Visual information is crucial for the representation of the space in which the hand and body move. The acquisition of visual information is achieved by eye and head movements, which are affected by concurrent hand and whole-body movements. This thesis investigates the interaction and control of head and hand movements in the context of unconstrained, visually-guided aiming and pointing tasks in a three-dimensional space. Measurements of head movements for target localization tasks indicate that head movement kinematics is composed of an initial component weakly correlated to target position, followed by multiple corrections. Since the eyes are estimated to aim at the target when the corrections occur, it is suggested that a goal of head movements is to achieve a desired final orientation (posture). This hypothesis is supported by experiments showing that (1) the proportional contribution of head movement in gaze displacement, which corresponds to 68% and 43% ( r2 = 0.95 and 0.65) of target azimuth and elevation, respectively, is consistent in spite of the variability in corrective movement kinematics; and (2) the final head orientation corresponds to an optimal posture for a given target position and task requirement that minimizes the error of the visuo-spatial representation in an egocentric reference frame associated with eye and head orientation. Furthermore, head posture and movement reflect the influence of the concurrent tasks performed by the whole-body or hands, as indicated by experiments showing that: (1) forward displacement of the center of mass induced by hand movement can be compensated by head elevation; (2) the head and hand movement controllers should negotiate the control of common links to achieve both global and segment-specific goals. Based on the above observations, a coordination model of unconstrained 3D reach movements, including multiple phases with specific controllers, was developed. A supervisory system coordinates appropriate control modes by discrete sampling of movement outcomes. The model suggests that unconstrained 3D movements are effectively controlled on-the-fly within a context, and may not require optimization schemes for coordination. The model implementation shows its capacity to simulate accurately visually guided reach movements, while preserving their dynamic characteristics.
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