Grey, Michael X. and Ames, Aaron D. and Liu, C. Karen (2017) Probabilistic Completeness of Randomized Possibility Graphs Applied to Bipedal Walking in Semi-unstructured Environments. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20190201-160913893
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Abstract
We present a theoretical analysis of a recent whole body motion planning method, the Randomized Possibility Graph, which uses a high-level decomposition of the feasibility constraint manifold in order to rapidly find routes that may lead to a solution. These routes are then examined by lower-level planners to determine feasibility. In this paper, we show that this approach is probabilistically complete for bipedal robots performing quasi-static walking in "semi-unstructured" environments. Furthermore, we show that the decomposition into higher and lower level planners allows for a considerably higher rate of convergence in the probability of finding a solution when one exists. We illustrate this improved convergence with a series of simulated scenarios.
Item Type: | Report or Paper (Discussion Paper) | ||||||
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Record Number: | CaltechAUTHORS:20190201-160913893 | ||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20190201-160913893 | ||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||
ID Code: | 92613 | ||||||
Collection: | CaltechAUTHORS | ||||||
Deposited By: | George Porter | ||||||
Deposited On: | 04 Feb 2019 15:45 | ||||||
Last Modified: | 19 Nov 2020 00:37 |
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