Abstract

In the last few years, robotic technology has been increasingly employed in agriculture to develop intelligent vehicles that can improve productivity and competitiveness. Accurate and robust environmental perception is a critical requirement to address unsolved issues including safe interaction with field workers and animals, obstacle detection in controlled traffic applications, crop row guidance, surveying for variable rate applications, and situation awareness, in general, towards increased process automation. Given the variety of conditions that may be encountered in the field, no single sensor exists that can guarantee reliable results in every scenario. The development of a multi-sensory perception system to increase the ambient awareness of an agricultural vehicle operating in crop fields is the objective of the Ambient Awareness for Autonomous Agricultural Vehicles (QUAD-AV) project. Different onboard sensor technologies, namely stereovision, LIDAR, radar, and thermography, are considered. Novel methods for their combination are proposed to automatically detect obstacles and discern traversable from non-traversable areas. Experimental results, obtained in agricultural contexts, are presented showing the effectiveness of the proposed methods.

Autore Pugliese

• Reina Giulio

Tutti gli autori

• Reina G. , Milella A. , Rouveure R. , Nielsen M. , Worst R. , Blas M.R.

Titolo volume/Rivista

BIOSYSTEMS ENGINEERING

Anno di pubblicazione

2016

ISSN

1537-5110

ISBN

Non Disponibile

Numero di citazioni Wos

10

Ultimo Aggiornamento Citazioni

23/04/2018

Numero di citazioni Scopus

15

Ultimo Aggiornamento Citazioni

22/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile