The effective monitoring and maintenance of power lines are becoming increasingly important due to a global growing dependence on electricity. The costs and risks associated with the traditional foot patrol and helicopter-based inspections can be reduced by using UAVs with the appropriate sensors. However, this implies developing algorithms to make the power line inspection process reliable and autonomous. In order to overcome the limitations of visual methods in the presence of poor light and noisy backgrounds, we propose to address the problem of power line detection and modeling based on LiDAR. The PL ${}^2$ DM, Power Line LiDAR-based Detection and Modeling, is a novel approach to detect power lines. Its basis is a scan-by-scan adaptive neighbor minimalist comparison for all the points in a point cloud. The power line final model is obtained by matching and grouping several line segments, using their collinearity properties. Horizontally, the power lines are modeled as a straight line, and vertically as a catenary curve. Using a real dataset, the algorithm showed promising results both in terms of outputs and processing time, adding real-time object-based perception capabilities for other layers of processing.

The use of unmanned marine robotic vehicles in bathymetric surveys is discussed. This paper presents recent results in autonomous bathymetric missions with the ROAZ autonomous surface vehicle. In particular, robotic surface vehicles such as ROAZ provide an efficient tool in risk assessment for shallow water environments and water land interface zones as the near surf zone in marine coast. ROAZ is an ocean capable catamaran for distinct oceanographic missions, and with the goal to fill the gap were other hydrographic surveys vehicles/systems are not compiled to operate, like very shallow water rivers and marine coastline surf zones. Therefore, the use of robotic systems for risk assessment is validated through several missions performed either in river scenario (in a very shallow water conditions) and in marine coastlines.

The ocean and the Blue Economy are increasingly top priorities worldwide. The immense ocean territory in the planet and its huge associated economical potential is envisioned to increase the activity at the ocean in the forthcoming years. The support of these activities, and the convergence to the Internet of Things paradigm, will demand wireless and mobile communications to connect humans and systems at remote ocean areas. Currently, there is no communications solution enabling cost-effective broadband Internet access at remote ocean areas in alternative to expensive, narrowband satellite communications. This paper presents the maritime communications solution being developed in the BLUECOM+ project. The BLUE-COM+ solution enables cost-effective broadband Internet access at remote ocean areas using standard wireless access technologies, e.g., GPRS/UMTS/LTE and Wi-Fi. Its novelty lies on the joint use of TV white spaces for long range radio communications, tethered balloons for lifting communications nodes high above the ocean surface, multi-hop relaying techniques for radio range extension, and standard access networks at the ocean. Simulation results prove it is possible to reach radio ranges beyond 100 km and bitrates in excess of 3 Mbit/s using a two-hop land-sea communications chain.

The design and development of the swordfish autonomous surface vehicle (ASV) system is discussed. Swordfish is an ocean capable 4.5 m long catamaran designed for network centric operations (with ocean and air going vehicles and human operators). In the basic configuration, Swordfish is both a survey vehicle and a communications node with gateways for broadband, Wi-Fi and GSM transports and underwater acoustic modems. In another configuration, Swordfish mounts a docking station for the autonomous underwater vehicle Isurus from Porto University. Swordfish has an advanced control architecture for multi-vehicle operations with mixed initiative interactions (human operators are allowed to interact with the control loops).

This work presents the integration of obstacle detection and analysis capabilities in a coherent and advanced C&C framework allowing mixed-mode control in unmanned surface systems. The collision avoidance work has been successfully integrated in an operational autonomous surface vehicle and demonstrated in real operational conditions. We present the collision avoidance system, the ROAZ autonomous surface vehicle and the results obtained at sea tests. Limitations of current COTS radar systems are also discussed and further research directions are proposed towards the development and integration of advanced collision avoidance systems taking in account the different requirements in unmanned surface vehicles.

This paper presents results of the INESC TEC participation in the maritime environment (both at surface and underwater) integrated in the ICARUS team in the euRathlon 2015 robotics search and rescue competition. These relate to the marine robots from INESC TEC, surface (ROAZ USV) and underwater (MARES AUV) autonomous vehicles participation in multiple tasks such as situation assessment, underwater mapping, leak detection or victim localization. This participation was integrated in the ICARUS Team resulting of the EU funded project aimed to develop robotic tools for large scale disasters. The coordinated search and rescue missions were performed with an initial surface survey providing data for AUV mission planning and execution. A situation assessment bathymetry map, sidescan sonar imaging and location of structures, underwater leaks and victims were achieved, with the global ICARUS team (involving sea, air and land coordinated robots) participating in the final grand Challenge and achieving the second place.