This paper presents an approach to the development of bipedal robotic control techniques for multiple locomotion behaviors. Insight into the fundamental behaviors of human loco-motion is obtained through the examination of experimental human data for walking on flat ground, upstairs and downstairs. Specifically, it is shown that certain outputs of the human, independent of locomotion ter-rain, can be characterized by a single function, termed the extended canonical human function. Optimized functions of this form are tracked via feedback linearization in simulations of a planar robotic biped walking on flat ground, upstairs and downstairs — these three modes of locomotion are termed “motion primi-tives.” A second optimization is presented, which yields controllers that evolve the robot from one motion primitive to another — these modes of locomotion are termed “motion transitions.” A final simulation is given, which shows the controlled evolution of a robotic biped as it transitions through each mode of loco-motion over a pyramidal staircase.

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