Search and rescue missions are complex operations. A disaster scenario is generally unstructured, time-varying and unpredictable. This poses several challenges for the successful deployment of unmanned technology. The variety of operational scenarios and tasks lead to the need for multiple robots of different types, domains and sizes. A priori planning of the optimal set of assets to be deployed and the definition of their mission objectives are generally not feasible as information only becomes available during mission. The ICARUS project responds to this challenge by developing a heterogeneous team composed by different and complementary robots, dynamically cooperating as an interoperable team. This chapter describes our approach to multi-robot interoperability, understood as the ability of multiple robots to operate together, in synergy, enabling multiple teams to share data, intelligence and resources, which is the ultimate objective of ICARUS project. It also includes the analysis of the relevant standardization initiatives in multi-robot multi-domain systems, our implementation of an interoperability framework and several examples of multi-robot cooperation of the ICARUS robots in realistic search and rescue missions.

In the robotic domain, it is common to deduce and use models that allow translating mathematically the element behavior. In some cases, these would serve as base to determine and develop a controller, for example. Beyond this, the simulation and experiments are reasons that leave to the development of models, becoming evaluation tools of the system behavior, especially when there are constraints of implementation or in experiments. However, the modeling is an approach to the reality, since it is difficult to translate the behavior of an element in a strict way and the disturbances to witch it is subject to. In this work, we address the modeling questions of an autonomous underwater vehicle.This paper describes the deducing of a dynamic model with six degrees of freedom of an underwater vehicle, considering all of its physical characteristics. This is achieved by the determination of all forces that actuates on the body during its motions and by the determination of the rigid body dynamic. The modeling method is presented as well as the coefficients determination. Finally, a comparison with experimental results is carried out.I.

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The use of the odometry and SLAM visual methods in autonomous vehicles has been growing. Optical sensors provide valuable information from the scenario that enhance the navigation of autonomous vehicles. Although several visual techniques are already available in the literature, their performance could be significantly affected by the scene captured by the optical sensor. In this context, this paper presents a comparative analysis of three monocular visual odometry methods and three stereo SLAM techniques. The advantages, particularities and performance of each technique are discussed, to provide information that is relevant for the development of new research and novel robotic applications.