Research to-date towards an understanding of human biped locomotion has been primarily experimental in nature, largely due to the complexity of the process. In view of the new, exciting possibilities of programmed electro-stimulation of paralyzed extremities to restore locomotion, a critical study at the theoretical level is greatly warranted.Optimal programming and modern control theory offer a new approach to the study. First, it is proposed that normal walking obeys a certain "principle of optimality". Next, at the dynamic level, modern control theory is used to derive the optimal moment profiles which actuate the locomotor elements to synthesize the observed patterns of the normal gait.Development of the problem structure relies closely on the functional characteristics of the biped gait, particularly the ideas of distinct phasic activities and the associated temporal patterns of a walking cycle.The result is a multi-arc programming problem with three stages. by equality constraints on the "states" while the swing phase is characterized by inequality state constraints. A novelty of the approach is that the theory could be used to study walking behavior under different environmental conditions, such as walking up-stairs or over a hole.Joining of the arcs is arranged in such a way as to maintain continuity of certain trajectories as well as repeatability of motion.A distinct feature of the present approach which differs from other studies is the presence of a minimizing performance criterion.Based on external characteristics of muscles and certain assumptions regarding normal locomotion, a simple quadratic type of performance index is proposed. This performance criterion is meaningful in that it is shown to be proportional to the mechanical work done during normal