Visual Control of Locomotion

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DESCRIPTION (provided by applicant): The long-term objective of this project is to develop a model of visually controlled locomotor behavior in complex, dynamic environments. First, what are the behavioral dynamics of locomotion - how are paths of locomotion determined for steering, obstacle avoidance, interception, and escape? Second, what are the control laws for locomotion - how is visual and proprioceptive information used to regulate these basic locomotor behaviors? In previous research, we investigated the basic locomotor behaviors of (a) steering to a stationary target, (b) avoiding stationary obstacles, (c) intercepting a moving target, (d) avoiding moving obstacles, and (e) escaping moving pursuers. We tested the first four behaviors individually and developed a dynamical model that successfully predicts human locomotor paths. The specific aim of the proposed research is to investigate how these components are integrated in more complex environments, and the perceptual strategies used to guide them. Using virtual reality techniques, head-mounted displays will be presented to a freely walking observer, the path of locomotion will be measured, and the resulting behavior formally modeled. Four studies are proposed: (1) Integration of steering and obstacle avoidance examines how steering to a stationary or moving target is integrated with avoidance of stationary or moving obstacles. (2) Control laws for steering and obstacle avoidance pursues interactions of optic flow, egocentric direction, and head/body alignment to guide walking to stationary targets and obstacles. (3) Planning or on-line control investigates whether steering is controlled on the basis of current information about the target and obstacles, or whether paths are planned in advance. (4) Steering in interactive environments investigates dynamic interactions between a participant and simulated agents that are programmed using the model, such as two people trying to pass each other or a person trying to walk through a crowd. The results will contribute to basic knowledge about the visual control of locomotion and provide a foundation for clinical research on visual-motor deficits and mobility problems in disease and aging. A working model would enable predictions of locomotor behavior in everyday environments, simulations of specific deficits, forecasting of mobility risks, and testing of potential accommodations.