Abstract
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.
Highlights
The European agriculture land surface is decreasing due to deforestation and urbanization while population continues increasing
Robots need to implement plenty of different tasks such as localize themselves [7] and navigate inside greenhouses [8]-[9]; acquire quality pictures to identify pests and their locations [10]; or process the obtained results to generate efficient highlevel instructions to command the robot according to an Integrated Pest Management (IPM) system [11]
The first area is mostly represented by outdoor robots for weed control such as the Graph Weeds Net [14], the RHEA project centered on both agriculture and forestry [15], BoniRob project dedicated to multipurpose farming [16], or CROPS project focused on precision spraying in vineyards [17]
Summary
The European agriculture land surface is decreasing due to deforestation and urbanization while population continues increasing. Combination of different robotic skills can be dificult and usually derive to ad-hoc solutions, but this is necessary to perform early pest detection. This work presents Robotframework, a novel robotic architecture that integrates navigation, manipulation, and perception skills while following high level instructions from an IPM decision support system for early pest detection and treatment in greenhouses. The architecture includes additional features that makes it applicable for similar precision agriculture applications where robot navigation, manipulation and perception skills are required. This generic architecture can remarkably reduce the development time required to perform Robot Operating System (ROS) based field robotic experiments due to efficient reuse of common modules across projects and robot platforms. The conclusions obtained from the assessment are discussed and the future work is presented
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