This thesis presents a framework for developing a library of gaits for highly non-linear, hyper-redundant, potentially compliant robotic systems. Examples of such systems that motivate this work include tensegrity robots, which combine both soft and rigid elements, and snake-like salamander robots. A library of gaits for such complex robots can be integrated with a search-based method so as to achieve more efficient exploration of the underlying state space when solving trajectory planning problems. The first component of the work corresponds to the definition of a Central Pattern Generator (CPG) for a spherical tensegrity robot inspired by similar solutions in the domain of modular, bio-inspired snake robots. The CPG provides a reparametrization of the underlying system, which can easily result in the generation of rhythmic gaits. The second component is a novel framework for simultaneously discovering effective gaits along different directions of motion by searching the space of CPG parameters. The framework defines multiple objectives, which are maximized though a parallel Bayesian Optimization (BO) process. The samples, which correspond to different gait parameters, are biased towards areas of previously observed high reward using a set of binary kNN classifiers with on-line updates. This integrated method is shown to be more efficient than Monte Carlo sampling of gait parameters or BO without classification or the classification only approach. The evaluation is performed in simulation using a high-dimensional spherical tensegrity robot.
Subject (authority = RUETD)
Topic
Computer Science
Subject (authority = ETD-LCSH)
Topic
Robotics
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_8442
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (viii, 32 p. : ill.)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Colin M. Rennie
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.