Robotics for Agro-Forestry Applications


ORGANIZED BY

Renato Vidoni

Free University of Bozen-Bolzano, Italy


Karl Von Ellenrieder

Free University of Bozen-Bolzano, Italy


Fabrizio Mazzetto

Free University of Bozen-Bolzano, Italy


Dario Mengoli

University of Bologna, Italy


ABSTRACT

Robotic systems are being increasingly utilized as fundamental tools for data-gathering, in particular for agriculture and forestry, allowing new perspectives and a greater understanding of plant health and processes. Significant advancements in robotic systems over the past decades have opened new research directions, and enabled new developments, in the monitoring of plant health, precision agriculture, crop management, etc. Recently, interest in the real-time control of agro-forestry processes using robots has been growing, which has brought new requirements for precision in the management of such processes. This poses new challenges in the field of integrated automation, as the need for precision in autonomously performed operations must take into account aspects of both environmental variability, and the interaction between robotic systems and living production systems.
The development of versatile robotic platforms, or intelligent implements, can enable innovation of the small/medium agricultural companies that are especially important in the European farming systems.
This special session aims to create a space for the discussion of advanced robot-based solutions for monitoring applications and autonomous agro-forestry process control, as well as any related issues, such as calibration, robot control, sampling, robot-sensor integration, real time data interpretation/perception, decision-making, planning and consequent action.


TOPICS

Topics include, but are not limited to:

  • Robots for soil/crop monitoring, yield estimation and phenotyping;
  • Robots for prediction, decision making and planning;
  • Robotized approaches for continuous day/night operations;
  • Robots for sample collection and analysis;
  • Robot-sensors integration and calibration;
  • Monitoring and mapping with swarm robots;
  • Robot localization and autonomous navigation;
  • Special aspects and solutions for real time data interpretation/perception;
  • Smart Implements
  • Data transfer and processing on board robots;
  • Measurement precision needs for real time agro-forestry in-field robotized actions;
  • Human-machine interaction and machine-production system interaction for agro-forestry applications;
  • Innovations and technology in orchards and open-field crops.


ABOUT THE ORGANIZERS

Prof. Renato Vidoni received his M.Sc. in Electronic Engineering - major in Industrial Automation - from the University of Udine, Italy, in 2005. From the same university he obtained his Ph.D. degree in Industrial and Information Engineering in 2009. Since 2015 he has been working as Professor in Applied Mechanics, Mechatronics and Robotics at the Free University of Bozen-Bolzano (Italy). He is responsible of the new FiRST - Field Robotics laboratory (co-responsible prof Von Ellenrieder) at the NOI-TechPark of Bolzano. His research activity deals with topics of the Applied Mechanics sector both in traditional fields, i.e. multi-body modelling and trajectory planning, as well in new and emerging domains, i.e. field and agro-forestry applications of robotics and mechatronics, bio-mimetics.


Karl von Ellenrieder received the B.S. degree in aeronautics and astronautics from the Massachusetts Institute of Technology, Cambridge, MA, USA, in 1990 and the M.S. and Ph.D. degrees in aeronautics and astronautics from Stanford University, Stanford, CA, USA, in 1992 and 1998, respectively. From 1998-2002 he was a Research Fellow at Monash University in Melbourne, Australia and from 2003-2016 he was a Professor of Ocean Engineering at Florida Atlantic University, Boca Raton, FL, USA. Since 2016 he has been a Professor of Automation with the Faculty of Science and Technology, at the Libera Università di Bolzano, BZ, Italy. Professor von Ellenrieder’s research interests are centered on the development and automatic control of field robots.


Prof. Fabrizio Mazzetto, MSc in Agricultural Sciences (1983) and PhD in Agricultural Engineering (1990), both at University of Milan (Italy). Now Full Professor of Farm Machinery and Mechanization at the Free University of Bolzano. His main research topics are related to: a) development of new prototypes for mountain contexts; b) ICT application to supply information management tasks of farm and forestry processes; c) development of precision agriculture and forestry techniques, d) rural energy applications. Past FAO-UNDP energy consultant and coordinator several national/international research projects. Now, member of the “Accademia dei Georgofili” of Florence and President of the 7th Section of the Italian Society of Agricultural Engineering, for ICT applications in agriculture. He is responsible of the new AgriForestry Innovation Lab at the NOI-TechPark of Bolzano dealing also with new approaches in the certification issues of farm machinery.


Dario Mengoli is currently a PhD student in Automation and Operational Research at the Department of Electrical, Electronic and Information Engineering of the University of Bologna.
He received his master’s degree in computer science engineering from the same university in 2008. He then worked as a freelance consultant until 2019, while he was involved in several research activities on robotics and agricultural task automation. Dario’s main research topics include autonomous navigation, prototypes development, machine learning and automation, with particular focus on mobile ground and aerial robotic platforms and software development. He is currently deeply involved in an innovative orchard project, supported by MIUR funding to departments of excellence, with the aim of creating a reliable sprayer and muncher robot to be integrated into a new concept of cultivar for apple production. Dario has also worked with emerging machine learning techniques, on the application of artificial intelligence and image classification algorithms to solve agricultural needs.


With the Patronage of


mipaaf
unitrento
unisannio
Aiia
gmee
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Sponsored By


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