dc.contributor.author | Sommer, Hannes | |
dc.contributor.author | Gilitschenski, Igor | |
dc.contributor.author | Bloesch, Michael | |
dc.contributor.author | Weiss, Stephan | |
dc.contributor.author | Siegwart, Roland | |
dc.contributor.author | Nieto, Juan | |
dc.date.accessioned | 2018-09-28T14:34:14Z | |
dc.date.available | 2018-09-28T14:34:14Z | |
dc.date.issued | 2018-07 | |
dc.date.submitted | 2018-06 | |
dc.identifier.issn | 2226-4310 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/118190 | |
dc.description.abstract | Over the last decades quaternions have become a crucial and very successful tool for attitude representation in robotics and aerospace. However, there is a major problem that is continuously causing trouble in practice when it comes to exchanging formulas or implementations: there are two quaternion multiplications commonly in use, Hamilton’s multiplication and its flipped version, which is often associated with NASA’s Jet Propulsion Laboratory. This paper explains the underlying problem for the popular passive world-to-body usage of rotation quaternions, and promotes an alternative solution compatible with Hamilton’s multiplication. Furthermore, it argues for discontinuing the flipped multiplication. Additionally, it provides recipes for efficiently detecting relevant conventions and migrating formulas or algorithms between them. Keywords: quaternion multiplication; attitude; rotation; convention | en_US |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.3390/aerospace5030072 | en_US |
dc.rights | Creative Commons Attribution | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_US |
dc.source | Multidisciplinary Digital Publishing Institute | en_US |
dc.title | Why and How to Avoid the Flipped Quaternion Multiplication | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Sommer, Hannes et al. "Why and How to Avoid the Flipped Quaternion Multiplication." Aerospace 5, 3 (July 2018): 72 © 2018 The Authors | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
dc.contributor.mitauthor | Gilitschenski, Igor | |
dc.relation.journal | Aerospace | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2018-09-21T07:11:44Z | |
dspace.orderedauthors | Sommer, Hannes; Gilitschenski, Igor; Bloesch, Michael; Weiss, Stephan; Siegwart, Roland; Nieto, Juan | en_US |
dspace.embargo.terms | N | en_US |
mit.license | PUBLISHER_CC | en_US |