Descripción del proyecto
Nuevas redes para llevar más robots al campo
La minería, la agricultura, la silvicultura y la construcción son las aplicaciones principales de los robots de campo, los cuales pueden funcionar en tierra, agua, aire o en el espacio. En las instalaciones agropecuarias hay robots construidos para realizar tareas especializadas como la recolección de fresas y el ordeño de vacas. En las minas, los robots se utilizan para registrar galerías inundadas y analizar concentraciones de mineral. El proyecto financiado con fondos europeos DEEPFIELD se propone mejorar las capacidades de aprendizaje profundo de los robots desplegados en exteriores. Ayudará al Instituto de Ingeniería de Sistemas e Informática, Tecnología y Ciencia (INESC TEC) de Portugal a convertirse en un centro de excelencia en el ámbito de la robótica de campo mediante la creación de relaciones con otros centros de investigación punteros de toda Europa.
Objetivo
Robots are active agents that need to interact with the physical world, to do so, robots are equipped with different sensors, whose data is used to build models that ultimately will allow robots to plan actions and make decisions.
Currently, there is strong focus in developing deep learning strategies “data driven” to help solve this perception problem, even though these approaches work well in dataset and benchmark scenarios. There are still strong limitations in the use of this techniques in real world robot activities, specially due to the strong dynamics in robots operational environment, that is pushing the development of new tools and methods to make these approaches feasible in the real world.
INESC TEC is strongly committed to become a centre of excellence with focus on field robotics, in particular, in the aerial and underwater robotics domain. In the last years, the centre for Robotics and Autonomous systems, of INESC TEC has advance its scientific knowledge in sensing and perception methods for robots navigation and localization in harsh operational environments. The key objective of INESC TEC is to become one of the European references in field robotics, and help to bring robot technology to solve real life problems where human intervention is still limited or non-existent.
This proposal aims at creating solid knowledge and productive links in the global field of deep learning in field robotics between INESC TEC and established leading research European institutions, capable of enhancing the scientific and technological capacity of INESC TEC and linked institutions (as well as the capacity of partnering institutions involved in the twinning action), helping raising its staff’s research profile and its recognition as an European research centre of excellence in field robotics. In particular, it takes INESC TEC and places it as the pivot of a network of excellence, involving four international leaders in deep learning technology and fied robotics.
Ámbito científico
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringrobotics
Palabras clave
Programa(s)
- H2020-EU.4.b. - Twinning of research institutions Main Programme
Tema(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-WIDESPREAD-2018-03
Régimen de financiación
CSA - Coordination and support actionCoordinador
4200 465 Porto
Portugal