Environmental constraints modify the way an interceptive action is controlled

This study concerns the process by which agents select control laws. Participants adjusted their walking speed in a virtual environment in order to intercept approaching targets. Successful interception can be achieved with a constant bearing angle (CBA) strategy that relies on prospective information, or with a modified required velocity (MRV) strategy, which also includes predictive information. We manipulated the curvature of the target paths and the display condition of these paths. The curvature manipulation had large effects on the walking kinematics when the target paths were not displayed (informationally poor display). In contrast, the walking kinematics were less affected by the curvature manipulation when the target paths were displayed (informationally rich display). This indicates that participants used an MRV strategy in the informationally rich display and a CBA strategy in the informationally poor display. Quantitative fits of the respective models confirm this information-driven switch between the use of a strategy that relies on prospective information and a strategy that includes predictive information. We conclude that agents are able of taking advantage of available information by selecting a suitable control law.

[1]  David M. Jacobs,et al.  An Empirical Illustration and Formalization of the Theory of Direct Learning: The Muscle-Based Perception of Kinetic Properties , 2009 .

[2]  Digby Elliott,et al.  A ménage À trois: the eye, the hand and on-line processing , 2002, Journal of sports sciences.

[3]  A. Chardenon,et al.  The perceptual control of goal-directed locomotion: a common control architecture for interception and navigation? , 2004, Experimental Brain Research.

[4]  D Kerzel,et al.  Time-to-passage judgments on circular trajectories are based on relative optical acceleration , 2001, Perception & psychophysics.

[5]  Richard Wilkie,et al.  Controlling steering and judging heading: retinal flow, visual direction, and extraretinal information. , 2003, Journal of experimental psychology. Human perception and performance.

[6]  Gilles Montagne,et al.  Is the learning of goal-directed displacement effector-independent? , 2004, Human movement science.

[7]  Zijiang J. He,et al.  Distance determined by the angular declination below the horizon , 2001, Nature.

[8]  David M Jacobs,et al.  Lateral interception I: operative optical variables, attunement, and calibration. , 2006, Journal of experimental psychology. Human perception and performance.

[9]  O. Meijer,et al.  Complex movement behaviour : 'the' motor-action controversy , 1988 .

[10]  Brett R Fajen,et al.  Perceiving Possibilities for Action: On the Necessity of Calibration and Perceptual Learning for the Visual Guidance of Action , 2005, Perception.

[11]  R. Bootsma,et al.  On the information-based regulation of movement: What Wann (1996) may want to consider , 1997 .

[12]  Brett R Fajen,et al.  Calibration, information, and control strategies for braking to avoid a collision. , 2005, Journal of experimental psychology. Human perception and performance.

[13]  William H. Warren,et al.  Optic flow is used to control human walking , 2001, Nature Neuroscience.

[14]  Matthieu Lenoir,et al.  Effects of contrasting colour patterns of the ball in the volleyball reception , 2005, Journal of sports sciences.

[15]  Julien Bastin,et al.  Muscular proprioception contributes to the control of interceptive actions. , 2006, Journal of experimental psychology. Human perception and performance.

[16]  Gilles Montagne,et al.  The learning of goal-directed locomotion: a perception-action perspective. , 2003, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[17]  F. C. Bakker,et al.  Catching balls: how to get the hand to the right place at the right time. , 1994, Journal of experimental psychology. Human perception and performance.

[18]  J. Bastin,et al.  Prospective strategies underlie the control of interceptive actions. , 2006, Human Movement Science.

[19]  J. Tresilian.  Hitting a moving target: Perception and action in the timing of rapid interceptions , 2005, Perception & psychophysics.

[20]  P J Beek,et al.  Modelling the control of interceptive actions. , 2003, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[21]  J M Flach,et al.  Sources of optical information useful for perception of speed of rectilinear self-motion. , 1990, Journal of experimental psychology. Human perception and performance.

[22]  Richard M Wilkie,et al.  Driving as Night Falls The Contribution of Retinal Flow and Visual Direction to the Control of Steering , 2002, Current Biology.

[23]  Claire F. Michaels,et al.  The optics and actions of catching fly balls , 1992 .

[24]  Julien Bastin,et al.  Testing the role of expansion in the prospective control of locomotion , 2008, Experimental Brain Research.

[25]  Wendy D. Zosh,et al.  Optic Flow Drives Human Visuo-Locomotor Adaptation , 2007, Current Biology.

[26]  A. Duchon,et al.  A Visual Equalization Strategy for Locomotor Control: Of Honeybees, Robots, and Humans , 2002, Psychological science.

[27]  G. Montagne,et al.  A Robust Solution for Dealing With Environmental Changes in Intercepting Moving Balls , 2005, Journal of motor behavior.

[28]  F. Lacquaniti,et al.  Visuo-motor coordination and internal models for object interception , 2009, Experimental Brain Research.

[29]  Scott M. Dittman,et al.  Monocular optical constraints on collision control. , 2001, Journal of experimental psychology. Human perception and performance.

[30]  William H. Warren,et al.  7 Action-Scaled Information for the Visual Control of Locomotion , 2006 .

[31]  David N. Lee,et al.  Plummeting gannets: a paradigm of ecological optics , 1981, Nature.

[32]  G. Montagne,et al.  The study of locomotor pointing in virtual reality: The validation of a test set-up , 2000, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[33]  W. Warren.  Action modes and laws of control for the visual guidance of action , 1988 .

[34]  Gregor Schöner,et al.  A dynamical systems approach to task-level system integration used to plan and control autonomous vehicle motion , 1992, Robotics Auton. Syst..

[35]  Hubert Ripoll,et al.  Time-to-contact estimation of accelerated stimuli is based on first-order information. , 2003, Journal of experimental psychology. Human perception and performance.

[36]  A. Chardenona,et al.  The visual control of ball interception during human locomotion , 2002 .

[37]  R J Bootsma,et al.  Visual information about time-to-collision between two objects. , 1993, Journal of experimental psychology. Human perception and performance.

[38]  Scott T. Grafton,et al.  Forward modeling allows feedback control for fast reaching movements , 2000, Trends in Cognitive Sciences.

[39]  Julien Bastin,et al.  The perceptual support of goal-directed displacement is context-dependent , 2005, Neuroscience Letters.

[40]  Gilles Montagne,et al.  Movement reversals in ball catching , 1999, Experimental Brain Research.

[41]  Brett R. Fajen,et al.  Intercepting moving targets: a little foresight helps a lot , 2009, Experimental Brain Research.

[42]  Richard M Wilkie,et al.  The role of visual and nonvisual information in the control of locomotion. , 2005, Journal of experimental psychology. Human perception and performance.