  Humans are efficient, yet expressive in their motion. Human walking behaviors
can be used to walk across a great variety of surfaces without falling and to
communicate internal state to other humans through variable gait styles. This
provides inspiration for creating similarly expressive bipedal robots. To this
end, a framework is presented for stylistic gait generation in a compass-like
under-actuated planar biped model. The gait design is done using model-based
trajectory optimization with variable constraints. For a finite range of
optimization parameters, a large set of 360 gaits can be generated for this
model. In particular, step length and cost function are varied to produce
distinct cyclic walking gaits. From these resulting gaits, 6 gaits are
identified and labeled, using embodied movement analysis, with stylistic verbs
that correlate with human activity, e.g., "lope" and "saunter". These labels
have been validated by conducting user studies in Amazon Mechanical Turk and
thus demonstrate that visually distinguishable, meaningful gaits are generated
using this framework. This lays groundwork for creating a bipedal humanoid with
variable socially competent movement profiles.
