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Inventi Impact - Machine Vision

Articles

  • Inventi:emv/50/14
    NEW TRENDS IN ROBOTICS FOR AGRICULTURE: INTEGRATION AND ASSESSMENT OF A REAL FLEET OF ROBOTS
    Luis Emmi, Mariano Gonzalez-de-Soto, Gonzalo Pajares, Pablo Gonzalez-de-Santos

    Computer-based sensors and actuators such as global positioning systems, machine vision, and laser-based sensors have progressively been incorporated into mobile robots with the aim of configuring autonomous systems capable of shifting operator activities in agricultural tasks. However, the incorporation of many electronic systems into a robot impairs its reliability and increases its cost. Hardware minimization, as well as software minimization and ease of integration, is essential to obtain feasible robotic systems. A step forward in the application of automatic equipment in agriculture is the use of fleets of robots, in which a number of specialized robots collaborate to accomplish one or several agricultural tasks. This paper strives to develop a system architecture for both individual robots and robots working in fleets to improve reliability, decrease complexity and costs, and permit the integration of software from different developers. Several solutions are studied, from a fully distributed to a whole integrated architecture in which a central computer runs all processes. This work also studies diverse topologies for controlling fleets of robots and advances other prospective topologies. The architecture presented in this paper is being successfully applied in the RHEA fleet, which comprises three ground mobile units based on a commercial tractor chassis.

    How to Cite this Article
    CC Compliant Citation: Luis Emmi, Mariano Gonzalez-de-Soto, Gonzalo Pajares, and Pablo Gonzalez-de-Santos, “New Trends in Robotics for Agriculture: Integration and Assessment of a Real Fleet of Robots,” The Scientific World Journal, vol. 2014, Article ID 404059, 21 pages, 2014. doi:10.1155/2014/404059. Copyright © 2014 Luis Emmi et al. This is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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