Feature–based Map Merging with Dynamic Consensus on Information Increments

Aragüés Muñoz, María del Rosario (Universidad de Zaragoza) ; Sagues, Carlos (Universidad de Zaragoza) ; Mezouar, Youcef

Resumen: We study the problem of feature-based map merging in robot networks. Along its operation, each robot observes the environment and builds and maintains a local map. Simultaneously, each robot communicates and com- putes the global map of the environment. The communication between the robots is range-limited. Our contributions are the proposal and careful study of the properties of an algorithm that considers separately robot poses and features positions, and that reaches consensus on the latest global map using the map increments between the previous and the current time steps. We give proofs of unbiasedness and consistency of this global map for all the robots, at each iteration. Our algorithm is fully distributed and does not rely on any particular com- munication topology. Under mild connectivity conditions on the communication graph, our merging algorithm asymptot- ically converges to the global map. The proposed approach has been experimentally validated using real RGB-D images.
Keywords Distributed robot systems · Networked robots

Idioma: Inglés

DOI: 10.1007/s10514-014-9406-z

Año: 2015

Publicado en: AUTONOMOUS ROBOTS 38, 3 (2015), 243–259
ISSN: 0929-5593

Factor impacto JCR: 1.547 (2015)

Categ. JCR: ROBOTICS rank: 11 / 25 = 0.44 (2015) - Q2 - T2
Categ. JCR: COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE rank: 61 / 130 = 0.469 (2015) - Q2 - T2

Factor impacto SCIMAGO: 1.928 - Artificial Intelligence (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2009-08126
Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2012-32100

Tipo y forma: Artículo (PostPrint)

Área (Departamento): Área Ingen.Sistemas y Automát. (Dpto. Informát.Ingenie.Sistms.)