Unimodal and Multimodal Perception for Forest Management: Review and Dataset

• Tipo: Outra Publicação em Revista Científica Internacional
• Data: 2021

Autores

da Silva, DQ (Autor) Outra; Filipe Neves Santos (Autor) FEUP; Armando Jorge Sousa (Autor) FEUP; Filipe, V (Autor) Outra; Boaventura Cunha, J (Autor) Outra

Revista

A Revista está pendente de validação pelos Serviços Administrativos.

Título: COMPUTATION

Vol. 9

Página Final: 127

ISSN: 2079-3197

Editora: MDPI

Indexação

ISI Web of Knowledge - 12 Citações

Scopus - 15 Citações

Outras Informações

ID Authenticus: P-00V-QXJ

DOI: 10.3390/computation9120127

Abstract (EN): Robotics navigation and perception for forest management are challenging due to the existence of many obstacles to detect and avoid and the sharp illumination changes. Advanced perception systems are needed because they can enable the development of robotic and machinery solutions to accomplish a smarter, more precise, and sustainable forestry. This article presents a state-of-the-art review about unimodal and multimodal perception in forests, detailing the current developed work about perception using a single type of sensors (unimodal) and by combining data from different kinds of sensors (multimodal). This work also makes a comparison between existing perception datasets in the literature and presents a new multimodal dataset, composed by images and laser scanning data, as a contribution for this research field. Lastly, a critical analysis of the works collected is conducted by identifying strengths and research trends in this domain.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 23