Projet MORE (Horizon 2020, appel à projets 2019)
Action : Doctoral Networks - Industrial Doctorates
Panel : Information Science and Engineering
Statut du projet : SIGNED

Ever-increasing demand for material and food, stricter emissions regulations, and continuous globalisation has put Europe’s construction, logistics, and agriculture sectors under immense pressure. Dramatic improvements in their productivity and efficiency are the only answer to these global challenges. Heavy-duty mobile (HDM) machinery are crucial workhorses in these sectors. Europe`s major HDM equipment companies (J. Deere, Liebherr, Bosch Rexroth, HIAB, Volvo CE) have joined forces with four highly specialised academic groups to deliver MORE, a timely project in response to these urgent needs. MORE will address these challenges by delivering innovative solutions driven by digitalisation and Artificial Intelligence (AI) in three areas: 1) Processes: world modelling by combining machine-earth interaction with vision, and optimising material flow in construction sites, 2) Machines: creating efficient power-train solutions for heavy-duty booms and 3) Control: object classification and world modelling to support long-term autonomy; obstacle avoidance in adverse conditions; innovative solutions on transfer-learning for earth moving and boom control to reduce operational and development costs, in different application areas. Europe’s HDM machine industry needs to invest heavily in digitalization, ‘green’ and innovative technologies, and address the serious labour shortage. There is thus a rapidly growing demand for experts in HDM machinery having the big picture of trends in AI, robotics, and energy systems as well as an understanding of the challenges and opportunities. MORE is an innovative European Industrial Doctorate (EID) research and training programme, the first of its kind, that will address this need and fill the gap in related research and training. Eight early stage researchers will be equipped with a set of research skills including robotics, machine learning, energy systems, as well as transferable skills such as entrepreneurship and career management.

Mots clés : heavy duty mobile machinery, non road mobile machines, field robotics, machine learning, robotisation, energy efficiency, construction, logistics, digitalization

Participants :
- Novatron oy (Finlande) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 327606.72 €
- Liebherr (Austria) (Autriche) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 219220.83 €
- Karlsruhe Institute of Technology (Allemagne) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 147459.9 €
- Örebro University (Suède) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 352478.7 €
- Hiab ab (Suède) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 211487.22 €
- Robert Bosch (Germany) (Allemagne) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 379182.6 €
- Tampere University (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 374407.68 €
- John Deere (United States) (Finlande) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 163803.36 €