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Humans are efficient, yet expressive in their motion. Human walking behaviorscan be used to walk across a great variety of surfaces without falling and tocommunicate internal state to other humans through variable gait styles. Thisprovides inspiration for creating similarly expressive bipedal robots. To thisend, a framework is presented for stylistic gait generation in a compass-likeunder-actuated planar biped model. The gait design is done using model-basedtrajectory optimization with variable constraints. For a finite range ofoptimization parameters, a large set of 360 gaits can be generated for thismodel. In particular, step length and cost function are varied to producedistinct cyclic walking gaits. From these resulting gaits, 6 gaits areidentified and labeled, using embodied movement analysis, with stylistic verbsthat correlate with human activity, e.g., "lope" and "saunter". These labelshave been validated by conducting user studies in Amazon Mechanical Turk andthus demonstrate that visually distinguishable, meaningful gaits are generatedusing this framework. This lays groundwork for creating a bipedal humanoid withvariable socially competent movement profiles.

Toward an Expressive Bipedal Robot: Variable Gait Synthesis and Validation in a Planar Model