  Locomotion for legged robots poses considerable challenges when confronted by
obstacles and adverse environments. Footstep planners are typically only
designed for one mode of locomotion, but traversing unfavorable environments
may require several forms of locomotion to be sequenced together, such as
walking, crawling, and jumping. Multi-modal motion planners can be used to
address some of these problems, but existing implementations tend to be
time-consuming and are limited to quasi-static actions. This paper presents a
motion planning method to traverse complex environments using multiple
categories of continuous actions. To this end, this paper formulates and
exploits the Possibility Graph---which uses high-level approximations of
constraint manifolds to rapidly explore the "possibility" of actions---to
utilize lower-level single-action motion planners more effectively. We show
that the Possibility Graph can quickly find routes through several different
challenging environments which require various combinations of actions in order
to traverse.
