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One of the biggest challenges in the field of maritime safety is the integration of all the systems related to the evacuation and emergency response under one Decision Support Tool that could broadly cover all the emergency cases and assist in the co-ordination of the evacuation process. Besides, for a decision support tool to be useful we need to be able to calculate the Available time to Evacuate based on real-time data, such as the passenger distribution on board and of course based on the various sensor data that will monitor the damage and its propagation. For all the above, the risk modelling tool developed in SafePASS H2020 project is able to estimate the potential fatalities both in the design phase and in real-time, assessing the evacuation and abandonment risk dynamically, based on real-time data related to the passenger distribution, route, semantics, LSA availability, procedural changes, and damage case (fire or flooding) propagation., This report constitutes a whitepaper written on behalf of the SafePASS project, describing the Risk modelling tool developed.

The damaged stability assessment for a passenger ship is a process requiring the simulation of multiple damage scenarios. Nevertheless, due to the stochastic nature of both the damage stability framework and the irregular waves environment, a considerable number of cases must be analysed. However, the probability density functions used to estimate the possible damage dimensions and locations along the ship necessitate a large amount of scenarios that are not critical for the ship survivability, especially for large passenger ship. To restrict the amount of damage scenarios, it is common practice to apply empirical rules, such as critical damages are only above two compartments, considering that damage stability regulations currently in force, ensure survivability levels beyond this extend of damages. However, a rigorous approach is lacking. To this end, in the present work, it is proposed to use more scientific-based methods to filter critical damages. The first method is based on preliminary static calculations, the second on the energy absorbed by the ship during an impact, the third on a purely dynamic approach. The methods are here critically compared on two sample passenger ships, showing their respective advantages and disadvantages.

International audience; Autonomous space vehicles such as orbital servicing satellites and planetary exploration rovers must be comprehensively aware of their environment in order to make appropriate decisions. Multi-sensor data fusion plays a vital role in providing these autonomous systems with sensory information of different types, from different locations, and at different times. The InFuse project, funded by the European Commission's Horizon 2020 Strategic Research Cluster in Space Robotics, provides the space community with an open-source Common Data Fusion Framework (CDFF) by which data may be fused in a modular fashion from multiple sensors. In this paper, we summarize the modular structure of this CDFF and show how it is used for the processing of sensor data to obtain data products for both planetary and orbital space robotic applications. Multiple sensor data from field testing that includes inertial measurements, stereo vision, and scanning laser range information is first used to produce robust multi-layered environmental maps for path planning. This information is registered and fused within the CDFF to produce comprehensive three-dimensional maps of the environment. To further explore the potential of the CDFF, we illustrate several applications of the CDFF that have been evaluated for orbital and planetary use cases of environmental reconstruction, mapping, navigation, and visual tracking. Algorithms for learning of maps, outlier detection, localization, and identification of objects are available within the CDFF and some early results from their use in space analogue scenarios are presented. These applications show how the CDFF can be used to provide a wide variety of data products for use by awareness and machine learning processes in space robots.

Data fusion algorithms make it possible to combine data from different sensors into symbolic representations such as environment maps, object models, and position estimates. The software community in space robotics lacks a comprehensive software framework to fuse and contextually store data from multiple sensors while also making it easier to develop, evaluate, and compare algorithms. The InFuse consortium, six partners in the industrial and academic space sector working under the supervision of a Program Support Activity (PSA) consisting of representatives from ESA, ASI, CDTI, CNES, DLR, UKSA, is developing such a framework, complete with a set of data fusion implementations based on state-of-the-art perception, localization and mapping algorithms, and performance metrics to evaluate them. This paper describes the architecture of this Common Data Fusion Framework and overviews the data fusion methods that it will provide for tasks such as localisation, mapping, environment reconstruction, object detection and tracking.

In robotics, when the demands for dexterity and versatility are high, traditional end effectors quickly show their limits and humanoid robot hands look like an appealing alternative. Unfortunately, although such hands can be built nowadays that are mechanically satisfactory, using them still remains problematic because their control is difficult. In this thesis, we have investigated three problems related to the control of humanoid robot hands: controlling the motion of the grasped object and the forces it is subject to, keeping hold of the object in case of external disturbances, and calculating the stiffness of the grasp, that is to say its elastic behavior. To manipulate the object, we propose a new control law, based on mathematical programming, that has the advantage of returning control torques which realize a trade-off between the different setpoints, possibly incompatible or unfeasible, and also respect the constraints due to physics and to the mechanics of the robot. To keep hold of the object when a disturbance happens, we propose a method to compute the tightening forces that make the grasp withstand the largest possible disturbance, in the direction where this largest possible disturbance is the smallest: a kind of critical disturbance for the grasp. Finally, we model the stiffness of the object as a function of the stiffness of the fingers, in the case when a relative rolling motion is possible between the fingers and the object. We prove that this stiffness is also function of the contact forces and the curvatures of the contacting surfaces.; En robotique, lorsque les exigences de dextérité et de polyvalence sont élevées, les effecteurs terminaux traditionnels montrent vite leurs limites et les mains robotisées humanoïdes semblent une alternative séduisante. Malheureusement, si l'on sait aujourd'hui fabriquer de telles mains satisfaisantes sur le plan mécanique, leur utilisation pose toujours problème car leur contrôle est difficile. Dans cette thèse, on s'est intéressé à trois problèmes relatifs au contrôle des mains robotisées humanoïdes : le contrôle du mouvement de l'objet saisi et des efforts qui lui sont appliqués, le maintien de l'objet en cas de perturbations extérieures, et la raideur de la prise, c'est-à-dire son comportement élastique. Pour la manipulation de l'objet, on propose une nouvelle loi de contrôle, basée sur un problème d'optimisation sous contraintes, qui a l'avantage de synthétiser des couples articulaires moteurs réalisant un compromis entre les différents objectifs de contrôle, possiblement conflictuels ou non atteignables, tout en respectant les limitations de la physique et du robot. Pour garder prise sur l'objet en cas de perturbation, on propose une méthode pour calculer les forces de serrage qui assurent la robustesse de la prise à la plus grande perturbation possible, dans la direction où cette plus grande perturbation possible est la plus petite : une sorte de perturbation critique pour la prise. Enfin, on donne une modélisation de la raideur de l'objet en fonction de celle des doigts, dans le cas où un mouvement relatif de roulement est possible entre les doigts et l'objet. On montre que cette raideur dépend aussi des forces de contact et des courbures des surfaces en contact.

In robotics, when the demands for dexterity and versatility are high, traditional end effectors quickly show their limits and humanoid robot hands look like an appealing alternative. Unfortunately, although such hands can be built nowadays that are mechanically satisfactory, using them still remains problematic because their control is difficult. In this thesis, we have investigated three problems related to the control of humanoid robot hands: controlling the motion of the grasped object and the forces it is subject to, keeping hold of the object in case of external disturbances, and calculating the stiffness of the grasp, that is to say its elastic behavior. To manipulate the object, we propose a new control law, based on mathematical programming, that has the advantage of returning control torques which realize a trade-off between the different setpoints, possibly incompatible or unfeasible, and also respect the constraints due to physics and to the mechanics of the robot. To keep hold of the object when a disturbance happens, we propose a method to compute the tightening forces that make the grasp withstand the largest possible disturbance, in the direction where this largest possible disturbance is the smallest: a kind of critical disturbance for the grasp. Finally, we model the stiffness of the object as a function of the stiffness of the fingers, in the case when a relative rolling motion is possible between the fingers and the object. We prove that this stiffness is also function of the contact forces and the curvatures of the contacting surfaces.; En robotique, lorsque les exigences de dextérité et de polyvalence sont élevées, les effecteurs terminaux traditionnels montrent vite leurs limites et les mains robotisées humanoïdes semblent une alternative séduisante. Malheureusement, si l'on sait aujourd'hui fabriquer de telles mains satisfaisantes sur le plan mécanique, leur utilisation pose toujours problème car leur contrôle est difficile. Dans cette thèse, on s'est intéressé à trois problèmes relatifs au contrôle des mains robotisées humanoïdes : le contrôle du mouvement de l'objet saisi et des efforts qui lui sont appliqués, le maintien de l'objet en cas de perturbations extérieures, et la raideur de la prise, c'est-à-dire son comportement élastique. Pour la manipulation de l'objet, on propose une nouvelle loi de contrôle, basée sur un problème d'optimisation sous contraintes, qui a l'avantage de synthétiser des couples articulaires moteurs réalisant un compromis entre les différents objectifs de contrôle, possiblement conflictuels ou non atteignables, tout en respectant les limitations de la physique et du robot. Pour garder prise sur l'objet en cas de perturbation, on propose une méthode pour calculer les forces de serrage qui assurent la robustesse de la prise à la plus grande perturbation possible, dans la direction où cette plus grande perturbation possible est la plus petite : une sorte de perturbation critique pour la prise. Enfin, on donne une modélisation de la raideur de l'objet en fonction de celle des doigts, dans le cas où un mouvement relatif de roulement est possible entre les doigts et l'objet. On montre que cette raideur dépend aussi des forces de contact et des courbures des surfaces en contact.