Project description
New network to bring more robots in the field
Mining, agriculture, forestry and construction are the main applications of hardworking field robots, which may operate on the ground, underwater, in air, or in space. On farms, there are robots built for specialised tasks such as strawberry picking and milking cows. At mines, robots are used to map flooded passages and analyse mineral concentrations. The EU-funded DEEPFIELD project aims to boost deep learning in field robotics. It will assist Portugal’s Institute for Systems and Computer Engineering, Technology and Science (INESC TEC)(opens in new window) to become a centre of excellence in field robotics via links with top-notch European research institutions.
Objective
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.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- 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
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Programme(s)
- H2020-EU.4.b. - Twinning of research institutions Main Programme
Topic(s)
Call for proposal
(opens in new window) H2020-WIDESPREAD-2018-2020
See other projects for this callSub call
H2020-WIDESPREAD-2018-03
Funding Scheme
CSA - Coordination and support actionCoordinator
4200 465 Porto
Portugal