Footstep and motion planning in semi-unstructured environments using randomized possibility graphs
- Creators
- Grey, Michael X.
- Ames, Aaron D.
- Liu, C. Karen
Abstract
Traversing environments with arbitrary obstacles poses significant challenges for bipedal robots. In some cases, whole body motions may be necessary to maneuver around an obstacle, but most existing footstep planners can only select from a discrete set of predetermined footstep actions; they are unable to utilize the continuum of whole body motion that is truly available to the robot platform. Existing motion planners that can utilize whole body motion tend to struggle with the complexity of large-scale problems. We introduce a planning method, called the "Randomized Possibility Graph", which uses high-level approximations of constraint manifolds to rapidly explore the "possibility" of actions, thereby allowing lower-level motion planners to be utilized more efficiently. We demonstrate simulations of the method working in a variety of semi-unstructured environments. In this context, "semi-unstructured" means the walkable terrain is flat and even, but there are arbitrary 3D obstacles throughout the environment which may need to be stepped over or maneuvered around using whole body motions.
Additional Information
© 2017 IEEE. This work was supported by DARPA grant D15AP00006.Attached Files
Accepted Version - 1610.00700.pdf
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Additional details
- Eprint ID
- 79320
- Resolver ID
- CaltechAUTHORS:20170725-083100456
- D15AP00006
- Defense Advanced Research Projects Agency (DARPA)
- Created
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2017-07-25Created from EPrint's datestamp field
- Updated
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2021-11-15Created from EPrint's last_modified field