A B-spline Mapping Framework for Long-Term Autonomous Operations

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

Romulo T. Rodrigues (Autor) FEUP; António P. Aguiar (Autor) FEUP; António Pascoal (Autor) Outra

Ata de Conferência Internacional

Título: IEEE International Conference on Intelligent Robots and Systems

Páginas: 3204-3209

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2018

1 October 2018 through 5 October 2018

Indexação

ISI Web of Knowledge - 1 Citação

Scopus - 3 Citações

INSPEC

Outras Informações

ID Authenticus: P-00Q-94X

DOI: 10.1109/iros.2018.8594456

Abstract (EN): This paper presents a 2D B-spline mapping framework for representing unstructured environments in a compact manner. While occupancy-grid and landmark-based maps have been successfully employed by the robotics community in indoor scenarios, outdoor long-term autonomous operations require a more compact representation of the environment. This work tackles this problem by interpolating the data of a high frequency sensor using B-spline curves. Compared to lines and circles, splines are more powerful in the sense that they allow for the description of more complex shapes in the scene. In this work, spline curves are continuously tracked and aligned across multiple sensor readings using lightweight methods, making the proposed framework suitable for robot navigation in outdoor missions. In particular, a Simultaneous Localization and Mapping (SLAM) algorithm specifically tailored for B-spline maps is presented here. The efficacy of the proposed framework is demonstrated by Software-in-the-Loop (SiL) simulations in different scenarios.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 6