All-terrain estimation for mobile robots in precision agriculture

Abstract

This paper presents a novel multi-sensor terrain classification approach using visual and proprioceptive data, to support autonomous operations by an agricultural vehicle. The novelty of the proposed method lies in the possibility to identify the terrain type relying not only on classical appearance-based features, such as color and geometric properties, but also on contact-based features, which measure the dynamic effects related to the vehicle-terrain interaction and directly affect vehicle's mobility. Using methods from the machine learning community, it is shown that it is not only possible to classify various kinds of terrain using either sensor modality, but that these modalities are complementary to each other, and can be therefore combined to improve classification results.


Autore Pugliese

Tutti gli autori

  • A. Milella; G. Reina; R. Galati

Titolo volume/Rivista

Non Disponibile


Anno di pubblicazione

2018

ISSN

Non Disponibile

ISBN

Non Disponibile


Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile


Numero di citazioni Scopus

Non Disponibile

Ultimo Aggiornamento Citazioni

Non Disponibile


Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile