dc.contributor.author | Tian, Yulun | |
dc.contributor.author | Koppel, Alec | |
dc.contributor.author | Bedi, Amrit Singh | |
dc.contributor.author | How, Jonathan P | |
dc.date.accessioned | 2021-10-27T20:22:38Z | |
dc.date.available | 2021-10-27T20:22:38Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/135250 | |
dc.description.abstract | © 2016 IEEE. We present Asynchronous Stochastic Parallel Pose Graph Optimization ($\textsc {ASAPP}$), the first asynchronous algorithm for distributed pose graph optimization (PGO) in multi-robot simultaneous localization and mapping. By enabling robots to optimize their local trajectory estimates without synchronization, $\textsc {ASAPP}$ offers resiliency against communication delays and alleviates the need to wait for stragglers in the network. Furthermore, $\textsc {ASAPP}$ can be applied on the rank-restricted relaxations of PGO, a crucial class of non-convex Riemannian optimization problems that underlies recent breakthroughs on globally optimal PGO. Under bounded delay, we establish the global first-order convergence of $\textsc {ASAPP}$ using a sufficiently small stepsize. The derived stepsize depends on the worst-case delay and inherent problem sparsity, and furthermore matches known result for synchronous algorithms when there is no delay. Numerical evaluations on simulated and real-world datasets demonstrate favorable performance compared to state-of-the-art synchronous approach, and show $\textsc {ASAPP}$'s resilience against a wide range of delays in practice. | |
dc.language.iso | en | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
dc.relation.isversionof | 10.1109/LRA.2020.3010216 | |
dc.rights | Creative Commons Attribution-Noncommercial-Share Alike | |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
dc.source | arXiv | |
dc.title | Asynchronous and Parallel Distributed Pose Graph Optimization | |
dc.type | Article | |
dc.contributor.department | Massachusetts Institute of Technology. Department of Aeronautics and Astronautics | |
dc.relation.journal | IEEE Robotics and Automation Letters | |
dc.eprint.version | Author's final manuscript | |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
eprint.status | http://purl.org/eprint/status/PeerReviewed | |
dc.date.updated | 2021-04-30T13:59:19Z | |
dspace.orderedauthors | Tian, Y; Koppel, A; Bedi, AS; How, JP | |
dspace.date.submission | 2021-04-30T13:59:20Z | |
mit.journal.volume | 5 | |
mit.journal.issue | 4 | |
mit.license | OPEN_ACCESS_POLICY | |
mit.metadata.status | Authority Work and Publication Information Needed | |