Robot ensembles for grafting herbaceous crops. (June 2016)

• Record Type: Journal Article
• Authors: Comba, Lorenzo; Gay, Paolo; Ricauda Aimonino, Davide
• Is Part Of: Biosystems engineering. Volume 146(2016:Jun.)
• Page Start: 227
• Page End: 239
• Publication Date: 2016-06
• Subjects: Robotics -- Vegetable grafting -- Automation; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2016.02.012
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Legislation and regulation is increasingly limiting the use of pesticides or chemical fumigants to counteract soil-borne pathogens. Therefore the use of disease resistant grafted plants is increasing. However, the grafting of herbaceous crops is a labour-intensive technique, with consequent costs. These aspects have encouraged the development of automated machines able to increase productivity and rooting success rate while reducing costs. This paper presents an innovative solution for automatic grafting of vegetable crops, suitable for small to medium sized farms. The concept is to use a group of cooperative robots, adaptable in number, to meet workload specifications. The machine consists of one or more grafting units, able to cut and join scions and rootstocks, and a supplying and sorting system based on an ensemble of single-axis, identical and independent robotic modules, displacing on a unique rail, which coordinates the movement and the selection of scions, rootstocks and grafted plants. Overall productivity is given by the number of grafting units, the number of robotic modules implemented in the supply system, and the efficiency of the control and task allocation strategy. Together with the description of the innovative aspects of the machine mechanics, designed to face intrinsic variability in vegetable objects, the objective of this paper was to present the ensemble synthesis of the control policies, based on heuristic scheduling priorities, to allocate and coordinate the team of robots to a set of spatially distributed tasks. Graphical abstract: Highlights: Design of a modular multi-robot grafting machine. Artificial vision to face to intrinsic variability of vegetal objects. Discrete-event system modelling and heuristic rule-based optimisation.