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A high-level motion control system for the animation of human-like figures is introduced which generates a wide variety of individual running styles in real time. Sequences such as a leisurely jog, a fast sprint or a bouncy run are conveniently obtained by interactively setting the values of ''running'' parameters such as desired velocity, step length, ''flight'' height or ''heel/toe'' strike while observing a running figure on the screen. The algorithm incorporates knowledge of how humans run at several levels: empirical knowledge defines the relationships between the running parameters; for example, a change in running velocity by the user triggers a change in step length to maintain a ''natural'' running stride. Physical knowledge calculates the trajectory of the body for the current running step. Knowledge about limb-coordination of a running stride is utilized for establishing both, state-constraints which define the support and flight states, and phase-constraints to ''guide'' the internal joint-angle interpolation for the stance and swing phases.
Bruderlin et al. (1996) studied this question.