The Workshop on Perception, Planning and Mobility in Forestry Robotics (WPPMFR 2020) will address recent advances and future directions of robotics in forestry and related fields, setting the floor for fruitful discussions promoted by attendees.
"The IEEE RAS Technical Committee on Agricultural Robotics and Automation (TC-AgRA) is pleased to support the 'Workshop on Perception, Planning and Mobility in Forestry Robotics 2020'. This topic is relevant to our Technical Committee, as forestry is considered an agricultural product in some contexts, and contains frequently-encountered problems in the agricultural domain such as perception, mobility, and manipulation in challenging and unstructured environments."
In this workshop, we will present an overview of this exciting area of application with such an important economical and societal impact, and address and discuss the challenges faced in research on forestry robotics, in particular in the key issues of sensing/perception, mobility, planning, autonomous decision-making, and safe co-operation with human operators. Participants will have the opportunity to listen to keynote presentations delivered by senior researchers in the field, present their own work, and participate in a round-table session and contribute with fresh insights to address the challenges still faced by research in this field.
The workshop is organized to ensure high quality discussion content, while also reflecting the current state of the art in the Forestry Robotics field, showcasing recent achievements by top international research groups and robotic companies, including access to detailed footage of forestry experiments, and live demos on real world datasets. These datasets will be shared among all participants, and whenever possible disseminated on the workshop webpage as open-source material. A scientific workshop focused on forestry robotics is unprecedented and allows for the approximation of the scientific community to the general public, promoting a unique discussion opportunity.
Forestry – the practice of creating, managing, using, conserving, and repairing forests, woodlands, and associated resources – has a substantial importance in the economy of many industrial countries, which is often overlooked. It provides direct and indirect economic gains, but also societal and environmental benefits. The increasing lack of manpower due to low salaries, harshness of its operations, and progressive abandonment of rural areas and of practices such as pastoralism, has driven forestry to become increasingly mechanized to increase productivity.
The exploration of biological natural resources is under pressure from population growth, climate change, political pressures affecting migration, population drift from rural to urban regions and the demographics of an ageing global population. The importance of forestry in this context and the effect that these pressures have had in its related industries have not always been fully acknowledged, at least up until the latest tragic outbreaks of wildfires in the last few years around the planet.
One way of solving these problems is to introduce and develop (semi-)autonomous vehicles and robots to potentially reduce running costs and remove the many health hazards involved in forestry, while still keeping the human “in the loop”. This approach is part of what is known as precision forestry. However, despite many advances in key areas, the development of autonomous robotic solutions for precision forestry is still at a very early stage. Until recently, state-of-the-art approaches depended on remote teleoperation, focused on slow progressing single robot solutions, and were either targeted for forest fire monitoring or limited to controlled laboratory settings. This stems from the considerable challenges imposed by rough terrain traversability, autonomous outdoor navigation and locomotion systems, limited perception capabilities, and reasoning and planning under a high-level of uncertainty. These harsh conditions have made it impossible, so far, to provide an effective and realistic way to assist human teams in forestry operations using robots.
|Joao Filipe Ferreira, Nottingham Trent University, Computational Neuroscience and Cognitive Robotics Group, Nottingham, UK and also the Institute of Systems and Robotics, University of Coimbra, Portugal|
|David Portugal, University of Coimbra, Institute of Systems and Robotics, Coimbra, Portugal|
|Maria Eduarda Andrada, University of Coimbra, Institute of Systems and Robotics, Coimbra, Portugal|
|Anthony Fragoso, California Institute of Technology, Aerospace Robotics and Control, Pasadena, USA|
|Fernando Auat, Federico Santa Maria Technical University, Department of Electronic Engineering, Valparaiso, Chile|
|Francisco Yandun, The Robotics Institute, Carnegie Mellon University, Pittsburgh, United States|
|Ola Ringdahl, Umea University, Department of Computing Science, Umea, Sweden|
|Stefano Mintchev, Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland|
|Nicholas Coops, Department of Forest Resources Management, University of British Columbia, Vancouver, Canada|
|Nicola Basilico, Department of Computer Science, University of Milan, Milan, Italy|
|Eduardo Montijano, Department of Computer Engineering and Systems, University of Zaragoza, Zaragoza, Spain|
|Vladimir Kubelka, Laval University, Northern Robotics Laboratory, Quebec, Canada|
|Pedro Machado, Nottingham Trent University, Computational Neuroscience and Cognitive Robotics Group, Nottingham, UK|
|Martin McGinnity, Nottingham Trent University, Computational Neuroscience and Cognitive Robotics Group, Nottingham, UK and also the School of Computing, Eng & Intel. Sys, Ulster University, Coleraine, Northern Ireland|
|Rui Paulo Rocha, University of Coimbra, Institute of Systems and Robotics, Coimbra, Portugal|
|Jorge Lobo, University of Coimbra, Institute of Systems and Robotics, Coimbra, Portugal|