Localización en entornos estructurados basada en la detección de esquinas

  1. Bayón Gutiérrez, Martín 1
  2. Prieto Fernández, Natalia 1
  3. García Rodríguez, Isaías 1
  4. Benavides, Carmen 2
  5. García Ordás, María Teresa 1
  6. Benítez Andrades, José Alberto 2
  1. 1 Grupo de Investigación SECOMUCI, Departamento de Ingeniería Eléctrica y de Sistemas y Automática, Universidad de León, Campus de Vegazana s/n, 24071, León, España
  2. 2 Grupo de Investigación SALBIS, Departamento de Ingeniería Eléctrica y de Sistemas y Automática, Universidad de León, Campus de Vegazana s/n, 24071, León, España
Revue:
Jornadas de Automática
  1. Cruz Martín, Ana María (coord.)
  2. Arévalo Espejo, V. (coord.)
  3. Fernández Lozano, Juan Jesús (coord.)

ISSN: 3045-4093

Année de publication: 2024

Número: 45

Type: Article

DOI: 10.17979/JA-CEA.2024.45.10877 DIALNET GOOGLE SCHOLAR lock_openAccès ouvert editor

Résumé

LiDAR (Light Detection and Ranging) sensors provide high accuracy and high resolution readings of the environment, which makes them a common sensor to be used in SLAM (Simultaneous Localization and Mapping) systems. The large volume of data provided by these sensors can be reduced to a set of characteristic points that define the environment, consequently simplifying the mapping and positioning process, while reducing the storage needed to preserve the measurements taken by the robot as well as the result of the SLAM process carried out. In this work, we propose a system for the estimation of the trajectory followed by a robot equipped solely with a 2D LiDAR. The point cloud is analyzed to extract a set of characteristic corners that compose the navigation environment, which allows for the estimation of the robot trajectory by means of PLGO (Pose-Landmark Graph Optimization). Experimental results show that the proposed method offers a localization accuracy similar to using ICP (Iterative Closest Point)

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