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Pregled bibliografske jedinice broj: 1139571

A Novel Genetic Scan-Matching-Based Registration Algorithm for Supporting Moving Objects Tracking Effectively and Efficiently


Lenac, Kristijan; Cuzzocrea, Alfredo; Mumolo, Enzo
A Novel Genetic Scan-Matching-Based Registration Algorithm for Supporting Moving Objects Tracking Effectively and Efficiently // IEEE Access, 9 (2021), 91741-91753 doi:10.1109/access.2021.3091520 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1139571 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
A Novel Genetic Scan-Matching-Based Registration Algorithm for Supporting Moving Objects Tracking Effectively and Efficiently

Autori
Lenac, Kristijan ; Cuzzocrea, Alfredo ; Mumolo, Enzo

Izvornik
IEEE Access (2169-3536) 9 (2021); 91741-91753

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Moving objects ; Scan-matching algorithms ; Intelligent systems ; Genetic optimization

Sažetak
In this paper we describe a scan-matching based registration algorithm for tracking moving objects which falls in the emerging area that predicates the integration between robotics and big data applications . The scan matching approaches track paths of a mobile object by comparing maps of the environment seen by the object during its movement. Algorithms described in this paper are hybrid, i.e. they compare maps by using first a genetic pre-alignment based on a novel metrics, and then performing a finer alignment using a deterministic approach. This kind of hybridization is, indeed, not new. However, the novel metrics used in this paper leads to important new properties, namely to correct arbitrary rotational errors and to cover larger search spaces. The proposed algorithm is experimentally compared to other approaches, and better performance in terms of accuracy and robustness are reported. Finally, our algorithm is also very fast thanks to the genetic pre- alignment task and the novel metrics we propose.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo



POVEZANOST RADA


Projekti:
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-295 - Ugradbeni sustavi za 3D percepciju (Lenac, Kristijan, NadSve ) ( CroRIS)

Ustanove:
Tehnički fakultet, Rijeka

Profili:

Avatar Url Kristijan Lenac (autor)

Poveznice na cjeloviti tekst rada:

doi doi.org

Citiraj ovu publikaciju:

Lenac, Kristijan; Cuzzocrea, Alfredo; Mumolo, Enzo
A Novel Genetic Scan-Matching-Based Registration Algorithm for Supporting Moving Objects Tracking Effectively and Efficiently // IEEE Access, 9 (2021), 91741-91753 doi:10.1109/access.2021.3091520 (međunarodna recenzija, članak, znanstveni)
Lenac, K., Cuzzocrea, A. & Mumolo, E. (2021) A Novel Genetic Scan-Matching-Based Registration Algorithm for Supporting Moving Objects Tracking Effectively and Efficiently. IEEE Access, 9, 91741-91753 doi:10.1109/access.2021.3091520.
@article{article, author = {Lenac, Kristijan and Cuzzocrea, Alfredo and Mumolo, Enzo}, year = {2021}, pages = {91741-91753}, DOI = {10.1109/access.2021.3091520}, keywords = {Moving objects, Scan-matching algorithms, Intelligent systems, Genetic optimization}, journal = {IEEE Access}, doi = {10.1109/access.2021.3091520}, volume = {9}, issn = {2169-3536}, title = {A Novel Genetic Scan-Matching-Based Registration Algorithm for Supporting Moving Objects Tracking Effectively and Efficiently}, keyword = {Moving objects, Scan-matching algorithms, Intelligent systems, Genetic optimization} }
@article{article, author = {Lenac, Kristijan and Cuzzocrea, Alfredo and Mumolo, Enzo}, year = {2021}, pages = {91741-91753}, DOI = {10.1109/access.2021.3091520}, keywords = {Moving objects, Scan-matching algorithms, Intelligent systems, Genetic optimization}, journal = {IEEE Access}, doi = {10.1109/access.2021.3091520}, volume = {9}, issn = {2169-3536}, title = {A Novel Genetic Scan-Matching-Based Registration Algorithm for Supporting Moving Objects Tracking Effectively and Efficiently}, keyword = {Moving objects, Scan-matching algorithms, Intelligent systems, Genetic optimization} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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