Distributed framework matching
This paper studies the problem of distributed framework matching (FM), which originates from the assignment task in multi-robot coordination and the matching task in pattern recognition. The objective of distributed FM is to distributively seek a correspondence which minimizes some metrics descri...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/162586 |
| _version_ | 1811679539556777984 |
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| author | Cao, Kun Li, Xiuxian Xie, Lihua |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Cao, Kun Li, Xiuxian Xie, Lihua |
| author_sort | Cao, Kun |
| collection | NTU |
| description | This paper studies the problem of distributed framework matching (FM), which originates from the assignment task
in multi-robot coordination and the matching task in pattern
recognition. The objective of distributed FM is to distributively
seek a correspondence which minimizes some metrics describing
the disagreement between two frameworks (i.e., graphs and their
embeddings). In view of the type of the underlying graph in the
framework, two formulations, undirected framework matching
(UFM) and directed framework matching (DFM), and their
convex relaxations, relaxed UFM (RUFM) and relaxed DFM
(RDFM), are presented. UFM is converted into a graph matching
(GM) problem with the adjacency matrix being replaced by a
matrix constructed from the undirected framework under certain
graphical conditions, and can be solved distributively. Sufficient
conditions for the equivalence between UFM and RUFM, and
the perturbation admitting exact recovery of correspondence are
established. On the other hand, DFM embeds the configuration
of the directed framework via another type of matrix, whose
computation is distributed, and can deal with the case of two
frameworks with different sizes of node sets. A distributed
optimization algorithm for solving RDFM is proposed and its
convergence results are established which allows DFM to be
solved in a fully distributed manner. Simulation examples on
both synthetic data and real world datasets demonstrate the
applicability and efficacy of our theoretical results in formation
control and object matching problems. |
| first_indexed | 2024-10-01T03:10:46Z |
| format | Journal Article |
| id | ntu-10356/162586 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:10:46Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1625862022-10-31T08:19:04Z Distributed framework matching Cao, Kun Li, Xiuxian Xie, Lihua School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Assignment Distributed Optimization This paper studies the problem of distributed framework matching (FM), which originates from the assignment task in multi-robot coordination and the matching task in pattern recognition. The objective of distributed FM is to distributively seek a correspondence which minimizes some metrics describing the disagreement between two frameworks (i.e., graphs and their embeddings). In view of the type of the underlying graph in the framework, two formulations, undirected framework matching (UFM) and directed framework matching (DFM), and their convex relaxations, relaxed UFM (RUFM) and relaxed DFM (RDFM), are presented. UFM is converted into a graph matching (GM) problem with the adjacency matrix being replaced by a matrix constructed from the undirected framework under certain graphical conditions, and can be solved distributively. Sufficient conditions for the equivalence between UFM and RUFM, and the perturbation admitting exact recovery of correspondence are established. On the other hand, DFM embeds the configuration of the directed framework via another type of matrix, whose computation is distributed, and can deal with the case of two frameworks with different sizes of node sets. A distributed optimization algorithm for solving RDFM is proposed and its convergence results are established which allows DFM to be solved in a fully distributed manner. Simulation examples on both synthetic data and real world datasets demonstrate the applicability and efficacy of our theoretical results in formation control and object matching problems. Ministry of Education (MOE) National Research Foundation (NRF) This work was supported in part by the National Research Foundation, Singapore under its Medium Sized Center for Advanced Robotics Technology Innovation, the Ministry of Education, Singapore, under Grant AcRF TIER 1-2019-T1-001-088(RG72/19), in part by the Wallenberg-NTU Presidential Postdoctoral Fellowship in Nanyang Technological University, Singapore, in part by the National Natural Science Foundation of China under Grant 62003243, and in part by the Fundamental Research Funds for the Central Universities under under Grant 08002150138. 2022-10-31T08:19:04Z 2022-10-31T08:19:04Z 2022 Journal Article Cao, K., Li, X. & Xie, L. (2022). Distributed framework matching. IEEE Transactions On Robotics. https://dx.doi.org/10.1109/TRO.2022.3193301 1552-3098 https://hdl.handle.net/10356/162586 10.1109/TRO.2022.3193301 en 2019-T1-001-088(RG72/19) IEEE Transactions on Robotics © 2022 IEEE. All rights reserved. |
| spellingShingle | Engineering::Electrical and electronic engineering Assignment Distributed Optimization Cao, Kun Li, Xiuxian Xie, Lihua Distributed framework matching |
| title | Distributed framework matching |
| title_full | Distributed framework matching |
| title_fullStr | Distributed framework matching |
| title_full_unstemmed | Distributed framework matching |
| title_short | Distributed framework matching |
| title_sort | distributed framework matching |
| topic | Engineering::Electrical and electronic engineering Assignment Distributed Optimization |
| url | https://hdl.handle.net/10356/162586 |
| work_keys_str_mv | AT caokun distributedframeworkmatching AT lixiuxian distributedframeworkmatching AT xielihua distributedframeworkmatching |