July 2013
Volume 13, Issue 9
Vision Sciences Society Annual Meeting Abstract  |   July 2013
Interception of a speed-varying target: On-line or model-based control?
Author Affiliations
  • Huaiyong Zhao
    Department of Cognitive, Linguistic and Psychological Sciences, Brown University
  • William Warren
    Department of Cognitive, Linguistic and Psychological Sciences, Brown University
Journal of Vision July 2013, Vol.13, 951. doi:10.1167/13.9.951
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      Huaiyong Zhao, William Warren; Interception of a speed-varying target: On-line or model-based control?. Journal of Vision 2013;13(9):951. doi: 10.1167/13.9.951.

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      © ARVO (1962-2015); The Authors (2016-present)

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Interception of a moving target appears to be based on the constant bearing strategy (CBS) (Chardenon, et al., 2002, 2005; Lenoir, et al., 1999, 2002), and is closely modeled by nulling change in the bearing direction of the target, based on current visual information (Fajen & Warren 2004, 2007). Alternatively, interception might be controlled by an internal model of the target’s motion that is continuously updated by current information (Hayhoe, et al., 2005). We investigate this question by testing whether CBS is sufficient to account for interception of a moving target that changes speed. Participants walked in a virtual environment (12m x 12m) to catch a target pole (2.9m high, 8.0m distant) moving on the ground plane. Displays were presented stereoscopically in a head mounted display (63°H x 53°V, 60 Hz), and head position was tracked (60 Hz). The target’s initial speed was 0.6 or 0.8m/s, and after 3s randomly changed speed by -0.3, -0.2, 0.0, +0.2 or +0.3m/s. Head trajectories on each trial were simulated using three models: (i) CBS was based on current information; (ii) CBS+RT added a fixed visual-locomotor delay of 400 ms (Cinelli & Warren, 2012); (iii) CBS+RT+Window incorporated an estimate of the target’s position and speed based on their averages within a moving temporal window (0 to 1000ms) (Greenwald, Knill, & Saunders, 2005). Model performance was measured by the mean distance between human and simulated trajectories at each time step. The results indicate that the CBS model accounts for human trajectories as well as the CBS+RT and CBS+RT+Window models, except in the 0.8+0.3m/s condition. Adding RT significantly improved model performance in that condition, but varying the Window did not improve it further. The results suggest that CBS+RT is sufficient to explain interception of a speed-varying target without an internal model of the target’s motion.

Meeting abstract presented at VSS 2013


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