Sensors 2010, 10(12), 11226-11247; doi:10.3390/s101211226

Sensor Architecture and Task Classification for Agricultural Vehicles and Environments

Received: 20 October 2010; in revised form: 26 November 2010 / Accepted: 1 December 2010 / Published: 8 December 2010
(This article belongs to the Special Issue Sensors in Agriculture and Forestry)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The long time wish of endowing agricultural vehicles with an increasing degree of autonomy is becoming a reality thanks to two crucial facts: the broad diffusion of global positioning satellite systems and the inexorable progress of computers and electronics. Agricultural vehicles are currently the only self-propelled ground machines commonly integrating commercial automatic navigation systems. Farm equipment manufacturers and satellite-based navigation system providers, in a joint effort, have pushed this technology to unprecedented heights; yet there are many unresolved issues and an unlimited potential still to uncover. The complexity inherent to intelligent vehicles is rooted in the selection and coordination of the optimum sensors, the computer reasoning techniques to process the acquired data, and the resulting control strategies for automatic actuators. The advantageous design of the network of onboard sensors is necessary for the future deployment of advanced agricultural vehicles. This article analyzes a variety of typical environments and situations encountered in agricultural fields, and proposes a sensor architecture especially adapted to cope with them. The strategy proposed groups sensors into four specific subsystems: global localization, feedback control and vehicle pose, non-visual monitoring, and local perception. The designed architecture responds to vital vehicle tasks classified within three layers devoted to safety, operative information, and automatic actuation. The success of this architecture, implemented and tested in various agricultural vehicles over the last decade, rests on its capacity to integrate redundancy and incorporate new technologies in a practical way.
Keywords: sensor architecture; intelligent vehicles; off-road autonomous vehicles; robotics; precision agriculture
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MDPI and ACS Style

Rovira-Más, F. Sensor Architecture and Task Classification for Agricultural Vehicles and Environments. Sensors 2010, 10, 11226-11247.

AMA Style

Rovira-Más F. Sensor Architecture and Task Classification for Agricultural Vehicles and Environments. Sensors. 2010; 10(12):11226-11247.

Chicago/Turabian Style

Rovira-Más, Francisco. 2010. "Sensor Architecture and Task Classification for Agricultural Vehicles and Environments." Sensors 10, no. 12: 11226-11247.

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