Opis projektu
Nowa sieć pozwoli na zatrudnienie większej liczby robotów w terenie
Górnictwo, rolnictwo, leśnictwo oraz budownictwo to główne branże, które mogą odnieść korzyści z zatrudniania robotów do prac terenowych wykonywanych na ziemi, pod wodą, w powietrzu lub w przestrzeni kosmicznej. Nawet gospodarstwa rolne wykorzystują obecnie roboty zbudowane z myślą o konkretnych zadaniach, takich jak zbieranie truskawek i dojenie krów. W kopalniach roboty są wykorzystywane do mapowania zalanych korytarzy i analizy stężeń minerałów. W ramach finansowanego przez Unię Europejską projektu DEEPFIELD naukowcy zamierzają wykorzystać potencjał głębokiego uczenia maszynowego w robotyce terenowej. Ponadto projekt pozwoli portugalskiemu Instytutowi Systemów i Inżynierii Komputerowej, Technologii i Nauki (INESC TEC) stać się centrum doskonałości w dziedzinie robotyki terenowej dzięki współpracy z czołowymi europejskimi instytucjami badawczymi.
Cel
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.
Dziedzina nauki
- 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
Słowa kluczowe
Program(-y)
- H2020-EU.4.b. - Twinning of research institutions Main Programme
Temat(-y)
Zaproszenie do składania wniosków
Zobacz inne projekty w ramach tego zaproszeniaSzczegółowe działanie
H2020-WIDESPREAD-2018-03
System finansowania
CSA - Coordination and support actionKoordynator
4200 465 Porto
Portugalia