The evolution of agriculture towards sustainability requires the implementation of new practices to limit herbicides and promote the emergence of systems adapted to social, economic and environmental constraints. To get rid of herbicides, weed management requires systemic strategies involving combined operations at various levels. While inter-row weeding already has alternative solutions, intra-row weeding management requires to better observe, decide and intervene locally in the parcels. Those 3 components (perception/decision/action) are key concepts of sensorimotor loops that are widely used in the Automation domain. Actually, automation control offers an inspiring point of view over weed management, it provides a framework and a set of extensively proven techniques. By designing and applying sensorimotor loops to Weed Management, ROSEAU provide a systemic approach involving multi-scale actions, from autonomous localized intra-row weeding to global robotized interventions design. The main contributions of ROSEAU concerns: - multi-scale weed detection and identification, - weed proliferation simulation and management, - robotic weeding intervention design and optimization, - robust robotic autonomy oriented toward agriculture contexts, - tool-based autonomous navigation, - adaptation, control and exploitation of intra-row mechanical and chemical weeding tools. These contributions are articulated in a coherent framework reinforcing the impact of each of them. With UMR AgroEcologie, IRSEEM, SITIA and Chambres Régionales d’Agricultures Pays de Loire et Bretagne, ROSEAU consortium gather world class references of both Agriculture and TIC domains, with previous challenges victories (IRSEEM at ANR Challenge Argos 2015, 2016), awarded works (UMR Agroécologie silver medal at SIMA 2011) and prolongation of previous successful collaborations between members. ROSEAU is reinforced by a Scientific and Technical Committee of experts in agricultural practices, usages, and humanities.