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Locomotion for legged robots poses considerable challenges when confronted byobstacles and adverse environments. Footstep planners are typically onlydesigned for one mode of locomotion, but traversing unfavorable environmentsmay require several forms of locomotion to be sequenced together, such aswalking, crawling, and jumping. Multi-modal motion planners can be used toaddress some of these problems, but existing implementations tend to betime-consuming and are limited to quasi-static actions. This paper presents amotion planning method to traverse complex environments using multiplecategories of continuous actions. To this end, this paper formulates andexploits the Possibility Graph---which uses high-level approximations ofconstraint manifolds to rapidly explore the "possibility" of actions---toutilize lower-level single-action motion planners more effectively. We showthat the Possibility Graph can quickly find routes through several differentchallenging environments which require various combinations of actions in orderto traverse.

Traversing Environments Using Possibility Graphs with Multiple Action Types