Abstract
Autonomous vehicles are being increasingly adopted in agriculture to improve productivity and efficiency. For an autonomous agricultural vehicle to operate safely, environment perception and interpretation capabilities are fundamental requirements. The Ambient Awareness for Autonomous Agricultural Vehicles (QUAD-AV) project explores a multisensory approach to provide an autonomous agricultural vehicle with such ambient awareness. The proposed methods and systems will aim at increasing the overall level of safety of an autonomous agricultural vehicle with respect to itself, to people and animals as well as to property. The obstacle detection problem is specifically addressed within the QUAD-AV project. The paper focuses on the presentation of the different selected technologies (vision/s tereovision, thermography,ladar, microwave radar) through the presentation of preliminary results.