLS, 2014, 14 (06) : 886 - 893
  • [6] Error-triggered on-line model identification for model-based feedback control
    Alanqar, Anas
    Durand, Helen
    Christofides, Panagiotis D.
    AICHE JOURNAL, 2017, 63 (03) : 949 - 966
  • [7] Evolution of an on-line model-based optimization system
    Shewchuk, C.F.
    Morton, W.
    Pulp and Paper Canada, 1994, 95 (06): : 29 - 34
  • [8] Towards on-line model-based design of experiments
    Galvanin, Federico
    Barolo, Massimiliano
    Bezzo, Fabrizio
    18TH EUROPEAN SYMPOSIUM ON COMPUTER AIDED PROCESS ENGINEERING, 2008, 25 : 349 - 354
  • [9] Model-based on-line handwritten digit recognition
    Li, XL
    Plamondon, R
    Parizeau, M
    FOURTEENTH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1 AND 2, 1998, : 1134 - 1136
  • [10] A mixture model-based on-line CEM algorithm
    Samé, A
    Govaert, G
    Ambroise, C
    ADVANCES IN INTELLIGENT DATA ANALYSIS VI, PROCEEDINGS, 2005, 3646 : 373 - 384