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dc.contributor.authorShkolnik, Alexander C.
dc.contributor.authorLevashov, Michael
dc.contributor.authorManchester, Ian R.
dc.contributor.authorTedrake, Russell Louis
dc.date.accessioned2011-03-25T20:06:36Z
dc.date.available2011-03-25T20:06:36Z
dc.date.issued2010-12
dc.identifier.issn1741-3176
dc.identifier.issn0278-3649
dc.identifier.urihttp://hdl.handle.net/1721.1/61974
dc.description.abstractA motion planning algorithm is described for bounding over rough terrain with the LittleDog robot. Unlike walking gaits, bounding is highly dynamic and cannot be planned with quasi-steady approximations. LittleDog is modeled as a planar five-link system, with a 16-dimensional state space; computing a plan over rough terrain in this high-dimensional state space that respects the kinodynamic constraints due to underactuation and motor limits is extremely challenging. Rapidly Exploring Random Trees (RRTs) are known for fast kinematic path planning in high-dimensional configuration spaces in the presence of obstacles, but search efficiency degrades rapidly with the addition of challenging dynamics. A computationally tractable planner for bounding was developed by modifying the RRT algorithm by using: (1) motion primitives to reduce the dimensionality of the problem; (2) Reachability Guidance, which dynamically changes the sampling distribution and distance metric to address differential constraints and discontinuous motion primitive dynamics; and (3) sampling with a Voronoi bias in a lower-dimensional “task space” for bounding. Short trajectories were demonstrated to work on the robot, however open-loop bounding is inherently unstable. A feedback controller based on transverse linearization was implemented, and shown in simulation to stabilize perturbations in the presence of noise and time delays.en_US
dc.description.sponsorshipUnited States. Defense Advanced Research Projects Agency. Learning Locomotion Program (AFRL contract # FA8650-05-C-7262)en_US
dc.language.isoen_US
dc.publisherSageen_US
dc.relation.isversionofhttp://dx.doi.org/10.1177/0278364910388315en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceMIT web domainen_US
dc.titleBounding on Rough Terrain with the LittleDog Roboten_US
dc.typeArticleen_US
dc.identifier.citationShkolnik, Alexander et al. “Bounding On Rough Terrain With the LittleDog Robot.” The International Journal Of Robotics Research 30.2 (2011) : 192 -215. Copyright © 2011 by SAGE Publicationsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronauticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverTedrake, Russell Louis
dc.contributor.mitauthorShkolnik, Alexander C.
dc.contributor.mitauthorLevashov, Michael
dc.contributor.mitauthorManchester, Ian R.
dc.contributor.mitauthorTedrake, Russell Louis
dc.relation.journalInternational Journal of Robotics Researchen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsShkolnik, A.; Levashov, M.; Manchester, I. R.; Tedrake, R.en
dc.identifier.orcidhttps://orcid.org/0000-0002-8712-7092
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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