Sampling based motion planning with reachable volumes: Application to manipulators and closed chain systems

Handle URI:
http://hdl.handle.net/10754/599551
Title:
Sampling based motion planning with reachable volumes: Application to manipulators and closed chain systems
Authors:
McMahon, Troy; Thomas, Shawna; Amato, Nancy M.
Abstract:
© 2014 IEEE. Reachable volumes are a geometric representation of the regions the joints of a robot can reach. They can be used to generate constraint satisfying samples for problems including complicated linkage robots (e.g. closed chains and graspers). They can also be used to assist robot operators and to help in robot design.We show that reachable volumes have an O(1) complexity in unconstrained problems as well as in many constrained problems. We also show that reachable volumes can be computed in linear time and that reachable volume samples can be generated in linear time in problems without constraints. We experimentally validate reachable volume sampling, both with and without constraints on end effectors and/or internal joints. We show that reachable volume samples are less likely to be invalid due to self-collisions, making reachable volume sampling significantly more efficient for higher dimensional problems. We also show that these samples are easier to connect than others, resulting in better connected roadmaps. We demonstrate that our method can be applied to 262-dof, multi-loop, and tree-like linkages including combinations of planar, prismatic and spherical joints. In contrast, existing methods either cannot be used for these problems or do not produce good quality solutions.
Citation:
McMahon T, Thomas S, Amato NM (2014) Sampling based motion planning with reachable volumes: Application to manipulators and closed chain systems. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Available: http://dx.doi.org/10.1109/IROS.2014.6943082.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
Sep-2014
DOI:
10.1109/IROS.2014.6943082
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).Parasol Lab., Dept. of Comp. Sci. and Eng., Texas A&M Univ., College Station, Texas, USA
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorMcMahon, Troyen
dc.contributor.authorThomas, Shawnaen
dc.contributor.authorAmato, Nancy M.en
dc.date.accessioned2016-02-28T05:53:13Zen
dc.date.available2016-02-28T05:53:13Zen
dc.date.issued2014-09en
dc.identifier.citationMcMahon T, Thomas S, Amato NM (2014) Sampling based motion planning with reachable volumes: Application to manipulators and closed chain systems. 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. Available: http://dx.doi.org/10.1109/IROS.2014.6943082.en
dc.identifier.doi10.1109/IROS.2014.6943082en
dc.identifier.urihttp://hdl.handle.net/10754/599551en
dc.description.abstract© 2014 IEEE. Reachable volumes are a geometric representation of the regions the joints of a robot can reach. They can be used to generate constraint satisfying samples for problems including complicated linkage robots (e.g. closed chains and graspers). They can also be used to assist robot operators and to help in robot design.We show that reachable volumes have an O(1) complexity in unconstrained problems as well as in many constrained problems. We also show that reachable volumes can be computed in linear time and that reachable volume samples can be generated in linear time in problems without constraints. We experimentally validate reachable volume sampling, both with and without constraints on end effectors and/or internal joints. We show that reachable volume samples are less likely to be invalid due to self-collisions, making reachable volume sampling significantly more efficient for higher dimensional problems. We also show that these samples are easier to connect than others, resulting in better connected roadmaps. We demonstrate that our method can be applied to 262-dof, multi-loop, and tree-like linkages including combinations of planar, prismatic and spherical joints. In contrast, existing methods either cannot be used for these problems or do not produce good quality solutions.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).Parasol Lab., Dept. of Comp. Sci. and Eng., Texas A&M Univ., College Station, Texas, USAen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.titleSampling based motion planning with reachable volumes: Application to manipulators and closed chain systemsen
dc.typeConference Paperen
dc.identifier.journal2014 IEEE/RSJ International Conference on Intelligent Robots and Systemsen
dc.contributor.institutionTexas A and M University, College Station, United Statesen
kaust.grant.numberKUS-C1-016-04en
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