Abstract
In this work an acoustic tag detector was developed for the integration in a mobile robotic fish tracking architecture. The present paper presents both the developed system and preliminary results with particular emphasis of the developed solution with the tag manufacturer receiver. The work has been developed in the context of the MYTAG Portuguese RD project, addressing the study and characterisation of the European flounder migrations in the northern estuarine environments of Portugal. The detector is to be integrated in a tracking system using autonomous surface vehicles and fixed buoys. The main objective is to detect tags inserted surgically in flounders for the MYTAG project, while simultaneously identifying them. A detector solution is presented allowing for the detection and identification of V7 VEMCO tags and preliminary comparative results with the commercially available manufacturer receivers are also presented and discussed.

Abstract
This paper describes the UX-1 underwater mine exploration robotic system under development in the context of the UNEXMIN project. UNEXMIN is an international innovation action funded under the EU H2020 program, aiming to develop new technologies and services allowing the exploration of flooded underground mines. The system is comprised by the UX-1 robot prototype, launch and recovery system, command and control subsystem and a data management and post-processing computational infrastructure. The UX-1 robot is a small spherical robot equipped with a multibeam sonar, five digital cameras and rotating laser line structured light systems. It is capable of obtaining an accurate point cloud of the surrounding environment along with high resolution imagery. A set of mineralogy, water parameters and geophysical sensors was also developed in order to obtain a more comprehensive mine model. These comprise a multi-spectral camera, electro-conductivity, pH, magnetic field sensors, a subbottom sonar, total natural gamma-ray detector, UV-light for fluorescent observation and a water sampling unit. The design of the system is presented along with the robot design. Some preliminary results are also presented and discussed

Abstract
This paper presents the perception system designed for the underwater mine exploration UNEXMIN robot. This autonomous underwater vehicle was designed in the context of the European 112020 ENEXIVIIN project to explore flooded underground mines The presented work addresses the sensor choice and placement options, the characterization of the system with results obtained in test tank and on field missions in mines. The perception software and computational architecture is also discussed with details on its distributed features. This perception system is comprised of one multibeam imaging/profiling sonar, one mechanically scanning sonar, digital cameras and a set of custom developed laser based structured light systems. The presented results from the Kaatiala mine (Finland) field trials and the Idrija mine tests (Slovenia) are discussed and allow for the performance analysis of the system.

Abstract
3D path planning with unmanned aerial vehicles in search and rescue scenarios is an important research area, due to the ability to explore damage areas that could be inaccessible for vehicles like ground robots. This paper presents two innovative real-time path planning algorithms based on PRM (Probabilistic Road Map) able to be implemented in UAV’s denoted by Grid Path Planning Roadmap Planning (GPRM) and the Particle Probabilistic Roadmap (PPRM). With the requirement of being implemented in a real search and rescue scenario like the EuRathlon competition, the GPRM method will produce a roadmap building step with obstacles inside a predefined grid while PPRM will follow a different approach by introducing an associated probability to each computed path in order to support the next sampling step path planning iteration. Both methods were evaluated and compared with the well known 3D path planning PRM in a search and rescue earthquake simulation environment developed in MORSE (Modular Open Robots Simulation Engine). © 2018 by World Scientific Publishing Co. Pte. Ltd.

Abstract
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. © Springer International Publishing AG 2018.

Abstract
This paper presents the modeling and simulation of a spherical autonomous underwater vehicle. The robot was developed under the European Union H2020 innovation action UNEXMIN for the exploration of underground flooded mines, and is a small spherical robot with thrusters and an internal pendulum for pitch control. A model of the vehicle is presented, initially without the pendulum, then an extended formulation is derived accounting for a multibody dynamic description of the system. Experimental identification results for the determination of drag parameters are presented as well. A Modelica based simulator is developed for dynamic simulation of the vehicle, and is integrated with the Matlab/Simulink environment. The simulator is then validated based on preliminary experimental results.