dc.contributor.author | Marchese, Andrew Dominic | |
dc.contributor.author | Katzschmann, Robert Kevin | |
dc.contributor.author | Rus, Daniela L | |
dc.date.accessioned | 2018-04-06T21:52:05Z | |
dc.date.available | 2018-04-06T21:52:05Z | |
dc.date.issued | 2014-09 | |
dc.identifier.isbn | 978-1-4799-6934-0 | |
dc.identifier.isbn | 978-1-4799-6931-9 | |
dc.identifier.issn | 2153-0858 | |
dc.identifier.issn | 2153-0866 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/114602 | |
dc.description.abstract | Soft continuum manipulators have the advantage of being more compliant and having more degrees of freedom than rigid redundant manipulators. This attribute should allow soft manipulators to autonomously execute highly dexterous tasks. However, current approaches to motion planning, inverse kinematics, and even design limit the capacity of soft manipulators to take full advantage of their inherent compliance. We provide a computational approach to whole arm planning for a soft planar manipulator that advances the arm's end effector pose in task space while simultaneously considering the arm's entire envelope in proximity to a confined environment. The algorithm solves a series of constrained optimization problems to determine locally optimal inverse kinematics. Due to inherent limitations in modeling the kinematics of a highly compliant soft robot and the local optimality of the planner's solutions, we also rely on the increased softness of our newly designed manipulator to accomplish the whole arm task, namely the arm's ability to harmlessly collide with the environment. We detail the design and fabrication of the new modular manipulator as well as the planner's central algorithm. We experimentally validate our approach by showing that the robotic system is capable of autonomously advancing the soft arm through a pipe-like environment in order to reach distinct goal states. | en_US |
dc.description.sponsorship | National Science Foundation (U.S.) (grant number NSF IIS1226883) | en_US |
dc.description.sponsorship | National Science Foundation (U.S.) (grant number NSF CCF1138967) | en_US |
dc.description.sponsorship | National Science Foundation (U.S.). Graduate Research Fellowship Program (primary award number 1122374) | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/IROS.2014.6942614 | en_US |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | en_US |
dc.source | Katzschmann | en_US |
dc.title | Whole arm planning for a soft and highly compliant 2D robotic manipulator | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Marchese, Andrew D., Robert K. Katzschmann, and Daniela Rus. “Whole Arm Planning for a Soft and Highly Compliant 2D Robotic Manipulator.” 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (September 2014). | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Mechanical Engineering | en_US |
dc.contributor.mitauthor | Marchese, Andrew Dominic | |
dc.contributor.mitauthor | Katzschmann, Robert Kevin | |
dc.contributor.mitauthor | Rus, Daniela L | |
dc.relation.journal | 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems | en_US |
dc.eprint.version | Author's final manuscript | en_US |
dc.type.uri | http://purl.org/eprint/type/ConferencePaper | en_US |
eprint.status | http://purl.org/eprint/status/NonPeerReviewed | en_US |
dc.date.updated | 2018-03-12T13:34:38Z | |
dspace.orderedauthors | Marchese, Andrew D.; Katzschmann, Robert K.; Rus, Daniela | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0001-7143-7259 | |
dc.identifier.orcid | https://orcid.org/0000-0001-5473-3566 | |
mit.license | OPEN_ACCESS_POLICY | en_US |