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Traversing Environments Using Possibility Graphs for Humanoid Robots

Grey, Michael X. and Ames, Aaron D. and Liu, C. Karen (2016) Traversing Environments Using Possibility Graphs for Humanoid Robots. . (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20190201-160859446

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Abstract

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 actions. We introduce the concept of the "Possibility Graph", which uses high-level approximations of constraint manifolds to rapidly explore the "possibility" of actions, thereby allowing lower-level single-action motion planners to be utilized more efficiently. We show that the Possibility Graph can quickly find paths through several different challenging environments which require various combinations of actions in order to traverse.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/1608.03845arXivDiscussion Paper
ORCID:
AuthorORCID
Ames, Aaron D.0000-0003-0848-3177
Record Number:CaltechAUTHORS:20190201-160859446
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190201-160859446
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92608
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:04 Feb 2019 15:49
Last Modified:04 Feb 2019 15:49

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