To meet the demands of a rising population greenhouses must face the challenge of producing more in a more efficient and sustainable way. Innovative mobile robotic solutions with flexible navigation and manipulation strategies can help monitor the field in real-time. Guided by Integrated Pest Management strategies, robots can perform early pest detection and selective treatment tasks autonomously. However, combining the different robotic skills is an error prone work that requires experience in many robotic fields, usually deriving on ad-hoc solutions that are not reusable in other contexts. This work presents Robotframework, a generic ROS-based architecture which can easily integrate different navigation, manipulation, perception, and high-decision modules leading to a faster and simplified development of new robotic applications. The architecture includes generic real-time data collection tools, diagnosis and error handling modules, and user-friendly interfaces. To demonstrate the benefits of combining and easily integrating different robotic skills using the architecture, two flexible manipulation strategies have been developed to enhance the pest detection in its early state and to perform targeted spraying in simulated and field commercial greenhouses. Besides, an additional use-case has been included to demonstrate the applicability of the architecture in other industrial contexts.INDEX TERMS Precision agriculture, robotic control architecture, mobile manipulator, pest detection and treatment, greenhouse.
The use of autonomous robots for certain tasks within agriculture applications can bring many advantages. The H2020-funded GreenPatrol project has developed an autonomous system for pest detection and treatment within commercial greenhouses. In this system the robot will navigate autonomously and regularly inspect crops using an array of cameras and algorithms to detect and treat pests at an early stage in order to improve yield, reduce pesticide use and improve worker conditions. A key enabler for this application is the localization and navigation function of the robot platform. In order to operate independently and autonomously, the robot must know in real-time its precise location and direction of pointing, it must be able to plan a route through the greenhouse from its current location to where it needs to go, it must be able to control its movements to reach its required destination, and it must be able to identify and avoid obstacles that may obstruct its route. In order to achieve these goals the robot subsystems include an absolute localization function, to provide precise absolute position and heading in a global reference frame in real-time, a relative localization function, to provide more fidelity of the exact location and orientation of the robot with respect to its surroundings in the greenhouse, and a navigation function, to plan the route through the greenhouse and provide movement instructions to the robot platform. This paper describes the localization system of the GreenPatrol robot and presents results of testing for each of the functions. The tests include simulations as well as data collections and tests of the real-time system using the robot platform. The results show the high performance of the positioning capability and heading information for the individual systems.
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