Control and Perception Framework for Deep Sea Mining Exploration This paper presents the control and perception framework used in the ROBUST EU Horizon 2020 project, aimed at integrate different technologies for developing an underwater autonomous robotic system for exploring deepsea mining sites. The vehicle firstly collects data of the initial zone of interest and it selects a sub area which is the most probable to contain a manganese nodule field; then it carries out a low altitude survey. When a possible nodule is detected by the cameras, the vehicle lands on the seafloor, allowing the following fixed based manipulation which is designed to perform the nodule analysis. The work reports the implemented control and perception architecture and the preliminary pool experiments results.

Resilient Autonomous Exploration and Mapping of Underground Mines using Aerial Robots This paper presents a comprehensive solution to enable resilient autonomous exploration and mapping of underground mines using aerial robots. The described methods and systems address critical challenges related to autonomy, perception and localization in conditions of sensor degradation, exploratory path planning in geometrically complex, large and multibranching environments, alongside reliable robot operation in communicationsdenied settings. To facilitate resilient autonomy in such conditions, a set of novel contributions in multimodal sensor fusion, graphbased path planning, and robot design have been proposed and integrated in micro aerial vehicles which are not subject to the challenging terrain found in such subterranean settings. The capabilities and performance of the proposed solution is fieldverified through a set of reallife autonomous deployments in underground metal mines.