This paper proposes swarm intelligence based approach for the real time coordination of groups of UAVs (Unmanned Aerial Vehicles) in tasks where values that are sensed from the aerial platform can be used to qualify the individuals. In particular, as an example application, here we consider environmental monitoring UAV teams. Their function is to monitor an area and when some undesired environmental condition arises, coordinate themselves to find the source as fast as possible. The swarm based algorithm has been extensively tested using a 3D simulation platform and validated with real UAVs flying over an industrial area.

This paper is concerned with the design and implementation of a new concept of robot to clean the underwater sections of ship hulls without using any magnetic attachment. The use of this type of robots on a regular basis to preserve a clean hull, usually when ships are in port or anchored, will improve the efficiency of the ships and will permit a reduction in the use of chemicals that are harmful to the environment to prevent the growth of marine life on the hull. The main contribution of the robot described in this paper is that it is a completely novel design that through an appropriate morphology solves the problems that arise when moving along hulls, including changing planes, negotiating appendices, portholes, corners, and other elements. It thus provides a basis for completely autonomous operation. The design and implementation of the robot is described and some simulations and tests in real environments are presented.

This paper describes the design and the control architecture of an unsupervised robot developed for grit blasting ship hulls in shipyards. Grit blasting is a very common and environmentally unfriendly operation, required for preparing metallic surfaces for painting operations. It also implies very unhealthy and hazardous working conditions for the operators that must carry it out. The robot presented here has been designed to reduce the environmental impact of these operations and completely eliminate the health associated risks for the operators. It is based on a double frame main body with magnetic legs that are able to avoid the accumulation of ferromagnetic dust during its operation. The control system presents a layered structure with four layers that are physically distributed into two separate components in order to facilitate different operational modes as well as to increase the safety requirements of the system. A low-level control component has been implemented on the robotic unit itself, and a mission planning and control component has been developed on a base station that is also used for interaction with the operator, when the monitoring of the robot's operation is required. This base station component contains three layers of the control system that permit the manual, semiautonomous and autonomous operation of the whole system. A prototype of the robot has been implemented and tested in realistic environments, ascertaining that the design and the control system are perfectly suited to the functions which the robot must carry out.