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Ambient Awareness for Autonomous Agricultural Vehicles
Project
Project code: 2810ERA093
Contract period: 01.04.2011
- 31.12.2012
Budget: 109,104 Euro
Purpose of research: Applied research
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 present project will focus on the development of sensors and sensor processing methods to provide an autonomous agricultural vehicle with such ambient awareness. The “obstacle detection” problem will be specifically addressed. The idea of this project is that of using different sensor modalities approaches to detect the various kinds of obstacles and to build an obstacle database that can be used for vehicle control.
The project investigates the potential of four sensor technologies: (stereo) vision, radar, ladar and thermography. Existing state-of-the-art sensors, some previously developed by the partners themselves, will be modified and interfaced in such a way that they can be demonstrated in an agricultural context. The German partner Fraunhofer IAIS contributes to the consortium by adapting its ladar sensor 3DLS and by developing the respective obstacle detection software.
The sensors will be mounted on an autonomous tractor and a data acquisition campaign will collect sensor data. These data will provide the basic dataset for the development of novel sensor processing and sensor fusion techniques aiming to detect and classify obstacles in an agricultural environment. 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. Furthermore, establishing a higher level of ambient awareness in the robot (or tractor) can increase the level of precision with which the vehicle can be controlled, which in turn is a pre-requisite for more efficient, environmentally friendly precision types of farming.
Section overview
Subjects
- Agricultural Engineering Plant Production
- Process engineering
Framework programme
Funding programme
Excutive institution
Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS)
