Sampling-based motion planning with reachable volumes: Theoretical foundations

Handle URI:
http://hdl.handle.net/10754/599553
Title:
Sampling-based motion planning with reachable volumes: Theoretical foundations
Authors:
McMahon, Troy; Thomas, Shawna; Amato, Nancy M.
Abstract:
© 2014 IEEE. We introduce a new concept, reachable volumes, that denotes the set of points that the end effector of a chain or linkage can reach. We show that the reachable volume of a chain is equivalent to the Minkowski sum of the reachable volumes of its links, and give an efficient method for computing reachable volumes. We present a method for generating configurations using reachable volumes that is applicable to various types of robots including open and closed chain robots, tree-like robots, and complex robots including both loops and branches. We also describe how to apply constraints (both on end effectors and internal joints) using reachable volumes. Unlike previous methods, reachable volumes work for spherical and prismatic joints as well as planar joints. Visualizations of reachable volumes can allow an operator to see what positions the robot can reach and can guide robot design. We present visualizations of reachable volumes for representative robots including closed chains and graspers as well as for examples with joint and end effector constraints.
Citation:
McMahon T, Thomas S, Amato NM (2014) Sampling-based motion planning with reachable volumes: Theoretical foundations. 2014 IEEE International Conference on Robotics and Automation (ICRA). Available: http://dx.doi.org/10.1109/ICRA.2014.6907820.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2014 IEEE International Conference on Robotics and Automation (ICRA)
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
May-2014
DOI:
10.1109/ICRA.2014.6907820
Type:
Conference Paper
Sponsors:
This research supported in part by NSF awards CNS-0551685, CCF-0833199, CCF-0830753, IIS-0916053, IIS-0917266, EFRI-1240483, RI-1217991, by NIH NCI R25 CA090301-11, by Chevron, IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).
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Full metadata record

DC FieldValue Language
dc.contributor.authorMcMahon, Troyen
dc.contributor.authorThomas, Shawnaen
dc.contributor.authorAmato, Nancy M.en
dc.date.accessioned2016-02-28T05:53:15Zen
dc.date.available2016-02-28T05:53:15Zen
dc.date.issued2014-05en
dc.identifier.citationMcMahon T, Thomas S, Amato NM (2014) Sampling-based motion planning with reachable volumes: Theoretical foundations. 2014 IEEE International Conference on Robotics and Automation (ICRA). Available: http://dx.doi.org/10.1109/ICRA.2014.6907820.en
dc.identifier.doi10.1109/ICRA.2014.6907820en
dc.identifier.urihttp://hdl.handle.net/10754/599553en
dc.description.abstract© 2014 IEEE. We introduce a new concept, reachable volumes, that denotes the set of points that the end effector of a chain or linkage can reach. We show that the reachable volume of a chain is equivalent to the Minkowski sum of the reachable volumes of its links, and give an efficient method for computing reachable volumes. We present a method for generating configurations using reachable volumes that is applicable to various types of robots including open and closed chain robots, tree-like robots, and complex robots including both loops and branches. We also describe how to apply constraints (both on end effectors and internal joints) using reachable volumes. Unlike previous methods, reachable volumes work for spherical and prismatic joints as well as planar joints. Visualizations of reachable volumes can allow an operator to see what positions the robot can reach and can guide robot design. We present visualizations of reachable volumes for representative robots including closed chains and graspers as well as for examples with joint and end effector constraints.en
dc.description.sponsorshipThis research supported in part by NSF awards CNS-0551685, CCF-0833199, CCF-0830753, IIS-0916053, IIS-0917266, EFRI-1240483, RI-1217991, by NIH NCI R25 CA090301-11, by Chevron, IBM, Intel, Oracle/Sun and by Award KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleSampling-based motion planning with reachable volumes: Theoretical foundationsen
dc.typeConference Paperen
dc.identifier.journal2014 IEEE International Conference on Robotics and Automation (ICRA)en
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-C1-016-04en
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